Category Archives: Marketing / Tech Interface

Measuring Distributor / Agent Loyalty in Service Businesses

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

Today we have a fellow Driller looking to compare the “loyalty” of sales / distribution agents for insurance products and use this information to manage business with the agents more effectively. In this case, knowledge of the business is exceedingly important because segmentation of business lines across regions will dramatically improve predictions.

Let’s do some Drillin’!

Q: Hi Jim,

I happened upon your site and found the information there very valuable – so much so that I ordered your book (customer is referring to Drilling Down).

A: Well, thank you very much for that!

Q: I’m a marketing manager with an insurance company that distributes its life, auto, home, and business insurance products through independent insurance agents.  These agents represent our company as well as others.

I’m interested in techniques for measuring agent loyalty – which I think would be demonstrated by the agents choosing to place business with our company instead of another company they represent for policies.

A: I’m not sure in this case anything is too terribly different from the scenarios used in the book. Essentially, agents or consumers demonstrate loyalty though their actions, and if you can track their actions, you can spot increasing or decreasing loyalty.  Your business is more complex in many ways than retail, but to the consumer (in your case agent), there are always choices to be made between alternatives, and changes in the purchase patterns agents or consumers generate often precede customer defection.

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Behavior Profiling for Long Sales Cycle B2B Customers

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

So Jim, this customer behavior profiling / prediction is great for consumer businesses, but what happens if you’re running a long sales cycle B2B biz where buying decisions take months if not years, and may involve a dozen decision makers? Well fellow Drillers, the answer is not as complicated as you might think – it’s about where to look for the predictive behavior outside of the sale transaction. Interested? Let’s get to the Drillin’ …

Q:  I read your section about how “R” and “F” are better indicators than “M” which I agree. But for the problem I face, do you have any ideas on how I can redefine “F” for my purpose?  If not, I can always use RM, but will face the drawbacks you mentioned in the book which I think are legitimate concerns for predicting potential value. 

(Jim’s note: this Driller is referring to the modified RFM model used in the Drilling Down book.  For an overview of what he is talking about see this description of what is in the book and this outline of RFM.)

A: Just to ground this discussion, I assume you are talking about Company XXX …
(a major enterprise software company with many products. He said Yes)

You should look for R and F in other places, if “short term” prediction is what you are after  (I’ll discuss long term in a minute).  Long cycle businesses like enterprise software can be more difficult to model because the variables you are looking to do an RF scoring on are not as obvious.  The sales activity may not be particularly predictive of customer behavior because the nature of the business precludes frequency of purchase.

For example, think customer service.  Where in your organization would you see RF show up relative to customer satisfaction?  Perhaps at the call center, help desk, or “outstanding issue” logs of the implementation team?  There could certainly be other areas, depending on how customer care is set up.  The question is: how does the Recency and Frequency of customer care predict the likelihood of customer defection?

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Omni-Channel Cost Shifting

One of the great benefits customer lifecycle programs bring to the party is unearthing cross-divisional or functional profitability opportunities that otherwise would fall into the cracks between units and not be addressed.  What I think most managers in the omni-channel space may not realize (yet) is how significant many of these issues can be.

To provide some context for those purely interested in the marketing side, this idea joins quite closely to the optimizing for worst customers and sales cannibalization discussions, but is more concerned with downstream operational issues and finance.  Cost shifting scenarios will become a lot more common as omnichannel concepts pick up speed.

Shifty Sales OK, Costs Not?

Why is cost shifting important to understand?  Many corporate cultures can easily tolerate sales shifting between channels because of the view that “any sale is good”.  On the ground, this means sourcing sales accurately in an omni-channel environment requires too much effort relative to the perceived benefits to be gained.  Fair enough; some corporate cultures simply believe any sale is a good sale even if they lose money on it!

Cost shifting  tends to be a different story though, because the outcomes show up as budget variances and have to be explained.  In many ways, cost shifting is also easier to measure, because the source is typically simple to capture once the issue surfaces.  And as a cultural issue, people are used to the concept of dealing with budget variances.

Here’s a common case:

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