# Are your customer metrics misleading you?

Are you measuring your organization's success by the right set of customer metrics? Unless you know their impact on achieving your main objectives, you may be incenting the wrong actions. wasting money and time, and allowing your competitors to take your best customers.

Let me show you what I mean, using baseball as an example. If I were to ask you to name a batting statistic, the odds are you’d say batting average. No surprise; when batters come to the plate, their batting average is displayed prominently on the scoreboard and on your TV or mobile device.

A player's batting average is simply his number of hits divided by the number of official times at-bat. That sounds like something you'd really want to know about a player--but is it the best batting metric? How can you compare it to the value of other batting statistics? The answer lies in determining how well each statistic ties to what the team is trying to achieve.

In baseball, the objective is to win. The way batters help their team win is in scoring runs. So, how well does batting average correlate with runs scored? Not that well, actually. The chart below plots full season, batting averages (x axis) against runs scored (y axis) for each Major League Baseball team over the past three years.

As you can see, there isn’t a particularly strong relationship between batting average and runs scored. That’s mostly because batting average doesn’t take into account two important factors: the kind of hits batters get and other ways batters get on base.

Getting a hit is the most common way a batter gets to base. Batting average counts every hit the same, whether it’s a home run, a single, or anything in between. Since the impact of a home run and a single are very different, batting average leaves a lot of available information on the table! Another statistic, __slugging percentage__ values home runs, triples, doubles, and singles proportionately.

__Walks__: The second most common way a batter gets to base is getting a walk. Batting averages don't include walks. Walks *are *included in another statistic, __on-base percentage (OBP)__.

Clearly, batting average is missing important (and readily available) data important to understanding a player's contribution. Baseball teams are well aware of this. So, they use a variety of statistics to assess batting performance.

One of these statistics is __On-base Percentage + Slugging (OPS).____ As you might imagine, this is simply a combination of the two statistics__ described above. OPS, therefore, factors in both walks and slugging. That turns out to make a lot of difference! Using the same data as the prior analysis, the chart to the right demonstrates OPS' relationship with runs scored.

Not much of a contest, is it? You don’t have to manage a baseball team to see why OPS is an important thing to know about your players.

Which type of consumer metrics are you using? Those that are entrenched or easy to understand or those that are tied to your business objectives? Do they incorporate the future value of your customers? Do they consider which customers have higher margins? Do you have an early-warning system should key customers or customer segments start to defect?

Based on these questions, how confident are you that you’re spending the right proportion of effort on customer acquisition and retention, media mix, service-level differentiation, and many other factors critical to engaging the most profitable customers?

If the answer to these questions is "no" or "not very," then it’s likely you can benefit from rethinking how you identify, develop, and measure the customer metrics that matter. As with the example above, this should start with an analysis of how the factors you can influence impact your key objectives.