Column: Engagement 2.0: Beyond Opens and Clickthroughs

The concept of customer engagement is an increasingly hot topic for anyone who publishes content online as well as for marketers and advertisers. However, what engagement exactly means and how it is measured remain vague.

One of the original models for measuring engagement is RFM, which stands for recency, frequency and monetary. Basically, it is a quantitative way to measure and express a customer’s value to a company by measuring how recently the customer purchased, how frequently she purchases and how much money she spent.

Using this scheme, each aspect of the customer’s purchase history is given a number from one to five, with five being the highest. These numbers are then shown as a three-digit figure, such as 541. This customer got the best recency score, a “4” for how frequently she purchases but only a “1” for her monetary score, meaning she doesn’t spend much when she does purchase.

This method of measuring engagement has been reasonably adequate through the years until the advent of the Internet and its ability to measure and track consumer behavior electronically. The Internet heralded a new triad in customer engagement: the all-important clickthrough rate, open rate and conversion rate. Click-throughs are when a customer or reader clicks on a link; opens are opening an e-mail; and conversions are the Holy Grail: a purchase.

These three measurements represent the basic actions that marketers hope for, and they provide at least a rough measure of a customer’s engagement. But why stop there?

When consumers are being bombarded electronically with ads and images, offers and deals, those marketers that better understand what drives behavior and who can provide a better way to assess and quantify that behavior will find themselves with an edge over their competition. Enter the era of Engagement 2.0.

A true measure of engagement must include behaviors besides opens and clicks. Even purchases, though an important number, do not tell the whole story.

For example, what about forwards? If a customer gets an e-mail she likes so much that she forwards it to her entire e-mail list, isn’t that worth something? Doesn’t that represent a truly engaged customer?

Or take a customer who opens all your e-mail but never makes a purchase. She is not necessarily more engaged, or more valuable, than a customer who opens 10 percent of your e-mail but spends loads when she does.

Conversely, if a customer opens your e-mail and then unsubscribes from your list, well, that’s a customer whom you failed to engage. In the old scheme, her opening it generates a positive engagement score; that she then unsubscribed is never captured.

As marketers and consumers grow ever more sophisticated, our models for representing and measuring consumer behavior must evolve as well. Any measurement is only as good as the components that go into it and the relative weight given each. The better and more accurate those pieces of the puzzle are, the more accurate and meaningful the resulting score will be. So if you are going to try to measure, ensure that you capture data that’s complete, and this may require a new, more complex model.

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