A Crash Course on Lagging and Leading Metrics

Definitions, pitfalls and pragmatic suggestions for harnessing the complementary powers of lagging and leading metrics

Metrics are essential to the product manager. They’re often framed as the hard ‘evidence’ that can back up the subjective opinions and insubstantiated hypotheses that are a necessary part of our strategy process. If you’ve got a goal, but no metrics to measure your impact, do you really know if you’ve hit the goal or not? And more importantly, do you even know how you’re intending to hit that goal?

What are lagging and leading metrics?

In the product world the terms ‘lagging’ and ‘leading’ have become a useful frame of reference for assessing metrics and their uses. From the outset though, I want to state the obvious; even though metrics might eventually provide hard data, deciding what to track and why is still an inexact science that requires context, prioritisation and clearly defined strategy.

In fact, I’d go as far as to say that picking the right metrics to measure your impact can actually help you identify gaps in your thinking, as you agonise over whether session length or returning users are the biggest boost to your product’s engagement.

So what are these categories and why does it matter?

Lagging metrics

Generally lagging metrics are those we are most familiar with. These are the headline metrics that are usually fairly obvious. They represent definitive results – they have already happened, and as such are firmly rooted in the past. By the same definition then, they are difficult to change, and impact on these numbers will usually be seen in the long term, far too slow to be impacted by daily or even weekly product decisions.

Examples might include:

• Conversion rates

• Net Promoter Score (NPS)

• Revenue per user

And so on.

Leading metrics

Leading metrics are trickier to uncover. They are short-term impacts that can be influenced by team or product decisions. In themselves, they usually do not signify explicit success, but when interpreted, they can provide a prediction that success is (or is not) on the way. You might look for leading indicators if you are running experiments on your product, or seeking early feedback.

Examples might include:

• Daily Active Users (DAU)

• Number of searches per user

• Support ticket volumes

• Time to first value (TTFV)

What we get wrong about lagging and leading metrics

1. We over-focus on lagging metrics.

It’s kind of inevitable that we would. We’re human after all, and in a world of measuring success, humans like certain, provable and definitive results. Lagging metrics are also far more obvious to track, and they’re more ‘visible’. They’re the numbers that will make it into reports and performance cycles. They are the results often demanded by senior leaders!

There’s nothing wrong with that, but when we over-focus, we root our thinking permanently in a long-term view around metrics which are difficult to have immediate impact on. Who hasn’t been in a meeting where a stakeholder has demanded metrics like this shift overnight, without a clear plan of how that should be done?

Often product strategy can be anchored around improving one of these lagging metrics. “Increase our monthly users!” is a great aspiration, but there are so many ways to do this. Are we to focus on acquisition? Or engagement levels? Or reduce cancellations? If you don’t answer the ‘why’ of what you’re trying to do and provide an angle (e.g. “focus on aggressive growth in our target audience sectors”) then your strategy is too broad and in a worst case, meaningless.*

2. We don’t use leading metrics enough

I get this too. Leading metrics are a bit scary, because they require interpretation. Maybe we have a fear of predictions proving incorrect, maybe we have stakeholders or managers who demand to know certainties about what’s happening on the product. Maybe the reality is that we lack the definitive strategy in place to know if something is significant or not.

To use leading metrics well, we need a super clear mental model about what we’re trying to achieve, and how the various components of our product contribute. Only then are we in a good place to feel confident about what we’re tracking and what it means. In my personal experience, my reluctance to use leading metrics has actually been a confidence issue with the chosen strategy, or a lack of strategy altogether.

And here’s the thing about leading metrics – in the same way that lagging metrics can bog down strategy – leading metrics can point you towards invisible problems or unique opportunities. Try tracking several things and see where the data leads you. Are you pushing all your resources into acquisition, but losing people at the other end through cancellation? Are you focussed on extending features when the existing scope is underutilized?

Using leading metrics is all about staying open to changing direction.

So how should we use them?

Use lagging metrics to measure impact

They come too late to fix problems, so don’t use them as a compass. Use them to look back and establish a baseline. Eventually, they can confirm your success more visibly for others, but you want to be in a position where you’re already aware of the direction of travel.

Lagging metrics can be a great input into long term strategy and goal setting, but make sure you’re not using them in isolation. Always ask why, or you won’t be able to identify the right levers to change them.

Use leading metrics to steer

Leading metrics do not guarantee outcomes, and that’s important to remember. However they do give early and important signals. Your job as a product manager is to understand which of these signals is important for your chosen product, and what these signals are telling you. Use them to set the direction of your team.

A good place to start is picking a handful of leading metrics to track per lagging metric. Your choice will depend on the goals of your product, the overarching product strategy and the unique context that only you – as product manager – can bring to the table. This is exactly the kind of problem solving you’re there for.

Things to try:

• If you don’t do so already, identify a couple of leading metrics to track for your product

• Build a dashboard for your chosen product. Separate the reporting into lagging and leading and see what insights it triggers

• ‘Test’ your product strategy by working backwards from your metrics. Where are your gaps? Are you focussed enough?

• Run a relevant experiment and monitor the impact on a few leading metrics

So in summary, don’t be afraid to speculate. As the product manager, you are the unique role in the team who can make the numbers meaningful. It could become your superpower!

* On the pitfalls of being too broad, if your strategy is ‘Make money’, congratulations, you share the same strategy as every other commercial company on the planet!