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How I Use Grow as a Product Manager to Measure Value, Quality, Execution—and Discover Opportunities
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It’s no secret that viewing company data can improve your ability to make winning decisions that get your numbers trending in the right direction. But the principles that help you create great metrics that are actionable and effective can seem like a secret. If you want to get the most value possible from your metrics, you need to ensure you’re looking at the right information in the right way.
Here are some important principles to keep in mind if you want to create actionable and effective metrics.
If you’re creating a metric without knowing what goal it should help you achieve, you should probably be asking yourself why you’re creating it at all.
Metrics should be tied to company, departmental, or team goals. Although some metrics will be more focused on team or departmental goals, they should ultimately tie back to and influence a larger company goal, like your North Star Metric.
On your journey to success, your company will encounter roadblocks, slow traffic, and detours. Metrics tied to company goals will help you maneuver through each obstacle to arrive at your company goals.
If your metrics are tied to something other than your company goals, don’t be surprised if you end up somewhere you didn’t intend to be.
Metrics should help you answer important questions about company performance.
For example, how many pageviews did our website get last month? How many of our customers canceled during the product trial period? How many of the customers added in July stayed on for more than six months? How many of my leads turned into demos?
If a metric doesn’t answer an important and specific question, you probably don’t need it.
The point of visualizing data on a metric is so you can easily review it and glean insights from it. When creating a metric, consider the following questions:
When deciding which question a metric will answer, keep it simple.
Trying to answer how many leads you acquired from each of your marketing channels, what was the acquisition cost of those leads, and how many of those leads turned into demos which then turned into customers is too much to showcase for one metric. All of that is important information to know, but it would be easier and more effective to visualize each of those things separately.
If metrics aren’t self explanatory, they’re failing in their purpose.
In most cases, metrics should communicate a simple message and showcase only a few variables. Those that display too much information waste time by provoking questions about how to read the metrics rather than understanding what the metrics display.
This doesn’t mean that metrics shouldn’t generate discussion—in fact, they ought to. But the discussion should be about how to act based off of the data and not about the metric itself.
Easy-to-read metrics can help you discover truths that would be difficult to see without effective visualization.
How do you know if you’re improving if you don’t have anything to compare your performance too?
There are many ways to use comparison in your metrics. For example, you may compare your performance with a specific goal, so you can quickly see if you need to improve and by how much. Perhaps you want to see how you’re improving over time, so you compare your current performance with previous performance.
Another useful type of comparison is by group. While a metric that tells you your demos are decreasing is useful, a metric that tells you all your demo sources are performing normally except for Facebook-generated leads is much better. One shows there is a problem, the other pinpoints where that problem is occurring.
In each case, using comparison in your metrics creates a point of reference that makes your data more meaningful and actionable.
To be effective, a metric needs ownership.
Who will take action when a metric is trending the wrong direction or who will continue to ensure it is trending the right way? Who is responsible for the results? If no one has ownership of a metric, you need to ask yourself, What outcome can I reasonably expect for this metric?
To be effective, metrics need to be owned by someone with the power to make a change. A metric with an owner who lacks the authority to impact its outcome is the same as having a metric with no owner at all.
Without accountable ownership, expecting meaningful change is unrealistic. Measurability without accountability never leads to improvement.
An effective metric should cause a change in behavior.
Metrics need to inspire and facilitate action. If a metric is trending in the wrong direction, someone should be thinking about what needs to change and how that change will occur. This is the culmination of what makes an effective metric. If an increase or decrease in performance doesn’t inspire some kind of change, why are you tracking it?
This is specifically important with your key performance indicators (KPIs). Your KPIs are metrics you’ve chosen that most closely align with your important business objectives. They focus you in on the vital data that can keep your business alive and well. Seeing your KPIs trend in the wrong direction should especially lead to change.
Knowing what it takes to create great performance metrics is half the battle. The other half is finding the right tool to build, view, and manage your metrics on. Grow gives you the power to create the metrics you need to see how your business is performing.
