A Guide to Leading vs. Lagging Indicators
Measuring what enables you to adapt course of action fast enough
The initial version of this episode was posted at LogRocket
Hey everyone,
How are you doing today?
Let’s take this free episode to clarify the difference between leading and lagging indicators. I promise to simplify this understanding and help you craft actionable metrics as easily as possible. It won’t take you longer than 5 minutes to read it.
Before jumping into metrics, let's share something (20 seconds).
At the end of last year, I launched the Anti-Bullshit Product Management video course. The feedback I’m receiving is amazing. If you want to learn how to do a bit of unconventional product management, you will love my course.
Back to metrics :)
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 knew how to deal with it.
Lagging metrics may point out weaknesses but won’t help you act fast enough to progress. That’s the job of leading metrics.
What are lagging and leading metrics?
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 contributing 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.
How do lagging and leading metrics differ?
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.
How do you use leading indicators to reach desired lagging ones?
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:
Sign-up rate
Add to cart rate
Search Conversion
Cart abandon rate
Bounce rate
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: specific numbers, like the “add to cart rate,” were pretty far 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 tested 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.
What can you use lagging indicators for?
When I coach product teams, sometimes they challenge me to use lagging indicators, and I get questions like:
Why should we bother with something we cannot act on?
How can I connect my daily decisions to something I cannot see?
Wouldn’t it be better to focus solely on leading metrics?
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 determine what leads to desired results.
Tools to help you structure your metrics
You will find dozens of tools to structure your metrics, which can be tricky as some information may live in different systems. Here are some examples:
Customer information — Salesforce
Finance and Accounting — ERP
Analytics — Google, MixPanel, Hotjar
Qualitative data — Google Drive, Miro, etc
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 compelling, but you can also use Tableau, PowerBI, and other tools.
Conclusion
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 of 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.
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Have a lovely day,
David
Thank you for this inspiring article! It makes me think especially as it shocked my conviction of conversion rate being an adequate leading metric. Can’t agree yet.
I’m a product manager in an e-commerce business and already concerned with the concept of leading and lagging indicators and I think consciously about them when a/b testing. I was actually often choosing conversation rate as leading metric in contrast to lets say revenue (would need for to wait for cancellations etc). The final step on my page is add-to-cart. I was always seeing a purchase as better proof of success as only adding to cart assuming both would happen in the same session. In that sense it is perfectly leading for me. Each day (or hour) I can check how many users converted in the past day/hour.
Do you say conversion is lagging because too many other factors (out of one‘s influence) play a role or do you say the actual time of measurement is too late?
Best,
Julius