19 Nov 08 - Mark Klein
As regular readers here know, we’re passionate about testing at Loyalty Builders. It’s the quickest way to improve your marketing campaigns. To spread the testing gospel, we recently posted a free online calculator to tell you how big a sample size is needed for your test, or to compute the power of a test with a given sample size. The calculator is designed for marketers, not statisticians, though several statisticians are using it. To make it more accessible to marketers, we also wrote an extensive tutorial, and that’s where the fun started.
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11 Sep 08 - Mark Klein
10. Ignorance: They’ve never heard of it.
9. Irrelevance: Most of their customers are one-time buyers, so how could mathematical marketing help?
8. Overconfidence: They think their current marketing program is working fine. They already know who their best customers are. They’re getting 80% of their revenue from 20% of their customers. What could be better?
7. Skepticism: They doubt it works; they believe all customers defect sooner or later.
6. Resistance to change: Regardless of whether it improves the bottom line in the long-run, they are unwilling to change doing business as usual.
5. Inexperience: Mathematical Marketing appears complex, requiring skills and people they don’t have.
4. Cost: It sounds expensive
3. Intimidation: Marketing is an art, and math belongs in the classroom.
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25 Aug 08 - Mark Klein
I was meeting with a new client recently who asked me what would be the effects on their business from adopting a mathematical marketing approach. I quickly responded with the obvious answers that came from my experience with many other companies, namely that they would see higher response rates and more revenue from their marketing campaigns. This was a results-oriented answer supported by multiple campaigns conducted by many different types of businesses.
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04 Aug 08 - Mark Klein
Some of my friends have helped me to a better understanding of the difference between loyalty and satisfaction.
They live in a mid-sized city in the mid-West. For a long time their city has been primarily served by Northwest Airlines, so they are frequent fliers on that airline. By many measures they are loyal customers of Northwest.
But when you talk with them you quickly learn that they are more trapped than loyal. They don’t have alternatives, and to them the airline is “Northworst". Loyalty may be high, but satisfaction is not. If there was another carrier, my friends would switch in the blink of an eye.
I’m sure you know instances of customer loyalty being more the lack of alternative vendors than of a favorable opinion. So how do you think a company should operate when many customers who appear to be loyal are really trapped?
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23 Jul 08 - Mark Klein
We believe that there is a big fallacy buried in the strategy of companies that use direct mail.
Most direct mailers, especially catalogers, have a ‘house list’ of customers to whom they mail. This list is scored by one methodology or another, for example recency or RFM (Recency, Frequency, and Monetary value). These companies usually talk about “mailing down” the list to some point called the “break-even point”. By this they mean they have ordered their scored list with their best customers at the top and their worst customers at the bottom, and have identified a point on the list below which it is unprofitable to mail. “Unprofitable” typically means that the mailing cost to reach these lower ranking customers exceeds the gross margin dollars that the mailing generates.
26 Jun 08 - Mark Klein
25 May 08 - Mark Klein
An interesting article, “Guessing the Online Customer’s Next Want” by Eric Taub, appeared last week in The New York Times. Taub starts out on the right track when he says, “Marketers have always tried to predict what people want, and then get them to buy it.” Many marketers do try to predict. Unfortunately many more don’t bother trying. As a result, you and I are inundated with uninteresting direct mail and email. Happily, Taub focuses on a retailer that does try, and on the methodology being used, collaborative filtering. Calling attention to this effort is worthwhile, and I’m pleased to see a spotlight on predictive analytics.
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16 May 08 - Mark Klein
This week, when I asked a new client what kinds of insights her company was expecting from using Longbow, I had to restrain myself from an offensive, too sharp reply. She said she wanted our analytics to identify her best customers. We get that request often, and sometimes it can drive me up the wall.
There were several reasons for my frustration. First, she should already know her best customers, because they are spending the most and buying often. How well could her company be managing if they don’t know their best customers? Second, if her company had been doing any segmentations at all, those top customers would stand out. Even unsatisfactory linear methods like RFM will identify best customers. Third, she was asking the wrong question.
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20 Apr 08 - Mark Klein
Sometimes I show some resolve and actually carry out my resolutions. Yesterday was one such day—I cleaned out my wallet, which was too light on money and too thick with cards from various loyalty programs. Pruning those loyalty cards made me look at each program and decide whether participation was worth it, whether there was there a decent quid pro quo for using the program.
The obvious description of customer loyalty programs is that they are a way for a company to thank its regular customers for their continuing patronage with rewards and discounts. Whether it is a coffee card for an extra java after ten purchases or free tickets to Hawaii after a winter of business trip, we all especially enjoy the “free” product or service. It’s nice to be appreciated and thanked.
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