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Forget Vanity Metrics, Focus on Actionable Metrics

  • The Find: One entrepreneur argues that too many of the numbers businesses pay attention to lack the specificity to be useful and are mostly designed to make us feel good about a product or service.
  • The Source: A guest post by entrepreneur Eric Ries, who is also a venture adviser to Kleiner Perkins, on the blog of Tim Ferriss, author of The 4-Hour Work Week.
The Takeaway: What's the difference between a "vanity metric" and an actionable one? Ries explains with two contrasting examples:
Consider the most basic of all reports: the total number of 'hits' to your website. Let's say you have 10,000. Now what? Do you really know what actions you took in the past that drove those visitors to you, and do you really know which actions to take next?
Now consider the case of an Actionable Metric. Imagine you add a new feature to your website, and you do it using an A/B split-test in which 50 percent of customers see the new feature and the other 50 percent don't. A few days later, you take a look at the revenue you've earned from each set of customers, noticing that group B has 20 percent higher revenue per-customer. Think of all the decisions you can make.
Seems obvious enough that actionable beats vanity, so why do we continue to rely largely on the latter? Well, vanity of course. Broad metrics like number of hits can be claimed by everyone. Was product development behind a rise in hits? Sales? Customer service? Who knows? Everyone can claim a piece of the pie. Also, of course, vanity metrics are the default on most analytics packages so they're the lazy man's answer to measuring business performance. So how can you make your numbers more actionable? Ries offers four tips, some exclusively for online businesses:
  1. Split-tests. A/B experiments produce the most actionable of all metrics, because they explicitly refute or confirm a specific hypothesis.
  2. Per-customer metrics. It's important to remember, "Metrics are people, too." Vanity metrics tend to take our attention away from this reality by focusing our attention on abstract groups and concepts. Instead, take a look at data that is happening on a per-customer or per-segment basis.
  3. Funnel metrics and cohort analysis. The best kind of per-customer metrics to use for ongoing decision making are cohort metrics. For example, consider an e-commerce product that has a couple of key customer life cycle events: registering for the product, signing up for the free trial, using the product, and becoming a paying customer. We can create a simple report that shows these metrics for subsequent cohorts (groups) over time.
  4. Keyword (SEM/SEO) metrics. SEM (Search Engine Marketing) and SEO (Search Engine Optimization) are great customer acquisition tactics, but they also can reveal important and actionable insights about customers if we treat customers who were acquired with a given keyword as a segment and then track their metrics over time.
For a much more detailed discussion of these types of metrics with relevant examples, check out the complete post.
(Image of 'Metric' in lights by Chameleo, CC 2.0)
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