In 2017, I received an exciting challenge as a product manager. The CPO told me, “We’re struggling to get our new e-commerce live. I want you to lead this transformation. Our goal is to keep the same conversion rate as our current website.”
As I heard the CPO, it became clear that they’ve been chasing lagging metrics for months and couldn’t figure out how to get the desired results. Luckily, I had faced this challenge before, and I knew how to deal with it.
Lagging metrics may point out weaknesses, but they won’t help you act fast enough to make progress. That’s the job of leading metrics.
In this article, you will learn the difference between lagging and leading metrics and how you can use them to optimize the health of your product.
Lagging metrics, also known as laggard indicators, represent desired results that take a long time to measure. Some common examples are revenue, net profit, customer satisfaction, etc. Such indicators are crucial for business and show how healthy the company is, but measuring them is lengthy.
Leading metrics represent indicators that contribute to a desired outcome but cannot guarantee one. Product teams use them to predict whether they will reach the desired lagging metric. Some examples are sign-up rate, bounce rate, add-to-cart, basket size, etc. Measuring leading metrics is quick and simple.
The challenge of lagging metrics is that one may only learn about the problem once solving it has become impossible. When you miss your quarterly revenue, what can you do about it?
On the other hand, leading metrics enable immediate action. They help you to understand what’s going wrong and can change the course of action before a problem becomes detrimental.
The magic happens when one learns how to combine lagging and leading metrics.
Returning to the example I started the post with, I had to figure out how to roll out a new e-commerce platform. The CPO was keen on keeping the overall conversion rate and ran a series of A/B tests to reach that. Yet, nothing seemed to work.
Conversion rate is a laggard metric. Many steps need to happen before a customer converts. Measuring only that won’t let you act.
To come up with the leading metrics, I asked myself what leads to conversion rate.
I brainstormed the following list:
Surprisingly, nobody looked at these metrics in detail. Back then, the team was obsessed with revenue protection, but ignored how to get there.
As I started looking at these metrics, I compared them to the current website and something stuck with me: certain numbers, like the “add to cart rate” were pretty apart from where they should’ve been. I decided to dig deeper.
It’s essential to look at different angles to understand where problems or opportunities are. I started with other devices and immediately noticed that the desktop performed better on the new platform, but mobile devices were tremendously bad.
I understood what happened as I started testing how our new website performed on mobile devices. A simple problem: small screen devices (most of our clients) didn’t see the call to action directly. They had to scroll down. As I learned, I got a designer and a software engineer together and we decided to change it.
After changing the design and running a few more A/B tests, we got better numbers on the new website than the previous one.
When I coach product teams, sometimes they challenge me to use lagging indicators, and I get questions like:
I understand their frustrations, but you need to know where you want to land. Without that, you miss the big picture.
Optimizing “add to cart” won’t motivate anyone, but accelerating growth to acquire a third investment round will.
Laggard metrics set the direction and definition of success. They enable teams to be creative and then figure out what leads to desired results.
You will find dozens of tools to structure your metrics, which can be tricky as some information may live in different systems. Here’s some examples:
Product managers need access to consolidated data to make better-informed decisions. Having access to tools can be a starting point, but it is pretty overwhelming.
A better approach is to start with consolidated dashboards that combine all data in a single place. In the example I mentioned, we used Looker, which I found effective, but you can also use Tableau, PowerBI, and other tools.
Knowing what to measure and what not to is fundamental to progress. Too much information will cause friction and analysis paralysis.
Keep it as simple as possible.
Be selective with the range of metrics. You don’t need tons of indicators. A team will be better off with five to eight strong indicators related to desired outcomes than several they can’t act on. Take your time to choose the most relevant ones that show how you can reach your lagging metrics.
Featured image source: IconScout
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