Showing posts with label ROI. Show all posts
Showing posts with label ROI. Show all posts

## December 13, 2011

### Do You Want To Prove That Engagement Leads To ROI? Try This Methodology

Are you one of millions of marketers/analysts trying to prove that engagement exists, and more important, leads to increased return on investment?

The pick up a broom and start sweeping ... I'll show you a method that loyalty marketers have been using for twenty years to prove that loyalty marketing delivers a return on investment.  I use more technical versions of this methodology to calculate the value of loyalty programs for current clients, running a full profit and loss statement on the outcome of this analysis.  Hint:  It works!

Step 1:  Create your engagement measure.  This will be a different metric for everybody, so there's no sense spending time discussing it, you are the expert at knowing your business.  Customers who you consider to be "engaged" receive a value of "1", while customers who you do not consider to be "engaged" receive a value of "0".  Only use the timeframe up to 10/31/2011 for your engagement period.

Step 2:  Create RFM-based variables.  For each customer, through 10/31/2011, calculate months since last purchase, number of 12-month purchases, number of 13+ month purchases, and historical average order value.

Your audience is comprised of all customers with 1+ purchase (via Step 2).

Step 3:  I will assume that you don't have profitability data, so let's make this really easy.  Create a variable called "Future" ... it has a value of "0" for all customers who did not purchase from 11/1/2011 to 11/30/2011 ... it has a value of "1" for all customers who did purchase between 11/1/2011 to 11/30/2011.

Step 4:  Match the query in Step 3 to the query in Step 2.  Then, match these queries to Step 1, all at a customer level.

Step 5:  Run a Logistic Regression (you can take this much further if you have profitability data ... Logistic Regression for response, OLS for spend/profitability).  Regress Future against Recency (usually Square Root of Recency), 0-12 Month Orders, 13+ Month Orders, Average Order Value, and Engagement.

If "Engagement" is a significant predictor with a positive coefficient, then you just proved that, for the month of November, engagement during October led to an increased probability of a customer purchasing in November.

Ok, here's the SPSS code required to run the Logistic Regression procedure I described above:

LOGISTIC REGRESSION VARIABLES future
/METHOD=FSTEP(WALD) root_recency freq12 freq99 average_order_value engagement
/CRITERIA=PIN(.05) POUT(.10) ITERATE(20) CUT(.5).
execute.

Here's the outcome of a trial I ran earlier today:
In this example, the square root of recency is easily most important.  Recent orders carry about 5 times the weight of older orders.  Large dollar orders result in customers less likely to buy again in the future.  And most important (while not terribly significant), customers who were "engaged" in October were more likely to buy in November, after accounting for all other RFM-based variables.

In fact, "engaged" customers were 22.7% more likely to buy again, all things being equal.

Armed with this outcome, we can put a profitability number on "engagement".  We'll make the financial analysis terribly simple, for demonstration purposes.

Let's assume that we have 250,000 customers in the database.  Of the 250,000 customers, 5,000 are considered "engaged".  Let's assume that our 250,000 customer database has a 3% chance of buying in November.  And let's pretend that, if a customer purchases, the customer will spend \$100.  Finally, let's pretend that 35% of demand flows-through to profit, and let's pretend that one employee is responsible for improving engagement, at a cost of \$8,000 per month (salary + benefits).

Total Expected Housefile Demand = 250,000 * 0.03 * \$100 = \$750,000.

Now, we know that 5,000 engaged customers are 22.7% more likely to purchase because they are "engaged", right?  So, our calculation changes a bit.

Total Expected Housefile Demand = (245,000 * 0.03 * \$100) + (5,000 * 0.03 * 1.227 * \$100) = \$753,405.

The impact of engaged customers is ... \$753,405 - \$750,000 = \$3,405.

At 35% profit, this translates to \$3,405 * 0.35 = \$1,192 profit.

But, we hired an individual to generate engagement, and we paid the employee \$8,000 to get the job done in November.

How many "engaged" customers do we need to make the effort worthwhile?  Well, we have 5,000 engaged customers who generated \$1,192 profit, prior to employee costs, or \$0.2384 profit per customer.  To offset employee costs, we need 8,000 / 0.2384 = 33,557 engaged customers.

So, at this point, here's what we know:

1. We demonstrated that engaged customers are 22.7% more likely to purchase, all things being equal.  In this example, Engagement does lead to improvements in customer loyalty. And isn't that what you really wanted to demonstrate?
2. We only have 5,000 customers meeting "Engagement" criteria.  As a result, we only generated \$3,405 of incremental demand.
3. After accounting for employee costs, our engagement efforts are not generating a positive ROI.
4. Every engaged customer is worth an additional \$0.24 profit, per month, to the company.
5. If subsequent engagement activities result in having at least 33,557 engaged customers, we can demonstrate that increased engagement can be accomplished at break-even levels.
Statisticians will poke holes in this entire argument, and that's fine ... they can build on or change the methodology to be more appropriate for their needs.

Statisticians, however, are not the audience I am speaking to.  I am speaking to you, the Marketing Executive / Analytics Expert.  And I just showed you a method that can easily demonstrate the return on investment of "Engagement" ... a method that is more scientific and more accurate than what you're taught out on Twitter.

Now go take this methodology, and do something with it!! Stop talking about how hard it is to measure the value of Engagement ... it isn't hard, I just showed you, for free, how to do it!!  No more excuses ... just go do it!!!!

If you'd like for me to do this for you, hire me (click here), and I'll tell you what engagement means to your business.

If you think this was valuable, would you at least tweet is or share it on Facebook or on Linkedin, as a way of demonstrating that Engagement can be linked to ROI?

Thanks,
Kevin

## March 22, 2009

### 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?

## December 11, 2008

### Rule Of Thumb For Marketing ROI / Profit

You've been through this drill before, haven't you? Your CMO or CEO or CFO wants to know "what would happen if we cut twenty percent from the marketing budget?".

This is where you use the square root rule to your advantage, allowing you to give a "back of the envelope" answer to questions that require a lot of time and energy.

Assume you spent \$1,000,000 on marketing last year, generating \$3,000,000 sales. Your profit factor is 35%, yielding profit of \$3,000,000 * 0.35 - \$1,000,000 = \$50,000 .

What would happen if you cut 20% from your marketing budget.

Step 1: Sales = ((\$800,000 / \$1,000,000) ^ 0.5) * \$3,000,000 = (0.894 * \$3,000,000) = \$2,683,282. The "0.5" number is the square root ... you are taking the square root of the ratio in change of marketing spend. In this case, a 20% reduction in spend yields a 10.5% reduction in sales.

Step 2: Profit = \$2,683,282 * 0.35 - \$800,000 = \$139,149.

In other words, you'd lose a little over \$300,000 in sales, but profit would increase by nearly \$90,000.

The square root rule allows you to play these "what if" scenarios ... and the scenarios are important. Sr. Management needs to get directional answers quickly. You don't want to do a ton of work, only to have the CFO tell you to run a new scenario where you cut marketing expense by 33%.

Is the square root rule 100% accurate? Absolutely not. In fact, there are times when it is blatantly inaccurate (affiliate marketing, shopping comparison sites, e-mail marketing).

When your leadership team needs an immediate answer, at an aggregate level, this rule of thumb works well.

## October 02, 2007

### Results From The E-Mail Marketing Budget Post

Each week, I am pitched by e-mail vendors, folks asking for access to my client base, or asking me to blog about their services to you, the loyal reader.

These e-mail marketers, researchers, and vendors are hopeful that corporations will increase their e-mail marketing budgets, so that vendor products and services might be considered.

A little over three days ago, after another week of pitches, I gave the vendor community an opportunity to discuss how a hypothetical corporation might increase their marketing budget, and to quantify the sales impact of various strategies.

Here is a link to the challenge:

How many comments did I receive from the vendor community?

Zero.

One way to impress the client-side of the vendor/client relationship is to offer useful and actionable thought leadership. Given the number of pitches I receive, vendors, researchers and marketers missed an opportunity.

In this example, the e-mail marketer generated \$10,400,000 demand per year by blasting a million e-mails per week, 52,000,000 per year. I asked folks to offer strategies that might increase demand, profit and ROI, quantifying the impact for my readers.

Let's talk about a few topics.

E-Mail Frequency: In this example, the corporation chose to send one campaign per week. Here is a table that illustrates the expected demand, profit and ROI based on number of contacts:

 Annual E-Mail Return On Investment By Frequency (in 000s) Demand Cost Profit ROI \$/E-Mail 1 Contact Per Month \$5,200 \$250 \$1,570 628.0% \$0.43 1 Contact Per Week \$10,400 \$1,000 \$2,640 264.0% \$0.20 2 Contacts Per Week \$14,708 \$2,000 \$3,148 157.4% \$0.14 3 Contacts Per Week \$18,013 \$3,000 \$3,305 110.2% \$0.12 4 Contacts Per Week \$20,800 \$4,000 \$3,280 82.0% \$0.10 5 Contacts Per Week \$23,255 \$5,000 \$3,139 62.8% \$0.09

Companies that do thorough e-mail contact strategy testing have learned several interesting facts. Notice that it is possible to start losing money as e-mail contact frequency increases. Increased frequency dilutes demand per e-mail --- so that even at a very minimal cost per e-mail contact, profit begins to decline after three e-mail contacts per week (in this example --- your mileage may vary).

E-Mail Targeting: Targeting strategies can effectively increase demand per e-mail. Many companies in my industry have an e-mail list where between ten percent and fifty percent of the list have no customer information appended to it. In other words, all you know about these folks is their e-mail address. You're not going to improve performance via targeting with these individuals.

With the remaining individuals, you might get a 30% increase in demand by executing e-mail targeting strategies. The weighted average of these two populations results in a conservative increase in demand of, say, 20%. The following table overlays the 20% increase in performance, adding the marginal cost required to execute the targeting strategy.

 Annual E-Mail Return On Investment By Frequency (in 000s) Demand Cost Profit ROI \$/E-Mail 1 Contact Per Month \$6,240 \$269 \$1,915 712.7% \$0.52 1 Contact Per Week \$12,480 \$1,075 \$3,293 306.3% \$0.24 2 Contacts Per Week \$17,649 \$2,150 \$4,027 187.3% \$0.17 3 Contacts Per Week \$21,616 \$3,225 \$4,341 134.6% \$0.14 4 Contacts Per Week \$24,960 \$4,300 \$4,436 103.2% \$0.12 5 Contacts Per Week \$27,906 \$5,375 \$4,392 81.7% \$0.11

Let's say your Chief Marketing Officer doesn't want to "spam" customers ... so the CMO allows you go to from one e-mail campaign per week to two targeted e-mail campaigns per week, each targeted campaign having five creative versions sent to customers based on past purchase history, past clickstream behavior, and past website preferences. Let's compare the expected results, current program vs. proposed program.

Current Program: 1x Per Week, Same Version To All Customers
• Demand = \$10,400,000.
• Marketing Cost = \$1,000,000.
• Profit = \$2,640,000.
• ROI = 264.0%
• Demand per E-Mail = \$0.20.
Proposed Program: 2x Per Week, Customer Receives One Of Five Possible Contacts
• Demand = \$17,649,000.
• Marketing Cost = \$2,150,000.
• Profit = \$4,027,000.
• ROI = 187.3%
• Demand per E-Mail = \$0.17.

Notice the difference in results between the current program and the proposed program.

Demand increases by 69%.
Marketing expense increases by 115%.
Profit increases by 52%.
ROI DECREASES.
Demand per E-Mail DECREASES.

My guess is that your CFO will be happy with you if you demonstrate that you'll double your e-mail budget, while delivering a 52% increase in profit and a 69% increase in demand.

What Did We Learn?

First, e-mail marketing is a lot like catalog marketing. There are simple ways to quantify the impact of frequency and targeting. Go ask the catalog marketer down the hall to help you, if this type of work is a challenge for your organization.

Second, once we quantify the impact of these strategies, investment in e-mail marketing is self evident. You'll quickly find the optimal contact strategy, one that yields an increase in demand and profit. The investment quickly cost-justifies itself.

Third, the outcome of the analysis points to areas where you may need help. You'll probably need help developing a targeted e-mail scoring algorithm. I've created many of these, I'm sure your e-mail vendor does a great job as well. The targeting algorithm is where the benefit occurs. I baked those costs into the example.

Fourth, you'll probably benefit by having a campaign management software tool to integrate the scoring algorithm with your selection criteria. If you're a cataloger, you are probably using Unica Affinium for catalog campaign management. Simply apply Affinium (or your campaign management tool or even use SAS/SPSS), and send the list with targeted versions by e-mail address to your e-mail vendor for blasting purposes. I baked these costs into the example.

Fifth, start demanding more of your e-mail vendors. Fluffy pitches and glowing articles mean little. In this example, ROI (as catalogers know) actually decreases! Yet, demand and profit increase. ROI doesn't pay the bills --- actual profit dollars pay the freight, keeping you employed.

Sixth, while not included in this analysis, you'll want to monitor opt-out rates as frequency increases. At one company I worked with, we noticed that if we went past "x" e-mail campaigns per week, too many people opted-out, causing us to lose all the profit we gained via the targeting strategy.

Ok, your turn. What strategies would you recommend, and what would the increase in demand and profit be after implementing these strategies?

## September 29, 2007

### You Decide: The E-Mail Marketing Budget

This might represent the marketing budget for a multichannel cataloger:

 Marketing Budget (Dollars in 000s) Profit = Variable Profit, Before Fixed Costs Annual Total Total Budget Demand Profit ROI Catalog Marketing \$10,000 \$37,500 \$3,125 31.3% E-Mail Marketing \$1,000 \$10,400 \$2,640 264.0% Search Marketing \$3,500 \$14,000 \$1,400 40.0% Online Marketing \$2,000 \$6,500 \$275 13.8% Total Marketing \$16,500 \$68,400 \$7,440 45.1%

Let's assume that the e-mail marketing program is reasonably basic in nature. In other words, the customer can opt-in on the website, or if the customer purchases online, the customer is automatically opted-in to the e-mail program, and can elect to opt-out at any time.

The e-mail marketing program has 1,000,000 addresses. The company does not execute targeted campaigns (i..e. unique creative to different customers with different interests), executes a weekly campaign to all 1,000,000 addresses, and generates on average \$0.20 per e-mail. The program typically offers free shipping as a purchase incentive.

The company has tested targeted versions of e-mail campaigns, observing a 35% increase in productivity.

Here's the question, folks. So many e-mail marketers feel that e-mail does not get its fair share of marketing dollars. In this case, what should the e-mail marketing investment be, what are the tactics this company should employ, and what is the expected increase in demand and profit (profit = 0.35 * demand - marketing cost)? Please let my readers know what you would do, how much you would spend, and what the financial benefit would be to this company.

## September 26, 2007

### E-Mail ROI: Again

The e-mail community is on a mission to prove it is "right".

The community continues to use the "ROI" metric as a way to shoot down paid search, portal advertising, shopping comparison sites, affiliates, and catalog marketers.

ROI is typically measured as the "profit dollars obtained in a campaign divided by the marketing cost to execute the campaign".

E-mail depends upon two very important metrics --- one dramatically working in its favor, one dramatically working against e-mail.

After factoring in staffing levels (which may be comparable for online advertising, catalog advertising, e-mail and search marketing), the incremental cost to do e-mail marketing is low --- almost zero.

By default, this yields a ridiculously high and meaningless "ROI" metric --- the metric e-mail advocates use to defend investment in e-mail ROI.

The metric working against e-mail is sales per contact. E-mail is awful at generating sales volume per contact. Catalogs and paid search are great at generating sales volume per contact/click.

The table below illustrates this fact:

 Return On Investment: Marketing Tactics Catalog E-Mail Paid Search Demand \$4,000,000 \$400,000 \$4,000,000 Net Sales \$3,200,000 \$320,000 \$3,200,000 Gross Margin \$1,600,000 \$160,000 \$1,600,000 Less Adv. Cost \$1,000,000 \$1,200 \$1,000,000 Less Pick/Pack/Ship \$384,000 \$32,000 \$384,000 Variable Operating Profit \$216,000 \$126,800 \$216,000 Profit As A % Of Sales 6.8% 39.6% 6.8% ROI 21.6% 10566.7% 21.6% Circulation / Search Clicks 1,500,000 2,000,000 3,000,000 \$ per Contact \$2.67 \$0.20 \$1.33 Orders 40,000 4,000 40,000 Cost per Order \$25.00 \$3.33 \$25.00

The dynamics of cataloging and search marketing are very different than the dynamics of e-mail marketing. You never hear e-mail advocates talk about a \$0.20 demand per e-mail delivered. Nope. E-mail advocates scan a profit and loss statement like this, pick out the two metrics that look the best (ROI and Cost per Order), and then beat up folks who work on other marketing tactics.

Chief Marketing Officers are pressured to drive sales now --- or they lose their job. It's hard to drive sales at \$0.20 per contact, when paid search and cataloging drive so much more volume than e-mail marketing.

Dive in head-first, and do your best to maximize all marketing activities. You should have a great e-mail program, using best practices and targeting strategies and personalization to maximize ROI. It is absolutely worth the effort!

Just listen with a grain of salt when you read the research reports and vendor marketing articles that tell you that e-mail has the best ROI, articles and reports that beat up others to justify investment in e-mail marketing.

Look at the net sales and profit dollars generated by each marketing activity, and let those metrics speak for themselves. E-mail will be able to stand on its own merits.

## September 11, 2007

### Blogging ROI For A Small Business, Like My Small Business

I'm frequently asked what the ROI is of my blogging efforts. Year-to-date, 30% of my project work is sourced from folks who subscribe to my blog, or found the blog via a search.

If you're a small business, and you're willing to give your audience something tangible, something they can actually use, you should be able to realize a positive ROI for your efforts.

### E-Mail Marketing Challenge: Assigning Customers To Versions

Deciding who receives a version of an e-mail campaign is a challenge.

You seldom read common-sense logic that explains what you should do, partly because it is hard work, partly because vendors want to monetize this process by doing the work for you.

Let's review a simple example, one that clearly outlines the challenges we all face.

The table below illustrates seven e-mail subscribers, and the amount each customer spent on Mens and Womens merchandise over the past year.

 Cust # Mens Womens One \$50 \$0 Two \$0 \$900 Three \$400 \$200 Four \$0 \$0 Five \$1,335 \$1,335 Six \$0 \$600 Seven \$150 \$150

Based on the purchase habits of these seven individuals, we have to assign three customers to the Mens version, and four customers to the Womens version.

Method #1 = Prioritization: One of the easiest strategies is to prioritize one version of the e-mail campaign over another. In other words, the database marketer may decide that the Mens version receives top priority. In that situation, the three highest-spending Mens customers get the Mens version, with everybody else receiving the Womens version.
• Mens Version = Customer Number Three, Five and Seven.
• Womens Version = Customer Number One, Two, Four and Six.
Had the Womens version been prioritized first, the assignment would have looked like this:
• Mens Version = Customer Number One, Four and Seven
• Womens Version = Customer Number Two, Three, Five and Six
Notice the challenge with this method. While this is the easiest method to execute, the method results in the version with the highest priority receiving the best customers. This means that the version with the highest priority will generally perform best. The version with lower priority will generally not perform as well.

Method #2 = Versions Based On Spend: In this case, customers are assigned to versions based on which merchandise division the customer prefers. This works well in theory. Notice in our case that customer numbers four, five and seven spent equal amounts in each version. Therefore, we have the following situation:
• Mens Version = Customer Number One and Three.
• Womens Version = Customer Number Two and Six.
• Ties = Customer Number Four, Five and Seven.
The database marketer could randomly decide which of the three customers with ties receives the Mens version, and then allocate the other customers to the Womens version.

Method #3 = Versions Based On Expected ROI: Experienced e-mail database marketers assign an expected ROI to each customer, for each version of an e-mail campaign. In this case, each customer is "scored" based on the demand per e-mail / ROI expected from the customer, if mailed either version of the e-mail campaign. The Womens version of the e-mail campaign is expected to perform twice as well as the Mens version of the e-mail campaign. Let's look at the "scores":

 Cust # Mens Womens One \$0.106 \$0.163 Two \$0.085 \$0.329 Three \$0.164 \$0.213 Four \$0.085 \$0.163 Five \$0.397 \$0.794 Six \$0.085 \$0.252 Seven \$0.126 \$0.187

When we score each customer based on expected sales per e-mail sent, we see a problem, don't we?

The Mens version is expected to perform half as well as the Womens version. So, when evaluating each version of the e-mail campaign, we come to the logical conclusion that we should only have one version of the e-mail campaign ... the Womens version ... right?

Now go sit down in the office of the Mens Merchandise Executive, and tell him/her that we won't be sending an a Mens e-mail to our customers, because customers don't respond to Mens merchandise. After you make that statement, cover your ears and duck!!!!

So, you're left with a tough choice. What you have to do is assign the best customers to versions, "subject to constraints". In this case, the constraint is that we have to send three Mens e-mail versions to customers, yet we want to maximize the total ROI for the campaign.

A good tool to solve this problem is "linear programming". I don't have enough room to go into all the math here, but if you use software from Unica (the folks who brought catalogers the "Affinium" campaign management tool), you can purchase an add-on that does this for you. The add-on isn't cheap, but you're likely to recoup your profit in short order.

Of course, there are many, MANY ways to solve this problem. Here's an opportunity for you to share your thoughts. How would you attack this challenge?

## August 30, 2007

### 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.

## July 16, 2007

### Multichannel Retailing Week: The CFO

As we complete the transition from catalog and retail to "multichannel retail", we find we don't have the technology solution or marketing strategy necessary to meet the needs of our customers.

This is where the multichannel CFO comes into play.

The multichannel CFO determines the investment strategy for the business. The CFO has a set budget, one largely determined by the growth trajectory of the business. As sales increase, investment can increase (though hopefully at a slower rate than sales, yielding more profit).

In the early days of the internet, some incremental sales were being added to the business. Coupled with competitive pressures, multichannel CFOs invested tremendous amounts of capital building and improving e-commerce enabled websites.

However, in our post-Google multichannel environment, things have changed. Direct-to-consumer sales are growing at subtle rates. This introduces risk in the investment portfolio of the multichannel CFO.

Take the traditional catalog CFO. This individual likes to look at the 'ad-to-sales' ratio on the profit and loss statement. If you sum catalog advertising and online advertising, and calculate the ad-to-sales ratio, you will likely see an increase in this ratio over the past five years. This means that the introduction of e-commerce has not grown sales at a sufficient rate to offset the increased advertising expense necessary to support multiple channels.

The traditional catalog CFO, armed with the information, is likely to challenge the CMO or Database Marketing executive to "mail smarter", and better leverage online marketing strategies, shifting dollars out of catalog and into paid/natural search, affiliates, portal advertising and e-mail.

Until ad-to-sales ratios improve, it will be difficult to convince traditional catalog CFOs to invest in multichannel solutions.

The traditional retail CFO has a different set of concerns. To please shareholders, the CFO must grow comp store sales, and must increase the number of new stores in new markets.

Ultimately, the traditional retail CFO has to decide whether it is a better to invest in multichannel technology improvement, multichannel advertising increases, new stores, remodeled stores, and all other internal investment needs necessary to run the business.

This is where we really fail the traditional retail CFO.

The traditional retail CFO has several "knowns":
• If the CFO invests in a new 6,000 square foot store, the business will probably get \$2,000,000 of net sales per year. It might cost \$1.7 million dollars to build the new store.
• If the CFO invests in remodeling a 6,000 square foot store, the business will probably get an additional \$400,000 of net sales per year. Maybe it costs \$0.7 million dollars to remodel a store.
• If the CFO invests in catalog or online advertising, there is a known incremental rate of return for the increased investment.
For multichannel investments, the CFO has a great big "unknown".
• Say the multichannel CFO invests \$1.7 million in inventory systems and point-of-sale systems to facilitate "buy online, pickup in stores".
• What are the incremental sales that will be generated by this strategy? Will the incremental sales be more than what is observed in a store remodel? Will the incremental sales be more than what is observed when a new store is built?
The CFO depends upon the multichannel advocate (the CMO or the Database Marketing executive or the catalog/online executive) to "prove" that a multichannel investment will generate a better ROI than a new store or remodeled store.

So, the multichannel advocate uses research reports, anecdotal information, 'our competitors are doing it so we have to do it', 'our customers demand it', and the time-honored "multichannel customers are 'x' times more valuable than single channel customer" metric to "sell" the multichannel strategy.

CFOs don't like flimsy comments like these. CFOs want to know, with certainty, that multichannel investment yields a competitive ROI that exceeds the internal cost of capital.

It is my opinion that this relationship, as described above, limits the pace at which multichannel organizations implement true multichannel solutions.

This would be a great place for a vendor, research organization, or consulting firm to provide actual facts that help the CFO. The CFO is going to look at Circuit City, the poster child for 'buy online and pickup in stores', and say 'Gee, that strategy hasn't helped them financially, why should I make the same mistake?' The vendor, research organization, or consulting firm is going to have to provide actual facts, positive and negative, if they want the CFO to advance shared objectives.

The Database Marketing team has to view the business differently, illustrating the long-term impact on the customer file. The potential long-term impact on the customer file is what fuels the investment in multichannel strategies.

Over the next decade, your multichannel CFO is going to become even more critical of the ad-to-sales ratio, and will demand that total net sales increase at a fast rate. If total net sales do not increase at above-average rates, it is unlikely we'll see CFOs supporting multichannel initiatives at the level we'd all like to see happen.

Your turn: Does your multichannel CFO have the right information necessary to make multichannel investment decisions? What information does your multichannel CFO need to improve multichannel systems and strategies?

## July 05, 2007

### 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.

## May 28, 2007

### 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.