Return On Investment And Employee Accountability

My career has been defined by return on investment (ROI). For the most part, if I did not deliver a significant return on investment for my company, I lost my job. As a consultant, I don't get paid, and I don't get hired if I don't deliver ROI to my clients.

As a Statistical Modeler, if my models didn't generate a million dollars of incremental profit, per year, every year, my job was in jeopardy.

As a Circulation Director, if my team did not generate a couple million dollars of incremental profit, per year, every year, I'd lose my job.

As Vice President of Database Marketing at Nordstrom, if my team did not generate millions of dollars of incremental profit, per year, every year, I'd lose my job. In fact, I had the President of my division call me into his office, back in 2001, telling me that the reason the business was failing was because of my ineptitude, or the ineptitude of the chief merchandising officer. He told me that the merchant or I would lose our job if things didn't improve.

Six months later, he lost his job. Eleven months later, the chief merchant lost her job.

There are many jobs in a company that require consistent improvement in ROI, in order for the individual to keep his/her job.

• A merchant's job is measured every single day. The merchant is required to pick the right merchandise, and if customers don't like it, the merchant loses his/her job. In many companies, garden-variety employees get to see how every merchant is performing.
  

• The inventory staffer is measured every single day. Have a bad fulfillment rate across the items you are responsible for, and you lose your job. The CEO/President and CFO pay really close attention to how inventory staffers manage the business. Not surprisingly, inventory people get canned when there's too much merchandise and too few customers.
  

• The online marketer is measured every single day. Run a terrible paid search program, have display ads that are unprofitable, hook up with affiliates that have a poor reputation, and you lose your job.

• The e-mail marketer is measured every single day. Every person in the company can watch your performance fluctuate. Sink your productivity from $0.18 per e-mail to $0.14 per e-mail, and you lose your job. What's really sad is that when the e-mail marketer performs really well, the e-mail marketer doesn't get the credit that is deserved.
  

• The catalog circulation director is measured every single day. Fail to acquire enough new customers, over-circulate catalogs, or make a circulation mistake (mailing the wrong people), and you lose your job. Up until a few years ago, there were few people more responsible for ROI than the catalog circulation director.
  

• The finance staffer is often measured. These folks disperse funds to appropriate projects, and are often measured by Return On Invested Capital. When your finance department screws up, they are fired.

• Store Managers are actively measured. If your comps are negative, you're finished --- even if the merchants and the marketers screwed everything up.
  

If you are one of these individuals, you go to work every single day with a cloud over your head. You are hyper-accountable.

And because you are hyper-accountable, you start to look at other employees in your company. There are many employees who are paid what you are paid, or are even paid more than you for a comparable skill level. These employees are important, needed individuals. But the metrics aren't always in place to determine return on investment. How would you measure the return on investment in these cases?

• Catalog or Internet Photography: How do you know when you have a creative staffer who has "an eye" for the right way to present merchandise? At least photography can be tested. But you won't find a dashboard in your company that measures the sales generated by your creative people, will you?
  

• Information Technology: Under what circumstances does the IT staffer hurt the business to the point where all employees are suffering? How would you measure it? Even worse, most employees are aware that IT employees are paid on a different wage scale (i.e. more) than are employees who are directly accountable for generating sales. You won't find a dashboard in your company that points to the IT staffers who generated the most sales. Sure, IT folks can miss deadlines and make mistakes ... but that happens with all employees. So what metrics do you look to in order to correlate sales generated by an IT staffer?
  

• Social Media: A growing contingent of social media experts are suggesting that you don't measure ROI in a traditional manner in social media, just read the Social Media SmartBrief or some of the top 25 Social Media bloggers to review the arguments. If you're one of the marketers who are actively measured on a daily basis, you're not always thrilled with your co-workers who Twitter and blog all day long and then suggest they shouldn't be measured the same way that, say, an e-mail marketer is measured. But you need these people, you need pioneers who are taking a westbound path on the Oregon Trail, right? So what are the metrics used to evaluate the pioneer?
  

• Offline Marketing: How do you measure the ROI of a newspaper ad, a billboard, radio, television, sponsorship? Not surprisingly, these are the programs that are the first to be cut in economic downturns ... but that isn't deserved either, just because it is hard to measure. Many of these programs can be tested, but aren't.
  

• Human Resources: How do you measure the return on investment of an HR staffer who is able to arbitrate arguments between employees? You really can't "test" HR staffer effectiveness to identify what impact that has on company sales, can you?
  

• Copywriter: In so many companies, copy evaluation is subjective. But it matters. At least copy can be tested, and in paid search, it is actively tested.
  

The Business Intelligence movement yielded three classes of employees.

• Employees where the relationship to sales can be easily and directly measured.
• Employees where the relationship to sales can be inferred via periphery metrics and testing.
  
• Employees where the relationship to sales cannot be measured.

If you can possibly become an employee who is measured on a daily basis, become that person. Those who are measured tend to rise to leadership positions within companies --- you see merchants running companies, you see finance folks running companies. Whether for good or bad, you don't see as many folks who aren't directly accountable for sales in leadership positions.

And if your area of responsibility can be measured via periphery metrics, by all means, identify every single periphery metric you can, and prove that you're moving the needle on something.

Finally, if you are one of the employees who love working in areas that are not directly accountable for sales, that's not your fault --- you need to do what love, right? So how does an organization evaluate your performance in a fair comparison to folks who are directly accountable for sales generation?

What are your ideas?

Return On Investment (ROI) In Direct Marketing

Click on the image to enlarge it.

We hear a lot of talk about ROI, or "Return On Investment", when evaluating direct marketing programs.

Catalogers know that paper drives more total sales, and more total profit, than any other form of direct marketing.

E-Mail marketers know that e-mail drives the best "ROI", measured as "total profit divided by total cost". E-Mail marketing has almost no cost associated with it, making it a tool marketers must use, and use properly.

Paid Search marketers know that they reach customers at a "time of need", thereby providing the most "efficient" form of advertising known to-date. No other form of advertising cuts out the waste of uninterested shoppers like paid search ... except I guess for natural search, which has no cost associated with it.

Portal marketers know that they make the brand known to customers who have not purchased previously. They know their investment is best measured on a "lifetime value" basis ... short-term metrics are not appropriate for portal advertising.

In the table attached to the top of this article, each form of advertising has various strengths and weaknesses. Your job is to evaluate your advertising objectives.

Objective: Drive large volume of sales/profit from existing customers.
Solution = Catalogs.

Objective: Precisely target merchandise to existing customers.
Solution = E-Mail, Paid Search.

Objective: Precisely target merchandise to customers in-need.
Solution = Paid Search.

Objective: Make your brand aware to potential customers.
Solution = Portal Advertising.

Objective: Acquire new customers.
Solution = Catalog, Portal Advertising, Paid Search

I didn't even talk about affiliate marketing or shopping comparison marketing, which also fit into this story.

Obviously, there are many different objectives and solutions, my list above is abbreviated and short. Strategically, consider what you want to accomplish, and allocate your advertising mix on the basis of total sales, total profit, and your objectives.

Don't be swayed by folks who tell you that one form of advertising is "better" than another. Each type of advertising has a purpose. Each type of advertising excels within one specific set of metrics.

Does Online Marketing Truly Increase Net Sales For Multichannel Retailers?

Online Marketing. For some businesses, it has been a revolutionary marketing tool that drives incremental sales and profit. Many online businesses thrive, using online marketing techniques like paid and natural search, affiliates, and portal advertising. A business like Zappos grows exponentially using online marketing strategies.

Our metrics seem to indicate that online marketing works. We've spent a lot of money installing software on top of our websites, and the software indicates that we get incremental traffic, conversion, and sales as a result of our marketing efforts. We see this in real-time, so it must be true.

Multichannel businesses often have different challenges than online-only business models. Multichannel businesses use traditional advertising, catalog advertising, and physical presence (retail stores) to drive sales.

Many multichannel businesses are seeing diverging trends, trends that lead to frustrating conclusions.

• The amount of money spent on marketing is increasing, when you add catalog, traditional and online advertising together.
  

• Annual retention rates, when measured across channels, are generally flat.
  

• The rate at which new customers are added to the business is generally slower than the rate at which investment in new customers is increasing.

For multichannel businesses, this suggests that increases in advertising expenditure are not yielding an overall positive return on investment. Any one advertising activity, when measured in a silo, appears positive. But the lump sum of advertising activities, and the increase in advertising over time, are not yielding a positive return on investment.

Just for fun, do a comparison. Look at your customer file in 1994, 2002, and 2006. Back in 1994, look at your ad-to-sales ratio, in the pre-internet era. In 2002, look at your ad-to-sales ratio, pre-search era. In 2006, look at your ad-to-sales ratio post-mass-media-collapse.

Similarly, look at your annual retention rate, and your annual purchase frequency, in 1994, 2002 and 2006.

If you see that your annual retention rate is flat or decreasing, your annual purchase frequency is flat or decreasing, or your ad-to-sales ratio is increasing, it suggests several possible challenges.

First, you might have to spend more on advertising today, because our customers are being carpet-bombed by competitors at every angle.

Second, there is one thing that fundamentally changed between 1994 and 2006 --- the internet! If ad-to-sales ratios are increasing, while retention rates or purchase frequency has remained flat, it suggests that online marketing has not fundamentally moved the needle at increasing customer loyalty, or cultivating new customers.

Third, if online marketing has not fundamentally moved the needle, it may mean that traditional advertising or catalog advertising needs to be trimmed-back in order to optimize the ad-to-sales ratio, and ultimately, profitability.

One way to evaluate online marketing is to see what percentage of those who respond to online marketing are truly "new-to-file" ... in other words, does online marketing truly drive new customer acquisition? Many multichannel organizations are observing that online marketing drives "existing" customers toward a purchase more than it drives "new" customers toward a first purchase. This could be a positive trend, in that online marketing rescues a customer about to defect.

More likely, this is a negative trend --- it simply means we've trained the customer to shop a certain way, and we spend additional money to achieve the same result. We calibrate our metrics to reflect that this is a "good" decision, when in reality, it isn't.

In conclusion, take a look at your advertising metrics, and your customer file information from 1994, 2002 and 2006. Are you spending more, as a percentage of sales? Are your annual retention rates increasing, flat, or decreasing? Are your annual purchase frequency metrics increasing, flat, or decreasing? This represents the starting point toward understanding if all the money multichannel marketers are now spending on online marketing are truly generating a positive return on investment.

How Much Do I Spend On Online/Catalog Advertising?

Lands' End was a fun place to work in the early 1990s. There were a lot of interesting minds, tossing around interesting ideas.

One of our debates was about the optimal level of advertising spend. One camp, led by our Circulation Director, believed that you circulate to an incremental 7% pre-tax level (prior to subtracting fixed costs). The theory was that the return on investment had to be sufficient to cover fixed costs ... that if you actually subtracted fixed costs from the equation, you were circulating to about break-even.

Another camp believed that you circulated to -5% pre-tax levels, because this way, you were capturing long-term profit that you were losing in the short term. At the end of five or ten years, your business was much bigger, because you acquired/reactivated a lot more customers than in the situation where you maximized short-term profit.

At Eddie Bauer, we circulated to break-even (prior to subtracting fixed costs), then shifted our strategy to invest to below break-even, in order to maximize the long term health of the business.

At Nordstrom, we tried our hardest to convince folks to invest in online marketing activities that maximized the long term health of the total business. We probably under-invested in the online channel, though we had the data to tell us what the 'right' thing was to do. The process of assigning a marketing budget did not provide us the flexibility to maximize the online channel (and ultimately, to grow store sales). This is a good lesson --- it doesn't matter what data you have, there are internal processes and existing cultures that simply cannot be changed.

In the past, we didn't have the right tools to understand the long-term impact of short-term advertising decisions. With Multichannel Forensics readily available these days, we can simulate different strategies, and identify the best long-term strategy.

I crafted an online/catalog business simulation, and ran three scenarios.

• Scenario #1 = Maximize profit each year.
• Scenario #2 = Maximize total profit over the course of five years.
• Scenario #3 = Maximize profit five years from now --- make that year as profitable as possible.

The table below show the results of the three simulations. All numbers are listed in millions:

Maximize Short-Term Profit
	Demand	Ad Spend	Profit
Year 1	$44.6	$5.6	$2.1
Year 2	$42.0	$5.2	$1.7
Year 3	$40.9	$5.1	$1.4
Year 4	$40.4	$5.0	$1.2
Year 5	$40.1	$4.8	$1.1
Totals	$208.0	$25.8	$7.4
Maximize Long-Term Profit
	Demand	Ad Spend	Profit
Year 1	$59.2	$9.9	$1.5
Year 2	$66.6	$11.0	$2.0
Year 3	$70.6	$11.6	$2.3
Year 4	$72.8	$12.0	$2.4
Year 5	$74.0	$12.2	$2.4
Totals	$343.2	$56.7	$10.6
Maximize Only 5th Year Profit
	Demand	Ad Spend	Profit
Year 1	$66.4	$12.5	$0.6
Year 2	$80.3	$14.9	$1.6
Year 3	$88.6	$16.3	$2.2
Year 4	$93.4	$17.1	$2.5
Year 5	$96.3	$17.6	$2.6
Totals	$425.0	$78.4	$9.5

Let's review each simulation.

In the first run, profit is maximized by year. Therefore, profit in the first year is $2.1 million. However, a much smaller business exists going into year two, with too few customers to generate large volumes of profit. Still, the management team tries to maximize profit in year two, then year three, year four, and year five. As a result, this business actually contracts. If we followed the rules of Wall St. (maximize short term profit), we may not protect the long term health of our business.

In the second case, online/catalog advertising spend is more than twice as much as in the first simulation. This means the business is more profitable in the long-term, and grows at a much faster rate.

In the third case, online/catalog advertising is fifty percent more than in the second case. This yields a marginally profitable business in year one, but in year five, the business is much larger, and more profitable.

For every online/catalog business, these scenarios can be easily created. The multichannel analyst provides management with three or more scenarios (as outlined above), and lets management determine the future trajectory of the business.

This is an important point --- abstract and geeky topics like lifetime value have little or no meaning to executives. Picking from one of three possible strategies is easy to do if you're an executive, and accomplishes the exact same thing as a geeky, technical lifetime value analysis.

Multichannel CEOs and CMOs: Simulations indicate that it is important to invest in unprofitable customer activities in the short term, in order to protect the long term health of your business. It is important not to focus on "this year". Where possible, invest in the short term, to protect the long term health of your business.

Lifetime Value And Return On Investment (LTV, ROI)

Multichannel CEOs and CMOs: How do you make decisions that shape the future of your business?

Recently, the best and brightest analytical minds (David, Jim, Ron) lamented the fact that Lifetime Value is not a widely accepted business concept. The concept was re-branded as "Return On Customer", with (at best) marginal corporate acceptance.

Loosely defined, lifetime value is the present value of future profits. Lifetime value frequently appears in two different ways. First, analytical folks focus on an analytical and financial approach to managing the business. Second, brand marketers focus on advocacy of customer rights as a way of increasing long-term shareholder value. If we could only get these two audiences to work together (analytics/finance and brand marketers), we might have something!

In many cases, Lifetime Value is discussed from an "outside-in" perspective. In other words, somebody outside a company (vendor, consultant) is trying to persuade somebody within an organization to purchase services, without knowledge of the real needs of the person "inside" a business. This can give LTV a bad name.

From an "inside-out" standpoint, many companies indirectly measure Lifetime Value.

• Catalogers are particularly good at measuring LTV, they manage list rental activities on the basis of LTV.
• In many cases, the Web Analytics folks don't have the software tools to do LTV measurement. Yet, they indirectly know this is important, because they like to measure the behavior of "new verses existing" visitors.
  
• Retailers often think of LTV in terms of "market share" or "most admired brand". Regardless whether this is flawed thinking or not, increased market share or being an admired brand deliver some of the benefits of a business with a customer base delivering outstanding LTV.

At some level, all companies and executives think about LTV. They just think about it differently than analytical folks, different than how the customer evangelist folks think about the problem.

Even better, let's get all the LTV evangelists together in a room, and let's see if they do things that are in the best interest of their own personal long-term health and financial benefit?

• We smoke, or drink alcohol, or overeat, all things that reduce our lifespan.
• We don't spend money in the best way. We purchase a Lexus or BMW or Mercedes that will depreciate from $60,000 to $0, when we could buy a Toyota Corolla. How does this decision help our own financial LTV?
• We pay via credit card, then pay interest. How does that help our financial LTV?
  
• We ignore health issues until they present dire consequences.

How can we expect "brands" to adopt LTV concepts when we don't take care of the LTV of our own financial or health concerns?

Like anything else in life, we know that LTV is good for us. All too often, we fail to follow through on what we know is good for us.

Based on my experiences working with business leaders, most would like to implement some version of LTV (they don't even know it is called LTV --- they just want a healthy long-term outlook that also generates lots of short-term profit). However, most Executives don't want the database marketing analyst hounding them about their thoughts and decisions.

• LTV is risk-averse. LTV might suggest that Apple focus on their core competency of making computers & software, might suggest they not invest in an unproven MP3 player that requires a significant capital investment.
  
• LTV tells you to invest in things that "work". Want to add new products to a catalog mailed to prospects? You can't, because new products probably don't have as good a LTV as existing products.
• Want to invest in a new creative representation of your "brand". You can't. LTV tells you that the existing creative is what is liked most by customers.
• Want to add a new catalog to your contact strategy? You can't, because LTV is telling you that you are over-saturating the mailing of your customers, lowering overall profitability.
• Want to add a third e-mail to the weekly contact strategy? You can't, because LTV tells you that too many customers opt-out after receiving more than two e-mail campaigns a week.
• Is your business in trouble, do you need to liquidate merchandise to open up your "open to buy"? Don't add a clearance catalog, because you'll lower the LTV of your full-price customers by converting them to full price + sale customers.

From time to time, LTV proponents struggle to see the business the way the Executive sees the business. Similarly, Executives make short-term decisions that mortgage or sub-optimize the long-term value of the business. Somewhere in-between these viewpoints represents the appropriate way to implement ROI-based decision-making within a business. That in-between place requires a culture that is willing to accept this thought process. Those cultures are hard to find.

Return On Investment When Business Is Good

If you're one of the lucky folks managing online or catalog marketing at a company that is "winning", you have an interesting opportunity.

Let's say that this profit and loss statement represented what you expected to happen in April.

Demand	$100,000
Net Sales	$85,000
Gross Margin	$42,500
Less Marketing Cost	$25,000
Less Fulfillment Expense	$10,200
Operating Profit	$7,300
% of Net Sales	8.6%
Ad to Sales Ratio	29.4%
Average Order Size	$85.00
Number of Purchasers	1,176
Cost Per Purchaser	$21.25
Profit Per Purchaser	$6.21

You expected to generate $7,300 profit, and 1,176 new customers.

You execute this marketing plan, and observe these actual results for the month of April:

Demand	$115,000
Net Sales	$97,750
Gross Margin	$48,875
Less Marketing Cost	$25,000
Less Fulfillment Expense	$11,730
Operating Profit	$12,145
% of Net Sales	12.4%
Ad to Sales Ratio	25.6%
Average Order Size	$85.00
Number of Purchasers	1,353
Cost Per Purchaser	$18.48
Profit Per Purchaser	$8.98

Courtesy of the magic of your merchandising team, customers loved what you offered them, spending 15% more than expected.

Here's the challenge. If you believe that during the month of May you will see similar results, you can pocket a similar level of sales and profit.

Or, you can increase your advertising, and acquire more names, while still generating the same level of profit you promised to your CFO. This example shows what could happen, if you boosted your advertising spend:

Demand	$143,635
Net Sales	$122,090
Gross Margin	$61,045
Less Marketing Cost	$39,000
Less Fulfillment Expense	$14,651
Operating Profit	$7,394
% of Net Sales	6.1%
Ad to Sales Ratio	31.9%
Average Order Size	$85.00
Number of Purchasers	1,690
Cost Per Purchaser	$23.08
Profit Per Purchaser	$4.38

This is one of those unique mysteries that complicate the lives of those of us who manage profit and loss statements for online or catalog channels.

Choice number one allows us to pocket an additional five thousand dollars of profit.

Choice number two allows us to achieve our budgeted profit, but grows the top-line by an additional $28,000, and adds an additional 337 customers that contribute to future sales and profit.

I've always advocated spending more money when times are good, and spending more money when times are bad (to liquidate merchandise, but not at liquidation prices) --- holding to the marketing budget when business is close to plan.

What would you do? Would you pocket the profit today, or, would you spend more to acquire more customers, customers that deliver future sales and profit? Your thoughts?

E-Commerce "Power" And Web Analytics

How 'powerful' is your e-commerce website?

In other words, does your website have enough recent visitors and purchasers to fuel the growth of your business?

'Power' is an area that web analytics tools and web analysts usually fail to consider when performing their valuable job function.

'Power' is simply an expectation of how productive your e-commerce website will be this year, based on last year's performance and this year's visitor counts.

Let's review a very simple example of E-Commerce 'Power'.

Step 1: Segment your January 2006 website visitors as follows:
*** Segment 1 = Any customer who purchased online in January 2006.
*** Segment 2 = Any visitor who did not purchase, but visited 3+ times in January 2006.
*** Segment 3 = Any visitor who did not purchase, but visited 2 times in January 2006.
*** Segment 4 = Any visitor who did not purchase, but visited 1 time in January 2006.
*** Segment 5 = Any visitor who did not visit in 1/2006, did visit 1+ time from 2/2005 - 12/2005.

Step 2: Once you have segmented your file, take the mean of online spend in February 2006 for each visitor/cookie in Segments 1-5.

Your analysis should look something like this:

Segment 1 = 15,000 January 2006 Buyers, Spending An Average Of $25.00 in February 2006.
Segment 2 = 50,000 January 2006 3+ Visits / No Purchase, Spending $9.00 in February 2006.
Segment 3 = 125,000 Jan-06 2 Visits / No Purchase, Spending $5.00 in February 2006.
Segment 4 = 1,000,000 Jan-06 1 Visit / No Purchase, Spending $2.00 in February 2006.
Segment 5 = 10,000,000 Feb-05 to Dec-05 1+ Visit, No Purchase, Spending $0.50 in Feb 2006.

Multiplying customers by average spend, then summing across five segments, yields $8,450,000 of demand generated on the website, during February 2006.

You are now ready to calculate your E-Commerce website's 'Power'. You need just one more step to complete the analysis.

Step 3 = Replicate Step 1, but instead of using January 2006 as your timeframe for segmentation purposes, advance your timeframe by one year for each segment. This reflects your website customer file, as it exists today.

Step 4 = Multiply this year's customer counts by last year's average spend. This gives you an expectation for how much existing customers and visitors will spend this year, if all other conditions are the same. Here is an example of the resulting analysis:

Segment 1 = 22,000 January 2007 Buyers, Spending An Average Of $25.00.
Segment 2 = 55,000 January 2007 3+ Visits / No Purchase, Spending $9.00.
Segment 3 = 135,000 Jan-07 2 Visits / No Purchase, Spending $5.00.
Segment 4 = 1,100,000 Jan-07 1 Visit / No Purchase, Spending $2.00.
Segment 5 = 14,000,000 Feb-06 to Dec-06 1+ Visit, No Purchase, Spending $0.50.

Multiplying customers by average spend, then summing across five segments, yields $10,920,000 of expected online demand during February 2007.

We've finally made it to the 'Power' calculation.

Power = This Year's Expected Demand / Last Year's Actual Demand.

Power = $10,920,000 / $8,450,000 = 1.292.

We did it!! Your portfolio of online purchasers and visitors are 29.2% stronger than last year. You should expect existing buyers and visitors to spend 29.2% more this year than last year, all things being equal.

In an ideal online environment, the web analytics folks will run this analysis for you at the start of the month, and communicate E-Commerce 'Power' to the executive team in the early stages of each month.

Multichannel CEO/CMO Takeaway: It is time to expect much more out of your web analytics team. Standard web analytics tools do a great job of telling you what happened during an individual session. Standard web analytics tools do a poor job of predicting the future. Leaders need to know what will happen in the future. Partner with your web analytics team on this simple segmentation exercise. You and your analytics folks will be able to forecast business problems before they happen.

During the next few years, we will hit a point where the online channel stops growing rapidly. Leaders need to be the first people to know that a demand shortfall is coming. Beat your competition to the punch by reacting to your E-Commerce 'Power' Analysis.

Setting Your Online Marketing Budget

Undoubtedly, many of you are putting the finishing touches on your online marketing, e-mail marketing, or catalog marketing budget for 2007. Oh, the excitement!

Is there anything more enjoyable than sitting across from your Chief Financial Officer, having to defend why it is important to advertise with a certain affiliate at a time when expenses need to be trimmed by ten percent?

CFO's demand rapid, financially-based answers to questions. The humble Chief Marketing Officer or Online Marketing Executive needs to be able to respond in a credible, but timely manner.

Most of the time, when asked a random question, you don't have the appropriate data with you to answer the question quickly. This is where the "square root" function comes into play.

Frequently, sales generated by advertising follow a "square root" function. In other words, if you had the opportunity to increase your marketing budget by twenty percent, your net sales would increase by the square root of 1.2. This number is (1.2 ^ 0.5) = 1.095. In other words, a twenty percent increase in marketing spend yields a 9.5% increase in net sales.

This becomes important when the CFO makes a random statement like,"Please reduce your marketing budget by ten percent, you have no choice in this, everybody must share in the pain."

Look at this example, where the online marketing budget is reduced by ten percent:

High-Level Online Marketing Scenario
		Reduce Ex-	Incremental
	Base Case	pense by 10%	Sales Lost
Orders	90,909	86,244	4,665
Average Order Size	$110.00	$110.00	$110.00
Cost per Order (CPA)	$22.00	$20.87	$42.87
Net Sales	$10,000,000	$9,486,833	$513,167
Gross Margin @ 40%	$4,000,000	$3,794,733	$205,267
Marketing Cost	$2,000,000	$1,800,000	$200,000
Pick/Pack/Ship Expense @ 13%	$1,300,000	$1,233,288	$66,712
Variable Operating Profit	$700,000	$761,445	($61,445)
Profit as a % of Net Sales	7.0%	8.0%	-12.0%
Ad to Sales Ratio	20.0%	19.0%	39.0%

Notice how the profit and loss statement changes. In this case, the CFO may have a good suggestion, as the incremental advertising dollars are not yielding a sufficient return on investment. Conversely, the numbers might work out in your favor, giving you the ammunition to actually ask the CFO for more money!

Not every business follows the "square root" rule. Your analyst can help you figure out which relationship makes the most sense to build the scenarios around. But in a pinch, go with the square root function. And then ask your CFO to quickly cost-justify some of her investments!!

Return on Investment Formulas In Multichannel Retailing

Let's talk about some of the equations that individuals use to measure advertising return on investment in the multichannel retailing industry.

Ad to Sales Ratio: This is one of the most frequently used equations. Assume you spent $10,000 on an online marketing campaign, and generated $50,000 net sales. The ad to sales ratio is calculated as ($10,000 / $50,000) = 20%. Obviously, the lower this percentage is, the better your advertising performed. Multichannel retailers compare advertising efforts against each other with this metric.

Sales per Ad Dollar: Some industry publications like to use this metric. In the above example, we simply calculate the inverse of the ad to sales ratio. ($50,000 / $10,000) = 5.00. In this case, you get five dollars of sales for every dollar of advertising spent. The higher the metric, the better your advertising performed. E-Mail pundits like to use this measure, since e-mail has virtually no cost, thereby insuring that it has a good "return on investment".

Cost per Order: Online marketers enjoy using this metric, one that is maybe the least effective metric of all. Assume that the $10,000 spent in our previous examples generated 400 orders. Cost per Order (sometimes labeled "CPA" for cost per acquisition) is ($10,000 / 400) = $25.00. Each advertising strategy is compared, with lower metrics preferred. This metric is highly skewed, because the metric doesn't account for how much was spent, per order.

Profit per Order: A more effective, but less-used metric, is profit per order. Let's assume that, in the example above, twenty-five percent of the sales generated are converted to profit. In this case, ($50,000 * 0.25 - $10,000) = $2,500 of profit is generated. Next, divide the $2,500 profit by 400 orders. This yields $6.25 profit per order. This is one of the better ROI measures, because all aspects of the profit equation, sales, margin, and marketing cost, are included. Better yet, this measure can be stacked-up against long-term value metrics. For instance, if a marketer loses $10.00 profit per order, but expects to get $50.00 lifetime value back, the marketer should invest in the marketing activity.

Internal Rate of Return: This metric is not frequently used, but reflects what happens if marketing dollars are continuously invested over the course of a year. In the Profit per Order equation, we netted $2,500 profit on an investment of $10,000. Let's assume that this marketing effort took place over a twenty-six week period of time. The internal rate of return is calculated as ($12,500 / $10,000) ^ (52 / 26) = (1.25 ^ 2) = 1.56. In other words, on an annual basis, this investment has a fifty-six percent interest rate. The interest rate can be compared against all other marketing activities (many of which have a different time window --- e-mail may have just seven days, for example).

Your turn! What return on investment metrics do you like to use to evaluate marketing activities at your company?

Top Four Articles From November

November saw a 40% increase in traffic. Thank you! Here's what you enjoyed reading the most in November.

• Number Four was a tie. "Business Review: Overstock.com", a discussion about profit and loss at the low-cost, low-margin online pureplay. Tied for fourth was "Return on Investment Equation and Copywriting". Google helped this out (do a search on ROI Formula, and see what appears in the top 7 results).
• Number Three was "Mergers and Acquisitions", a discussion about Eddie Bauer being purchased.
  
• Number Two was "Williams Sonoma, Incremental Online Sales and Matchback Analysis". Our multichannel retailing audience enjoyed this post.
• And the Number One article was, in a landslide, "Please Help Our Industry Measure Advertising Effectiveness!". The spreadsheet, which needs to be solved by January 31, 2007 (all valid answers will be published here), has been downloaded by individuals in nearly a dozen different countries. My hope is that a good mix of data miners, and folks from industry leaders like Abacus, Merkle, Acxiom, Unica, Experian, SAS, SPSS and others genuinely try to do good for the multichannel retailing and online industry, and provide a solution to this problem.