Good Metrics
Nalpeiron Software Analytics Blog, November 2013 http://blog.nalpeiro ... d-metrics/
Good Metrics
The first way to define a good metric is look at what a bad metric is. A bad metric is one that does not help drive your business to either get users to return (the sticky engine), to have users spread the word on your behalf (the virality engine), or persuade customers to pay for your product (the paying for your product engine!)
According to Lean Analytics, a good metric is comparative and understandable. Being able to compare one set of numbers to another puts everything in context: April’s conversion rate increased over March’s; a 50% year over year increase in customer acquisition, etc. People have a much easier time understanding metrics when presented in digestible ways, and the purpose of providing metrics is so that the business can benefit, not just the geeks in accounting! If a business is to be data-driven, everyone needs to be involved. Even front-line staff can become sales people once given the right data to present.
Ratios are also good metrics. A company can use ratios to compare how increasing one behavior results in more and more positive results until it begins to attain negative results. By testing this over a period of time, the ratios can provide valuable information about where that place is where the negative begins. Or perhaps what the financial investment is to keep increasing the positive, and when it begins to fall off at a certain point. Or where a lower positive can be maintained at a considerably lower investment, where the gains are too small to justify the increases in funding.
But the most important metric, say the authors, is one that truly changes a business’s behavior. “What will you do differently based on changes in the metric?” (Lean Analytics, p10) They describe two types of metrics: Accounting and Experimental. These can include: qualitative, quantitative, actionable, exploratory, reporting, leading, lagging, correlated and causal metrics. (For detailed explanations of these, see pp 13-16 of Lean Analytics).
There is no set definition as to which metrics are going to be the correct ones to use, because the key performance indicators for every business are going to be different. And, in fact, if the business is really watching what their customers are doing and learning from what they are doing, they may discover that the product they thought they were providing is nothing at all like the product the customers have discovered they have a use for.
What is important is to first make sure that you are using software usage monitoring to track customers’ behavior. Next that tracking software usage is to some extent focused on getting users to return (stickiness) and getting users to spread the word (virality). If the product is already at the getting paid stage a metric to watch is customer lifetime value and customer acquisition cost: “Making more money from customers than you spend acquiring them is good, but the equation for success isn’t that simple. You still need to worry about cash flow and growth rate, which are driven by how long it takes a customer to pay off. One way to measure this is time to customer breakeven – that is, how much time it will take to recoup the acquisition cost of a customer.” (Lean Analytics, p. 48)
Being open-minded to really seeing what is really making customers return and invite their friends to use your product are the basic keys to discovering what is truly driving user adoption of your product.