Tag Archives: Customer State

Measuring dis-Engagement

Engagement Matters – Until it Ends.  Right?

Here’s something that continues to puzzle me about all the efforts around measuring Engagement and using these results as a business metric or model of online behavior.

If Engagement is so important to evaluate – and it can be, depending on how you define it – then doesn’t the termination of Engagement also have to be important?  If you desire to create Engagement, shouldn’t you also care about why / how it fails or ends? And if the end is important, what about how long Engagement lasts as a “quality” metric?

Seems logical the end of Engagement might matter.  Let’s call it dis-Engagement.  Simple concept really: of the visitors / customers that are Engaged today (however you define Engagement), what percent of them are still Engaged a week later?  3 months later?

Whatever dis-Engagement metric you decide to use, a standard measurement would create an even playing field for evaluating the quality of Engagement you create.  From there, a business could invest in approaches producing the most durable outcome.

Since Engagement is almost always defined as an interaction of some kind, tracking dis-Engagement could be standardized using metrics rooted in human behavior.  Recency is one of the best metrics for an idea like this because it’s universal, easy to understand, and can be mapped across sources like products and campaigns.  Recency is also predictive; it provides comparative likelihoods, e.g. this segment is likely more engaged than that one.

Plus, using Recency would align online customer measurement with offline tools and practices.  This could have implications for ideas like defining “current channel”, e.g. customer is now engaged with this channel, has dis-engaged from that channel.

Taking this path brings up a couple of other related ideas, in line with the discussion around customer journey and entwined with the whole customer experience movement.

Peak Engagement

Let’s say there is Engagement, and because we’re now measuring dis-Engagement, we see Engagement end.  So, is Engagement a one-shot state of being, meaning the value should be measured as such?  Or, does longer lasting Engagement have value, and if so, what about when it ends? Shouldn’t we want to find the cause of dis-Engagement?

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Increase Profit Using Customer State

The following is from the March 2011 Drilling Down Newsletter.  Got a question about Customer Measurement, Management, Valuation, Retention, Loyalty, Defection?  Just ask your question.  Also, feel free to leave a comment and I’ll reply.

Want to see the answers to previous questions?  Here’s the blog archive; the pre-blog newsletter archives are here.

Q: We’ve been playing around with Recency / Frequency scoring in our customer email campaigns as described in your book.  To start, we’re targeting best customers who have stopped interacting with us.  I have just completed a piece of analysis that shows after one of these targeted emails:

1. Purchasers increased 22.9%
2. Transactions increased 69%
3. Revenue increased 71%

A: There you go!

Q: My concern is that what I am seeing is merely a seasonal effect – our revenue peaks in July and August.  So what I should have done is use a control group as you described in the book – which is what I am doing for the October Email.

A: Yep, that’s exactly what control groups are for – to strain out the noise of seasonality, other promotions, etc.  But don’t beat yourself up over it, nothing wrong with poking around and trying to figure out where the levers are first.

Q: Two questions:

1.  What statistical test do I use to demonstrate that the observed changes are not down to chance

2.  How big should my control group be – typically our cohort is 500-800 individuals

A: Good questions…

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