This Week In Business: The Most Important Time In A Customer Relationship

If you are like me, you've read a lot of content about customer loyalty.

If you are able to analyze actual customer transactions, you quickly learn that the most important time in a customer relationship is the three months following a first purchase. When I run a life table analysis, I'll frequently observe that something like 40% of customers will ever purchase again --- and within the first three months, half of the 40% place their subsequent order.

My simulations strongly suggest that the two levers that really propel a business into the future are customer acquisition and first-time to second-time buyer conversion.

So focus on this important time in a customer relationship --- manage the tactics you love to employ (free shipping, discounts, promotions, all of that stuff), and add a customer service strategy (i.e. actually ask the customer if everything went well during the first order, ask the customer if she needs anything else). Treat this early timeframe with urgency!

A Laundry List Of Attributes

There's no reason that an Online Marketing Simulation (buy the book at Amazon.com or buy the Kindle version of the book) has to focus only on e-commerce purchase attributes.

For instance, here's a laundry list of attributes that are worth capturing:

• Customer subscribes to e-mail campaigns.
• Customer unsubscribes to e-mail campaigns.
• Most recent e-mail campaign click-through date.
• Customer only buys via free shipping.
• Customer prefers expedited shipping.
• Customer frequently abandons shopping cart.
• Customer never abandons shopping cart.
• Customer spends more than 15 minutes on your site.
• Customer spends less than 15 seconds on your site.
• Customer likes visiting clearance/sale pages/products.
• Customer actually read your privacy statement (hint, pay attention to this).
• Customer participated in live chat.
• Customer clicked on Facebook or Twitter icon.
• Customer generated a review of one of your products.
• Customer volunteers demographic information.
• Customer gave you contact information in an offline channel.
• Customer who clicked on "contact us" link.
• Customer watched one or more of your videos.
• Customer is a proprietary credit customer.
• Customer buys gift cards for others.
• Customer redeems gift cards.
• Customer clicked on your "careers" link.
• Customer clicks on your store locator link.
• Customer adds items to a "wish list".
• Customer clicks on your "Espanol" link.
• Customer returns merchandise.
• Customer returns more than 2/3 of merchandise purchased and has purchased 3+ times (hint, stop marketing to this customer).
• Customer purchased an extended warranty.
• Customer asks to have product automatically sent to her on a monthly basis.
• Customer utilizes rebates.
• Customer shops by brands.
• Customer shops by products.
• Customer enlarges images.
• Customer clicks on Top Sellers.
• Customer clicks on a toolbar to share products via social media.
• Customer clicks on "read reviews".
• Customer abandons items rated at two or fewer stars on a 1-5 scale.
• Customer uses site search function.

And on and on and on the list goes!

Take this information, and categorize the customer into one of forty segments, based on all of the information in the list. Combine the forty segments by five "grades" of productivity (A, B, C, D, F), and you have the perfect setup for an Online Marketing Simulation!

Dear Catalog CEOs: Selling?

Dear Catalog CEOs:

I am hearing the whispers ... "if this Holiday season isn't considerably better than last year, we're going to have to evaluate the viability of our brand."

Owners and CEOs frequently ask me to do a quick sales forecast for the next five years. A file is sent to me (CD/DVD in the mail or a file is posted on an ftp site) with various customer attributes, one row for every item a customer has ever purchased. The columns include things like household_id, order date, item number, merchandise division, quantity, price, demand, disposition (returned, item not shipped, etc.), payment tender, physical channel (phone, mail, web), advertising channel (e-mail, affiliate, search, catalog).

With this information, I look at past purchase behavior, and develop a sales forecast for the next five years. Maybe the following historical trend is representative of your business:

• 2004 = $48 million.
• 2005 = $52 million.
• 2006 = $54 million.
• 2007 = $52 million.
• 2008 = $48 million.
• 2009 = $42 million.

My job is to forecast 2010 - 2014. I'll take a run through the next five years, assuming that all marketing practices in 2010 - 2014 are the same as in 2009:

• 2010 = $39 million.
• 2011 = $37 million.
• 2012 = $36 million.
• 2013 = $35 million.
• 2014 = $34 million.

At this point, the Owner / CEO will ask me what would happen if the economy improved by 10%. I run a simulated forecast, assuming that the economy improves significantly.

• 2010 = $43 million.
• 2011 = $42 million.
• 2012 = $42 million.
• 2013 = $43 million.
• 2014 = $44 million.

We run different scenarios, based on different sets of assumptions.

• "What happens if we cut customer acquisition spend?"
• "What happens if we reduce spend on existing customers?"
• "What happens if we shift offline ad spend online?"
• "What happens if we eliminate eight pages in every catalog?"
• "What happens if we improve homepage conversion by ten percent?"

Based on the assumptions, we iterate toward what we perceive to be a fair "valuation" of the business, based on sales potential and profitability.

CEOs and Owners: You can use the Multichannel Forensics framework to understand what your catalog business might be worth. Ask your analytics team to follow the framework, generating forecasts for you.

I can easily produce the forecasts for you as well, e-mail me for details.

You'll have to admit, having this information is pretty darn important, especially if this Holiday season doesn't turn out as optimistic as one might hope.

Ad Curves

Folks on Twitter asked me to write a brief about "Ad Curves", a methodology I use to estimate what happens to sales when, say, the e-mail contact frequency is doubled, or catalog pages are cut in half, or the paid search budget is increased by 50%.

If you're interested, and I know you are interested, please download the brief here.

Hint: If you combine Online Marketing Simulations with Ad Curves, you can identify the optimal, most profitable advertising investment strategy over the next five years, optimizing long-term performance instead of optimizing conversion rates. Executives really like the outcomes outlined by these tools/techniques!

Analysts and Executives

If you are an analytics expert, and only have time to read one long blog post this year (i.e. an article longer than 140 characters), read this article from Joseph Carrabis. Jim Novo tweeted the article yesterday, thanks for pointing it out.

The article helps illustrate a huge gulf between Analytics experts and Executives, one that is about as big as the Gulf of Mexico.

Let's go back to 1994. I was Manager of Analytical Services (what would now be called 'Business Intelligence', to use the parlance of the day) at Lands' End. And I had just analyzed the results of a year long 2^7 factorial design (called MVT, or 'Multivariate Testing', to use the web analytics parlance of the day).

The results of the test were, to say the least, controversial.

One VP managed a $40,000,000 business unit that generated $2,000,000 profit, as measured by Finance. The test had 128 segments, 64 of which did not receive any catalogs from this business unit. Comparing the 64 segments that received catalogs from this business unit to the 64 segments that did not receive catalogs from this business unit yielded the following results:

• Receive Catalogs From This Division: Total Business = $900,000,000, $8,000,000 profit.
• No Catalogs From This Division: Total Business = $885,000,000, $8,300,000 profit.
• Incremental Difference: $15,000,000 Demand, ($300,000) profit.

In other words, when you stop mailing catalogs from this division, customers re-allocated their demand to other catalogs. A $40,000,000 business unit that generated $2,000,000 profit was, in reality, a $15,000,000 business that was losing $300,000 profit.

The results were statistically significant, meaning that if we rolled out a strategy where we shut down this division of the company, we'd make the right decision at least 95 times in 100.

My job was to present my findings (there were similar findings for other business units) to the VP team that led each of the business units involved in the test. The results were from a perfectly executed test with statistically significant findings that no Analyst, I repeat, NO ANALYST, would question. Any Analyst would ask how quickly the new strategy could be implemented.

I stood in front of the team of Executives, including our CEO. I shared the results.

What do you think happened?

Let's just say that the audience didn't respond with enthusiasm.

Imagine being an Executive, earning $175,000 a year, having some dweeby, geeky, inexperienced, dolt-like wing-nut pimple of an employee pull out 85 powerpoint slides generated from the results of a 2^7 factorial design that suggests the Executive should shut down his division, now. Do you think the Executive will embrace the findings? Do you think the Executive will say, "Ok, that sounds great. I'll just lay off 155 employees and wrap things up before Christmas, and I'm sure I'll get another job in another city after pulling my kids out of the school they love, because your results are absolutely self-evident?" Or do you think the Executive will fight tooth and nail for his/her job, and the jobs of the people s/he leads?

Hint: The Executive will do the latter. And so would you.

What is completely missing from our real-time, web analytics, business intelligence, on demand, multi-channel integrated world of data is leadership.

Leadership doesn't lie about or create false expectations about the power of web analytics or business intelligence. You're not going to triple your conversion rate by switching from Omniture to Coremetrics. You're not going to increase comp store sales by 5% by implementing Business Objects, MicroStrategy, SPSS, or SAS. Leadership will clearly communicate what the data is, and what it means.

Leadership makes connections between Executives and Analysts. An Executive is far more likely to trust an Analyst if the Executive has worked with the Analyst, and realizes that the Analyst is actually representing "The Voice of the Customer". It is the job of the Analyst to convert geeky, dweeby, nerdy findings into a "story" that resonates with the Executive. The Analyst cannot do this unless the Analyst has been in meetings with the Executive, knows how the Executive thinks, and knows what the Executive needs to be successful. You don't ever set up an Analyst to fail by throwing the Analyst in with the wolves. You create a safe environment, so that the Analyst can share findings without having to duck a flurry of fists.

Leadership teaches, constantly. It is never about being "right". Too often, the Analyst has data that appears to be compelling. The leader teaches context, always trying to illustrate that the Analyst is there to support a greater mission, and by doing so, the Analyst will benefit. I'd rather have an Analyst with a Bachelor of Science degree providing solid findings in a team environment than a Doctorate employee demanding that the company implement highly sophisticated findings immediately, regardless of the repurcussions.

Leadership translates information into English, or the language used in the country where you work. In other words, you remove the geek-speak, the web analytics parlance or the business intelligence parlance or the statistical mumbo-jumbo that you use when talking with Analytics experts. Nobody cares that a landing page conversion rate will outperform another landing page, based on a test of 22,948 visitors with a T-score of 2.07. Every Executive cares that the test suggests that annual sales will increase by $394,000 if a certain strategy is employed, and that the Executive will make the right decision 95 times in 100.

What is missing today is Leadership. It is missing from the Vendor community, it is missing all across Executive teams that lead Corporate America, and it is sorely missing from conference agendas. We need fewer "three easy steps to Twitter success" lectures. We need more "how to communicate with an Executive in order to be effective" lectures.

If you are an Analyst, find one person, any person, in your company who appears to make magic happen through people, by working well with others. Ask to adhere yourself to this person for three months, so that you can see how this person does her job. Then emulate this person. Your company is not going to do this for you, you must take the initiative yourself.

If you are an Executive, invite an Analyst to a meeting as an observer. Have the Analyst sit in the back of the room, and don't let the Analyst speak unless spoken to. Let the Analyst hear real business issues, and let the Analyst listen to the interactions that happen as decisions are actually made. There's no more valuable thing for an Analyst than to see how things actually work, so that the Analyst can calibrate work in a way that makes the Analyst more effective.

Analysts and Executives. Leadership is the glue that could actually join these two audiences in a mutually beneficial relationship.

Gliebers Dresses: Home Page Design

Welcome to this week's Executive meeting.

Glenn Glieber (Owner): "... so I will be performing at 2:30pm and 7:30pm at the community theater. Look for me, I'll be playing the role of Myles Standish!"

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

Kevin: "Yup, it's me."

Roger Morgan (Chief Operations Officer): "Today, we're going to talk about home page design."

Meredith Thompson: "Well, I want to talk about home page design. What we do at Gliebers Dresses is just so awful. It's not aspirational. If I'm a customer, I want to be romanced."

Roger Morgan: "What is awful about our website?"

Meredith Thompson: "Everything! Like I said, it isn't aspirational. It's a bunch of images and a hundred links. I mean, who cares about our privacy policy? And we spend more space touting our loyalty program than we spend touting merchandise."

Pepper Morgan (Chief Marketing Officer): "Describe what you want to see, Meredith."

Meredith Thompson: "Gladly. Here, let me draw this up on the grease board. I'm imagining a white, blank screen. A store front gets bigger and bigger, as if you are approaching it, a building with the words 'Gliebers Dresses' listed above doors that are opening. You walk through the doors, and music begins to play, maybe Madonna's 'Frozen' or something hip like that. Models begin to walk by, absolutely beautiful women of all sizes, all wearing our dresses, striding past. Now you're presented with rounders, with tags on top of the rounders telling the departments that the merchandise represent. I mean, just imagine seeing this, and then look at our website, which is a lot more like Newegg."

Roger Morgan: "Meredith, what you described violates just about every e-commerce best practice out there. The customer has something like two seconds to be impressed, and if she's not impresses, she's on her way to the next website. Neptune Research did a study and said you have to have at least one hundred links on the home page, or the customer won't convert at an optimal rate."

Lois Gladstone (Chief Financial Officer): "How much would something like that cost?"

Roger Morgan: "Well, first of all, we'd have to put the project on the book of work and prioritize is appropriately. Second of all, I don't think cost is the concern, I think conversion is a concern. How the heck does the customer find what she wants when fake women are walking past her on a computer screen?"

Meredith Thompson: "Roger, that's why I am a merchant and that's why you code websites. You're a tech person, you don't know anything about aspirational retail. If it were up to you, you'd have a home page with 820 links coded in Microsoft Frontpage. My job is to lead the customer. You cannot lead the customer with hyperlinks and thumbnail images. Nobody, I repeat nobody, likes to shop that way."

Roger Morgan: "And yet, Woodside Research tells us that the best performing home pages are the ugliest home pages."

Meredith Thompson: "That's because a bunch of tech folks do everything. At almost all companies, it's impossible for the merchant to sell product because the tech folks impose their will. Maybe if merchants could do what they wanted to do, merchandise would fly off the shelves. I mean, this is garbage. Modern e-commerce is all about merchants providing great product, only to have the IT department stifle all innovation. Pepper, help me out here."

Pepper Morgan: "Why don't we just test Meredith's hypothesis? There are dozens of companies that allow you to easily test different pages or offers, let's just plug in one of those services, and see what works best?"

Meredith Thompson: "Never. You lead the customer, you don't test and iterate. Testing is for cowards."

Roger Morgan: "No! I've paid thousands of dollars for research reports over the years, and those research reports tell us what the best practices are. Why ruin conversion rates just to test the ideas of a merchant?"

Pepper Morgan: "Roger, you believe in best practices, don't you? Well, when you're testing different strategies, you are employing best practices, right?"

Roger Morgan: "I think best practices are in place so that you don't have to test, somebody else did the work for you, and you get to benefit from their experience. Lois has to be happy with that, because we save money that way."

Pepper Morgan: "And Meredith, I think it is reasonable to test your strategy. If it works, you are brilliant. If it doesn't work, then maybe you can appreciate all of the efforts of all employees who are trying to help you sell your merchandise."

Meredith Thompson: "No, no testing. We need to have courage, to take a stand. Do you think I test my products? It is clearly NOT a best practice to test the merchandise that works best, you take your shots and you believe in your skills and you lead the customer. Testing is for cowards, for people who have no confidence or skill."

Pepper Morgan: "Kevin?"

Kevin: "When a business is generating ten percent pre-tax profit, these discussions don't happen."

Meredith Thompson: "What do you mean?"

Kevin: "Businesses that are winning tend to have a climate of trust."

Roger Morgan: "Are you saying we don't trust each other?"

Kevin: "I think you support each other. This whole discussion went sideways because Meredith doesn't trust the creative team, because Roger doesn't trust that merchandising might have ideas that fall within his area of expertise, and because Meredith and Roger don't trust Pepper to do what all marketers do, that being testing of strategies, because the tests might expose faulty strategies that Meredith and Roger are accountable for. In an environment of trust, Roger and Pepper would be happy to test Meredith's strategy, and Meredith would be happy to do a test, not a rollout."

Glenn Glieber: "Kevin, aren't we paying you to help us improve our profitability? All you did was throw stones at our business leaders."

Kevin: "Ok, allow me to say this differently. Testing is a best practice in marketing. Therefore, I think it is wise to test Meredith's strategy, and if her strategy works, go with it. If her strategy doesn't work, then go with what you are currently doing."

Glenn Glieber: "Fine, we'll test the strategy. Pepper, hire a vendor to help us implement the test. Meredith, work with Pepper on your idea of what the new home page looks like. And let's get this test done soon, I want to be able to impact 2010 if we can. Now, on to the next topic. I have two free tickets to my performance as Myles Standish, who wants them?"

Subtle Differences

Buy the book on Amazon.com, or buy the Kindle version here!

Time to open up your spreadsheets! (e-mail if you would like a copy).

Ok, enter the value "0.00" into cells C6 - G6. Next, enter the value "0.00" into cells B101 - B340. Finally, enter "1,000" into cell B189.

Next year, we'll retain 38.4% of these customers (cell C11). These customers will order 1.49 times (cell C16), buying 2.47 items per order (cell C17), paying $48.02 per item (cell C18). Notice that as time goes by, these customers become more loyal, buying more expensive items. By the end of year five, these customers are purchasing $83.00 items.

Now, enter "0.00" into cell B189. Enter "1,000" into cell B190.

Next year, we'll retain 36.8% of these customers (cell C11). So basically, these customers are very similar to the customers outlined earlier. However, these customers will order 1.6 times next year, buying 3.0 items per order, paying $40.89 per item.

In other words, these customers are subtly different --- about the same repurchase rate, but buying more items per order, and buying cheaper items as well.

Over time, these customers also buy more expensive items, but only spend $71.89 per item by year five. But notice that these customers are worth more in year five than the customers in the first segment (spending $77,000 in year five, vs. $57,000 in the other segment).

There are such subtle differences between customers in the businesses we manage. Our dashboards and reports suggest similarities. Over time, similar customers with subtle differences in purchase behavior diverge, becoming fundamentally different customers. When we optimize our business for short-term results, we miss out on the things that cause us to have a healthy business in the long-term.