- "Multi-Channel customers are the best customers."
- "Your best customers participate in Social Media, so you have to join the conversation so that you can reap the rewards."
- "The biggest spenders love loyalty programs, so you need to reward best customers to remain competitive in today's highly complex retail landscape."
If you have access to customer data, you can do some research on your own. And when you do some research on your own, you learn about a curious pattern that happens when drafting simple queries based on "best" customers vs. all other customers.
Look at the data in the table at the start of this post. Let's query the table. We'll calculate the average amount of spend a customer had if they possess the attribute, and the average amount of spend the customer had if the customer does not possess the attribute. Here we go.
Lives In An Urban Zip Code:
- Yes = $900. No = $475.
- Strategy: Find urban customers, because urban customers are your best customers. Or encourage your customers to move from a rural environment to an urban environment, because they will spend $425 more if they move, based on your findings.
- Yes = $900. No = $475.
- Strategy: Partner only with Visa on special promotions, ignoring all other tender types, because Visa purchasers are your best customers. Or offer a promotion to get AMEX customers to switch to Visa, because you'll benefit from the switch.
- Yes = $733. No = $600.
- Strategy: Give discounts and promotions to Twitter followers, because those are your best customers and they will evangelize your brand for you.
- Yes = $850. No = $580.
- Strategy: Ignore Android and focus only on Apple, because your best customers love Apple. Apple customers outspend other customers by $270 each. Or better yet, encourage Android customers to switch to the iPhone, because it will benefit your brand.
- Yes = $967. No = $425.
- Strategy: Get all of your customers to participate in your loyalty program, because customers in the loyalty program outspend non-members by more than $500.
- Yes = $733. No = $600.
- Strategy: Fully invest in a bricks 'n clicks environment like Borders or Blockbuster, because your best customers shop multiple channels.
- Yes = $800. No = $600.
- Strategy: Develop a catalog marketing program that is targeted to your best customers, because best customers love receiving paper in their mailbox. Or try to force your customers to shop from a catalog, because they will become better customers. Explore television commercials, billboards, and radio advertising as well, because your best customers are offline mavens.
- Yes = $1,033. No = $375.
- Strategy: Force all customers to pay for expedited shipping, because when you do that, you end up with customers who spend 2.9 times as much as customers who don't pay for expedited shipping.
- Yes = $975. No = $233.
- Strategy: Give a customer $10 off their next order if they return merchandise today, because customers who return merchandise spend $700 more than customers who don't return merchandise. By providing a financial incentive to return merchandise, you will increase customer value.
- Yes = $700. No = $600.
- Strategy: Send every customer in your database a free Yahtzee! game, because customers who possess a Yahtzee! game outspend all other customers by $100.
It's a fascinating analysis, because for 85% of the attributes you analyze, you'll find that customers who possess the attribute outspend customers who do not possess the attribute. It's a mathematical "dilly of a pickle", if you will ... it turns out that your best customers tend to do everything, and that skews the results, causing nearly every query to exhibit a "best customer bias".
Seriously, go perform this analysis on your own customer database. If you're a vendor, go run this analysis on your customer base, you'll see the same thing.
"Best Customer" analytics that depend upon simple queries provide highly misleading results ... in fact, the outcomes are utterly impossible to decipher.
And you know this is true. If it were not true, then you would have capitalized on all of the ideas that you read in trade journals, blogs, Twitter, you name it, and your annual retention rate would have increased from 45% to 60%, right? But you go back a decade, and you see that you've added channels and loyalty programs and advanced analytics and increased online spend and participated in offline marketing programs and social media and mobile and ... well ... you haven't increased your retention rate ... and spend is up at an inflationary rate.
Oh boy.
A better, but more complicated analysis, is to pick a period in time (say January 1, 2010). Freeze customers as of 12/31/09, tabulating customer attributes at that time. Then regress all attributes (like the ones in the table above) against spend during 2010. If the coefficient for an attribute is significant and positive, then you know that the attribute contributes positively to future spend.
I know, it's humbling to know that everything you've been taught isn't yielding profitable increases in customer retention. It's frustrating to know that the secret to success is having a profitable customer acquisition program. Run your own analytics against your own customer database, and learn for yourself why traditional "best customer" analyses are hopelessly flawed.
I like to give credit where credit is due and you deserve credit for that lucid post!
ReplyDeleteOh I love this post Kevin! You really get the point across. I'm still laughing!!
ReplyDeleteReminds me of when the newspaper reported that car thieves love to steal Honda Civics because they ranked first in the number of stolen cars in British columbia that year. Their angle was it's safer to buy a different kind of car. Because the number of stolen cars had nothing to do with the fact Civics per capita here is 1.2... :-D
Yup, that's the thing, simple queries/metrics lead to odd conclusions!
ReplyDelete