Monthly Archives: April 2024

Context Parameters for Best Use of Recency Metric

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

Time to take a look at some basic strategy framework ideas in a customer retention program. You have to know where you are first before you can decide what actions to take, and this initial analysis will prompt ideas for action. Trust me, finding out specifically what is happening in an actionable way is the most critical step to the design and execution of a customer retention program. Not doing this is why so many of the programs fail. Ready, Driller? Let’s do it.

Q:  I’m reading some of your information you have on your web site, regarding Recency / Frequency.  I’m curious about the statement that Recency is the number one most powerful predictor of future behavior – if you did some thing recently you’re more likely to do it again.  

A:  Yes.  Funny thing about web sites, it’s hard to control what sequence people read things in.  From the questions below, I believe I have failed to introduce you to the Recency metric in the right context.  Shame on me!

Q:  With regards to purchases, how is this so?  I can think of numerous instances where this might not be true.  In fact, I would guess that price of purchase would be a more likely indicator of whether or not someone would purchase again.  If I’m running Best Buy, and someone comes and buys a washer / dryer, I would not expect they’d be buying another one anytime soon.  Ditto furniture, cars, travel bookings, etc.

A:  Two important “context” issues surrounding Recency.  First, Recency is a “relative” metric, it doesn’t exist by itself, but “relative” to other data points.  In the case of customers, Recency and the “likelihood” is a relative comparison of two customers, two customer segments, or a customer versus the average customer, for example.  So for a washer / dryer purchase, looking at the customer in question, Recency answers the question, “how likely is this person to purchase relative to another customer”.  It’s a scoring system, a ranking of likelihoods to (in this case) buy, or visit, or download, or whatever.

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