Category Archives: Marketing Research

Do NPS / CES Feedback Metrics Predict Retention? Depends…

Analytics Education, Customer Experience, DataBase Marketing, Marketing Research, Marketing thru Operations
Survey Says?

Several questions came in on the ability of surveys to predict actual behavior, covered in the post Measuring the $$ Value of Customer Experience (see 2. Data with Surveys). My advice is this: if you are interested in taking action on survey results, make sure to survey specific visitors / people with known behavior if possible, then track subjects over time to see if there is a linkage between survey response and actual behavior.  You should do this at least the first time out for any new type of survey you launch.

Why?  Many times, you will find segments don’t behave as they say they will.  In fact, I have seen quite a few cases where people do the opposite of what was implied from the survey.  This happens particularly frequently with best customers – the specific people you most want to please with modifications to product or process.   So this is important stuff.

You’ve Got Data!

Turns out there’s a new academic (meaning no ax to grind) research study out addressing this area, and it’s especially interesting because the topic of study is ability of customer feedback metrics to predict customer retention.  You know, Net Promoter Score, Customer Effort Score and so forth, as well as standard customer satisfaction efforts like top-2-box.

The authors find the ability of any of one of these metrics to predict customer retention varies dramatically by industry.  In other words, you might want to verify the approach / metric you are using by tying survey response to actual retention behavior over time.

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Adoption and Abandonment

DataBase Marketing, Marketing Research, Measuring Engagement, Web Analytics

Out of the Wharton School we have a nice piece of behavioral research on the effect speed of Adoption has on longer-term commitment.  The article, The Long-term Downside of Overnight Success, describes research finding “the adoption velocity has a negative effect on the cumulative number of adopters”. 

This research dovetails nicely with a lot of the topics discussed here on the blog lately, so I thought I’d use it (with a nod to Godin’s post on Strategy vs. Tactics today) to provide some fodder for thought.

First, the importance of Psychology in Marketing.  So many of the “discoveries” arrived at through  brute force testing of Online Advertising are already well known in the greater discipline of Marketing through Psychology.  For more on this read “The Other 3P’s” and if you’d like to do something about lack of knowledge in this area, make sure to read this comment on source books.

Second, this research is a great example of isolating the true drivers of behavior.  The idea of looking at baby names to isolate the real behavior from “technology and other commercial effects” while including “symbolic meaning about identity” results in a broad, Strategic-level answer to the question, not a Tactical one. 

Why is this important?  It means the results can be applied across a host of different Marketing situations, rather than only a specific one. 

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Marketing Science (Journal)

Analytical Culture, Analytics Education, Marketing Research

As I said in the Heavy Lifting post, I think the Web Analytics community is becoming increasingly insular and should be paying more attention to what is going on outside the echo chamber in Marketing Measurement.  I also think the next major leaps forward in #wa are likely to come from examining best practices in other areas of Marketing Measurement and figuring out how they apply to the web.

For example, did you even know there is a peer-reviewed journal called Marketing Science, which calls itself “the premier journal focusing on empirical and theoretical quantitative research in marketing”?

Whoa, say what?

This journal is published by the Institute for Operations Research and the Management Sciences, and articles are the work of premiere researchers in visitor and customer behavior from the best known institutions around the world.  In case you didn’t know, “peer-reviewed” means a bunch of these researchers (not including the authors, of course) have to agree that what you say in your article is logical based on the data, and that any testing you carried out adhered to the most stringent protocols – sampling, stats, test construction, all of it.

And, most mind-blowing of all, they show you the actual math right in the article – the data, variables, formulas, graphs – that lead to the conclusions they formulate in the studies.  You know, like this:

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