The One Key Metric, North Star Metric, or One Metric That Matters has become standard operating procedure in startups as a way to manage a growing business. Pick a metric that correlates the most to success, and make sure it is an activity metric, not a vanity metric. In principle, this solves a lot of problems. It has people chasing problems that affect user engagement instead of top line metrics that look nice for the business. I have seen it abused multiple times though, and I’ll point to a few examples of how it can go wrong.
Let’s start with Pinterest. Pinterest is a complicated ecosystem. It involves content creators (the people who make the content we link to), content curators (the people who bring the content into Pinterest), and content consumers (the people who view and save that content). Similar to a marketplace, all of these have to work in concert to create a strong product. If no new content comes in, there are less new things to save or consume, leading to a less engaging experience. Pinterest has tried various times over the years to optimize this complex ecosystem using one key metric. At first, it was MAUs. Then it became clear that the company could optimize usage on the margin, instead of very engaged users. So, the company then thought about what metric really showed a person got value out of what Pinterest showed them. This led to the creation of a WARC, a weekly active repinner or clicker. A repin is a save of content already on Pinterest. A click is a clickthrough to the source of the content from Pinterest. Both indicate Pinterest showed you something interesting. A weekly event made it impossible to optimize for marginal activity.
There are two issues at play here. The first is the combination of two actions: a repin and a click. This creates what our head of product calls false rigor. You can do an experiment that increases WARCs that might actually trade off repins for clicks or vice versa and not even realize it because the combined metric increased. Take that to the extreme, and the algorithm optimizes clickbait images instead of really interesting content, and the metrics make it appear that engagement is increasing. It might be, but it is an empty calorie form that will affect engagement in a very negative way over the long term.
The second issue is how it ignores the supply side of the network entirely. No team wants to spend time on increasing unique content or surfacing new content more often when there is tried and true content that we know drives clicks and repins. This will cause content recycling and stale content for a service that wants to provide new ideas. Obviously, Pinterest doesn’t use WARCs anymore as its one key metric, but the search for one key metric at all for a complex ecosystem like Pinterest over-simplifies how the ecosystem works and prevents anyone from focusing on understanding the different elements of that ecosystem. You want the opposite to be true. You want everyone focused on understanding how different elements work together in this ecosystem. The one key metric can make you think that is not important.
Another example is Grubhub vs. Seamless. These were very similar businesses with different key metrics. Grubhub never subscribed entirely to the one key metric philosophy, so we always looked at quite a few metrics to analyze the health of the business. But if we were forced to boil it down to one, it would be revenue. Seamless used gross merchandise volume. On the surface, these two appear to be the same. If you break the metrics down though, you’ll notice one difference, and it had a profound impact on how the businesses ran.
One way to think of it is that revenue is a subset of GMV, therefore GMV is a better metric to focus on. Another way to think of it is the reverse. Revenue equals GMV multiplied by a commission rate for the marketplace. So, what did they do differently because of this change? Well, Seamless optimized for orders and order size, as that increased GMV. Grubhub optimized for orders, order size, and average commission rate. So, while Seamless would show restaurants in alphabetical order in their search results, Grubhub sorted restaurants by the average commission we made from their orders. Later on, Grubhub had the opportunity to test average commission of a restaurant along with its conversion rate, to maximize that an order would happen and maximize its commission for the business. When GrubHub and Seamless became one company, this was one of the first changes that was made to the Seamless model as it would drastically increase revenue for the business even though it didn’t affect GMV.
This is not to say that revenue is a great one key metric. It may be better than GMV, but it’s not a good one. Homejoy, a service for cleaners, optimized for revenue. Their team found it was easier to optimize for revenue by driving first time use instead of repeat engagement. As a result, their retention rates were terrible, and they eventually shut down.
Startups are complicated businesses. Fooling anyone at the company that only one metric matters oversimplifies what is important to work on, and can create tradeoffs that companies don’t realize they are making. Figure out the portfolio of metrics that matter for a business and track them all religiously. You will always have to make tradeoffs between metrics in business, but they should be done explicitly and not hide opportunities.
Currently listening to A Mineral Love by Bibio.