Catalog Matchbacks: FAQs About Why They Cost You Profit

You had questions about my thesis that catalog matchbacks are costing you profit. Let's answer your questions.

Question: "What do you have against the vendor community? How can you criticize folks who've helped us through tough economic times, and are always there for us?"

Let me be clear. I am not being critical of members of the vendor community who have your best interests at heart. Plenty of folks in the list industry and the co-ops make the right decisions for you every single day. In fact, I recommend many folks from Millard or ALC or Abacus to you (as examples), when asked.

Always remember, however, that most in the catalog vendor community make more money when you mail more catalogs. There is a disincentive for the vendor community to share best practices in housefile contact strategy testing, because doing so is detrimental to their business, and could result in the vendor employee losing his/her job. I've witnessed this conflict first hand, where the vendor gives you an answer that ultimately benefits the vendor more than you. So do the right thing for your business, ask valid questions of your vendor reps, and closely monitor their response.

Question: How can you mail catalogs and get negative demand, I don't understand?

One of the myths of the "multichannel era" is that everything fits together, is additive or even multiplicative! This simply isn't true, and is clearly illustrated every time you execute a catalog housefile mail/holdout test. Advertising doesn't necessarily cause customers to spend more. Sometimes (often), advertising causes customers to change behavior. Some catalogers find that when you don't mail catalogs, demand from e-mail marketing doubles ... in essence, the lack of a catalog causes the customer to switch loyalty to e-mail marketing. You can't see that outcome unless you execute the test. That is an example of "negative demand". In other cases, mailing the catalog causes customers to spend more on e-mail marketing, this is the classic "multichannel era" outcome of 1+1=3. It does happen. But you cannot know it until you execute mail/holdout tests.

Question: If I execute a mail/holdout test, I'll lose demand, and I can't afford to do that when the economy is so bad. Why are you constantly recommending that I do something that hurts my business?

I wouldn't recommend that you do something that hurts your business. I am asking you to execute the test so that you can identify the most profitable catalog mailing strategy. Take a look at the image at the start of this post. On the left-hand side of the table, you see what happens when you follow your matchback results. You'll mail 12 catalogs to this customer segment. On the right-hand side of this table, you see what happens when you test different numbers of catalog mailings to a customer. You see that demand happens whether you mail catalogs or not to a customer. You see that 8 catalogs is the optimal strategy. You see that if you mail 8 catalogs, you increase profit by +/- 20%, per customer. Show me what other strategy you have in your toolkit to immediately increase customer profitability by 20% today?? If you want help executing/analyzing/implementing a contact strategy view of catalog customers, contact me!

Question: Are matchbacks invalid for outside lists?

No, go ahead an use matchbacks for outside lists, that's a good way to evaluate prospects.

Question: We go to great lengths to capture key codes on online orders. Why do we need to execute mail/holdout tests when we ask the customer to enter a key code?

Here's a neat finding from mail/holdout tests ... if you don't mail a catalog, a customer is likely to use an older catalog and will enter an older catalog key code. Or other times, the customer will just visit your website because she loves your brand. Imagine that? She'll simply come to your website unprompted by a catalog mailing, and will place an order, sans key code. That's the best measure of customer loyalty ... a customer willing to shop without advertising. How will you ever be able to accurately measure customer loyalty unless you execute the mail/holdout test?

Question: We know that 80% of our online orders are matched back to a catalog, so we know that matchback analytics are right for our business. Why would you ever recommend abandoning a methodology that is so useful?

There are two issues with your comment. First, when a catalog brand gets 80% of online orders from catalog mailings, the catalog brand is not doing a good job of online marketing. Second, the matchback algorithm is incorrectly allocating orders to catalogs. As stated earlier, your most loyal customers will always shop from you, regardless whether you mail catalogs or not. In other words, you don't need to advertise as often to your best customers ... they already love you!! How can it possibly hurt to execute a mail/holdout test and learn the optimal number of catalogs to mail to a customer?

Question: In your examples, if you don't mail catalogs, catalog demand decreases. We cannot support top-line sales declines. Why would you advocate hurting our business?

I'm advocating a strategy that makes you more profit. Profit dollars matter. My strategy means you end up spending less on catalog marketing, generating a decrease in top-line sales. I recommend re-investing that money in customer acquisition, online marketing/search, mobile, and in some cases social media strategies, in order to grow your business. If done right, top-line sales won't decrease, and you'll be more profitable.


Ok, it's time for your questions. What do you want to learn?

Catalog Matchbacks Are Incorrect, Costing You Profit

During the past ten years, I've analyzed, plus/minus, a hundred different contact strategy tests. In these tests, we hold out a group of customers, to understand how much the customer will spend if we don't mail catalogs.

In every case, the holdout tests indicate that the incremental sales generated by a catalog mailing are less than what is illustrated in a traditional matchback algorithm.

The matchback incorrectly assumes that just because a customer was mailed a catalog, then any online order was "caused" by the catalog.

This, my loyal readers, is simply not the case.

The image at the top of this post is typical of what I usually see. This would be a modestly-sized $60,000,000 catalog business with thirteen annual mailings. As you can see, when comparing the results of a matchback with the results of a mail/holdout test, demand is overstated by about 40%.

And as a result, profit is completely mis-stated. Your matchback reporting tells you that you generated more than $600,000 profit ... when in reality, you only generated a little over $300,000 in profit.

This means that you are grossly over-circulating to your housefile segments.

This happens all of the time. In the case of a $60,000,000 business, it is reasonable to expect that matchback analytics are costing you a million dollars of annual profit, per year.

Yes, you are losing a million dollars of profit on a sixty-million dollar business, per year, because you are using matchback analytics instead of mail/holdout results to evaluate your business.

Always remember that there are audiences that benefit from matchback analytics. This audience is not likely to help you evaluate your business in the most profitable way possible, because use of matchbacks benefits their business model.

• The USPS
• Your Printer
• Your Paper Rep
• Your Co-Op
• Your List Vendor

Always remember that there is an audience that benefits from mail/holdout test methodology.

• You

Which audience do you think you should focus on?

Please start using mail/holdout methodology, and improve the performance of your business. As always, I am here to help you.

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

E-Mail Marketing, Search, Matchback, Attribution

One of the mysteries of marketing in 2009 is the concept of attribution, a process where we matchback orders derived in one micro-channel to the advertising micro-channel that drove the order.

For whatever reason, the e-mail blogosphere and vendor community fails to capitalize on this opportunity.

My Mutichannel Forensics projects repeatedly indicate that e-mail marketing and search marketing play a unique micro-channel role. E-Mail marketing is a "love" channel, if you will. The 10% to 50% of your twelve-month buyer file that subscribes to e-mail marketing "loves you" more than the average customer. These customers have better "RFM" characteristics, not because of e-mail marketing necessarily, but because the customer is a good customer who wants to learn more.

And then we have search, which works in the opposite direction. The customer who "loves you" doesn't implicitly trust you. As a result, she wants to make sure that she's getting the best deal possible, the best combination of merchandise and value.

When you have customers who want to see your e-mail campaigns and then want to use search, you have a classic micro-channel combination that must be tabulated in your database, and analyzed going forward.

At minimum, we need to run matchback algorithms for e-mail marketing. Catalogers have been running matchbacks for the past fifteen years, taking credit for orders that were not necessarily driven by catalogs. E-Mail marketers, however, have been exceptionally slow to embrace attribution and matchback programs. I don't understand why.

It's a fairly simple process. Say you deliver an e-mail marketing campaign on a Tuesday. Take all customers who ordered on Tuesday, Wednesday, Thursday, and Friday, and match them back to your e-mail campaign. And by the way, make sure you have a holdout group, a group who did not receive the e-mail campaign, and do the same process --- subtracting the difference between mailed and holdout group for true incremental value.

Now, any orders that are generated by search marketing are matched back and attributed to the e-mail marketing campaign. And here's where we need to make an adjustment ... we need to make a guess at all of the unconverted searches that were caused by e-mail marketing, and allocate the cost of those unconverted searches back to the e-mail marketing campaign. If the typical search conversion rate is, say, 3%, you have to multiply converted searches by 33, and then multiply that total by the cost-per-click, in order to get at the right advertising cost.

Two things usually happen, two things that are highly relevant to e-mail marketers.

1. E-Mail marketing causes search activity, and that search activity results in orders that are normally credited to search and should be credited to e-mail. This can result in e-mail marketing being more productive that usually measured to be.
2. E-Mail marketing causes the "search audience" to do a bunch of unproductive searches. As a result, the "search segment" is actually unprofitable --- causing the e-mail marketer to withhold e-mail marketing campaigns to customers who search all of the time.

The latter point is worth noting ... the e-mail marketer should be creating segments in the database of customers who utilize search on a frequent basis ... electing to develop a different contact strategy for the "E-Mail / Search" micro-channel combination.

Online Buyers: An Easy Catalog Circulation Tip To Save Money

Catalog marketers looking to reduce expense often decide to not mail catalogs to online buyers.

This can be a challenge, because so many of those matchback algorithms suggest the catalog played a role in the online order (though we can not prove the catalog caused the order).

When I'm conducting a Multichannel Forensics analysis, I like to categorize every one of the 365 days of the year as a "catalog day" or an "online day". In other words, I sort every day based on sales totals ... days where telephone orders are dominant are called "catalog days". Days where telephone orders are not dominant are called "online days".

Not surprisingly, online buyers purchasing on "online days" are less responsive to catalog marketing than are online buyers purchasing on "catalog days". Toss in Google activity or e-mail activity, and you've got a recipe for catalog cost savings!

Modern Segmentation, Modeling, And Planning

Much of the segmentation/modeling/planning process involves predicting a future purchase, followed by the determination of an appropriate targeting strategy.

For instance, in this catalog example, we predict two things.

1. We predict the Response Rate to a future catalog.
2. We predict the Average Order Size for a segment being mailed a future catalog.
   

Based on these two predictions, and a forecast for the cost of mailing a catalog, we arrive at the following segment-level mailing prediction and profit/loss statement (after online/retail matchback):

	Prediction
Response Rate	1.8%
Avg. Order	$125.00
$ Per Book	$2.25
Flow-Through %	35.0%
Flow-Through $	$0.79
Book Cost	$0.70
Profit	$0.09

The marketing world of 2009 requires a different level of sophistication.

In the future, we will change the planning and prediction process. This segment will be split into two sub-segments.

1. Subsegment #1 = Customers with the same RFM-style classification, but never historically purchased using Paid Search, Affiliates, or Shopping Comparison Sites.
2. Subsegment #2 = Customers with the same RFM-style classification, but historically purchased using Paid Search, Affiliates, or Shopping Comparison Sites.

In each case, we'll measure future response, but we'll also predict the expected marketing cost associated with self-service customers using Paid Search, Affiliates, or Shopping Comparison Sites. If the catalog or e-mail drives customers to these micro-channels, we incur additional marketing expense. Here's the sub-segment prediction:

	Subseg #1	Subseg #2
Response Rate	1.8%	1.8%
Avg. Order	$125.00	$125.00
$ Per Book	$2.25	$2.25
Flow-Through %	35.0%	35.0%
Flow-Through $	$0.79	$0.79
Book Cost	$0.70	$0.70
Pred. Search/Aff/SC Cost	$0.02	$0.18
Profit	$0.07	($0.09)

In this example, Subsegment #2 generates additional expense, because they like to use Paid Search, Affiliates, and Shopping Comparison sites after receiving a catalog. Therefore, we have to predict what the amount of incremental expense is likely to be. The same level of prediction is required to properly manage future e-mail campaigns.

For Statistical Modelers, this opens up a whole new area of exploration --- it's like drilling for oil in areas where exploration was prohibited.

For the Catalog Circulation Director, this gives you the opportunity to fundamentally change the contact strategy for self-service online shoppers, while generating a boatload of profit for your brand.

For the E-Mail Marketer, you have a once-in-a-lifetime chance to motivate your Executive team to deliver e-mail campaigns to unprofitable customers less often --- and you'll have the proof!

For the vendor community, especially for matchback vendors, you have a whole new product you can develop --- one that integrates purchases and expenses in a holistic and actionable manner. Or maybe the folks at Coremetrics or Omniture can get a jump on the catalog vendor community, and take ownership of this new opportunity.

Best of all, all of you e-mail vendor employees who regularly read this blog have a chance to build an application that improves the profitability of e-mail marketing efforts for your clients --- a good thing!!!

Catalog ROI Is Overstated Because Of Search

Last week, we chatted about how E-Mail ROI is mis-calculated. My stats tell me that you found the article interesting.

Catalog advertising causes the same issues that e-mail marketing causes, often on a larger scale.

The typical catalog marketer matches paid search orders that occur within 30/60/90 days of a catalog mailing back to the catalog that the circulation team believes is responsible for creating the order.

However, the typical catalog marketer does not match back unconverted paid search expenses to the catalog responsible for causing unconverted paid search to happen.

Take a look at this profit and loss statement.


This is a fairly typical catalog profit and loss statement.

Notice converted paid search orders. These orders are matched-back to the catalog. Some catalogers match the paid search expense of those orders back to the catalog.

Almost nobody matches the unconverted paid search clicks back to the catalog that caused paid search to happen. In this example --- a reasonably honest assessment of a catalog profit and loss statement, the catalog caused 3,200 paid search orders to happen. However, at a 3% conversion rate, the catalog caused about 100,000 paid search clicks to happen.

The average cataloger does not allocate the cost of the incremental 96,800 unconverted clicks back to the catalog that caused the clicks to happen.

So three things happen.

1. The cataloger significantly over-circulates the catalog, because the additional expense is not allocated to the catalog driving paid search. The catalog marketing effort is less profitable than it appears.
   
2. The cataloger significantly mis-understands the impact of catalog marketing. In this case, circulating 1,000,000 catalogs caused 100,000 paid search clicks. The marketer fails to see that the catalog caused a 10% "engagement rate". This is a big deal --- the catalog is causing far more customer engagement than is typically measured.
   
3. A portion of the 100,000 paid search clicks result in purchases with the competition, reducing your Net Google Score.

Eventually, we'll create a database infrastructure that allows us to capture appropriate customer interactions. This will fundamentally change how we market to customers.

• We will attribute unconverted paid search clicks back to the customer/catalog combination, in our promotional history files. Instead of recording an $0.80 cost for the catalog, we'll record a $0.80 + $0.50 = $1.30 cost to the customer, incorporating the cost of the search. Ask your database, co-op, or web analytics vendor if they are able to do this for you.
  

• When we make mailing decisions (e-mail or catalog), we will make the decision based on the historical paid search expenditure of the segment we're considering. We won't send as many catalogs or e-mails to customers who augment their experience with unconverted paid search. This is a big deal, folks ... we'll be much more profitable when we make this transition.

• Example: Say your break-even on an $0.80 catalog is $2.50. Now you have a customer who loves to click on paid search ads when she receives a catalog. Your "real" cost of mailing the catalog is $1.30, driving your break-even over $4.00.

• Example: E-Mail marketing is essentially free, until it isn't free! The new e-mail marketing discipline will require us to make e-mail marketing decisions, at a segment level, based on anticipated paid search expense. All of a sudden, e-mail marketing is fundamentally changed --- the discipline becomes nearly identical to catalog marketing.
  

• Another Issue: We have the same problems with Affiliate Marketing and Shopping Comparison Sites. If catalog marketing drives a customer to an affiliate, and that affiliate skims 7% off the top of an order, the catalog needs to receive an expense penalty for driving demand to the affiliate.
  

We've spent a decade doing matchback analytics. Now, we need to provide the vendor community some leadership, so that matchback analytics account for the expense side of the ledger. We are continually making bad decisions because our database infrastructure fails to capture important information.

Who do you see doing this type of work out there, and what was the impact of this style of analysis?

Prove It: Matchback Attribution

One of our loyal readers is trying to goad me into ripping a recent article on Multichannel Merchant. I won't link to the specific article, because 95% of the content the author writes about will increase your profits, and I don't want for this to be a criticism of the author, who is simply trying to give advice that will help you.

But I do want for us to consider one of the quotes, the exact quote sent to me by a loyal reader.

• "Correlation analysis suggests that as much as 90% of the unallocated orders that come to the Web for the multichannel marketer are directly related to catalog mailings".

We need to consider three phrases in the sentence.

1. Correlation analysis suggests (this means we cannot prove the findings that follow).
   
2. As much as (this means the real number is always lower than what we will be quoted).
3. Directly related (this means we cannot prove causation).

Based on the linkage of three phrases, an entire industry moves forward with an agenda, an agenda based on a linkage of assumptions that may or may not be correct.

Do you realize the leap of faith required to believe in this sentence?

We listen to quotes like this because we want to believe the sentence.

Now it is entirely possible that those who adhere to the tenants of the sentence quoted above are right, and will experience unbridled success. I grant you this point.

But are you willing to grant me my point ... what if one, two, or three components of the sentence are wrong? What does that mean to the success of the businesses we manage?

Matchback attribution. Prove it!!

Day Of Week

In recent Multichannel Forensics projects, there has been a increased focus on understanding the days that online buyers purchase merchandise.

Here's what you might want to pay attention to.

1. Customers who order over the telephone in the first two weeks following a catalog in-home date (or first two days following an e-mail in-home date) are dependent upon advertising.
2. Customers who order online, and order in the first two weeks following a catalog in-home date (or first two days following an e-mail in-home date) are probably dependent upon advertising.
3. Customers who order online, and order during "dead periods", when no catalog or e-mail campaign is active, are "organic" customers, customers likely to purchase in the future without the aid of advertising.

Pay really close attention to scenario #3, folks, as you can save a lot of expense here without compromising sales levels.

These days, I code every day of the year, based on whether that day is a "traditional direct marketing day" or whether it is an "organic day". Customers ordering on "organic days" are less likely to need advertising to fuel future purchases than are all other customers.

Demand that your matchback vendor provide you with visibility into this phenomenon.

Measuring Paid Search, E-Mail, And Social Media Influence Via Matchbacks

Ted asks "how do you measure influence rather than direct sales"?

Direct marketers use Matchback Analytics to attribute sales to the activity that theoretically caused the purchase to happen. Matchbacks were originally designed to prove that catalog mailings were responsible for web sales. Now, matchbacks are well suited to measure influence.

Let's look at a few customer orders.

Order #1: Customer received catalog on November 1. Customer purchased online on November 10, using the keycode from the back of the catalog. This one is easy, the catalog gets credit for the order.

Order #2: Customer received catalog on November 1. Customer received marketing e-mails on November 3 and November 5. Customer purchased online on November 10, and did not use a keycode. The catalog brand would probably allocate this order to the catalog, ignoring any role that e-mail marketing played in the purchase.

Order #3: Customer received catalog on November 1. Customer received marketing e-mails on November 3 and November 5. Customer clicks through to the website from a paid search term on November 10, purchases online, and does not use a catalog keycode. Catalogers would like to allocate this order to the catalog, paid search mavens might want to allocate this order to paid search, e-mail marketers probably lose out in this instance.

Order #4: Customer received catalog on November 1. Customer clicks through to the website from a blog featuring merchandise offered in the catalog. Customer purchases online on November 10. Catalogers would immediately allocate this order to the catalog.

In the last three instances, the marketer "assumes" that one form of media drove the order, and creates business rules to proceed with allocation of sales. And, of course, in the last three instances, the catalog marketer makes incorrect assumptions. The assumptions are better than the assumptions made in 1999, but the assumptions are flat-out wrong.

When a catalog brand measures influence, there are two different allocations.

There is direct allocation, as illustrated above.

Then we have influence allocation.

In Order #2, the catalog gets credit (if that is how matchback business rules are written), while each e-mail campaign gets half-credit for influence.

In Order #3, the catalog gets credit, while two e-mail campaigns and paid search receive one-third credit for influence.

In Order #4, the catalog gets credit, while social media receives 100% influence credit.

Each quarter, we produce a table that illustrates, for each channel, direct attributed sales, and influenced sales.

	Direct Sales	Influenced Sales	Index
Catalog Marketing	$10,000,000	$1,200,000	0.12
E-Mail Marketing	$1,000,000	$4,000,000	4.00
Paid Search	$2,000,000	$4,000,000	2.00
Other Online Marketing	$1,000,000	$1,000,000	1.00
Social Media	$100,000	$3,000,000	30.00
Mobile Marketing	$100,000	$1,000,000	10.00

What you are likely to see is that emerging channels have a high "influence index". In other words, we don't attribute orders to the emerging channels --- we simply don't have business rules to do this, so we attribute orders to the most established channels. But if we focus on influenced sales, we notice that channels like e-mail and paid search and social media play a bigger role, helping cause an order to happen.

Influenced sales make a huge difference in viewing a "mutlichannel strategy". In the illustration above, e-mail, paid search and social media are key influencers. They do not get direct ROI attribution, but are clearly used by the customer as part of the purchase process. From a strategic standpoint, these channels should receive strategic attention. Or maybe catalog marketing should not receive direct credit for all orders!

Either way, the marketer views the world differently when focusing on both ROI and influenced orders.

A final note: In a perfect world, the marketer executes catalog and e-mail test/holdout groups, then measures influence in mailed/holdout groups, subtracting the differences to measure true ROI and true influence.

Catalog And E-Mail Drive Retail Sales Via Matchback Analytics In Some Instances

Jim Wheaton brings us an article that those of us who've analyzed the data firmly believe in --- that after controlling for prior customer frequency, multichannel customers are not fundamentally better than single-channel customers. The article explores how analysis of customer behavior can trump established marketing beliefs.

I am reminded of a meeting in 2003 at Nordstrom. Our sales rep from Abacus visited, suggesting that matchback analytics would prove that our catalog marketing efforts drove a billion dollars or more of retail volume (our retail business was maybe $5 - $6 billion at that time). Abacus clients were using matchbacks, learning that retail customers who received catalogs were likely to buy in stores in the days after receiving a catalog. Our Abacus rep took a leap of faith --- the mailing of catalogs caused a billion dollars in retail sales --- the catalog caused the sales to happen.

And Abacus was right, based on the analytics available to them. You run a matchback analysis, and you see that retail customers buy in the days following the mailing of a catalog.

Multichannel Forensics, however, suggest a subtle distinction that we must keep in mind.

• Matchback algorithms are reasonably accurate when the retail channel is in Acquisition Mode.

• Matchback algorithms are somewhat accurate when the retail channel is in Hybrid Mode.

• Matchback algorithms are highly inaccurate when the retail channel is in Retention Mode.

If you don't have the bandwidth to run a Multichannel Forensics analysis, at least run mail/holdout groups through your matchback algorithm, subtracting the difference in matches.

There is a faction of the marketing community that sees matchbacks as a religion, and this is ok, because it is sometimes better to do matchbacks than to do nothing. That being said, subtle performance differences and profit increases happen when we combine Multichannel Forensics, Test/Holdout Groups, and Matchback Algorithms --- for catalog mailings and especially e-mail campaigns.

Back to Nordstrom. We did the testing, we did the Multichannel Forensics analysis, and we did Matchback Analytics. Our findings ran contrary to the best practices suggested by the marketing establishment.

We killed our catalog program in June 2005. From July 2005 - June 2006, comp store sales were positive. In other words, without $36,000,000 of catalog advertising that matchback algorithms suggested were driving maybe a billion dollars of retail sales, we were able to increase retail sales. Multichannel Forensics and Test/Holdout groups told us that a retail brand in Retention Mode yielded highly misleading Matchback results.

So this is the deal. The vast majority of the marketing establishment believes that catalog and e-mail marketing drive sales to other channels, as evidenced by matchback analytics. And these folks may be correct, especially if channels operate in Acquisition Mode. When channels operate in Hybrid Mode or Retention Mode, the rules change --- the organic percentage overrides matchback analytics.

Catalog And Retailer Differences In Matchback Strategy And Contact Strategy Optimization

There's this huge shift in multichannel marketing strategy in recent years, with catalog matchback algorithms playing a significant role in the shift.

Fashion retailers (Neiman Marcus, Saks, Bloomingdales, Nordstrom) either eliminated traditional catalog marketing programs, or are in the process of significantly reducing circulation. Folks at Williams Sonoma are significantly trimming circulation.

When I talk to some of you, you tell me that these folks can cut circulation because they are retailers --- the retail channel somehow generates brand awareness that fuels a brand in a way that minimizes the need for advertising. You might be right, we simply cannot test your hypothesis.

Mechanically, retail brands are better at developing a testing discipline.

Here's an example. We randomly sample twenty customers, ten receive a catalog, ten do not, and measure performance across channels during the three weeks that a catalog is active. Here's what we observe:

Mailed			Holdout
Cust 1	Buy Store		Cust 11
Cust 2			Cust 12
Cust 3			Cust 13	Buy Online
Cust 4			Cust 14
Cust 5	Buy Phone		Cust 15
Cust 6	Buy Online		Cust 16
Cust 7			Cust 17
Cust 8			Cust 18
Cust 9	Buy Online		Cust 19
Cust 10			Cust 20	Buy Online

Here's the fundamental difference between the retailer and the catalog brand.

The retailer will compare the mailed group and the holdout group. In the mailed group, four out of ten customers responded --- in the holdout group, two out of ten customer responded. The retailer calculates response as (4 - 2) / 10 = 20%.

The cataloger does not execute the test. Instead, the cataloger takes the mailed group, identifies the four responses, matches the responses back to the mail file, and calculates response as 4 / 10 = 40%.

Again, notice the significant difference in response, using the two methodologies.

• Retailer = 20% Response Rate.
• Cataloger = 40% Response Rate.

In this comparison, the organic percentage is 20% / 40% = 50%. Half of the demand would happen without any advertising.

This fundamental difference in approach causes a shift in strategy.

• Retailer = Cut Circulation, Re-Allcoate Marketing Dollars Elsewhere, Learn!!
  
• Cataloger = Maintain Circulation, Ask For Additional Funding For Online Marketing, And Significantly Over-Spend In The Catalog Marketing Channel, Driving Down Profit.
  

This problem is systemic across the catalog industry. Matchback vendors aren't trying to rip you off, they simply aren't. But there isn't an incentice to create a "best practice" that accounts for the differences that retailers observe when executing contact strategy testing and what catalogers measure via matchback analytics.

A simple solution for catalogers is to execute a test similar to the one designed above. Do not tell the matchback vendor about the holdout group. Have the matchback vendor run the control group through the matchback algorithm, and see how many orders are allocated to the holdout group. Subtract the results of the holdout group from the results of the mailed group, and you have true incremental demand as illustrated in the retail example at the beginning of this post.


Hillstrom's Contact Strategy Optimization: A New E-Book.

Hillstrom's Contact Strategy Optimization On A Budget

Hillstrom's Contact Strategy Optimization On A Budget is a new e-book and spreadsheet available from the MineThatData Store at Lulu.com.

Contact Strategy Optimization is not a new concept. During my time at Lands' End in the early 1990s, we worked with a team of IBM researchers on an optimization solution that formed the embryonic version of the solutions offered by Decision Intelligence.

During the past two weeks, many of you told me that you don't want to spend tens or hundreds of thousands of dollars on black box algorithmic solutions that optimize the number of catalog contacts to various customer segments. That being said, you told me you want a solution ... one that can be implemented by Business Leaders, Analysts, and Managers ... one that can be implemented on a budget.

So I wrote this e-book, outlining a reasonably simple approach to identifying the most profitable combination of catalog mailings and e-mail marketing messages to different customer segments.

What Do You Get, What Will You Learn?

• You'll learn that matchback algorithms over-state the importance of catalog marketing, causing us to mail too many catalogs to our customers.

• You'll learn that the "organic percentage" is the most important metric to understand when considering an appropriate contact strategy.

• You'll learn that contact strategy testing is critical to understanding multichannel customer behavior.
  

• You'll learn how cannibalization between catalog mailings and e-mail marketing messages directly influence a profitable contact strategy.

• You'll apply versions of the "square root rule", identifying profitable strategies.

• You'll receive access to a URL where you can download a spreadsheet that allows you to play "what if" games using your own assumptions and your own customer segment performance.
  

This is not meant to be an elegant or mathematically perfect solution. This e-book and spreadsheet are written for you, the Executive or Analyst who has to come up with solutions on a limited budget.

Do you not have a quarter of a million dollars to spend on an optimization solution, but have access to $79? If so, purchase "Hillstrom's Contact Strategy Optimization On A Budget"! For those of you who criticize me for giving away too much information, you'll be happy, because the contents of this e-book will not be made available on this blog.

$79 is a fair price, considering you'll be given tools that could result in hundreds of thousands of dollars of annual profit, don't you think?

So visit the MineThatData Store on Lulu.com, and download this e-book for the nominal fee of $79.

The Most Important Catalog Marketing Metric: Organic Percentage

The most important metric in catalog marketing is called the "organic percentage".

The metric is defined as the percentage of demand, at a segment level, that would occur if no catalog mailings were delivered to a customer.

Most of the catalogers I speak with assume that the organic percentage is zero --- in other words, if catalogs were not mailed to a customer segment, the segment would not spend any money.

Of course, this assumption is false, perpetrated by biased matchback algorithms that incorrectly assign online orders to catalogs mailed to the customer, when in reality, the catalog had nothing to do with the generation of the order in question. You'll know that your matchback results are biased if the percentage of demand you add on to your acquisition segments (after matchback) is significantly lower than it is for housefile customers.

Catalogers who attempt contact strategy tests, say over a three month period of time, find relationships like this.

• Telephone - Only customers have an organic percentage around 10%.
• Telephone + Online customers have an organic percentage around 25%.
• Online - Only customers have an organic percentage around 40%.

In other words, if no catalogs are mailed to an online-only customer, the online customer will still spend 40% of the demand they would spend if they are mailed all of the catalogs during the quarter.

The organic percentage metric is critical, because it dramatically impacts your calculation of profit and loss. If you have a high organic percentage, then you are significantly overmailing customers, regardless of what your matchback analytics vendor tells you. If you have a low organic percentage, then you have no choice but to mail catalogs in order to generate demand.

The image at the beginning of this post shows the difference in profitability for the same segment of customers, comparing a 10% organic percentage to a 40% organic percentage. The ten percent level requires four mailings per quarter. The forty percent level maximizes profit at just one mailing per quarter. Think about what you could do with the expense from the three additional mailings?

If there were just one metric I'd ask catalogers to track at a segment level, during 2009, it would be the "organic percentage" metric. Knowing this metric fundamentally changes how you decide to contact different customer segments.

How important is this percentage? Take a brand like Nordstrom. This is an $8.5 billion dollar business that is luck to generate ten percent of that total from marketing activities. Therefore, the organic percentage is ninety percent. This brand generates ninety percent of sales without the aid of traditional marketing activities. That's a strong brand.

Think about Zappos. There's the volume they generate due to online marketing and search marketing, and then there's the volume they generate via word of mouth. I'd guess that half of their volume happens without the aid of marketing, plus or minus twenty percent.

And then think about a traditional cataloger. The traditional cataloger believes that the vast majority of demand happens becaue of catalog mailings. If mail/holdout tests validate this, then the cataloger is at the mercy of catalog marketing --- if customers are no longer responsive to this form of marketing, demand dries up.

The goal, of course, is to build a brand that has a high organic percentage, not needing advertising to drive sales and profit.

We can learn how much of customer demand is generated by advertising by executing thorough mail / holdout tests, in both catalog marketing and e-mail marketing.

How Nordstrom Profitably Ended A Catalog Marketing Program, By Kevin Hillstrom

Something is going on in catalog marketing when I receive repeated inquiries asking how Nordstrom ended a traditional catalog marketing program and increased direct-to-consumer sales. An increasing number of catalog marketers are starting to re-think marketing strategy.

As a result of numerous recent queries from catalog and retail brands across the United States and Europe, I am going to write this essay explaining the decision-making process, and the high-level results. The goal is to help our industry. Please feel free to forward this article to your colleagues --- the hyperlink is embedded here.

If you have questions that I failed to answer here, please ask your question in the comments section of this post, so that all members of our industry may benefit from the answer.


How Nordstrom Profitably Ended A Catalog Marketing Program, By Kevin Hillstrom.

The year was 2004, and the world was a different place. Gas cost less than $2.00 per gallon. President Bush was re-elected for a second term as President of the United States. Finding Nemo won the Oscar for the best Animated Picture. Brett Favre pondered retirement from the Green Bay Packers. Barack Obama, an obscure Jr. Senator from Illinois, gave a stirring seventeen minute speech at the Democratic National Convention.

The catalog marketing world was buzzing over a term called "multichannel". Most brands were between five and nine years into their foray into e-commerce. During this time, telephone sales generally declined, while e-commerce sales dramatically increased. The accepted best practice was to mail catalogs to customers, causing the customer to purchase merchandise over the telephone, online, or in stores. The customer chose the channel she wanted to purchase in. The brand needed to be "multichannel", needed to be present in each channel to accommodate this savvy shopper. The catalog, based on an analytics tool called "matchback analytics", was at the core of this new marketing strategy.

The entire catalog marketing ecosystem liked this view of the world. Printers continued processing catalogs, makin' bacon in the process. Paper reps benefited from the strategy. Co-op marketers provided the analytics that proved this strategy worked, then benefited from the strategy as catalogers leased households from a half-dozen co-op databases. List rental and management organizations protected their future as well. List processing vendors enjoyed the benefits of continued merge/purge processing. E-commerce vendors enjoyed increased website traffic, causing demand for online software. Even e-mail vendors benefited, because catalog customers volunteered an e-mail address at the time of a phone or online purchase, fueling the growth of the e-mail marketing industry. Paid search vendors benefited, because the catalog customer went to Google to research products viewed in a catalog. Google benefited!

The marketing world agreed that mailing catalogs was the "right" thing to do.

In 2004, Nordstrom finally had a highly profitable direct marketing division. A division that lost 10% of net sales in 1999 and 2000 broke even in 2002, and came off of a profitable year in 2003. In 2004, sales and profit were and increasing.

The catalog strategy included marketing of a subset of merchandise, with many items not available in stores. The merchandise included items that sold well in the telephone channel, and did not include the vast majority of items that sold well in stores, did not include many items that sold well online.

By all accounts, this was a successful division.

And then management asked a simple question.

"What would happen if we integrated our channels, offering largely the same merchandise in all channels, without implementing a traditional catalog marketing program?"

Imagine if you are part of the management team of the direct-to-consumer channel, and you are asked this question. You are responsible for putting catalogs in the mail. And somebody is now questioning whether you should do this anymore.

As Vice President of Database Marketing, I built an entire team responsible for putting catalogs in the mail and measuring the effectiveness of these catalogs. What do you think I thought of this question? How would you respond to the question?

A task force of sixteen leaders was assembled. The leaders included Regional Managers, responsible for store performance in their region, Information Technology leaders, the Chief Marketing Officer, many members of the direct-to-consumer management team, and yes, even me.

If you are Vice President of Database Marketing, and you are asked to participate on this team, you are going to be asked questions by members of this team. Your direct-to-consumer team are going to ask you to demonstrate the importance of a traditional catalog marketing program. Your Chief Marketing Officer is going to ask you to present unbiased facts about customer performance.


What were some of the questions leadership wanted answered?

Question: Will catalog customers just switch their behavior, and shop online if catalogs are no longer mailed to them?

Answer: Some customers will switch. Many customers will simply stop purchasing. We tested not mailing customers catalogs in 2001, 2002, 2003, and 2004. We knew exactly what would happen. Without a reinvestment of advertising dollars, sales would decrease.


Question: If catalogs aren't mailed, won't customers just switch to e-mail marketing?

Answer: No. This strategy had also been tested. If a customer receives a catalog, she spends maybe $X across the phone, online, and retail channels. If a customer receives an e-mail marketing campaign, she spends maybe (0.12)*$X across the phone, online, and retail channels. When we tested not mailing catalogs to an e-mail customer, e-mail performance increased slightly. Almost all of the $X would be lost, not recouped by e-mail marketing. And we all know this, we measure e-mail marketing and compare it to catalog marketing and paid search.


Question: What role does catalog marketing play in acquiring new customers?

Answer: Catalog marketing played an important role in the acquisition of new customers. Like all catalogers, Nordstrom rented customers from competing organizations, and exchanged names with competing organizations. Privacy advocates and the Chief Marketing Officer strongly believed that the renting/exchange of names was not in the best interest of Nordstrom or the Nordstrom customer, and if a traditional catalog marketing strategy didn't exist, the rental/exchange strategy would disappear.


Question: Are Nordstrom customers truly "multichannel"?

Answer: Sometimes. Customers did purchase in multiple channels, in fact, a significant minority of total sales came from customers buying from multiple channels. The reality, however, was that customers were migrating from one channel to another, eventually landing in the store channel. Kind of a "duh", when you think about it, huh? The customer acquired over the telephone via a catalog eventually purchased online without the aid of catalog marketing, then shifted spend into the store channel, using the website to research merchandise. This evolution of customer behavior, identified via Multichannel Forensics, suggested that another marketing strategy could be employed, one that would be at least as effective as the traditional catalog marketing strategy.


Question: Do customers purchase from all merchandise divisions?

Answer: No. And this is an important point. The traditional catalog marketing strategy offered a subset of merchandise. If that subset of merchandise were no longer offered, those customers were likely to simply go away, and not cross-shop the rest of the offering, placing any potential new strategy at risk.


Question: Should a multichannel strategy include integration of silos across the organization?

Answer: In this case, it was decided that with a new multichannel strategy, without a true catalog program, that functions should be integrated across the company. This would prove to be a painful process. Pundits underestimate the human challenges associated with integrating people. Time would prove that people would lose their jobs trying to make this integration happen. It is hard, financially, to integrate systems and technology. It is hard, emotionally, to integrate people ... or to let a lot of people go.


Ultimately, it was decided that the traditional catalog marketing strategy would be terminated, effective June 30, 2005.

Here are some of the tactics that were employed.

• Traditional catalog customer acquisition programs were terminated in early 2005, to prevent the acquisition of customers who would later be disappointed.
• No announcements were made of the elimination of the catalog marketing strategy to loyal catalog customers.
• A new catalog marketing strategy would be employed, one where the vendors of the merchandise paid the cost of a page of catalog marketing to advertise their product.
• The privacy policy would be changed. Nordstrom would not rent or exchange any customer information with any competing or non-competing brands.
• E-mail marketing frequency would increase from one contact a week to two contacts per week.
• The online marketing budget would be increased, in an effort to acquire customers lost via the termination of the catalog marketing strategy.
• Systems and people would be integrated, across the company.

The Results:

• Long-time, loyal catalog-only customers did not take kindly to the new strategy, by and large choosing to not purchase again. "Dual-Channel" customers (phone + website) maintained their online spend, but stopped the spend they used to place over the telephone, for obvious reasons.
  
• The investment in online customer acquisition offset the losses from the traditional catalog customer acquisition strategy.
• The increase in e-mail contact strategy helped offset some of the loss of demand from long-time catalog customers.
  
• A subset of catalog customers shifted their spend online.
• The combination of online customer acquisition and catalog customer shift resulted in a net increase in net sales in the direct-to consumer channel. Yes, I said an increase! You can read through the 10-K statements and discover that fact for yourself.
  
• Many leaders in the direct-to-consumer channel chose to leave the company.
• Many positions were eliminated, positions associated with our call center, positions associated with catalog production and circulation expertise. Integration of creative teams (direct-to-consumer and retail) was a challenge.
• The new catalog marketing strategy did not perform as well, in fact, I had not previously worked with a program as unproductive as this one. When you let your vendors determine the merchandise that is advertised to customers, you set yourself up for sales decreases.
  
• The new catalog marketing strategy was, from a profit standpoint, wildly profitable. When you let your vendors pay for the cost of a page of advertising, you are, by default, guaranteeing profit.
• Many online marketing metrics improved without a catalog marketing program in place. In other words, in the past, we'd mail a catalog, causing a customer to use Google to do a search. In theory, the order would be shared between catalogs and paid search. Now, paid search got full credit.
  

Impact On The Database Marketing Department

• I ultimately eliminated eight of twenty-four positions in the department.
• The most seasoned catalog marketing staff left the company, or chose to work in the online marketing division.
• Eight positions were re-trained for work in Social Media, E-Mail Marketing, Online Marketing Analysis, Web Analytics (stuff that Coremetrics couldn't do for us). We integrated Coremetrics data with retail and telephone purchase data, creating a whole new area of emphasis.
  
• Eight positions went essentially unchanged (from a job requirements standpoint), though the focus of their work was on driving multichannel sales, not channel-specific sales.
• My role as Vice President of Database Marketing was ultimately de-emphasized, resulting in me starting my own consultancy.

Describe Some Of The Pitfalls:

• I must re-emphasize how difficult it is to integrate people. Catalog Marketers, Online Marketers, and Store Marketers think about things differently. As you de-emphasize one area, you make some employees feel bad, while others feel more powerful. That's a dangerous cocktail.
  
• Have a customer acquisition plan. You cannot kill a catalog marketing program without risking the future of the business. You can successfully migrate online by having a plan that fuels customer acquisition online.
• Geography Matters! A customer in rural North Dakota or Vermont is not going to be a multichannel customer. Take away her catalog, you take away her sales potential. A customer in suburban Chicago will shop all channels. A customer in Silicon Valley will buy online. Have a strategy for each customer segment, based on geography. Your results will vary.
  
• Product Matters! Know exactly what your catalog customer loves to purchase, your online (Google) customer loves to purchase, and if you have a store customer, what your store customer loves to purchase. Product differences dictate differences in advertising strategy (e-mail, paid search, catalog marketing, traditional advertising). Your multichannel efforts will be much more successful if you know what specific customers with specific channel preferences like to buy.

The pundits had a lot to say about this strategy. The usual suspects in the co-op and list world blasted my team and I in 2005. I recall reading the quotes in trade journals ... stuff like "Lands' End tried this in 1999 and it didn't work". I recall receiving phone calls from the catalog vendor community, folks blaming me for "letting this happen".

Then the strategy worked well. REALLY WELL. Much better than I ever expected it to work.

And then the pundits criticized me again. This time, the blather was all about "the only reason this worked is because of your brick and mortar presence ... the strategy will never work for a traditional cataloger". Hey pundits, why did the strategy work in Birmingham, or Madison, or Tucson, or Des Moines, or Boise, or New Orleans, or Evansville, or Omaha, or Topeka, or Oklahoma City, cities where Nordstrom didn't have a retail presence? When I speak at conferences, the audience loves to blast me on this topic. I am continually amazed how the opinions of many carry more weight than the experiences of the few who actually went through the process and have the scars to prove it.

The reason the strategy worked had nothing to do with the fact that we had a store presence. The reason the strategy worked was because we did two things well.

1. We knew, from our Multichannel Forensics work, how customers shopped across channels. We ran five-year simulations of the new plan, and knew directionally what to expect.
2. Leadership had a plan! They didn't just kill a program and not significantly re-invest elsewhere. They invested in systems, people, online marketing, and cross-channel merchandising strategy. We increased e-mail frequency.

Remember, the change in strategy resulted in an increase in net sales in the direct-to-consumer division, and did not fundamentally impact retail comp store sales. I was surprised by the results.

This can work for you if you do your homework. Have you tested what happens if you do not mail a customer a catalog for a year? Six months? Have you ever doubled your online marketing budget for a month, testing what happens to all channels when you dramatically change your marketing strategy? Have you tested altering your merchandising assortment in print and e-mail marketing? Have you figured out how to acquire new customers without paper in the mail? Have you ever tested raising prices as an instrument to potentially increase demand? Have you studied customer behavior by geography?

Maybe the right strategy is to have six mailings a year instead of sixteen. Maybe the right strategy is to have thirty mailings a year instead of sixteen. Maybe the right strategy is to have your vendors fund your catalog program. Maybe the right strategy is to stop mailing catalogs altogether. The answer is different for every company. There are no right or wrong answers. Your situation is unique. But your situation isn't one that should be executed on the basis of opinions, or gut feel, or guesses, or the collective opinion of an industry or vendor ecosystem.

Without a doubt, the right thing to do is to start testing different strategies.

Ok, your turn. What questions do you have that I failed to answer? Please do not e-mail your questions, please ask them (anonymously if you wish) in the comments section, so that all of our readers can benefit from the discussion.

Hillstrom's Multichannel Secrets, 59 Tips Every CEO Should Know, Now Available At Lulu.com

Paid Search And Catalogs

So many of my Multichannel Forensics projects now include both referring URL information and catalog / e-mail promotional history.

When you have this type of information, you quickly notice that customers blend advertising strategies into a slurry of confusion that results in the same purchase the customer used to place with you fifteen years ago.

This caused our industry to dive head first into matchback analytics. We try so hard to allocate every order that happened in the past.

It might be time to view the future.

In other words, we can measure past relationships, modeling them to see what a customer might do in the future.

For instance, I notice that some customers use paid search and catalogs as a combined effort, then use paid search and e-mail as a combined effort, then use paid search, then simply purchase without the benefit of any advertising.

Identify these customers, mail fewer catalogs to them, and focus ad spend on customers who require various forms of marketing to place orders.

Matchback Bias

You're probably partnering with your list organization, data warehouse vendor, or co-op on the never-ending scope of matchback analytics.

The goal, of course, is to prove that catalog marketing is a vital piece of the modern marketing puzzle. You're trying to truly understand the ROI of this activity. That's why you try so hard to attribute every online order back to one of the dozens of catalogs you mailed in the past year.

Now let me ask you this.

Do you go through the same effort to attribute every phone order back to the original online source?

You don't?

I met with a business that is doing just that. They combine their web analytics tool and their matchback analytics platform to attribute phone orders back to the online marketing activity (which is usually organic/natural search) responsible for driving the phone order.

Why is it that our industry is so bent on proving that catalog marketing drives online orders, but doesn't invest the energy to prove that online marketing drives phone (and store) orders?

Our view of the world is biased, folks. And that bias favors co-ops, printers, the USPS, the paper industry, and the list rental/exchange industry.

Your thoughts?

Who Benefits From Flawed Matchback Analyses?

This is my final discussion about matchback analyses for awhile, as I'm sure many of you are ready to read about other topics. But I got chewed on, I was told to stop talking and get on the multichannel bandwagon. That bandwagon may be financially hurting some catalogers. Somebody needs to talk about that.

Let's think about the industries that benefit from incorrectly executed matchback analyses. Mind you, I'm not picking on any specific individual --- I've observed many folks in these industries who counsel clients in a positive way.


The USPS: Ever wonder why it seems like there are more catalogs in your mailbox these days, compared with a decade ago? Here's a secret ... if you mail every one of your internet buyers a catalog, a matchback analysis might tell you that the catalogs drove all online orders within twelve weeks of the catalog mailing ... even if search and e-mail marketing and organic demand were truly responsible for the orders. The USPS (and now the good folks in the UK as well) commission studies that "prove" that catalog mailings drive online orders. I'm not saying catalog mailings don't drive online sales --- I'm just saying we are significantly overstating the importance of catalog mailings via flawed matchback algorithms.

The Co-Ops: Catalogers love co-ops these days. Catalogers get names that perform better, and get them at a lower cost than via list vendors. So co-ops have a financial incentive to promote flawed matchback algorithms (though some truly try their hardest to do a good job). By "proving" that catalogs drive online orders, catalog clients order more names from the co-op, driving co-op sales and profit. An even bigger conflict of interest occurs when co-ops actually execute the matchback algorithm for the client.

Merge-Purge Houses: The cataloger gets matchback results from the co-op, orders more names, names that are merged at the merge-purge house, driving increased sales and profit for the merge-purge house. Also, many merge-purge houses run matchback analyses for catalogers, earning $$$ for their efforts.

Printers: If catalogs are "proven" to drive 70% to 80% of online sales (which does occasionally happen, but not as often as we're being told), then printers benefit, too. The cataloger mails more catalogs than they normally would, which drives sales and profit for the printer. If the printer delivers catalogs deep into the mail system, then the printer can earn more $$$ too.

Paper Industry: Some of my feistier conversations have been with folks in the paper industry. More catalogs means more paper, which means more $$$ for those in the paper industry.

List Industry: I'm much less critical of the list industry, because by and large, these folks acted with integrity for the past decade, recommending that clients shift names from lists to the co-op industry, knowing all-too-well that it would result in the death of the list industry. But flawed matchback analyses help those in the list industry as much as they help the co-ops.

Trade Journals: We read about multichannel marketing and matchback analyses in trade journals. These publications depend upon the vendor community for advertising revenue. The vendor community depends upon the trade journal to "get the word out". This symbiotic relationship benefits from promotion of matchback analyses that may not accurately reflect the "truth".


So, let's look at the ecosystem that depends upon matchback analyses that are sometimes flawed.

Co-ops and merge-purge vendors do the matchback analysis, attributing too many online orders to the catalog channel. This causes the cataloger to order more names from co-ops and list vendors than they should, financially helping co-ops and list vendors. These names go into the merge-purge process, financially helping merge-purge vendors. Next, the names go to the printer. Paper reps financially benefit from over-mailing, as do printers. The printer delivers the catalogs deep into the mail system, where the USPS benefits by delivering too many catalogs to customers. Then trade journals tell us all about multichannel customer behavior, funded by the profits the vendor community get from matchback analyses.

It looks to me like the entire catalog ecosystem benefits from flawed multichannel matchback analyses. The only parties who don't benefit are customers, who may not want the catalogs, and catalogers who over-mail catalogs, causing harm to the profit and loss statement.

This is why I've been told to stop talking, to "get on the multichannel bandwagon". This is why I try hard to freely share information with catalogers and multichannel retailers.