Tag Archives: Marketing thru Operations

Modeling Customer Behavior with Small Databases

Analytics Education, DataBase Marketing, Driller Q & A, Marketing thru Operations, Measuring Engagement, ,

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

Topic Overview

Hi again folks, Jim Novo here.

We’re about to take a trip into the world of small scale databases. In particular, how does a not-for-profit with a small database of donors go about using predictive models? Answer: Keep it simple. Try to avoid using a lot of variables; look for the most powerful and stick with those until you are able to uncover additonal info and grow the database. Ready?

Q: I am new in the NFP (Jim’s note – Not For Profit) sector and would like some advice re:  segmentation models to optimize campaign results – both response and value (Short Term  and Long Term).  Do you know or is there any knowledgebase of how the various techniques – behavioural, RFM, demographic, geographic – generally rate against each other?

A: Not other than my web site / book, which generally covers all the simple models. There is plenty of info around on the web though.

Assuming the end Objective is a donation, the behavioral stuff is going to be much more productive than the geo / demographics are. It’s like a pyramid.  My friend Avinash “stole” (with my permission) a slide from my presentation on this topic and put it on the web, you can see it here.  You’re looking for an “action” (donation), so actions (behavior) will be the most useful segmentation, at least as a primary cut.  Then you can get into geo /  demo stuff if it improves the model.

Q: As my database is small I don’t have the luxury of testing multiple techniques and causal factors.  I will probably run tests in series but would like a general idea of which ones to test first to cut down the time.

A:  Not sure what you mean by “small”, but in general, the more complex a behavioral segmentation approach is the larger the database it needs to be useful.  So for example, with classic RFM (125 segment scores), the bare minimum for it to make any sense is probably 5000 records, and you should really have at least 10,000.

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How Much is Promotional Proneness Costing You?

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

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

Topic Overview

Hi again folks, Jim Novo here.

Is your mission to increase Sales or Net Margin dollars? Worth getting some clarity on if you’re not sure, and if it’s Margin dollars you are after, watch out for Promotional Proneness. What’s that? The tendency of customers to learn promotional patterns and “wait for a discount”, which can significantly impact campaign profitability. Got Proneness? Read on Fellow Driller, you will learn how to find out – by measuring it using control groups!

Q:  I really have enjoyed your book.

A:  Thanks for buying it, and for taking the time to tell me you enjoyed it!

Q:  I’ve created a first draft of a customer retention strategy that outlines proposed offers at various trip wire stages, and based on your order frequency.  So, if you are a one time buyer, and you are 8 weeks over your average buying frequency, you get a certain offer, and this would differ if you were a 4-time buyer, and are just one-week over your average buying Frequency.  As you suggested, the offers increase in value the longer it’s been since you’ve purchased.

A:  So you are segmenting by Frequency and Latency and then using Recency as a trigger.  You must have really learned something from the book, I don’t think I ever covered that one specifically!  But it makes a lot of sense to use Latency instead of Recency to segment in a category with a high percentage of consumable products (FYI Dear Reader – office supplies), since there is some expectation for re-supply and the purchase rate should be relatively constant for paper, toner, pens, etc.

Q:  But how do you prevent teaching behavior that causes the customer to wait until the better offers come?  These offers would only be sent to people that hit the trip wire (not individuals buying on their own).  How do we not teach a behavior that encourages the customer to wait for the better offer?

Continue reading How Much is Promotional Proneness Costing You? →

Behavioral versus Demographic Data

Analytical Culture, Customer Experience, DataBase Marketing, Driller Q & A, Marketing thru Operations, Measuring Engagement, ,

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

Topic Overview

Hi again folks, Jim Novo here.

Most businesses want their visitors or customers to “do something” – to take an action of some kind. Trying to drive action, businesses engage in marketing / advertising to reach “audiences” with their message.

These audiences can be quantified in a number of ways using Demographics, Sociographics, and Psychographics for the purpose of “targeting” the campaign. The idea is to make the campaigns more efficient by focusing resources on the types of people thought to be more interested in the product or service.

This is fine. But from psychology and actual practice, we know behavior predicts behavior and demographics do not. So given you want people to engage in a behavior, why would you not use behavior to target campaigns? OK? Let’s do some Drillin’!

Q:  Just finished my print out version of the latest Drilling Down newsletter, and came across what is probably your best quote ever: “You should be really most interested in what people do and why, rather than who they are, because behavior predicts behavior, demographics do not”.

A:  “Print out” version?  Are you implying my newsletter is too long?  You’re not alone… :0

Q:  Man !… I’m having the design department make a big banner and hang it next to the web analytics team cubicles…

A:  My favorite story on this issue: for years we thought the “best buyer demo” at Home Shopping Network was affluent women 50+.  I mean, you hear their voices on TV, you see their letters, you just know, right?  Then we did an enhancement of the database with what was then the most comprehensive and powerful demo package available.  And it didn’t look right, there were “too many young people”.  So we rejected it.

Continue reading Behavioral versus Demographic Data →