Category Archives: DataBase Marketing

Hacking the RFM Model

Customer Experience, DataBase Marketing, Driller Q & A, Measuring Engagement, Newsletters, Web Analytics

Jim answers questions from fellow Drillers
(More questions with answers here, Work Overview here, Index of concepts here)

Q: First of all thank you for your help.  I have some questions I would be pleased if you answer them for me.

A: No problem!

Q: 1. RFM analysis – is it possible to use some other ranking technique rather than quintiles Using quintiles for bigger databases will cause many tied values, isn’t it a problem?

A: Sure, you can use it any way it works best for you. There is no “magic” behind quintiles, you can use deciles or whatever works best. It’s the idea of ranking by Recency, Frequency, and Value that is the key concept in the model.

I’ve seen dozens and perhaps hundreds of variations on the core RFM model, depending on how you classify a “variation”. One change that’s common is changing the scaling, as you mention above, to accommodate the size of the database. Smaller databases use quartiles or even tertiles. Larger databases, choose the ordered distribution that meets the need.

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Got Discount Proneness?

Analytical Culture, Customer Experience, DataBase Marketing, Measuring Engagement, Web Analytics

Discount Proneness is what happens when you “teach” customers to expect discounts.  Over time, they won’t buy unless you send them a discount.  They wait for it, expect it.  Unraveling this behavior is a very painful process you do not want to experience.

The latest shiny object where Coupon Proneness comes into play is the “shopping cart recapture” program.  Mark my words, if it is not happening already, these programs are teaching customers to “Add to Cart” and then abandon it, waiting for an e-mail with a discount to “recapture” this sale – a sale that for many receiving the e-mail, would have taken place anyway. 

The best way to measure this effect is to use a Control Group.

When I hear people talking about programs like this (for example, in the Yahoo analytics group) what I hear is “the faster you send the e-mail, the higher the response rate you get”.

That, my friends, is pretty much a guarantee that a majority of the people receiving that e-mail would have bought anyway.  Hold out a random sample of the population and prove it to yourself.  There is a best, most profitable time to send such an e-mail, and that time will be revealed to you using a controlled test.  The correct timing is almost certainly not within 24 or even 48 hours.

That is, if you care about Profits over Sales, and trust me, somebody at your company does.  They just have not told you yet!

When you give away margin you do not have to give away on a sale, that is a cost.  Unless you are including that cost in your campaign analysis, you are not reflecting the true financial nature of the campaigns you are doing.  If you are an analyst, that’s a problem.

If you are using cart recapture campaigns, please do a controlled test sooner rather than later.  Because once your customers have Discount Proneness, it will be very painful to fix.

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Heavy Lifting

DataBase Marketing, Web Analytics

Another eMetrics (Toronto) has passed and I have to say this:  Web Analysts and Marketers proved once again they are up to the task of continuously improving the Productivity of their efforts!

At the same time, (and as I expressed during the sessions on the analytical culture), I fear that many in the web analyst community are becoming very “inwardly focused”.  They tend to talk more among themselves about the pennies they are making / saving while tripping over the dollars that are right there to be had if they reached out to other analytical disciplines in the company or measurement community.

Many among us knew this was a danger from our BI experiences.  If all you ever do is talk to each other about new shiny objects, your contribution to the business effort can suffer.  BI struggles every day with this weight, the challenge of being labeled “really smart but irrelevant”.  I don’t think we want this to happen to WA.

So with this backdrop, some of the conversations I heard at eMetrics Toronto about certain measurement practices were disturbing.  For example, it seems very few people are measuring their customer contact efforts properly, and in time this lack of analytical rigor is going to damage the WA effort for all practitioners.

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