Category Archives: Driller Q & A

Member Retention in Professional Orgs

DataBase Marketing, Driller Q & A, Marketing thru Operations, Newsletters

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

Q: I have recently purchased your book Drilling Down and going through the many interesting concepts.

A: Thanks for that!

Q:  I work for a membership Organization and we would like to conduct some analysis into who we may lose and approach them even before their membership lapses.  But the only problem here is that we carry data only on the purchases made (though many of our members do not purchase our products and stay a member) and web site visits.

A:  Are you *sure* that’s all the data you collect?  I once worked with a professional membership org that thought they only had one data source, but turns out they had 8 – from 8 different areas of the org – that nobody really knew about.

Q:  How do I know if a particular member is going to resign and lapse soon with this limited amount of behavioral data?  Recently it’s been a concern that we are losing members who have been with us for more than 10 years and who are in their mid career profession (aged between 30 to 45) and indicated no specific reason for resignation. 

This has been going on for the last few months and now we would like to strategically target these customers and approach them even before they react negative.  What concepts could help me to do this? Your guidance would be much appreciated.

A:  OK, my answer will be in two sections: if you (hopefully) find you have more data than you think, and if you really don’t have any other data to fall back on.

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Relational vs. Transactional

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

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

Q: I am hoping you can help answer a question for our team. By way of introduction, I am the CEO of XXXX. We are a specialty retailer / restaurant of gourmet pizza, salads and sandwiches. We would like to know restaurant industry averages (pizza industry if possible) for customer retention – What percentage of customers that have ordered once from a particular restaurant order from them a second time?  I am hoping with your years of expertise and harnessing data you may be able to assist us with this question. Look forward to hearing from you.

A:  Unfortunately, in those said years of experience, I have found little hard information on customer retention rates in QSR and restaurants in general (if anyone has data, please leave in Comments).  It’s just the nature of the business that little hard data, if collected, is stored in such a way that one can aggregate at the customer level. The high percentage of cash transactions doesn’t help matters much; there’s a lot of data missing.

Over the years, sometimes you see data leak out for tests of loyalty programs, and of course clients sometimes have anecdotal or survey data, but this isnot much help in getting to a “true” retention rate. More often than not you discover serious biases in the way the data was collected so at best, you have a biased view of a narrow segment. Often what you get is a notion of retention among best customers, or customers willing to sign up for a loyalty card, but not all customers. And the large “middle” group of customers is where all the Marketing leverage is.

What to do about this predicament?

There are really two issues in your question; the idea of using industry benchmarks when analyzing customer performance, and the measurement of retention in restaurants.

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RFM versus LifeCycle Grids

DataBase Marketing, Driller Q & A, Measuring Engagement, Newsletters

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 the excellent book! I’m really excited about digging into our own customer data to see what we’ll learn.

A: Thank you for the kind words!

Q: However, when you’re creating the RF Scores, what is the standard timeframe you should use? I have access to about 5 years worth of purchase data – should I create RF scores based on the last 5 years, 3 years, 2 years, 6 months?

Our sales are quite cyclical, so I think the baseline should probably be at least a year, and I’m considering doing two years. It seems as though if I get too much larger than that, my results will be too watered down.

I’m also planning on generating “historical” RF scores by filtering my data to reflect the purchases only up to a certain point. So, to generate a Q1-09 score, I’d create it from sales data of Q1-07 through Q1-09. The Q2-09 score would be from Q2-07 through Q2-09, etc. Does this make sense? It will allow us to see the changes that have been happening in our company even though we’re only just now looking at the data. It will give me a picture of what it would have looked like, had I looked at it back then.

A:  I think you have accurately understood the situation and have the right approach! This type of analysis is very sensitive to time frame.

There are really 2 broad types of customer analysis. There is analysis for action in the present, a Tactical approach driving towards a “we should do this now” result, and the more Strategic analysis, which is informational and says “this is what we should have done then” and / or “this is why we should make these business changes”. The shorter time frame is Tactical, the longer timeframe Strategic.

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