OMS: Frequently Asked Questions (FAQ)

After more than a thousand downloads of the original Online Marketing Simulation (OMS) presentation, there are questions!


Question: I've been practicing web analytics for a decade. I'm perfectly happy analyzing conversion rates and executing multivariate tests, and my boss has never once asked me for something like this. Why would I ever need to execute an Online Marketing Simulation?

Answer: Your business leaders are telling me they want you to do this type of work for them. Your CMOs, CFOs, and CEOs communicate to me that they want to know what will happen to their business in the future. Your leaders are being pressured to understand if their business is capable of significant growth in the future. They want to know which micro-channel is best positioned to provide future growth (e-mail, affiliates, search, social media). They want to know if e-mail marketing performance improves if they increase spend in paid search. They want to know if making radical adjustments to offline advertising will impact sales online. They want to know what happens to the rest of the business if they decide to end all affiliate marketing programs. They want to know what total online sales will look like in 2014. They want you to give them the answers to these questions. I think your company is best served when you can provide "the C-Suite" with these answers.


Question: All of the Web Analytics bloggers and experts seem to be ignoring this topic. Is it possible that they know what's best for us and that you are talking about something that just isn't part of the typical web analytics tool kit?

Answer: Of course it is possible that they are right! But let's be honest. The Web Analytics community needs to integrate all offline and online data, and then become proficient not only at measuring what is happening, but forecasting what it means to the future health of a business. The vast majority of Web Analytics bloggers and consultant experts haven't had a need to solve a problem like this, especially when e-commerce was growing organically at 20% or 30% a year. Those days are over. Few e-commerce experts and web analytics experts have had to deal with the pressures of a stalled business, so they haven't ever had the need for a tool like the OMS. Over the next five years, you will see an evolutionary push toward advanced tools like the OMS. The marketplace and a stagnant economy will force it to happen.

Question: Your presentations are too vague. I don't think you're doing a good job of communicating this topic to your audience. What can you do to improve your presentation of this topic?

Answer: I'll try to improve and offer more concrete examples. This isn't an easy topic to communicate. I'll continue to work hard to improve the communication of this topic.


Question: Google gives away Google Analytics for free, so why shouldn't you give your programming code away for free? If you believe so strongly in this concept, why not evangelize it by giving it away, and then find some other way to monetize your activities?

Answer: I invested more than half of my professional career writing and testing the programming code necessary to create an application that predicts sales by micro-channel. This tool is perfect for the forward-looking CEO, an individual who wants to understand the future of an online, retail, or direct marketing business. I've invested tens of thousands of hours on this topic. That being said, I did outline the exact methodology in the presentation. If you are handy with programming code, and are a wiley analyst, you can replicate the algorithm based on the information in the presentation. Go do it!!

Question: "Our web analytics data is cookie-based, and we all know about the problems with cookies. So I think that invalidates the Online Marketing Simulation, right?"

Answer: "Absolutely not. Use the data you have, and where you don't have good visitation data, use your purchase data, which is much more important anyway. Please do not become paralyzed because you have incomplete data!"

Question: Have Omniture, WebTrends, Unica, or Coremetrics approached you about incorporating your algorithm into their software applications? It would be great if we could do this right from the platform we do all of our analyses from. Why not partner with them if you want this tool to become widely used?

Answer: No, they have not approached me about incorporating the methodology in their software applications. But representatives from every one of those companies are reading this series and are actively downloading the presentation, based on my blog/site web analytics data. The same holds for the major Web Analytics bloggers and consultants, my web analytics data show that they're all downloading and reviewing the content. If you like what you've been reading, communicate your interest to them, because people are paying attention.


Question: Must we use a Factor Analysis as part of the simulation routine? Must we use regression models to rank customers from best to worst? Why make this so complicated?

Answer: Absolutely not. Create your own segmentation scheme, and run the simulations with your version of segmentation. It's the simulation/algorithm that matters, not the methodology that is used to place customers within segments.


Question: How is this different than the Multichannel Forensics work you've done for catalogers?

Answer: The core of the Multichannel Forensics methodology is the core of the OMS tool. We're simply shifting the focus now, from figuring out how catalog advertising impacts the business, to figuring out how a myriad of online micro-channels and merchandise categories interact to impact the future of your business. Think of this as Multichannel Forensics on steroids. All of the concepts in the Multichannel Forensics book hold up well in the OMS framework.


Question: What is the most interesting thing you've learned while running Online Marketing Simulations for clients?

Answer: The way that subtle changes in the merchandising strategies of advertising channels impact the future merchandise preferences of customers. When you optimize e-mail campaigns based on the merchandise sold in e-mail campaigns, you impact the merchandise divisions that will sell well in the future. When you focus on various keywords, you impact the merchandise divisions that will sell well in the future. When you focus on discounts and promotions, you dramatically alter the responsiveness of your customer file to full-price merchandise in the future. It is amazing how things like discounts and promotions act like a virus (or a poison) that spreads through the whole customer ecosystem, reducing your ability to sell full-price merchandise. The OMS is perfectly suited for illustrating the poison of discounts and promotions, showing you how a heavy season of promotions in Fall 2008 dampen full-price business in 2011. The OMS tool literally allows you to see how you "infect" your business with viruses, even though you strongly believe you are optimizing your business for positive results today.

Give the presentation a read, and let me know what questions you have. If we get enough questions, I'll dedicate another post on the topic.

Dear Catalog CEOs: Matchbacks

Dear Catalog CEOs,

During the past decade, matchback analytics have become an indispensable part of catalog marketing. Without matchback analytics, it is possible you would not have a catalog channel.

The age of the "matchback" changed our perception of marketing.

Do you remember the good 'ole days, like way back in 1994, before we had an e-commerce website, back in the stone age of catalog marketing?

Back in 1994, we cared a lot about the concept of "cannibalization". We executed a lot of exotic multi-variate tests to detect cannibalization. For instance, say we mailed two catalogs, one on September 1, one on October 1.

• September 1 Catalog = $5.00 per catalog.
• October 1 Catalog = $5.00 per catalog.
• Total Demand = $10.00 per customer.

And then, we got excited! If we could generate $5.00 per catalog, maybe we should add a third catalog. So in 1995, we added a third catalog, on September 15.

• September 1 Catalog = $4.00 per catalog.
• September 15 Catalog = $4.00 per catalog.
• October 1 Catalog = $4.00 per catalog.
• Total Demand = $12.00 per customer.

Remember what we thought? We were happy with the new catalog, but we were concerned with the performance of the two existing catalogs. It was almost like they weren't working well anymore! And in fact, if we ran a profit and loss statement, we found that $12.00 of customer demand across three catalogs was less profitable than $10.00 of customer demand across two catalogs.

We thought about cannibalization, a lot. We were genuinely concerned about how one marketing activity cannibalized another activity.

Then matchback analytics came along. The data enabled the catalog vendor community to change our minds about how we thought about marketing activities.

We stopped thinking about "cannibalization". Heck, these catalogs didn't cannibalize business. Nope, these catalogs "added" business, they "drove" business to other channels.

The industry script (supporting an additive model vs. cannibalization) benefits the catalog ecosystem. The co-ops and database vendors created reporting that illustrated how catalogs drove sales across all channels. Their reporting supported the notion that we should rent more names from the co-ops. In other words, matchback reporting fuels the financial success of the co-op and list industry. The paper industry supports the concept of matchbacks. Printers support the concept of the matchback. The USPS supports the concept of the matchback. Your favorite Catalog Consultancy that helps you with mailing plans benefits from the matchback. Even third-party opt-out services benefit from matchbacks ... without matchbacks, they serve fewer customers who are getting unwanted catalogs.

The industry script benefits the entire catalog ecosystem.

Now let's focus on you, the Catalog CEO. Do you benefit from matchback algorithms?

As we head into the Holiday season, I'd like to ask you to do our industry a favor:

• Randomly sample 5,000 or 10,000 customers from the universe you would mail your best-performing Holiday catalog to.
• DO NOT mail these customers your best Holiday catalog.
• Code these customers as a unique segment, and enter these customers into your matchback routine with your favorite matchback vendor. Remember, these customers were not mailed a catalog, so your matchback vendor should show that no orders are matched back to the catalog that you did not mail.

If your matchback vendor matches online orders back to a catalog that was not mailed, then you have an estimate for how much your matchback vendor is over-stating the results of your catalog mailings.

Catalog CEOs, this is a very important topic. If your matchback vendor is over-stating your catalog performance because your vendor fails to take cannibalization into account, then you are over-mailing your customer base, and in all likelihood, you are wasting marketing dollars, squandering profit.

Increasingly, I am hearing of big discrepancies between matchback results and real-world results obtained via holdout tests. One company told me that every phone order was paired with one online order matched-back in their matchback algorithm. And yet, when they executed a holdout group, they only saw a 5% drop in total demand --- almost no phone demand or online demand was lost when the catalog was not mailed.

In other words, cannibalization was so significant that the catalog was basically adding no incremental demand. This is an important concept --- cannibalization testing shows no additional demand, while matchback algorithms show that catalogs drive online business, forcing you to mail more catalogs.

Do you understand the distinction?

Catalog CEO's, please ask your marketing folks to give this test a try. The entire catalog industry ecosystem benefits from matchback algorithms, and they aren't supporting matchback to be evil ... it's the best available reporting folks have. I'm asking you to question your results, to execute a test and validate that the matchback algorithms are giving you honest results. I don't benefit from doing this test, I have no financial interest in positive or negative results. Only you will benefit if you find that orders are being mistakenly attributed to catalog mailings.

So see for yourself! Run a holdout test, code the customers as a segment, run them through your matchback algorithm, and see if there is a bias that is causing you to over-state your results.

Thank you for your consideration,

Kevin Hillstrom, President, MineThatData

J. Crew: Required Reading

If you want to move beyond the "three easy steps to running a multichannel business ... 1 offer great product, 2 make it available in all channels, 3 offer great customer service" punditry, and learn about real people talking about real issues in a real multichannel business, then read the transcript of the Q2-2009 J. Crew Conference Call.

The comments represent the horse sense that is sorely missing from those selling multichannel solutions, from those offering 140 character untested nuggets of wisdom on your favorite micro-blogging service.

For instance, did you know that 40% of the J. Crew online assortment is not available in stores? This violates best practice #1 of multichannel marketing --- "offer the same merchandise at the same price in all channels". And yet, the business is successful in a horrific economic downturn.

Did you also know that J. Crew is wiping out catalog circulation, down 36% vs. last year, violating best practice #2 of multichannel marketing --- "catalogs drive sales across all channels".

J. Crew also is also staying away from the markdown business, violating best practice #3 of multichannel marketing --- "offer incentives and promotions that are redeemable across all channels". Mr. Drexler mentions that once you get in that business, it takes decades to get out.

J. Crew violates best practice #4 of multichannel marketing --- "cater to the long tail of inventory, offering the best customers numerous options to satisfy their needs." J. Crew states that "excess inventory is worse than expired milk".

J. Crew violates best practice #5 of multichannel marketing --- "use multiple channels to grow market share". J. Crew states that you need 150% of the inventory to accommodate 100% of the customers.

Pay close attention to what multichannel leadership talk about, and compare it to what the micro-blogging community and vendor community talk about.

OMS: They Bought Via An E-Mail Campaign. Now What?

You have a customer who purchased online a couple of years ago. Since then, you've sent this customer an opt-in e-mail message, twice a week, 200+ in total.

Today, for whatever reason, that customer is ready to purchase something. Through no fault of her own, the customer receives another e-mail campaign from us. The customer has a choice. Should she click through the e-mail message and purchase? Or should she just key in your website url and purchase?

Does it even matter?

Let's go to the Online Marketing Simulation and find out.

First, we simulate 1,000 2x buyers, first purchase online, second purchase online, both purchases = $150, both purchases from Merchandise Division #3. This will be our benchmark.

• Annual Repurchase Rate = 41%.
• Demand: Year 1 = $104,000, Year 2 = $68,000, Year 3 = $48,000, Year 4 = $38,000, Year 5 = $33,000. Total = $291,000.
• Online Buyers via Offline Source: Year 1 = 124, Year 2 = 75, Year 3 = 49, Year 4 = 37, Year 5 = 31.
• Online Buyers via E-Mail: Year 1 = 162, Year 2 = 88, Year 3 = 55, Year 4 = 41, Year 5 = 34.
• Online Buyers via Search: Year 1 = 32, Year 2 = 20, Year 3 = 13, Year 4 = 10, Year 5 = 8.
• Online Buyers, Pure Web: Year 1 = 99, Year 2 = 53, Year 3 = 34, Year 4 = 26, Year 5 = 22.

Now, we'll simulate what happens if these 1,000 customers instead place their second order via E-Mail.

• Annual Repurchase Rate = 43%.
• Demand: Year 1 = $102,000, Year 2 = $79,000, Year 3 = $63,000, Year 4 = $54,000, Year 5 = $48,000. Total = $346,000.
• Online Buyers via Offline Source: Year 1 = 129, Year 2 = 85, Year 3 = 62, Year 4 = 50, Year 5 = 43.
• Online Buyers via E-Mail: Year 1 = 204, Year 2 = 117, Year 3 = 80, Year 4 = 61, Year 5 = 51.
• Online Buyers via Search: Year 1 = 26, Year 2 = 17, Year 3 = 13, Year 4 = 10, Year 5 = 9.
• Online Buyers, Pure Web: Year 1 = 100, Year 2 = 63, Year 3 = 45, Year 4 = 35, Year 5 = 30.

If the customer converts to an E-Mail purchase, then future value is increased by about $50,000 ... or $50 per customer, so that's a good thing (your mileage will vary). Now look at a sampling of the key online micro-channels. Customers buying from offline sources are not significantly changed. Customers, however, become much more likely to buy via E-Mail (duh).

But there's a more interesting outcome when we look at merchandise divisions. Let's look at the outcome for Merchandise Division #5.

• Pure Web Buyer: Year 1 = 86, Year 2 = 73, Year 3 = 55, Year 4 = 45, Year 5 = 40.
• Pure Web + E-Mail Buyer: Year 1 = 171, Year 2 = 111, Year 3 = 84, Year 4 = 69, Year 5 = 61.

This is why we focus on the Online Marketing Simulation, the "OMS". The simulation tells us how customers are likely to behave in the future because of an action that happened in the past. Combined with Web Analytics, OMS yields very interesting insights, insights that help business leaders make decisions today that profitably influence the future.

In this case, when we encourage a customer to purchase from an e-mail campaign, we change the future merchandise preference of the customer. The executive in charge of Merchandise Division #5 should be partnering with the e-mail marketing team, given the synergy identified in the OMS run.

An OMS analysis complements your Web Analytics enviornment. With Web Analytics, you are easily able to look back in time. With OMS, you get to see the future.

Williams Sonoma Q2 2009 Results

Thought you might find this quote interesting, from their Q2 conference call (click here for the actual transcript):

"In direct marketing we continue to move forward with our catalog circulation optimization strategy. During the quarter year over year advertising expense declined 26% net of a 34% increase in on-line marketing. We continue to believe that refining the balance between catalog sales and on-line marketing is a significant opportunity and we will be participating in a strategic test with Google at the end of the month to test this initiative at the next level."

The second-most popular project I work on is catalog optimization --- reducing catalog expense without a major hit to topline sales. It's a very popular topic these days, for obvious reasons.

Here's a quote about Pottery Barn Kids: "We will also continue to shift our advertising spend from catalog to e-commerce as we capitalize on the new functionality in customized e-mail, affiliate marketing and search."

Here's an exchange you might enjoy --- anybody who's ever been responsible for reducing catalog marketing expense while at the same time is responsible for growing the online channel can relate to this:

Anthony Chukumba – Ftn Capital Markets
I had a quick question in terms of the catalog circulation optimization effort. Your catalog circulation if I wrote these numbers down correctly, catalog circulation declined 19% and your catalog pages declined 25%, but year over year your direct to customer business was down 24%. I guess what I'm wondering is do you feel comfortable that you haven't cut back too much on your catalog circulation? In other words, it strikes me as a little bit out of line that you're direct to customer sales be down even more than your catalog circulation. It sort of implies that some of the circulation you got rid of wasn't necessarily marginal kind of dead beat circulation.

Sharon McCollam
A substantial piece of the reductions were in the Pottery Barn brand, so I'll let Laura speak to the specifics related to Pottery Barn and their strategies, and then I'm going to let Pat talk about the broader catalog circulation optimization strategy. Laura could you take this specifically related to the Pottery Barn brand where you're doing a lot more versioning?

Laura Alber
We have been actually, this is a very important question for all of us and we continue to have a lot of discussion and research done on the subject and we look at it monthly and go through and look at where there are opportunities and make adjustments, and it's a very productive process.
We do have less promotions than last year, so as Sharon said earlier, there are sales that we drove last year that weren't as profitable as they should have been and weren't good for the brand longer term, and that is part of what you're seeing with the direct to consumer decline that's worse than the catalog circulation cut.

Howard Lester
And just to extend that a bit across all of our brands, the techniques, we're in our 23rd year of using the sophisticated regression analysis to rank our file when we go to mail it. And over the growth years, we were looking at how we could use this to find the next best prospect. In this environment, we're able to use these techniques to identify those people who would most likely not buy and not mail them, and we have done a number of control groups and are very confident that the circulation we've cut would have produced minimal sales compared to the cost of having mailed those catalogs. The other point that Sharon brought out earlier, and Laura mentioned, is that we're able to divert some of our catalog spend to on-line digital marketing that is producing more attractive results and we are very optimistic about our opportunities here especially in the back half of the year across a wide range of digital marketing efforts from e-mail, to affiliates to re-targeting to paid search and also the initial results of Google's new caffeine algorithm which tends to favor brands and pushing up our page rankings.

Gliebers Dresses: CMO Candidate #3

We're about to sit in on the final Executive Meeting group interview. Today, the interview candidate is Stan Klepsky, who was previously the Executive Vice President of Marketing for the Bentley catalog.

Glenn Glieber (Owner): "... and Candi, you can tell Anderson Cooper that we are NOT using Twitter and the Save Gertie campaign to artificially drive up our follower numbers to compete with CNN."

Meredith Thompson (Chief Merchandising Officer): "Kevin, is that you?"

Kevin: "Yup, it's me."

Candi Layton (HR and Chief Customer Officer): "We continue our fine tradition of group interviews at Gliebers Dresses with the final CMO interview, featuring Stan Klepsky, the former EVP of Marketing for the Bentley Jewelry catalog."

Stan Klepsky: "Thanks for having me today, everybody, I REALLY appreciate it. I requested a catalog of yours a couple of weeks ago, and spent considerable time thumbing through it over the last week. What a beautiful piece of creative imagery! You don't go too far, you know? Sometimes these fashion people reduce density and show one image per page and somehow expect the catalog to sell stuff. This catalog is a perfect blend of merchandising and creative. You have these wonderful callouts, too. Here, look at page 49, you illustrate eight lovely dinner dresses, and then direct the customer to the web for your extended assortment. Beautiful! I imagine that works really well, and drives considerable online volume. Your web analytics team must salivate when they think of the 20% conversion rates they get from that kind of qualified traffic. And you've even kept the order form in the catalog. That's a great, low-cost way to not alienate your older customer. All of the details of cataloging are in place. You call out your new loyalty program via a dot whack on the cover, hey, how's that going, huh? Buy four dresses, get free shipping for the rest of the year, that's an amazing value! I think this catalog is easy to shop, I mean, look at the copy in this thing. The copy creates a sense of warmth, yet, there's a personality to the copy that makes the catalog human. You know how all of those e-commerce websites are so cold, so sterile, same layout and same fonts and same colors and same links and same guarantee of secure shopping, all optimized for performance in the exact same way using the same web analytics software and same industry consultants. I can just picture the woman, I imagine her name is Nancy, sitting on the couch, 9:35pm at night, glass of wine in her hand and a Jim Brickman CD playing in her Bose Wave Radio, thumbing through this classic marketing vehicle. Oh, I tell you, this thing ..."

Meredith Thomspon: "YES! That's what I'm talking' about! We need to think about the target customer, and market to that target customer the way she wants to be marketed to."

Lois Gladstone (Chief Financial Officer): "Let me ask you a question. We're not made of gold bullion around here. How would you minimize catalog expenses yet drive sales increases in all channels?"

Stan Klepsky: "Oh that's an easy one, friends ... REMAILS! You take this beautiful catalog sitting here in front of us, and you just swap out the cover and back page with new images, change the item numbers for tracking purposes, and then mail the same catalog to the same customer. In fact, do this three or four times with the same catalog. You save a ton of money on catalog expense, and you only experience a dropoff in performance of maybe 20% or 25% per remail. I'm sure you're already maximizing your remail strategy, but if you aren't, that's the place where I'd start. And those remails drive web volume, too. Heck, I'm sure you're just like every other catalog brand, generating 70% or 80% of your online volume from the catalog. All of those online pundits, talking about PPC, they don't know their PPC from an SCF, do they? It's the paper catalog that makes the online thing go, folks! Ask an online marketer to drive business without paper, and they'll just stare at you, wondering how they will ever get traffic that converts at a 12% rate."

Pepper Morgan (Interim Chief Marketing Officer): "What do you think of a different strategy, one where you alternate large page counts with small page counts --- mailing the small page counts to a deep audience?"

Stan Klepsky: "Geez Pepper, that sounds risky. I like the tried and true remail formula. It's been used for decades. It's an established best practice. I'd have to see a few years of performance on the strategy, and I'd have to see a half-dozen companies utilize that strategy effectively before I'd climb on board that train. You know, I don't think anybody at ResponseShop has told me that anybody is employing that kind of strategy. I'd want to see the folks at ResponseShop issue a white paper, telling us that the strategy is a newly established best practice before I'd sign up for it, you know what I mean? Cataloging is not a place for reckless experimentation, Pepper. There's a reason cataloging is a one-hundred year craft and e-commerce is a decade-long experiement."

Meredith Thompson: "A lot of folks are telling us we cannot grow a catalog business in the modern world of e-commerce. Can we grow the catalog portion of our business?"

Stan Klepsky: "Geez Meredith, who's been painting that kind of graffiti on your wall? Cataloging is a simple business model, really. It's all about segmentation. See, you segment your customers by recency, you know, 0-6 month, 7-12 month, 13-18 month, you get the picture. Then you segment by frequency, you know, one time buyers, and those multi-buyers. Now that you've got your segmentation strategy, you surgically determine a promotional strategy. Your current customers, those 0-6 month folks, they get a free shipping offer, well, wait, you already have that loyalty program, so why not just promote the loyalty program, right? And then you've got those 37-42 month buyers, well, you simply stimulate them with a compelling offer, like 20% off your next order of $50 or more, and you make sure you put that $50 hurdle in there to protect your profit and loss statement, right? You run a whole bunch of tests at different hurdle levels, too, trying to find the optimal hurdle level. I'd be happy to run the profit and loss scenarios for you, And then you've got outside lists. Aren't those folks at ResponseShop something else? You just get on the phone with your account rep, I personally like working with Eldon Mayer, and you just say something like 'I need 6,375,000 names for our next catalog', and they apply that harmony model and then you plop those names in the merge and coordinate with your printer to maybe put a personalized inkjet message on the back cover, because customers really like that personalization stuff ... heck, maybe you even inkjet a personalized URL on the back cover, and then use your web analytics tool to track the performance of the inkjet messaging, that should make those Web Analytics folks just salivate, right?. Anyway, ResponseShop can integrate all of that for you along with their own measurement system that matches back online purchases to the catalog that drove the online purchase, you just tell Eldon Mayer how you want the analysis to look and I tell you what, it's as if he can make the analysis look the way you want it to look! And my goodness, at last year's catalog conference, ResponseShop had the best party of the whole lot, I mean, did you get a load of the prawn pyramid they wheeled out at 9:00pm? And how the heck did they get Christopher Cross to perform at the party? Wow, he really brought down the house with that acoustic version of 'Sailing'. So yes, you can grow a catalog business, you just have to follow established best practices. I think too many people have forgotten about best practices, they're just out there winging it, writing manifestos telling us that the world changed, that you cannot do things the way you used to do them. I'm here to tell you that if you follow the rules, you'll follow a prescription for success!"

Roger Morgan (IT and Operations): "Stan, can you explain the climatological conditions that cause Oklahoma to be called 'tornado alley'?"

Stan Klepsky: "That's an odd question, Roger, but thanks for volunteering it. I think it has something to do with the Gulf of Mexico, right? I think the Weather Channel had an episode of 'Storm Stories' about that topic, right? You know, one of those stories about a tornado that blew through Norman, OK, and some school teacher told her kids to get in the basement but little Timmy decided to go outside and then the teacher had to rescue him just as the tornado leveled the school, and just as you're caught up in the human drama of the storm, they cut away to a commercial with that goofy insurance duck riding in a racecar and then they have your local forecast on the 8s and you're wondering why your picnic is going to be ruined by a 40% chance of thundershowers, some containing high winds and hail."

Candi Layton: "You have a real passion for cataloging. Is passion missing from commerce?"

Stan Klepsky: "Oh Candi, it's so true, the passion is gone. There's nothing like the in-home week of a catalog. You get in to work on a Monday morning, and you look at your flash sales reporting on an hourly basis, don't you? You compare sales by hour vs. your plan, and then you see deviations, like sales are up 120% vs. forecast and you ask yourself if the plan is wrong or if the catalog is being delivered too soon by the post office or if the catalog is really going gangbusters, right? And then you dig into the zip code reporting and you realize that the catalog is only generating sales in Louisiana, Alabama, Georgia, and South Carolina, so you get on the horn with your printer and you ask them why the heck they transported the catalogs to the BMCs and SCFs too fast, and your printer says they did everything like you told them to do it, so then this is becoming a big puzzle that you have to solve because maybe this catalog is actually below plan and you just don't know it, so you start studying the merchandise trends and you have to study those trends via telephone sales because the e-commerce sales are clouded with activity like some banner ad on MSN that has a 0.00004% click-through rate and then you realize that it is noon and it is time for lunch, but you skip lunch because now your reports, your 'KPIs' as the kids say, are showing you that you're getting sales from Arizona and California too and the catalog is merely 20% above plan so maybe your forecast is wrong. All of that happens before 1pm on the Monday of an in-home week. It's so much fun! And by Tuesday at 1pm the whole company wants to 'call the catalog', right? Everybody wants to say, based on 36 hours of sales performance, if the catalog is above plan or below plan, heck, you have those inventory hounds all over you about placing reorders or about creating a 48 page clearance catalog that could also potentially be a package insert or even be selectronically bound into an upcoming catalog, so you're problem solving those issues prior to your Tuesday 1pm forecast meeting with the inventory team. And then everybody questions your forecast, and why they do that I don't know, because they couldn't forecast the sunrise if they had a newspaper in front of them that printed the time the sun was going to rise in the morning."

Lois Gladstone: "What is the role of the e-commerce channel for a catalog brand?"

Stan Klepsky: "It's the gold standard of direct-to-consumer shopping these days, isn't it? I just purchased an MP3 player from an online electronics retailer, free shipping and two day delivery, how do you beat that? The whole e-commerce world has just exploded, and it's a darn good thing that there are catalogs and retail stores to fuel the whole thing. I honestly think that without stores or catalogs, e-commerce wouldn't exist. Heck, I purchased my MP3 player from an online pureplay because another electronics cataloger sent me a catalog. The catalog created demand, then I went online and found the best price, cheapest and fastest shipping, and bodda-bing, I've got my MP3 player. The catalog created the demand for a competing online pureplay. Catalogs and Stores are always creating demand. If I weren't speaking to like-minded individuals, and I were interviewing at an online brand, I'd probably ask them one question --- 'after you strip out all of the traffic that your offline competitors drive to your site, after you strip out all of the traffic that is associated with Google, after you stop adoring the 0.000004% click-through rate on MSN, how the heck are you going to get customers and prospects to visit your site?' Wouldn't you ask them that question?"

Kevin: "Stan, I have a question for you. Where you think the catalog industry is heading?"

Stan: "Kevin, good question. Do I look like Carnac? Ha! Remember when websites were created back in the 1990s? We were all intoxicated by Amazon.com, and Pets.com, right? But the whole thing was a big gold rush, and the winners were a small number of online brands and then all of the established brands that simply added e-commerce functionality to their existing business and crushed the online brands. Honestly, most of us didn't fundamentally change how we did business, and we did just fine, didn't we? Our catalogs drove e-commerce sales, allowing us to basically conduct business the way we did back in 1994. Now, all of these social media experts are telling us with their manifestos and tweets that e-commerce and old-school cataloging is dead, that it is all about community and online relationships. And honestly, how do you become a social media expert? Is there a form I have to fill out? There's like 12,000 social media experts, and they seem really good at pointing out everybody else's faults, right? If that's all it takes to be a social media expert, sign me up, I can point out faults, too. Anyway, once again, we're going to be proven right. Time will tell us that, in the case of Gliebers Dresses, we're just selling dresses ... that's all that Gliebers Dresses has ever done, with the catalog at the core of the experience, creating all of the romance while tweets are orbiting the brand like moons orbiting Jupiter, if you know what I mean. There's always going to be a woman, in bed at 9:30pm, nightstand light on, thumbing through her Gliebers Dresses catalog. Sure, she might tweet about a hoodie dress she saw for her daughter, and maybe in the future she's looking at her catalog on the Kindle. Sure, she might click through an e-mail campaign and buy online. But the core experience begins with the woman in her bed at 9:30pm thumbing through a catalog."

Kevin: "Stan, have you personally experimented with Social Media, and if so, what role does social media play at a modern catalog brand?"

Stan: "Social Media, schmoshial media. What a pile of dog doo. I started my own Twitter account a few months ago. I put absolute nuggets of gold out there, too, not the standard pap that the social media consultants throw out there. Have you read some of this stuff? You'll read that "brands need to communciate with an authentic voice", or "unless you join the conversation, you're destined for the scrap heap." How do you have an authentic voice 140 characters at a time? I put good stuff out there, real facts, stuff like "personalized ink jet messages increase response rates by an average of 1.2%." or "work with ResponseShop to identify highly responsive multi-buyers.", or "selectronically bind four pages of winners in the middle of your saddle-stitched catalog to improve profitability", you know, the kind of stuff that actually makes companies money. Nobody followed. Nobody. And yet, you go read the pap that those social media folks write, and they've got 27,483 followers, apparently all of them are craving to have authentic conversations with brands. Nobody has a conversation with a brand. Brands sell you stuff, you buy stuff, that's all there is to it. When have you ever had a real relationship with a brand? Who'd want one? Would you rather have dinner with your friend, Perry, or would you rather have dinner with a brand? That's why I love cataloging. I keep going back to the woman sipping from a glass of Syrah in her pajamas, thumbing through the pages of a well-done catalog selling vehicle, with George Winston playing on her Bose Wave Radio. Would you rather have your brand represent that image, or would you rather have your brand have an authentic voice that gets re-tweeted, 140 characters at a time, to 27,483 followers?"

Glenn Glieber: "Well, we're basically out of time. Stan, thanks for being so generous with your thoughts. On to the next topic, Pepper, I'm feeling a bit uncomfortable with the May 2010 catalog, I really think we need more pages. Could you work up a scenario for the May catalog, seeing what kind of sales increase we get if we go from 108 pages to 116 pages? Thanks!"

Stan: "Ohhh, I can do that. I like to add in demand at half the rate of pages added. So if your catalog was scheduled to generate $3,000,000 in demand, and you go from 108 to 116 pages, I'd estimate a 3.5% increase in demand based on a 7% increase in pages. Just add in $110,000 of demand, and see what the profit and loss statement looks like."

Glenn Glieber: "Pepper, why can't you calculate that information on the fly like Stan just did?"

Gliebers Dresses: CMO Candidate #2

We're here today to have a discussion with CMO Candidate #2, Maria Garcia, Online Marketing Executive at BlueDotRedDotGreen.com.

Glenn Glieber (Owner): "... this Twitter campaign to Save Gertie is out of control. Who the heck paid for the airplane to fly over the building for an hour yesterday with a 'Save Gertie' banner trailing from the tail section? Now we're being mocked in the SmartBrief on Social Media publication. Many of you didn't think I read that thing, but I'm a hip CEO. Roger set me up a bunch of alerts and subscribed me to all of the leading trade journals, so I can follow the madness. And this is madness. Pepper, you're in charge of marketing, if Candi cannot fix this via social media, then please issue a press release or something that tells our side of the story."

Meredith Thompson (Chief Merchandising Officer): "Kevin, is that you?"

Kevin: "Yup, it's me!"

Candi Layton (HR and Chief Customer Officer): "We're about to continue a great Gliebers Dresses tradition, the group interview! Today, our candidate is Maria Garcia. She's the Online Marketing Executive at BlueDotRedDotGreen.com, an online pureplay that focuses on personalized products. Let's start the discussion."

Meredith Thompson: "How do you forecast demand for personalized products?"

Maria Garcia: "We're never trying to forecast how many t-shirts will have the phrase 'Have a Blast!' on them. We do a reasonable job of knowing how many t-shirts we'll sell by size and color."

Lois Gladstone: "You don't have a catalog to drive sales. So ... how do you drive sales?"

Maria Garcia: "Honestly, we have a vibrant online community that sells for us. You only get access to our discounts and promotions by being part of our community, and you only become part of the community by being invited by a friend, sort of like the way that Gilt operates, an indirect discount competitor of yours. This creates a level of exclusivity that is hard to match."

Meredith Thompson: "But how do you communicate the message without a catalog?"

Pepper Morgan (Interim CMO): "Let me ask the question in a different way. If you had the advantage of having a catalog, like we do here at Gliebers Dresses, how would that change how you would communicate with customers?

Maria Garcia: "In many ways, I think the catalog represents a different shopping environment, and a different customer. If I were lucky enough to be hired here, I'd look to keep the audience that likes to shop with catalogs, and I'd look to build a whole new audience using the community-based tools I've developed at BlueDotRedDotGreen.com. I'd even consider creating a spin-off brand, similar merchandise, but different website, different brand identity, different level of community building, you know?"

Roger Morgan (IT and Operations): "Maria, can you describe the ingredients that comprise a hot dog?"

Maria Garcia: "What kind of question is that?"

Kevin: "I have a question for Maria. How do you measure the lifetime value of a customer who brings other customers into the community? In other words, you cannot be part of the community without being invited by a friend. So how do you measure the incremental value of community members who invite many friends?"

Maria Garcia: "Our database links all invites to the original community member. We allocate lifetime value on the basis of invites. We know that each invite is worth $70 of lifetime value. Before beginning this program, individuals who participated in our promotional program were worth $30 of lifetime value. So we know that each invite is worth an incremental $40 of lifetime value. Roger, would you be able to set up an environment like that here, so that if we implemented an invite-based community program, we could measure long-term value?"

Roger Morgan: "Sure, we'd just have to put that project on the book of work, and prioritize it as appropriate. Now Maria, I have a question for you. Which state was admitted to the Union first ... Wyoming, or New Mexico?"

Maria Garcia: "What kind of question is that?"

Kevin: "What type of tools do you use to analyze customer behavior?"

Maria Garcia: "We have an in-house customer database, and we feed database attributes from Google Analytics to our in-house customer database, called 'Cheyenne'. We do ad-hoc analyses with 'R', SQL, and Microsoft Access."

Roger Morgan: "How did you arrive at that toolset?"

Maria Garcia: "We purposely go with inexpensive, open-source solutions. Our merchandising systems are all written with open-source software, and are fully integrated with the customer database."

Roger Morgan: "Must be nice to build things from scratch, as opposed to having to integrate new solutions with old platforms."

Candi Layton: "You don't have a lot of catalog experience. How would you compensate for that lack of experience?

Maria Garcia: "I'd lean on Meredith, to be honest. Based on our discussion earlier today, she knows everything. I think the two of us could bring out the best in traditional techniques and new thinking."

Pepper Morgan: If Glenn asked you to forecast the change in performance of a catalog that was 116 pages, and now will be 124 pages, how would you do that?"

Maria Garcia: "I'd ask Meredith! Seriously, she would know of some sort of short-cut that I could use."

Lois Gladstone (Chief Financial Officer): We don't have a lot of money for marketing at Gliebers Dresses. How would you make every penny count in your marketing efforts?

Maria Garcia: "We don't have much money at BlueDotRedDotGreen.com. Outside of a bit of paid search, almost all of our marketing is community-based marketing, it's basically free marketing."

Glenn Glieber: "I love free marketing!"

Maria Garcia: "And honestly, we'd love the free publicity you are getting over the Save Gertie campaign. Why would you ever want to stop that? Let the drama play out for another week or two, and then actually Save Gertie, send her someplace to 'retire' --- heck, have your Twitter audience decide where Gertie is saved. That should be worth a ton of PR."

Roger Morgan: "I think we want to eat Gertie, right Glenn?"

Meredith Thompson: "At our core, we're a cataloger. I haven't heard you say anything that suggests you believe in the future of cataloging. As Chief Marketing Officer, how would you grow our catalog business?"

Maria Garcia: "I don't think you should hire me if you want to grow a catalog business. You should hire me if you want to grow your dress business. Last time I checked, your business was named 'Gliebers Dresses', not 'Gliebers Catalog', right? It is my opinion that catalog marketers are obsessed with the catalog marketing channel. Why aren't catalogers obsessed with the merchandise? I've spent a lot of time researching the catalog industry, and I must admit, I'm baffled. While online brands have grown like weeds in the last decade, the catalog industry seems mesmerized by vendorspeak, the non-stop messaging that suggests that there's no better marriage in marketing history than a 128 page catalog with 120 pages of dead trees that the customer couldn't care less about, coupled with a website that acts as a glorified order form. And then you read about who it is that puts out these messages, and it is companies like ResponseShop. You guys work with ResponseShop, right? Well of course ResponseShop is going to volunteer messages like this, because it is in their financial best interest to do so. Tell me why the catalog industry hasn't revolted against this type of information campaign, because this information campaign sure failed to launch catalogers into the 10% EBT stratosphere, right?"

Glenn Glieber: "Well, we have to get Maria on a plane, so we'll have to stop this stimulating discussion right here. Pepper, I'm feeling a little bit uncomfortable with our page counts for the March 2010 catalog. Could you work up a quick scenario where we add, say, eight pages, and then see what that does to the bottom line? Thanks!"

OMS: Keyword Optimization

Any online marketer and web analytics practitioner looks to maximize the performance of her business. Typically, this is done by analyzing campaign performance. The marketer and web analytics practitioner work together to make sure that current activities are optimized.

The Advanced Web Analytics Practitioner knows that all current activities cause changes in future activities.

For instance, a set of keywords may yield lower costs, higher conversion, and as a result, an increase in short-term profit. From an SEO, Online Marketing, and Web Analytics perspective, this is all good.

From an Online Marketing Simulation (OMS) standpoint, it may be good, it may not be good!

In my dataset, Merchandise Division #4 represents a product line with more expensive price points. Merchandise Division #3 is an extension of Merchandise Division #4, with less expensive price points. Not surprisingly, customers flock to Merchandise Division #3!

So, let's run simulations of future performance on 1,000 customers. Remember, we categorize customers based on combinations of future value, advertising channel preference, physical channel preference, and merchandise preference. This yields anywhere between maybe 80 and several thousand segments. Once done, we apply twelve-month sales and profit value to each segment, we migrate customers to their new segment, then we replicate the process four more times, with the ultimate destination being the segments that these 1,000 customers will reside in five years from now.

The first simulation is for a paid search customer buying from Merchandise Division #3, the division with lower price points.

• Annual Repurchase Rate = 24%.
• Demand: Year 1 = $51,000, Year 2 = $35,000, Year 3 = $28,000, Year 4 = $25,000, Year 5 = $23,000.
• Merchandise Division #3 Buyers: Year 1 = 128, Year 2 = 72, Year 3 = 52, Year 4 = 45, Year 5 = 42.
• Merchandise Division #4 Buyers: Year 1 = 113, Year 2 = 65, Year 3 = 48, Year 4 = 41, Year 5 = 38.

Ok, now let's run simulations of future performance on 1,000 customers buying from Merchandise Division #4 via paid search --- this division has similar product, but higher price points.

• Annual Repurchase Rate = 42%.
  Demand: Year 1= $123,000, Year 2 = $76,000, Year 3 = $52,000, Year 4 = $41,000, Year 5 = $35,000.
• Merchandise Division #3 Buyers: Year 1 = 169, Year 2 = 103, Year 3 = 70, Year 4 = 54, Year 5 = 46.
• Merchandise Division #4 Buyers: Year 1 = 258, Year 2 = 137, Year 3 = 87, Year 4 = 66, Year 5 = 55.

The typical web analytics practitioner partners with the online marketer, seeking to optimize conversion rates and transaction profitability. Once the transaction is complete, the typical web analytics practitioner and online marketer moves on to the next conversion.

In this case, which customer are you willing to pay more to acquire? I'm willing to pay a fortune for the customer who purchases from Merchandise Division #4. I'll gladly sub-optimize my short-term business in order to acquire a customer that will spend more in the future in both Merchandise Divisions!

This is what Advanced Web Analytics via the Online Marketing Simulation (OMS) is all about. We want to understand how our optimized short-term decisions impact the long-term health of our business.

Keyword Optimization requires a view of long-term performance, in order to be successful. The OMS environment can point you in the right direction.

OMS: Mini-Primer

Some of you are looking for less theory, more practicality, as you explore the Online Marketing Simulation framework.

Let's start at a very simple level.

This spreadsheet, from my Multichannel Forensics work, simulates migration of customers across just two channels.

The exact same concepts that are at work in a 2-channel Multichannel Forensics five year simulation apply to a 100x100x100x100x100 segment migration (future customer value, advertising channels, physical channels, merchandise preference) in the Online Marketing Simulation framework.

If you can understand 2x2x2x2x2, you can conceptualize 100x100x100x100x100, or 1,000x1,000x1,000x1,000x1,000!

Heart Attacks and Web Analytics / OMS

Imagine that you are in for your annual physical.

Your doctor tells you that you are a heart attack waiting to happen. You are overweight, your cholesterol is high, you eat bad foods (i.e. nachos), you don't exercise.

You can choose to heed the advice of your doctor. You openly welcome Crestor into your life, you begin eating turkey breasts instead of bacon cheeseburgers, you walk three miles a day, you do the things necessary to minimize the risk of a heart attack.

Or you can keep going down the path you're on ... hoping that 0 or 00 won't come up on the roulette wheel.

Which brings us to Web Analytics and the Online Marketing Simulation, better known as "OMS".

Web Analytics is great, in that you are potentially given all of the information necessary to understand the health of your business today. You've got metrics (cholesterol) and multivariate testing (ekg). Maybe the health of your business isn't so great.

Here's why you need consider the Online Marketing Simulation (OMS) environment. If you decide to keep eating nachos (discounts and promotions), you increase your personal happiness (conversion rate), but you edge yourself closer to a heart attack (bankruptcy). The OMS environment allows you to play "what if" games --- what if I switch from nachos to boiled chicken, what is the probability of living a longer, healthier life --- or in the case of your business, what if you switch from free shipping in your e-mail campaigns and paid search activities to acquiring customers without discounts/promos, what impact will that have on your business, long-term?

With traditional Web Analytics, you're the doctor telling the patient about the potential for a heart attack.

With the OMS, we get to see all of the likely outcomes of our dietary and lifestyle changes.

Find a techie who can program the OMS environment for you, if you cannot create it yourself. If you don't have the resources and are interested in an Online Marketing Simulation (OMS) project, contact me here. Or the best solution of all ... encourage your favorite Web Analytics vendor (Omniture, Coremetrics, WebTrends, Unica) to partner with me on migrating this algorithm to their platform!

OMS: Real-Time Scoring

In my OMS projects, I create three different families of scores:

1. Probability of a customer purchasing in the next twelve months.
2. Amount a purchaser will spend in the next twelve months.
3. Factor analysis scores for channel x merchandise combinations.

The scores yield a series of segments --- as few as maybe 80, as many as several thousand.

Each segment has a predicted future value --- that future value fuels the simulation of five year sales and profitability of your online business.

This information could easily be incorporated into your Web Analytics platform, allowing you in real-time or near real-time to see how today's purchasers influence the future trajectory of your business.

For example, you query customers who purchased in the twelve months ending last night. Each customer is scored via the OMS algorithm, and placed in one of the segments. Then, the future value for the next twelve months is summed across segments. At this point, you know that your current twelve-month buyer file is going to generate, say, $33,000,000 in the next year.

Tomorrow you have an e-mail campaign that goes absolutely bonkers. Woo-hoo! Replicate the scoring process mentioned above, just shift the twelve-month window by a day, and re-score everybody. Sum future volume. Say the total is $34,000,000. Now you know that your e-mail campaign went bonkers today, but also added a million dollars of value to your future business.

That's something you'd want to know, wouldn't you? And knowing it in real-time or near real-time is even better.

That's the power of the OMS algorithm.

Gliebers Dresses: CMO Candidate #1

We're ready for the group interview of CMO candidate #1, Duncan Berkshire, DVP of Brand Marketing for Blast Candy Bars. Let's go to the Executive Meeting.

Glenn Glieber (Owner): "... and Candi, I have no idea who started this 'Save Gertie The Pig' campaign on Twitter, but it ends today. You've got to get these people to stop re-tweeting this message. I mean seriously, we had something like 1,300 followers on Monday, and now in just two days we've added 9,000 followers, every one of them passionate about saving Gertie. Folks keep phoning the call center, pleading with our associates to Save Gertie. You know, the only way this thing got on Twitter is from somebody in this room, because Dorothy sure doesn't interact with social media. Candi, end it, now, or at least tweet that you'll Save Gertie if they buy four dresses and enroll in our loyalty program."

Meredith Thompson (Chief Merchandising Officer): "Kevin, is that you?"

Kevin: "Yup, it's me."

Candi Layton (HR and Chief Customer Officer): "Kevin, we're about to begin the final part of our CMO interview with Duncan Berkshire, the group interview. We've all had a chance to interview Mr. Berkshire individually, so let's not waste any time and get on with this important part of the Gliebers Dresses culture."

Lois Gladstone (Chief Financial Officer): "Duncan, can you describe for us a situation where management demanded that you grow sales, and you were able to act in a nimble manner to immediately grow sales?"

Duncan Berkshire (Group Interview CMO Candidate): "In 2006, Blast candy bars were struggling to maintain market share. We started a new marketing campaign, with the tagline 'Have a Blast!' I worked with grocery executives. I increased slotting fees for better product placement. The strategy paid off, as sales increased 2.8% in the ninety days following implementation of our global branding strategy."

Lois Gladstone: "Was the strategy profitable?"

Duncan Berkshire: "We really focused on driving sales. We let the finance folks calculate the ROI of brand marketing activities."

Pepper Morgan (Interim Chief Marketing Officer): "Let's say that Glenn wants to increase the November catalog from 124 to 140 pages. How would you quantify the sales impact of a decision like that?"

Duncan Berkshire: "You might consider putting together a few focus groups, and ask if this type of strategy makes any difference in the eyes of the customer."

Pepper Morgan: "Do you believe that you can mathematically quantify the change from 124 to 140 pages, prior to putting the catalogs in the mail?"

Duncan Berkshire: "I think the math is irrelevant without understanding how customers might respond to a change of that nature."

Candi Layton: "Gliebers Dresses has always stood for Quality, Value, and Fashion. How would you capitalize on our strengths to better communicate what we're famous for?"

Duncan Berkshire: "My question for all of you is this ... are you truly known for quality, value, and fashion? Seriously, have you asked your customer if that is what you're known for? You use your catalogs to tell the customer you're known for quality, value, and fashion. Gliebers Dresses isn't what Gliebers Dresses says it is. Gliebers Dresses is what the customer perceives Gliebers Dresses to be."

Meredith Thompson: "Show me where you can purchase fashion at our level of quality and value?"

Duncan Berkshire: "Again, it has nothing to do with what you actually are, it has everything to do with what the customer perceives you to be. For instance, how do you get your message out to potential new customers?"

Pepper Morgan: "We go to ResponseShop, an industry-leading co-op, and we pay them six cents a name for one-time use, and they use some geeky math formula to decide the potential new customers that should hear our message."

Duncan Berkshire: "Exactly. Now it is two months later, and you want to communicate your value proposition to potential new customers. What do you do?"

Meredith Thompson: We go back to ResponseShop, and we pay them six cents a name for one-time use, and they use some geeky math formula to decide the potential new customers that should hear our message, many of whom heard the message last time. This is an industry best practice, everybody does this! We use what they call a 'harmony model' to identify prospects who have purchased merchandise that is 'in harmony' with the merchandise we offer."

Duncan Berkshire: "Exactly. Are you renting the same names, or are you renting different names?"

Pepper Morgan: "Oh, we don't get to know anything about the names we're getting access to, that information is controlled by the analysts at ResponseShop."

Duncan Berkshire: "Exactly. See, your strategy for communicating quality, value, and fashion to potential new customers is to let a math whiz who doesn't even work at your company dictate who hears your message. You have no marketing strategy for how you will evangelize your brand to new customers, and you have no communication strategy for educating customers about your quality, value, and fashion proposition. If you are from outside the catalog industry, like I am, the strategy sounds highly suspect. Why would you ever let a math whiz at ResponseShop dictate your communication strategy?"

Roger Morgan (IT and Operations): "Duncan, how many chocolate chips are needed for the perfect chocolate chip cookie?"

Duncan Berkshire: "I have no idea. But I really like those Otis Spunkmeyer cookies, hot out of the oven, with a tall glass of cold chocolate milk."

Glenn Glieber: "Oh boy. OH BOY! That sounds so good. What's the name brand, Otis Spunkmeyer? Are they available in the freezer section? Dorothy's got to get those for me."

Meredith Thompson: "But we aren't letting ResponseShop control our message. We have a website with secure e-commerce transactions. Our website exudes quality, value, and fashion."

Duncan Berkshire: "And how do you drive traffic to the website?"

Meredith Thompson: "We have existing customers, we have the prospects that ResponseShop decides to mail on our behalf, and we have all of those customers who click on keywords."

Duncan Berkshire: "And who decides if your keywords even make it to the first page of a search engine?"

Pepper Morgan: "Obviously, our paid search program is optimized against our primary competitors and the long-term value of various keywords. A decent amount of our traffic, however, comes from natural search."

Duncan Berkshire: "Exactly. Who controls that traffic?"

Lois Gladstone: "The search engines control the traffic."

Duncan Berkshire: "Exactly. Mathematical algorithms from the search engines control your website traffic. Mathematical algorithms from ResponseShop control your catalog traffic. What, exactly, do you control?

Roger Morgan: "Duncan, what city are Longaberger Baskets made in?"

Duncan Berkshire: "Dresden, Ohio."

Meredith Thompson: "We control the merchandise we offer. We control the price. We control how the merchandise is creatively presented to the customer. We control our e-commerce platform. We control the quality of the paper in our catalogs. We control the contact strategy to existing customers. We control the versioning of our e-mail program. We control our expenses. We control everything, don't we?"

Duncan Berkshire: "Exactly. The job of a catalog brand marketer is to control the traffic. You have no control over your traffic, algorithms decide everything for you. You trust algorithms to evaluate whether prospects cares about quality, value, and fashion. The catalog brand marketer clearly communicates quality, value, and fashion in a way that resonates with the customer, so that the traffic that comes to your website is already pre-qualified, is already wanting what you have to offer. We'll have to invest money to do that. If you decide to hire me, that's what you are getting. You are getting an 'algorithm-free' approach to driving qualified traffic to your brand. Who are you going to trust, geeky math algorithms, or me and my decades of experience growing the Blast Candy Bar empire?"

Kevin: "Duncan, what role should a Chief Marketing Officer play in helping a catalog company find the optimal mix of channels?"

Duncan Berkshire: "I believe the CMO is responsible for teaching all employees how customers are interacting with emerging channels. The CMO must demonstrate that customers are shifting behavior from existing to emerging channels. The CMO must create a roadmap that helps employees see that there is nothing to fear as customers change behavior. And then, the CMO must make darn sure that s/he protects the profit and loss statement, working with the finance team. I don't think the CMO needs to be able to calculate a profit and loss statement, but he should fully lean on the CFO for that responsibility. This is not a time for careless mistakes. I mean, I look at your business, and I'm thinking there isn't much difference between your business and the newspaper industry --- the only difference being you monetized your algorithm-based online traffic, whereas the newspaper industry gave away their online content. And let's go a step further. Your online competitors don't charge for shipping and handling, you appear to make several million dollars a year in shipping and handling revenue. You're going to need to have a plan in place to deal with this issue --- there is absolutely no reason why any rational customer will, in the future, choose your merchandise over a competitor when you require her to pay an additional $14.95 to have the merchandise shipped to her in 5-7 business days."

Glenn Glieber: "I'm afraid we'll have to cut off these fascinating insights right here, folks, we need to get Duncan on a plane. Thanks everybody for the stimulating discussion. Now on to our next topic. Pepper, I'd like to add four pages to the January catalog. Now I know we cut four pages out of the January catalog last month to fund Candi's customer initiatives, but I'm starting to think that was a bad idea. Can you recommend how we might merchandise the four additional pages to make the biggest splash, coordinate with Meredith on the strategy, and then work with Lois to add the expense to the profit and loss statement? Thanks!"

Presentation On Web Analytics And OMS

Download this presentation on how Web Analytics and the Online Marketing Simulation work together to give you a peek into the future of your online business.

There are more than three-dozen slides in the .pdf file, chocked-full of ways that I'm asked to apply the OMS to the challenges CEOs face when trying to understand where their online business is heading over the next five years. The future sales trajectory of the online channel has become a really hot topic, now that organic online growth is drying up.

If you're technically adept, you can take the framework I outlined and create your own OMS. Or, give me a holler, and I'll be glad to build an OMS that outlines the future of your online business.

Let me know what you think of the presentation --- especially those of you in the Web Analytics community, what are your thoughts?

Join Me At IMC Vancouver, September 16-18

I've been invited to speak on a panel at the Internet Marketing Conference in Vancouver, September 16 - 18!!

The keynote speaker is Avinash Kaushik, so that alone is a can't miss, isn't it?

I'll be on a panel on Friday morning. The topic is "Measuring Online Marketing in a Real Time World". I think the conference organizers did a nice job of getting panelists ... I'll share the stage with Manoj Jasra, Braden Hoeppner, Amanda Rose, Stephane Hamel, and Eric Hansen. You can pretty much guess that I'll be talking about what I see in the OMS runs I've worked through.

If you are attending, please take advantage of the 20% off speaker discount --- enter the code "imc-speaker" when registering, in order to receive your discount.

I look forward to speaking with you at the conference!

Gliebers Dresses: Free Shipping

Welcome to the Gliebers Dresses Executive Meeting!

Glenn Glieber (Owner): " ... so my nutritionist tells me that I have to eat heart-healthy food. Well cripes. She gives me this recipe for what she calls 'heart healthy muffins'. And they really aren't that bad, even with two tablespoons of FiberSure in the recipe and a whole boatload of turbinado instead of brown sugar. I baked eight of these things for the county fair, I entered them in the 'healthy muffin' category. Dorothy and I went to the fair around noon yesterday to check on my exhibit, and guess what? I'm the only person who entered anything in the 'healthy' category. But get this ... they give me a second place ribbon. How in the name of Earl Tupper do you get a second place ribbon if you are the only entry in a category?"

Meredith Thompson (Chief Merchandising Officer): "Kevin, is that you?"

Kevin: "Yup, it's me."

Candi Layton (HR and Chief Customer Officer): "Lois, can you continue your discussion about our free shipping problem?"

Lois Gladstone (Chief Financial Officer): "Candi was out on Twitter yesterday, and she noticed that there's a ton of Twitterers who tweet about free shipping."

Candi Layton: "So I searched for Gliebers Dresses and free shipping, and sure enough, there's a bunch of our offer codes out there, and it looks like customers go to Twitter to use them. They're the same codes I authorized Roger to use when customers have a problem ... you know, the customer has a bad experience, so we give them free shipping to make everything better. Now I've heard you can find these things on Google, too, but I'm a social media person, and Google is so old-school, you know, I mean, they just aren't even a factor in the real-time web."

Lois Gladstone: "I noticed when preparing the preliminary August profit and loss statement that free shipping, outside of the 3,000 customers who are now in the loyalty program, was eight percent of sales, eight percent --- and we didn't have a single free shipping promotion all month."

Roger Morgan: "I queried the customer database, and yes, these are valid codes, straight from the call center, the very codes we created to act upon instances where the customer needs to be offered free shipping to make up for a bad experience."

Candi Layton: "I really think my customers are telling these websites the free shipping codes on purpose. I think they are taking advantage of our kindness."

Lois Gladstone: "Or maybe somebody in the call center is in on it --- they get a cut if they tell these websites what the codes are."

Roger Morgan: "My employees would never do that. They're the best in all of New England."

Lois Gladstone: "Pepper, can't you do something about this?"

Pepper Morgan (Interim Chief Marketing Officer): "Like what?"

Lois Gladstone: "Shut these websites down, enter into litigation, something, do something!"

Pepper Morgan: "Why don't we just change the codes, each customer service free shipping code expires daily, so then the coupon sites can't keep up with us?"

Roger Morgan: "Oh, we cannot do that. Our order entry system requires that offer codes be tied to either calendar months, fiscal weeks, or catalog source codes. So the best we can do is offer new codes on a monthly or weekly basis."

Candi Layton: "Do you understand what a terrible customer experience this creates? You work hard to be part of our loyalty program, you spend a fortune so that you can earn free shipping for the rest of the year, and then some customer searches Twitter and finds codes to use to buy from us, codes that give the customer free shipping."

Pepper Morgan: "But Candi, we created the bad customer experience by trying to improve the customer experience without attempting to understand how the customer experience might go sideways when a customer is given a free shipping offer code."

Lois Gladstone: "Eight percent of net sales will be tied to free shipping this month. It was the difference between being profitable and being unprofitable."

Roger Morgan: "I've been saying for a year that we need to upgrade the order-entry system. If we invested the money in our infrastructure, we wouldn't have this problem."

Candi Layton: "Folks, I didn't mean to do this. I was just trying to improve the customer experience. I never meant to give away $30,000 of shipping revenue."

Roger Morgan: "What would Chip Cayman do at a time like this? Maybe we can get him on the phone?"

Meredith Thompson: "Kevin, how would you handle this?

Kevin: "First, stop creating offer codes for free shipping unless you're going to run an actual free shipping promotion. And if you're going to run an actual free shipping promotion, give free shipping to everybody, regardless whether they have a code or not. Make the darn code ubiquitous --- print the thing in catalogs and e-mail campaigns and put it on the homepage of the website and put it up on Twitter, make sure folks share it via Facebook, allow them to text it to their friends --- allow every single customer on the planet to share the code with their friends and family, and make sure the code expires in a week so that it creates a sense of urgency. Instead of making free shipping a scarcity, make it something that is available for everybody. That would make for a great customer experience. Given the size of your business, you'd load up on new customers, too. If you did that, it would almost be like free marketing, given the PR you'd get."

Glenn Glieber: "I love free marketing!"

Kevin: "Second, go in the database, and correlate people who were using the code with employees who were authorized to give out the code to help improve the customer experience. This way, you may find if you have employees who link the codes to websites and Twitter accounts. Roger can deal with any employees on a one-on-one basis, if employees were causing the problem. I can run this analysis for you."

Roger Morgan: "Maybe our loyalty program should be linked to some sort of card, a card with a number on it that can be accepted by the order-entry system. I'm clearly not an expert at this, but the card could link to a credit card number in the database, and if anybody uses the loyalty card number and does not use a valid credit card, then the transaction is stopped right there. I believe the order entry system can handle this, because there are enough fields available to support a loyalty card number."

Pepper Morgan: "Maybe when we give away free shipping as part of fixing a customer service issue, we tie free shipping to each employee's employee number --- enter the employee number into the order entry system, and then track what happens. I realize this is a gross oversimplification of our order entry system, but it would be wise to spend a bit of money modifying the system to handle the things you can control. We may not be able to stop a Twitterer who tells her followers about your free shipping offer code. We can control the elements of our order entry system, and how they interface with the customer."

Kevin: "And third, we keep reading about all of those KPI (key performance indicator) dashboards. Well, add expense by free shipping by code to the dashboard. Theoretically, you want to give away free shipping from your loyalty program, so that should be something you post to the dashboard every week, and should be something you try to get people excited about. Conversely, post free shipping expense in all of these other codes to the dashboard, and create an incentive to keep that expense down --- encourage people to reduce fraud."

Glenn Glieber: "As long as it doesn't cost more than a few thousand dollars to update the order entry system, then let's go ahead and fix this thing. Roger, figure out some workaround and get this resolved by the end of day today. Ok, let's move on to the next issue that roasted my pork, folks. As you know, our annual picnic is on September 12. And somehow, yesterday, at the 4-H auction at the fair, I was the top bidder for a 219 pound pig named Gertie. I was just trying to drive up the price so that Sarah Wheldon would pay through the nose. I kept thrusting my paddle up in the air, and she kept thrusting her paddle in the air, and the auctioneer keeps yelling "how about $3.40?" and the guy next to the auctioneer screams "YEP" and then the auctioneer looks at me and says "how about $3.50?" and I raise my paddle and the guy belts out another "YEP" and this exchange just keeps going back and forth. And then, out of nowhere, Sarah just stops. Well, the audience bursts into a wild applause, I mean it was like I just won the state basketball tournament or something! They tell me that I just paid $8.60, a record for the fair. I have no idea who these people are who keep patting me on the back. Some guy can't stop laughing, he calls me a 'freakin rube', well, I didn't appreciate that one. It's wild excitement, I'm telling you. And then Pamela, this fourteen year old freckled girl with dusty brown hair in a pony tail, the very girl selling the pig in this straw-covered, foul smelling arena, comes up to me and with tears in her eyes says that I just paid for her first year of college. Well, I say, 'private, public, or community?', thinking community college because I thought I paid $8.60, but in reality, I paid $8.60 per POUND for a 219 pound pig. Do the math, folks, because that's a lot of bacon to shell out for a pig. Dorothy is just livid, she's telling me she wanted to go to Mirival for some sort of organic dining week that she read about in O magazine, and now she's stuck sharing barley, oats, and wheat with a 219 pound pig named Gertie. Anyway, I'm thinking that we're going to solve this problem by having a pig roast for our annual picnic on September 12, and I'm thinking that Roger is going to prepare the best pig roast in history, so thanks Roger for picking up the ball on this important issue! Gertie is staying at Dairyview Farms, just call 555-555-3984 and give them slaughtering instructions."

OMS: Shopping Cart Abandonment

Web Analytics software and practitioners do a very nice job of illustrating the rate that various segments of customers abandon shopping carts.

The next step we can take on this journey is to understand what the consequences are of an abandoned shopping cart. In other words, given that a customer abandoned a shopping cart, we need to measure what happens next, and then quantify the sales and profit impact of what happens next.

Recall the OMS framework authored over the past few weeks ago. We can add variables to this framework. Add dummy variables that tell whether the customer abandoned a shopping cart in the last week (1 = yes, 0 = no), last month (1 = yes, 0 = no), or even last year (1 = yes, 0 = no). Add these variables to your pre-post datasets, and run them through your factor analysis, integrating shopping cart abandonment with channel and merchandise preferences. Enter the variables into your regression models, too, while you're at it. Essentially, you make shopping cart abandonment part of the 100 to 1,000 segments that forecast future customer behavior.

Or define the information however you like ... no rules here!

At this point, you'll be able to run simulations that show how customers evolve, based on past shopping cart abandonment activity.

For instance, we can compare four customers. We'll assume that prior to last month, all other attributes are equal:

1. Customer purchased merchandise online last month.
2. Customer abandoned a shopping cart last month.
3. Customer visited website last month, didn't put anything in shopping cart.
4. Customer didn't bother to visit website last month.

For each of the four customers, we run a five year sales simulation, based off of past customer behavior. For 1,000 simulated customers, you might find an outcome that looks like this (your mileage will vary):

1. Purchaser: Year 1 = $100,000, Year 2 = $70,000, Year 3 = $50,000, Year 4 = $35,000, Year 5 = $25,000, Total = $280,000.
2. Shopping Cart Abandoner: Year 1 = $85,000, Year 2 = $65,000, Year 3 = $45,000, Year 4 = $35,000, Year 5 = $25,000, Total = $255,000.
3. Visitor, No Cart: Year 1 = $60,000, Year 2 = $40,000, Year 3 = $30,000, Year 4 = $20,000, Year 5 = $15,000. Total = $165,000.
4. No Visit: Year 1 = $40,000, Year 2 = $25,000, Year 3 = $15,000, Year 4 = $12,000, Year 5 = $10,000. Total = $102,000.

See, within the OMS context, we get a different level of business intelligence. In this example, an abandoned shopping cart costs us $25,000 of demand per 1,000 customers ... a loss of $25 per customer, over five years.

But worse, look at the website visitor who doesn't even make it to the shopping cart. In this case, the unconverted customer (no shopping cart, no purchase) spends $115,000 less per 1,000 customers ... a loss of $115 per customer, over five years.

Of course, even the unconverted visit is worth something. We get an incremental $63,000 per 1,000 simulated customers when a customer visits, vs. no visit at all. In other words, OMS is projecting in this instance that there is a downstream value to every action on a website, and that value can be calculated via five-year simulations. In this case (and remember, your mileage will vary --- use the principals here to estimate the numbers for your own business).

• An visit is worth an incremental $63,000 per 1,000 customers over five years, $63 per customer.
• An incremental item into the shopping cart adds $90,000 per 1,000 customers over five years, $90 per customer.
• An incremental purchase adds $25,000 per 1,000 customers over five years, $25 per customer.

In Web Analytics, we look back in time to report what happened. In OMS, we look forward, simulating a likely future outcome based on what happened in the past. Combined, Web Analytics and OMS make good business sense, and provide the answers a CEO frequently looks for.

If this style of shopping cart abandonment analysis makes sense to you, contact me for details on an OMS project!

OMS: Up-Selling and Cross-Selling

Up-Selling and Cross-Selling merchandise to a customer is an established e-commerce best practice, right? Retailers love to capture the additional margin dollars at the end of a transaction by offering the customer the opportunity to add an item to her order.

With a standard Web Analytics software tool, we can identify how customers respond to a cross-sell or up-sell opportunity.

With the Online Marketing Simulation (OMS), we can see what the downstream impact is of a customer who responds to an up-sell or cross-sell opportunity.

Let's simulate 1,000 new customers who purchased three items for $50 each via paid search. In my dataset, I have eight merchandise divisions. Let's assume that the customer purchased three items from merchandise division #3. Here's a five year simulated run for this customer:

• 12 Month Repurchase Rate = 24%.
• Future Demand: Year 1 = $51,000, Year 2 = $35,000, Year 3 = $28,000, Year 4 = $25,000, Year 5 = $23,000.
• Merchandise Division #1 Buyers: Year 1 = 22, Year 2 = 15, Year 3 = 12, Year 4 = 11, Year 5 = 11.
• Merchandise Division #2 Buyers: Year 1 = 26, Year 2 = 18, Year 3 = 15, Year 4 = 13, Year 5 = 12.
• Merchandise Division #3 Buyers: Year 1 = 128, Year 2 = 72, Year 3 = 52, Year 4 = 45, Year 5 = 42.
• Merchandise Division #4 Buyers: Year 1 = 113, Year 2 = 65, Year 3 = 48, Year 4 = 41, Year 5 = 38.
• Merchandise Division #5 Buyers: Year 1 = 66, Year 2 = 42, Year 3 = 34, Year 4 = 30, Year 5 = 28.
• Merchandise Division #6 Buyers: Year 1 = 20, Year 2 = 15, Year 3 = 13, Year 4 = 12, Year 5 = 11.
• Merchandise Division #7 Buyers: Year 1 = 28, Year 2 = 19, Year 3 = 15, Year 4 = 13, Year 5 = 13.
• Merchandise Division #8 Buyers: Year 1 = 36, Year 2 = 25, Year 3 = 19, Year 4 = 17, Year 5 = 16.

Ok, those metrics don't have much meaning unless you have something to compare them to. Now let's assume that you, the online marketer, were able to cross-sell or up-sell this customer one additional item, a $50 item in Merchandise Division #7.

How does this one additional item, a $50 item in Merchandise Division #7, impact the future trajectory of this customer? We'll pop the results into the OMS ... let's see what the simulation tells us!

• 12 Month Repurchase Rate = 41%.
• Future Demand: Year 1 = $104,000, Year 2 = $68,000, Year 3 = $48,000, Year 4 = $38,000, Year 5 = $33,000.

Let's just stop right there. The simulation suggests that a new paid search customer with this one additional item from a different merchandise division is instantly worth between 50% and 100% more. Clearly, your mileage will vary, some of you will experience no incremental long-term value, some of you will experience double or triple this outcome. The goal, of course, is for you to strategically think whether this issue has applicability to your business.

Here's how customers purchased from the eight merchandise divisions in my dataset.

• Merchandise Division #1 Buyers: Year 1 = 37, Year 2 = 28, Year 3 = 21, Year 4 = 18, Year 5 = 16.
• Merchandise Division #2 Buyers: Year 1 = 39, Year 2 = 33, Year 3 = 25, Year 4 = 21, Year 5 = 19.
• Merchandise Division #3 Buyers: Year 1 = 227, Year 2 = 123, Year 3 = 79, Year 4 = 61, Year 5 = 53.
• Merchandise Division #4 Buyers: Year 1 = 225, Year 2 = 119, Year 3 = 78, Year 4 = 61, Year 5 = 52.
• Merchandise Division #5 Buyers: Year 1 = 86, Year 2 = 73, Year 3 = 55, Year 4 = 45, Year 5 = 40.
• Merchandise Division #6 Buyers: Year 1 = 36, Year 2 = 28, Year 3 = 22, Year 4 = 19, Year 5 = 17.
• Merchandise Division #7 Buyers: Year 1 = 44, Year 2 = 35, Year 3 = 25, Year 4 = 21, Year 5 = 18.
• Merchandise Division #8 Buyers: Year 1 = 55, Year 2 = 43, Year 3 = 32, Year 4 = 26, Year 5 = 23.

Pay close attention to Merchandise Division #7. This was the division where the up-sell / cross-sell item was purchased from. There is some improvement in the number of buyers in this division. Now pay attention to Merchandise Divisions #3 and #4 --- these divisions are expected to get a significant bump in customers.

Yes folks, your actions in one area of your business cause unexpected changes in the business performance of another area of your business. In this example, the cross-sell of one item from Merchandise Division #7 causes Merchandise Division #4 to experience a significant improvement in performance within this customer segment (in fact, almost all divisions experience improvement). Merchandise Division #4, of course, had no role in either simulated transaction --- it simply benefits from something that happens elsewhere in your business.

Would you make different business decisions if you knew how this dynamic impacted your e-commerce business?

This is what Advanced Web Analytics, specifically, the Online Marketing Simulation (OMS) is all about. We're looking to see how the decisions we make today impact the future of our business. Most Web Analytics applications look backward, measuring what happened in the past. The OMS environment looks forward.

OMS: Nuts And Bolts, The Algorithm!

I promised some details!

Here's what I like to do. I'll take client data, and create a set of attributes that are of interest to the management team. In the dataset I'm currently working on, here are the attributes:

• Recency: Months Since Last Purchase.


• Demand12: Demand Spent In Past 12 Months.


• Demand99: Demand Spent 13+ Months Ago.


• Price_Item: Average Price Per Item Purchased.


• Items_Order: Average Number Of Items Per Order.


• 24 Channel Attributes: This business has twelve purchase channels (i.e. paid search, affiliates, etc.). I create 1/0 (1=yes, 0=no) indicators that tell if the customer purchased from that channel in the past 12 months, and if the customer ever purchased from that channel 13+ months ago. Dollar values can also be used instead of 1/0 indicators.


• 16 Merchandise Attributes: This business has eight tabs, if you will, across the top of the homepage, representing eight merchandise divisions. I create 1/0 (1=yes, 0=no) indicators that tell if the customer purchased from that merchandise division in the past 12 months, and if the customer ever purchased from that channel 13+ months ago. Dollar values can alos be used instead of 1/0 indicators.

So, this dataset has 45 variables, one row per customer. The file contains data through today.

Next, I need to reduce the dimensionality of the database. There's literally an infinite number of ways to combine the 45 variables, right? Somebody could have last purchased 1 month ago, spending $64.95, whereas another customer could have last purchased 1 month ago, spending $61.95.

I do this via a combination of Logistic Regression (Response), Ordinary Least Squares Regression (Spend), and "Factor Analysis" (Merchandise and Channels). Yes, I realize this is geeky.

The combination of Logistic Regression, Ordinary Least Squares Regression, and Factor Analysis result in a series of "strategic segments". Each segment is a combination of customer quality, channel preference, and merchandise preference. Some of the segments are very responsive, some are not responsive. Some buy from all merchandise divisions, some only buy from one merchandise division, and have a specific channel preference.

For smaller companies, I limit the number of segments to 100 or less. For bigger companies, I'll use 1,000 or more segments ... it all depends upon how many customers end up in each segment.

Once I determine what segment a customer resides in, I create a brand new dataset, replicating every variable for every customer as the customer looked exactly one year earlier (in social media, you might use a week timeframe instead of the yearly timeframe we use in e-commerce). I create the same segmentation strategy, and assign a segment id to each customer based on the way the customer looked last year.

Now each customer is assigned to a segment from one year ago, and a segment today. I aggregate this dataset down to every last-year / this-year segment combination (100 x 100 = 10,000 segment combinations). When simulated over five years, there ends up being 100 x 100 x 100 x 100 x 100 = lots of combinations!

Once I have the 10,000 segment combinations, I can take a sample customer (i.e. first time buyer purchasing an iPod via paid search), and simulate how that customer will migrate and evolve over the next five years. I can see what merchandise that customer will buy in the future, I can see the channels the customer will purchase from in the future, and I can calculate the incremental demand and profit the customer will generate.

Best of all, I can compare this customer vs. any other customer, to see how customers will evolve. Will a paid search iPod buyer evolve differently from an e-mail inkjet printer buyer? Will either customer use a retail channel in the future? Am I unwittingly altering the future trajectory of my business by optimizing for inexpensive keywords?

These are the problems that CEOs are asking me to solve for them, problems not easily answered by a typical Web Analytics toolset.

At a 30,000 foot level, that's the nuts and bolts behind the Online Marketing Simulation (OMS) that I've developed.

As we work through future examples, consider the following questions:

1. Can my Web Analytics software tool do this analysis?


2. Can my Web Analytics analyst do this analysis for me?


3. Can my Web Analytics software vendor do this analysis for me?


4. Can the leading Web Analytics consultants / bloggers do this analysis for me?

If the answer to each question is "no", then the Online Marketing Simulation (OMS) is something you'll want to investigate.

Gliebers Dresses: Marketing Candidate Interview Schedule

The Gliebers Dresses Executive Meeting will focus on candidates for the open Chief Marketing Officer position.

Glenn Glieber (Owner): "... it really is amazing that Sarah Wheldon is telling the world that Anna Carter is going to shut down their catalog division in 2010. Are they stupid? Is she stupid? Was she stupid when she worked here? She was the biggest catalog advocate in this whole company. She added all of those catalog in-home dates in order to grow sales. Now, she's being interviewed on CNBC, bragging about how Anna Carter will save all of this money, telling the world that there are enough online channels to more than make up for the sales lost by a paper catalog. I even heard that Catalog Decide, the leading opt-out vendor, is thinking of naming her their Executive of the Year. Cripes, all of this publicity will cause their outcome to be positive. But don't people understand that the catalog is the backbone of the brand? She's going to kill their business, I'm telling you. Their web sales will plummet by 40% or 50%, they won't have any telephone sales, and Anna Carter is going to simply 'go off'. Maybe Anna hired her to be the fall person for when this strategy fails."

Meredith Thompson (Chief Merchandising Officer): "Kevin, is that you?"

Kevin: "Yup, it's me".

Candi Layton (HR and Chief Customer Officer): "Well, Pepper and I combed through the 275 resumes that we received, and we've narrowed the field down to three highly qualified individuals. During the next two weeks, we will fly the candidates to New Hampshire."

Meredith Thompson: "Will we continue our long-standing tradition of group C-Suite interviews?"

Candi Layton: "Absolutely. There's no reason to mess with tradition here at Gliebers Dresses."

Roger Morgan (IT and Operations): "Oh, I'm so excited! It is so much fun to cross-examine potential candidates so that we can evaluate their skills and group dynamics. Lois, remember what I asked you when you interviewed with us last year?"

Lois Gladstone (Chief Financial Officer): "You asked me to tell you the capital of Nebraska."

Roger Morgan: "And the look on your face when you answered 'Lincoln' told me that you could handle pressure. Those dot.com folks at Google and Microsoft ask goofy questions like that, and look at what kind of candidates they recruit ... they get the best of the best, folks, while we all get the best of the rest. We need to compete with them, to use their tools to our benefit!"

Candi Layton: "So we have three candidates. Maria Garcia is the Online Marketing Executive at BlueDotRedDotGreen.com, an online brand that allows users to make personalized gifts. Duncan Berkshire is the Divisional Vice President of Brand Marketing for Blast Candy Bars, and Stan Klepsky was previously the Executive Vice President of Marketing for the Bentley catalog, they sell jewelry. He was downsized in December. I guess Bentley chose to promote the Online Marketing Director to the EVP/Marketing position."

Roger Morgan: "Just think of the questions I can ask, questions that will get these candidates out of their comfort zone!"

Meredith Thompson: "Were there any candidates that had fashion apparel experience?"

Candi Layton: "Well, Pepper, obviously. But otherwise, no, there were no candidates that were at a Sr. Management level with fashion apparel experience."

Meredith Thompson: "Why interview these folks, why not just put Pepper in the job?"

Roger Morgan: "Can we interview Pepper first? Pepper, quick, what is the capital of Idaho?"

Candi Layton: "Kevin, are there things that you look for when you interview marketing leaders?"

Kevin: "Regardless of the position, I like to create a 'quiz'. Since all interviews require some level of interpersonal banter, it is very likely that each candidate fails to receive equal treatment. The quiz has maybe five or ten open-ended questions. You're trying to learn how the candidate approaches certain issues."

Lois Gladstone: "What type of questions would you ask?"

Kevin: "I'd ask technical questions. For instance, if a catalog had 96 pages and was going to generate $3 million in sales, and you increase the catalog to 124 pages, what do you think the sales estimate is for this catalog?"

Roger Morgan: "$3.6 million?"

Kevin: "I'd ask the candidate how s/he would grow sales from catalog marketing, knowing that sales from catalog marketing have been in decline for more than a decade, just to hear how the candidate thinks about the problem."

Roger Morgan: "Mail more!"

Kevin: "I'd ask the candidate questions about the future of marketing. How would the candidate implement a mobile marketing strategy? How would the candidate measure whether social media is worth spending time on, assuming that social media will never be responsible for more than 1% or 2% of sales? How would the candidate decide which widgets to implement on the homepage? How would the candidate develop a 'pull marketing strategy'? How would the candidate integrate e-mail and social media? How many versions of an e-mail marketing campaign maximize sales? What would happen to the sales of e-mail subscribers if you stopped sending e-mail campaigns to them?"

Roger Morgan: "Do we have answers to any of those questions?"

Kevin: "I'd give the candidate a series of metrics from a recent pay-per-click campaign, and ask the candidate to calculate profit-per-new-customer. I'd give the candidate a series of events, you mail a catalog on June 1, the customer receives an e-mail on June 3, the customer orders on June 5 after clicking through the e-mail ... and then I'd ask the candidate to determine the percentage of the order that was driven by the catalog, vs. the percentage of the order driven by the e-mail campaign. You're looking to see how the candidate thinks, and you can objectively compare the answers of each candidate. And I'd ask the candidate theoretical questions about how the candidate would deal with promotions and firings and determining bonus payouts and conflicts with the owner."

Candi Layton: "Kevin, can you come up with the list of questions, and then we'll let each candidate know that there will be a one hour quiz?"

Kevin: "Sure."

Roger Morgan: "I'm really looking forward to this!"

Glenn Glieber: "Ok folks, on to the next topic. Lilly Benson in Accounts Payable says that a deer stands outside her window every day, eating our flowers and, in general, the deer stares at her and freaks her out. She wants the deer shot. She says it is an eight pointer, so it would be quite the prize for somebody. Jennifer Tillman at the Call Center heard about this, and thinks that is an inhumane way to deal with a simple problem. Jennifer wants to spray the plants with a formula that discourages deer from eating the plants, and then Jennifer wants to trap the deer, and haul the deer to Maine. But Pat Thorson in design lives in Maine, and thinks it is wrong to transport animals across state lines. Roger, can you develop a plan to deal with this deer situation by early this afternoon?"

OMS: The Online Marketing Simulation

This is the fourth part of our series on Advanced Web Analytics and Online Marketing Simulations (OMS).

The goal of an Online Marketing Simulation (OMS) is to help us see how decisions that are made today influence the long-term health of our business. We're going to use an analysis process that is not commonly, if ever, used in Web Analytics.

We manage the Online Marketing Simulation (OMS) by linking conditional probabilities, simulating how a group of customers are likely to evolve over the next five years (or if you're analyzing social media, maybe the next five days!).

Let's look at a very simple example. You have three micro-channels in your online business.

1. Online Orders via E-Mail Marketing
2. Online Orders via Paid Search
3. All Other Online Orders

In this simple example, 10,000 customers purchased in 2007 via paid search, not purchasing via e-mail marketing or via any other method of generating an online order. We follow the 10,000 customers to see how they evolve during 2008. Let's assume that the 10,000 customers migrated as follows in 2008:

• 6,000 did not purchase during 2008.
• 1,500 purchased via all other online orders.
• 1,200 purchased via paid search.
• 200 purchased via paid search and all other online orders.
• 700 purchased via e-mail marketing.
• 100 purchased via e-mail marketing and all other online orders.
• 200 purchased via e-mail marketing and paid search.
• 100 purchased via e-mail marketing, paid search, and all other online orders.

Since we are analyzing three micro-channels in this example, all via yes/no indicators, we have 2*2*2=8 possible future outcomes.

The majority of customers (6,000 of the 10,000, 60%) did not purchase during 2008.

Notice that 1,700 customers purchased via paid search during 2008. This is one of the interesting things that we don't take into account when using the web analytics tools from the leading paid and free vendors to measure conversion rates --- we don't factor in how today's actions influence tomorrow's business. In this example, 10,000 paid search customers in 2007 yield 1,700 paid search customers in 2008.

Are you budgeting for future paid search activity that you are causing because of today's paid search optimization activities?

This is what the Online Marketing Simulation (OMS) environment does. We look at the future trajectory of all customers. Instead of looking at three dimensions (paid search, e-mail, all other), we look at a dozen or two dozen or more dimensions. We look at many combinations of prior activity, measuring the percentage of customers who migrate to a future state of activity. And we don't have to look only at advertising micro-channels, we can fold in the merchandise categories the customer purchases from (or views online if you wish). Once each customer is placed in his/her future state, we replicate the process, showing where the customer will migrate in year two, then year three, then year four, then year five.

In the example above, we can estimate how much paid search expense we will incur over the next five years because of today's paid search and conversion rate optimization practices. We can estimate how many customers will purchase via e-mail marketing over the next five years because of today's paid search and conversion rate optimization practices. We can see how one merchandise category will grow or shrink if we change our e-mail marketing strategies. We can sum demand, expense, and profit, short-term and long-term.

In the next OMS post, we'll begin to work through an actual dataset with numerous dimensions, so that you can see how the Online Marketing Simulation (OMS) environment really works. The example will be representative of the type of consulting I do for clients, helping them understand how the online channel will evolve based on today's decisions.

As we work through examples over the next month, ask yourself four questions after each post:

1. Can my Web Analytics software tool do this analysis?
2. Can my Web Analytics analyst do this analysis for me?
3. Can my Web Analytics software vendor do this analysis for me?
4. Can the leading Web Analytics consultants / bloggers do this analysis for me?

If the answer to each question is "no", then the Online Marketing Simulation (OMS) is something you'll want to investigate.

Gliebers Dresses: Winners And Order Starters

It's time for the Tuesday Gliebers Dresses Executive Meeting.

Glenn Glieber (Owner): "So what song do all of you think we should try to license for our annual Homecoming celebration? I'm partial to 'I'm Still Standing' by Elton John."

Meredith Thompson (Chief Merchant): "Kevin, is that you?"

Kevin: "Yup, it's me."

Pepper Morgan (Interim Chief Marketing Officer): "Here's our problem, Kevin. We want to know what we should advertise to our customers."

Meredith Thompson: "See, I think it is important to ride winners, you know, items that work year-in and year-out. I think we should beat those puppies into the ground, extracting as much profit as is humanly possible out of them."

Pepper Morgan: "And I think our brand needs a breath of fresh air. We're all about fashion, and fashion changes, all the time."

Meredith Thompson: "But we're lucky if we hit on three out of ten new items that we introduce. New merchandise is risky. You merchandise pages four and five of a catalog with new merchandise, and if that merchandise fails, we're sunk."

Pepper Morgan: "If we don't feature the new merchandise, then the customer perceives that our brand is stale. Reese Witherspoon didn't wear one of our dresses because we ran it on the homepage for seventeen consecutive months."

Meredith Thompson: "I think we need to protect profit, right Lois? We're not in a position where we can just feature risky items at the front of a catalog, on the homepage or key landing pages, or in e-mail marketing campaigns."

Kevin: "There's a few things we do know. We know that the product that has always worked best has less risk associated with it, and as a result, has better productivity. We also know that the items that work best in each catalog, on average, are new products that go absolutely crazy. We also know that the items that are dogs in each catalog are, on average, new products. Our 2010 contact strategy employs a strategy to capitalize on this issue. Recall that the small page count catalogs will feature only the best products. Because we can count on the productivity to be high, and because the page counts are small, we can mail very deep into the customer file and prospect list. With new products, the risk is greater, so we only advertise new products to the best customers, thereby mitigating the risk of offering a poor-performing product to a poor-performing customer."

Meredith Thompson: "But what do you feature in a catalog or e-mail campaign or landing page? In other words, even in one of our smaller catalogs, do we feature newer products, or time-tested winners?"

Kevin: "Have you run an 'order starter' analysis?"

Pepper Morgan: "What is that?"

Kevin: "If your order entry system captures the first item a customer asks for in an order, followed by the second item, then the third item, and you assume that this is the order of purchase intent for the customer, then you can record the items that cause customers to 'start' an order. Roger, does the order entry system record information in this manner, and then feed the customer database in this manner?"

Lois Gladstone (Chief Financial Officer): "Roger is out of the office today, he's speaking at an e-commerce conference about multichannel marketing integration. But I believe the databases are populated that way."

Meredith Thompson: "What does Roger know about multichannel marketing integration?"

Kevin: "Any item that appears first in an order is given a value of '1'. The item that appears second is given a value of '2', and so on. Take all of your new and existing items featured in catalogs and e-mail campaigns, and see which items 'start' orders. In theory, those are the items that could be merchandised at the front of a catalog, or featured in an e-mail campaign. Typically, but not always, you'll see that the first twenty pages in a catalog should have a decent number of order starters featured. You'll often see that e-mail campaigns work well when order starters are featured in the creative. Your mileage may vary, but at least do the analysis to find out."

Candi Layton (HR and Chief Customer Officer): "I'll ask my Twitter followers to weigh in on the topic, ok?"

Lois Gladstone: "We'd be better off having Reese Witherspoon in the first twenty pages of every catalog, and in every e-mail campaign. She can start some orders for us!!"

Pepper Morgan: "We did ask her PR team if she'd be willing to accept compensation in exchange for a series of catalog and e-mail marketing and homepage appearances. Her PR team turned down our request."

Lois Gladstone: "How about Morgan Fairchild? Is she available?

Candi Layton: "Who?"

Lois Gladstone: "Or what about Susan Sarandon? Didn't she wear a Gliebers Dress in Bull Durham?"

Meredith Thompson: "No, that was an Anna Carter dress."

Lois Gladstone: "Rats."

Glenn Glieber: "I think we've exhausted this topic. Thanks Kevin, we'll have Bow Tie Guy run the order starter analysis for us. Now let's get back to the theme song for the annual Homecoming celebration."

Candi Layton: "What about 'Every Morning' by Sugar Ray? I mean, we come in here and work every single morning, don't we?"

Lois Gladstone: "What about 'Every Day Of The Week' by Jade? We come in here and work every day of the week, don't we?"

Meredith Thompson: "Rainy Days And Mondays Always Get Me Down?"

Lois Gladstone: "Wasted Days And Wasted Nights by Freddy Fender?"

Glenn Glieber: "PEOPLE, I'm serious! I need a theme song."

From Conversion Rate to Repurchase Rate to Multiple Probabilities

We're up to the third part in our series on Web Analytics and Online Marketing Simulations (OMS).

My central thesis is that by emphasizing conversion rates, we optimize our business based on the advertising sources that cause a customer to purchase now. By doing this, we create an inefficiency. We overlook customers who yield a positive outcome in what we deem an inefficient manner.

Here's an example.

• We all know that pay-per-click customers convert at less-than-thrilling rates.
• We know that pay-per-click customers can be expensive, maybe costing us $0.10 per click, or $0.40 per click, or $0.70 per click.
• Over time, pay-per-click customers can become e-mail subscribers.
• And e-mail subscribers often have higher-than-average conversion rates if they click-through an e-mail campaign.
• And e-mail marketing is really close to free, having virtually zero variable cost.

If we want to optimize conversion rates, we'll steer ourselves away from expensive pay-per-click programs with low conversion rates, right? At the same time, we'll want to maximize our e-mail marketing program, with low costs and high conversion rates.

If we want to optimize repurchase rates, we'll take a different action. We want pay-per-click customers, because pay-per-click customers become e-mail subscribers. We want to optimize the multi-year process of acquiring an expensive pay-per-click customer who becomes a profitable e-mail customer.

If we optimize via conversion rate, we won't "seed" our business with the pay-per-click customers who become e-mail subscribers with high conversion rates. We optimize our business in the short-term, but create a long-term inefficiency that limits our ability to grow over time.

We have an opportunity to add to our responsibilities. We have an opportunity to measure what are called "conditional probabilities". Here are examples of conditional probabilities:

• What is the probability of a customer becoming an e-mail subscriber, given that she last purchased via pay-per-click?
• What is the probability of a customer becoming a loyal customer, given that she has become an e-mail subscriber?
• What is the probability of a customer buying from multiple channels, given that she has become a loyal customer?

By linking each of these conditional probabilities, we arrive at a customer that generates an optimal amount of profit, over time. Within each step, we may have numerous instances of sub-optimal conversion rates, but those sub-optimal situations result in a customer that is optimally profitable. We combine conditional probabilities with demand and profit calculations, allowing us to simulate the future based on the actions we manage today.

From an Advanced Web Analytics standpoint, we create a table that records customer actions in a prior period of time, and in a future period of time. In the future period of time, we also tag the amount of demand the customer generated in the future period of time. The list of variables below is not exhaustive, and variables can be combined (receive catalog, buy via pay-per-click), creating what I call "micro-channels".

Prior Period of Time (1 = yes, 0 = no).

• Did customer visit the website?
• Did customer put merchandise in a shopping cart?
• Did customer purchase from the website?
• Did customer purchase multiple times from the website?
• Did customer purchase via e-mail?
• Did customer purchase via pay-per-click?
• Did customer purchase via affiliates?
• Did customer purchase via offline catalog marketing?
• Did customer purchase via display ads?
• Did customer purchase via social media?

The same set of variables are replicated for a future period of time, along with demand and profitability (if available) metrics. Obviously, the same customer will not have the same attributes, as customer behavior changes.

The prior timeframe is usually defined as a year, the future timeframe is usually defined as a year. That being said, there's no reason you cannot explore different timeframes, weeks, months, seasons, etc. However, you identify more inefficiencies, more opportunities for profit, when you lengthen the timeframe.

When the dataset is created, the analysis begins. We begin to link the conditional probabilities together, finding customer behavior that leads to long-term sales and profit. In our next blog post in this series, we'll begin to explore how this information comes to life.

Gliebers Dresses: The Aftermath

Welcome to the Gliebers Dresses Executive Meeting.

Glenn Glieber (Owner): "... maybe the most amazing comment came from our old friend, Sarah Wheldon. When the Times asked Sarah what Anna Carter thought of Reese Witherspoon wearing a dress from Gliebers, Sarah said that, and I quote ... 'Gliebers is a great company, and a worthy competitor. But they are a lot like a brontosaurus stuck in a tar pit, facing extinction. They are simply not nimble enough, nor in a position to capitalize on their own good fortune.' What did we ever do to her to cause her to spew venom like that?"

Meredith Thompson (Chief Merchandising Officer): "Kevin, is that you?"

Kevin: "Yup, it is me."

Pepper Morgan (Interim Chief Marketing Officer): "Kevin, have you had a chance to analyze the traffic from the Reese Witherspoon event?"

Kevin: "Yes I have. Our Multichannel Forensics analysis tell us that 7,000 customers purchased a dress during the past three days. The forecast was for 3,000 orders. Of the 7,000 orders, 4,500 came from first time buyers, while 2,500 came from existing buyers. We expected to have 1,000 orders from first time buyers and 2,000 orders from existing buyers. So, we have a 4.5x increase in orders from first time buyers, and a 25% increase in orders from existing buyers."

Roger Morgan (Operations and IT): "It has been amazing to watch online conversion rates. Conversion rates were in the mid-20% range three days ago. Today, traffic is five times that of normal levels, but conversion rates are only around 2%. In other words, those who had to have the dress got the dress on the first day, and now, we're getting lots of traffic that seems to want to see just who the heck Gliebers Dresses is."

Kevin: "It will be very important to follow the new buyers, folks. After we run our matchback program and remove all new customers who received a catalog, we'll have a pool of customers that we can code as being acquired during the 'Reese Witherspoon Event'. At other companies, customers acquired in this manner tend to be less valuable, long-term, and tend to be less responsive to traditional advertising. The customer was buying an 'event', if you will, she wasn't necessarily buying from Gliebers Dresses. At least that's a hypothesis that we'll have to prove or disprove."

Meredith Thompson: "Oh I hope you are wrong. These customers have to love Gliebers Dresses, or they wouldn't buy our dress, would they?"

Candi Layton (Chief Customer Officer and HR): "You should hear what people are saying on Twitter. @ReeseIsLegallyGreat said "I can't wait to get my Reese Witherspoon cocktail dress from Gliebers. Hubby promised to take me to Olive Garden if I wear it!" And look at this comment from @Fashion092658, she says "Reese Witherspoon and Gliebers Dresses are a perfect fit!"

Pepper Morgan: "We did get in touch with Reese Witherspoon's PR folks. Unfortunately, her PR team communicated to us that we are not to, in any way, promote her affiliation with our dresses in the catalog or on the website."

Roger Morgan: "What about e-mail? Have we found a loophole here?"

Pepper Morgan: "I think they mean that they don't want us to promote her via our brand."

Lois Gladstone: "Just running some back-of-the-envelope numbers here. Sales will increase by about a million dollars this month, yielding about $300,000 or more of incremental profit. I'd be willing to take a third of that and give it to Ms. Witherspoon as a promotional fee if she were willing to grace the cover of our catalog."

Roger Morgan: "I'd prefer to take $100,000 and make website improvements that increase conversion rate."

Candi Layton: "I'd prefer to take $100,000 and give every one of these customers expedited shipping, so that they spread the word about how great Gliebers Dresses really is."

Lois Gladstone: "I'm serious, folks. Given what we've learned this week, show me a place where we'd get a better ROI than plastering Reese Witherspoon on the cover of our Holiday catalog?"

Meredith Thompson: "Scotty Jennings could design an entire line around Reese Witherspoon. Imagine ... 'the Reese Witherspoon Collection' from Gliebers Dresses, now available at Macys. Catalogs, e-mails, television commercials, true multichannel retailing too. We need to dream big, folks."

Pepper Morgan: "Ms. Witherspoon's PR team said that they did not wish to be associated with our catalog or website."

Lois Gladstone: "That's just what people say when they're looking for money. Toss her a quick $100,000, and she'll go on The Today Show and tell the world how much she loves us."

Meredith Thompson: "Come on Pepper, get Reese Witherspoon to work with us!"

Roger Morgan: "I really think we need to spend incremental profits on our infrastructure, so that we can take care of our core customer when the buzz goes away in a few days."

Lois Gladstone: "Come on Pepper, get Reese Witherspoon!"

Candi Layton: "It would be huge on Twitter, I can promise you that."

Glenn Glieber: "Well folks, that's enough. Fun stuff! Based on our meeting today, I don't think we looked like a brontosaurus stuck in a tar pit, facing extinction. We were full of vibrant ideas. Ok, on to the next topic. Ruth Crandall from the call center wants to add a few fields to the order entry screens to capture customers who purchase because of special events, like our Reese Witherspoon deal. Roger, could you make those improvements to the order entry system by tomorrow morning?"

Roger Morgan: "It would be easier if I had $100,000 to fund the improvements!"

From Conversion Rates To Repurchase Rates

In Moneyball, Michael Lewis explained how the Oakland A's, with a very low payroll, optimized wins by finding market inefficiencies. Baseball historically focused on metrics like batting average and runs batted in. Oakland focused on "on base percentage" and "slugging percentage", finding athletes who generated good outcomes in these metrics at lower-than-average salaries.

In other words, the existing best practice was to find great athletes with good batting averages and an ability to drive in runs. Oakland identified a different set of metrics, and then found players who were good at generating these metrics at a low cost. Oakland won a ton of games from 1999 - 2006, using this methodology.

In Online Marketing, we look to optimize conversion rate, and we have the best set of tools we've ever had to do this style of optimization.

But we're not making big strides in understanding how to increase customer spend over time. In other words, we work really hard to increase conversion rates, maybe from 4.1% to 4.5%. But we somehow aren't able to engage customers in a way that increases loyalty. E-commerce sales have largely grown from traffic, not from increases in repurchase rates, orders per buyer, items per order, or price per item. In the future, growth must come from increases in repurchase rate, orders per buyer, items per order, and price per item.

So if you are an online marketer, I'm going to encourage you to evolve your thinking. I'm not going to ask you to abandon all of the metrics and optimization strategies you've historically employed. I am going to ask you to think differently.

Let's start by defining a metric. The name of the metric is "Repurchase Rate". Simply put, this metric is defined as the percentage of customers who purchased last year, and then purchase again this year. Now if your business is not an e-commerce business, then go ahead an think about whatever the "action" is that you want to maximize --- if you are Twitter, you might look at a "Re-Use Rate", how many people use your service again today, given that they used your service yesterday.

Why is "Repurchase Rate" important? Let's look at two customers. Both customers purchased one time during 2007, on December 10, 2007:

• Customer #1: Visit 2/1/2008, Visit 2/8/2008, Visit and Buy 2/12/2008, Visit 7/1/2008, Visit and Buy 7/2/2008, Visit 9/10/2008, Visit 10/1/2008, Visit 12/1/2008.
• Customer #2: Visit and Buy 2/15/2008, Visit and Buy 7/2/2008, Visit 12/1/2008.

Both of these customers have a 100% "Repurchase Rate", and both customers ordered two times during 2008. Both customers last visited the website on 12/1/2008. In many ways, both customers yield the same outcome --- both customers purchased twice during 2008.

But from a "Conversion Rate" standpoint, these customers are very different. Customer #1 has a much lower conversion rate than does Customer #2. Our web analytics tools are often configured to favor Customer #2.

When we favor Customer #2, we favor the actions that cause Customer #2 to come to our website. And as a result, we will spend more money, via optimization, on the actions that generate a lot of customers who look like Customer #2.

So my thesis is this: Why not look for the actions that generate customers who have good Repurchase Rates? By optimizing "Repurchase Rate", a metric measured across a multi-month or multi-year period of time, we find customers who may look bad when measured via "Conversion Rate", but are equally or more valuable to the long-term health of the business.

In other words, there is a market inefficiency that exists when everybody focuses on "Conversion Rate". By instead focusing on "Repurchase Rate", we identify customers who appear to be poor converters, but spend the same amount in the future as do other customer who convert well. The secret is that we can grow our business faster than our competition, because we are optimizing on a different set of measures.

Next week, we'll begin to explore the math that allows us to optimize via "Repurchase Rate". The math will lead us to a simulation environment that helps us understand the long-term impact of short-term decisions.

Gliebers Dresses: The Cocktail Dress

It is time for another Executive Meeting.

Glenn Glieber (Owner): "... and I'm telling you, during my staycation, I enjoyed all sorts of programming. Have you checked out all the excitement in "Judge TV"? Probably not, you're busy working for me, right? Anyway, you can spend all day learning about the ways that landlords ripped off tenants, or how a girlfriend stole Craftsman tools from a deadbeat boyfriend as payment for 1984 Camaro he stole from her. There's Judge Judy, Judge Joe Brown, The People's Court, Judge Mathis, Judge Alex, Divorce Court, Christina's Court, Judge Karen, Judge David Young, Family Court with Judge Penny, Judge Hatchett, Judge Jeanine Pirro. Six straight hours of entertainment, all paid for by advertising. Heck, I even bought one of those things that rubs dead skin off of your feet, just $19.95 plus shipping and handling. Wow, what a week!"

Meredith Thompson (Chief Merchandising Officer): "Kevin, is that you?"

Kevin: "Yup, it's me."

Meredith Thompson: "We are so excited, Kevin, we're just bouncing off the walls today!"

Kevin: "Why?"

Pepper Morgan (Interim Chief Marketing Officer): "Haven't you heard?"

Kevin: "Heard what?"

Candi Layton (Chief Customer Officer and HR): "TMZ TOOK A PICTURE OF REESE WITHERSPOON WEARING ONE OF OUR STRAPLESS COCKTAIL DRESSES LAST NIGHT! OH MY GOD!"

Roger Morgan (Operations And IT): "And now the website is going absolutely crazy!

Candi Layton: "People are tweeting about this everywhere. Our cocktail dress is trending as one of the top ten terms on Twitter today!"

Meredith Thompson: "We're almost sold-out of the dress already!"

Roger Morgan: "The conversion rate of customers who look at the dress is more than thirty-two percent. 32%. Can you believe it?"

Candi Layton: "And people are tweeting about it everywhere!"

Lois Gladstone (Chief Financial Officer): "This is going to save our bacon in August. For the first time in my tenure, we're going to post a sales increase."

Roger Morgan: "We don't have enough people at the call center to handle the call volumes. Right now, the average wait time to speak with a customer service representative is thirteen minutes."

Meredith Thompson: "Normally, we'd let Roger have it for wait times more than a minute. But we just don't care, today. The building is alive!"

Lois Gladstone: "Pepper, can we get an e-mail out there, like immediately, featuring the fact that Reese Witherspoon wore our dress and that we've got a whole lot of other fantastic items that customers would love?"

Roger Morgan: "And can you put those social media buttons in the e-mail, so that our customers can spread the message for us?"

Meredith Thompson: "And can you stay away from directly promoting the cocktail dress, since we're almost sold out? No, wait, maybe you promote it and we'll take backorders and create all sorts of pent up demand."

Candi Layton: "The minute the e-mail is out there and Roger has the landing page ready, I'll put something out on Twitter."

Roger Morgan: "This is real multichannel advertising, folks!"

Meredith Thompson: "I can see it now. The cover of the Holiday Gliebers Dresses catalog, featuring the lovely Reese Witherspoon!"

Lois Gladstone: "Pepper, do you think you could get in touch with Reese Witherspoon? Do you think you could ask her to appear on the cover of the catalog? I mean, she's wearing the dress, so she loves us, right? But don't be like a creepy stalker, ok? Just express the benefits of being aligned with the Gliebers Dresses brand."

Candi Layton: "Reese Witherspoon on the cover of the catalog!"

Roger Morgan: "Reese Witherspoon on the homepage!"

Lois Gladstone: "Reese Witherspoon on Oprah, wearing one of our dresses. That would literally launch us into orbit! Just imagine Oprah introducing Glenn Glieber ... 'Here's Glenn Glieberrrrrrrrrrrrrrrr'!"

Meredith Thompson: "Reese Witherspoon being interviewed by Ryan Seacrest, wearing something elegant from Gliebers Dresses".

Kevin: "You could Skype in to the Oprah show, Glenn."

Meredith Thompson: "Reese Witherspoon telling America that all of the cast members of her new movie are planning on wearing Gliebers Dresses at the premiere."

Lois Gladstone: "And all of this is free, folks. We didn't do a darn thing to make this happen!"

Glenn Glieber: "I love free marketing!"

Kevin: "You'll want to create a new field in your database. Any customer who purchased this dress during the 'hype' period should be categorized appropriately. Our Multichannel Forensics work show that about 35% of first time buyers purchase again within twelve months, with half of the second purchases happening within just three months. In other words, if the new customer is going to purchase again, the customer is likely to purchase again soon. Our job is to see if the customers who are swept up in 'Reese Witherspoon Mania' ever purchase again, or if they are truly swept up in the event and have no interest in buying again. Pay close attention to e-mail click-through rates among customers who purchased this dress, as that will give you an 'early read' as to whether these customers are engaged with Gliebers Dresses, or whether these customers are trying to look like Reese Witherspoon. And we'll want to pay very close attention to the mix of new vs. existing customers buying this dress. We want to see if this energized our customer base, or if this was a great way to bring in new customers.".

Meredith Thompson: "I'm at the Academy Awards, listening to Reese Witherspoon tell E! Television on the red carpet that her new dress was designed by the famed designer, Scotty Jennings, of Gliebers Dresses. And then Reese calls Carson and I over, and the entire place gives us an ovation!"

Candi Layton: "And I'll 'live-tweet' the whole thing!"

Pepper Morgan: "Kevin, do customers who respond to mania like this ever purchase again?"

Kevin: "These customers act differently than a customer you rent from Anna Carter. They frequently spend less, long-term. We'll want to thoroughly simulate what the long-term impact of a phenomenon like this will have on the business. Again, we'll use e-mail to get an early read on how these customers perform. If the performance isn't there, we'll want to significantly limit the number of catalog mailings and e-mail campaigns these customers receive."

Glenn Glieber: "Outstanding. I'm so proud of all of you. Your hard work is finally bearing fruit. Always remember that we're a merchandising brand first --- without the merchandise, we have nothing. This is yet another of those 2% solutions that I'm looking for. Now on to the next topic. I watched a lot of 'One Life To Live' during my staycation. Do any of you think that maybe the actresses on 'One Life To Live' might want to wear our dresses, assuming we gave them to the staff for free? I'm just thinking that if I became hooked so easily, maybe the average person would buy from us if she knew that a cast member was wearing one of our dresses. Pepper, can you get on the horn with ABC and see if they want to support our merchandise assortment on-air?"

Web Analytics, Online Marketing, Metrics

Note: Every Monday and Wednesday in August, we'll be talking about Web Analytics and Online Marketing Simulations (OMS). The discussions will build in depth and math as the month moves along.

There's never been a better time to be a Web Analytics expert!

There's never been a more challenging time to be a Web Analytics expert, either.

Do you want to know how customers who visit your site via iPhones convert? No problem! Care to measure the bounce rate of new customers? Have at it! Need to know the cost per conversion of visitors from Wyoming visiting because of PPC? Easy!

Online marketing is calibrated around a metric called "conversion rate". We are able to segment visitors via a veritable plethora of dimensions, using a mouse to drop in metrics based on dimensions we define on the fly. It's easy, it's fun, it is actionable, it increases sales! More important, we're able to create A/B tests, allowing us to optimize our results in real time. Technically, we know more about how customers interact with advertising than ever before. What's not to like about being a Web Analytics expert?

That's one side of the spectrum.

Over on the other side of the spectrum are what I call "strategic questions". Strategic questions are a different animal altogether. Strategic questions are harder to answer, because the answer isn't found by using metrics to optimize conversion rate.

Strategic Question #1: You are a retailer with three stores in Akron, OH. Management is considering closing one store, and is hoping that the other two stores and your e-commerce website will pick up the sales lost if one store is closed. What is the impact on website sales if one store is closed?

Strategic Question #2: Your merchandising team added a new product line in July. This product line is already responsible for 5% of company sales, a huge success. However, the product manager for an existing product line experienced a 25% reduction in sales in July. She believes that the new product line cannibalized her assortment. Other product managers don't agree, because their products experienced sales gains during July. Nobody tested offering/not-offering the new product line to customers. What impact did the new product line have on the old product line?

Strategic Question #3: You implemented five new initiatives. Each initiative increased conversion rate, based on A/B tests, by 10%. And yet, in total, your conversion rate is down 10% vs. last year. Your CEO holds you accountable for increasing conversion rate. How are you going to demonstrate that the conversion rate decrease is not your fault? What offline data do you need to make your case to management?

Strategic Question #4: Management is considering closing down your catalog division. Management wants to know what e-commerce sales will look like in 2015 if there has not been a catalog to support e-commerce sales for a five year period of time. What is your estimate for e-commerce sales in 2015, without a catalog division there to support e-commerce sales?

Here's the trap that the Web Analytics expert is in. All of the big Web Analytics providers (Coremetrics, Unica, Omniture, for example) can help you answer these questions. You can, in theory, import data or link to data or export data or build a data mart and, technically, get to an acceptable answer.

But if your focus is on the powerful combination of conversion rates and optimization, it will be hard to conceive an analytical framework that yields an answer acceptable to a CEO.

As mentioned a few weeks ago, we're going to spend a lot of time in August exploring how our focus on conversion/optimization limits our ability to answer strategic questions. In August, we'll show how we can use a simulation environment to better understand strategic issues in online marketing. We'll explore how we can see the future via a different framework.

If you want to prepare for our month-long discussion, consider these authors, folks who use different metrics to re-define their craft, or explain how the "new" is really borrowed from the "old".

• Basketball: The Wages Of Wins, explaining why scoring does not lead to wins.
• Football: Advanced NFL Stats, illustrating the ways that traditional metrics fail to explain success.
• College Football: Smart Football explains why the "spread" offense is not orginal, is largely borrowed from plays from fifty or more years ago.
• Here's an article about Patrick Ewing that has many similarities to Web Analytics, arguing that you optimize the end result by sub-optimizing components, by having less talented players shoot more so that the best player's performance is optimized. Of course, this is contrary to Web Analytics and Online Marketing theory, but it does help explain why a decade of optimization sometimes leads us to lower conversion rates over time.