9 Product Adoption Metrics You Should Be Tracking

As a product manager, you know you need to be tracking product adoption metrics. Product development is often described as a process of continuous discovery. And a key part of that discovery is all about unearthing trends, patterns, and insight from customer behavior. After all, if you’re not tracking what your customers are doing – and how they’re using your product – how will you know what needs to be improved?

We’re talking here about product adoption metrics – the statistics and data that shine a light on exactly how your product is landing with your target audience. Importantly, these metrics go beyond sales and acquisition ones; adoption metrics paint a picture through the user journey of how your product is actually being used.

So, what’s worth tracking? And what can these metrics really tell your product development team? Let’s take a look at what the right product adoption metrics can mean for your roadmap…

In this article, we’ll be covering the following topics:

• What is product adoption?
• Why measure product adoption?
• How do you track product adoption?
• 9 essential product adoption metrics to track
• What to do with all that insight?

What is product adoption?

Imagine a customer downloads your product, installs it, creates an account, and then… Never touches it again. On paper, that’s still a conversion – a tick in the box for user acquisition. If they’ve agreed to pay a monthly subscription, it’s even a sales acquisition.

But if they don’t use what you’ve made, you can’t class it as product adoption.

Product adoption, then, is when people put your product to use. Often, people pass the adoption threshold when they’ve completed the onboarding flow, completed a series of key user actions, or continue to use the core features after the initial novelty period wears off.

For a tool like WeTransfer, that might be when they first upload a document to share. For Slack, it might be when they make their first channel and send their first message. For us at ProdPad, it could be when a team member fills out the Now, Next, Later sections on their roadmap.

Whatever the case, product adoption is usually defined as the moment when your users realize the value proposition you’ve created for them. It’s when their behavior indicates that the product is proving useful.

When you’re tracking product adoption, you’re really seeking actionable insights and answers to a few key questions:

• Is our product actually solving the problem we set out to solve?
• Are our users using our features as we want them to?
• Could the user experience be improved?
• Was the last version rollout successful?
• When and why do our users churn?

Why is measuring product adoption metrics important?

Product adoption metrics provide richer insight than the comparatively bottom-line stuff around signups and revenue.

If a million people create an account for your product, download it, open it, and then bounce right off it, you’ll only know that if you’re tracking product adoption data. And that’s powerful because if you know what’s really happening at the user level, you can learn where the experience gaps are and think about how best to close them. 

On the flip side, without that vital layer of information, you might be lulled into a false sense of security. A million signups – even paid ones – might seem great, but if those users don’t make it to that ‘value realization’ stage, you can be sure they won’t renew their subscription when the next payment cycle comes around.

Put simply? Product adoption metrics are behavioral in nature, which makes them great at figuring out pain points and validating assumptions about what people love or don’t love about what you have to offer.

In turn, that insight can help inform your product roadmap – uniting product teams and customer success teams around known issues and user bottlenecks. 

Lastly, product adoption metrics can also make for incredibly persuasive tools when you’re pitching to potential investors.

While product acquisition is a strong indicator that your marketing or sales efforts are firing on all cylinders, product adoption data shows investors that people actually love to use what you’ve made – and that they plan on continuing to do so long into the future. Which, ultimately, is an indicator of sustainable revenue and an attractive proposition.

How do you track product adoption?

Tracking product adoption is done using product analytics tools. These are software platforms that nestle in under the skin of your product and keep a keen eye on various parameters to do with user behavior.

Product analytics tools can generate trends across your whole user base, as well as drill down to individual users. In either case, they’ll present you with a bunch of stats and key behavioral trends that your resident data scientist can analyze to report on how things are going.

Product analytics tools are at their best when they’re easy to use but rich in features, with customizable fields that let you tailor dashboards and reporting to be relevant to your product.

Our recommended product analytics suites are:

• Mixpanel
• Amplitude
• Pendo
• Fullstory
• Heap
• Gainsight PX
• Google Analytics

At ProdPad, we use Mixpanel for its fancy customization options and robust reporting, but if you want to learn what each tool does – and what makes them worthwhile – we’ve got a full rundown of each one here:

9 essential product adoption metrics to track

1. Product adoption rate

This is really the big catch-all metric in the product adoption space: are people actually using your product? Product adoption rate sorts signups from active users over a given timeframe to determine how many people go beyond simply creating an account.

People who’ve signed up but don’t use your app are a danger because they’ve yet to discover the value in your offering, so having a low product adoption rate is a dangerous place to be.

Questions to ask yourself when setting this up: What are the user adoption metrics you need to be tracking? Do you have a feature adoption strategy in place? Where is the sweet spot on the product adoption curve and how do you help your users get there faster?

2. Active users

Daily active users (DAU) and monthly active users (MAU) are metrics that show how sticky your product is. If you have a high number of daily users logging in and hitting those adoption goals or taking meaningful action every day, then you know that what you’re doing is working.

Obviously, every product will have a different idea of what success looks like, here. For a business messaging product like Slack, for example, you’d want users to be signing in and using the product throughout every working day. If it’s something that only needs to be used every now and again, though – perhaps a personal accountancy tool – you wouldn’t expect people to be logging in just for the sake of it.

Either way, a lower-than-expected active user count can be a hint that you can make the product work a bit harder. Maybe you can incentivize or gamify daily logins? Duolingo is a great example here. Or maybe you can add features that help with a different part of your users’ day? For example, the transcription service Otter.ai connects to Outlook calendars to make keeping on top of meetings a breeze.

3. Feature usage frequency

Similarly, keeping an eye on how often each individual user is actively using the product can clue you into broader trends. If users are relentless in their use early on but soon drop away, it might be because they’ve found a competitor that does what you’re doing for a better price. Or it might be that their problem has been permanently solved.

The reverse is also true: if users slowly increase their product usage frequency over time, it suggests that they’re gradually understanding just how valuable your product is. That’ll help you find the length of the learning curve as well as time-to-value, which we’ll come onto shortly.

4. Onboarding completion rate

Divide the number of users who completed the onboarding process by the total of users who started, and you’ll have your onboarding completion rate. It’s an important stat to keep an eye on because it can point to a number of issues.|

Low onboarding completion might, for example, suggest that you’re boring or scaring people away with the signup and introductory process. Or it might mean that, during that process, you’re not making a strong enough case for the product’s feature suite.

Remember you can and should keep onboarding simple, sometimes an amazing onboarding experience is a lot less involved than you might think – start with emails or in-app messages to guide your users to the most valuable features first.

5. Feature adoption rate

Let’s say you’ve just shipped a new version of your product. It’s the big 2.0 rollout that adds an incredible new product feature: users can now send each other cat GIFs. Feature adoption rate is the metric that’ll tell you how it lands.

To track this, you’ll need to specify a given feature to monitor within your product analytics suite, and then see how its usage figures compare to the total volume of users. Sometimes new features can take a while to catch on, but a low feature adoption rate over a prolonged period usually means that the feature in question isn’t resonating with your user base. That means it either needs to be killed or retooled.

6. Time-to-first action and time-to-value

Time-to-first-action is about tracking how long it takes for a user to complete a specific task. It’s a great way to hone in on the more granular aspects of your product’s capabilities. Taking the silly example above, you might want to see the average time it takes for a user to send their first cat GIF to a colleague.

If you determine that taking that specific action is when users find value in the product, that’s also how you’ll calculate time-to-value. Sometimes time-to-value doesn’t need to be tied to a feature or action, though; it can be anything. You might choose to determine that users have found the value in your product over time, after 30 days of consecutive use, for example.

7. Customer lifetime value (CLV) and customer acquisition cost (CAC)

In order to figure out your customer lifetime value, you need to know your customer acquisition cost (CAC). The former is the value you’ve garnered from your customers after you subtract the latter – which is how much it cost you to get them through the door.

Happy customers who renew their subscriptions on an annual basis will make for high customer lifetime value, so long as the costs associated with attracting each customer (including all your operational costs) don’t outweigh what they’re paying.

8. NPS and CSAT

Net Promoter Score is determined by asking your users a pretty simple question:

On a scale of 1-10, how likely would you recommend [product or brand] to a friend or colleague?

It’s an industry-standard metric that denotes how satisfied customers are with what you’re doing. After all, nobody would recommend something to their peers unless they really liked it.

Similarly, CSAT (customer satisfaction) surveys ask:

How would you rate your overall satisfaction with [product]?

Here, respondents use a 1-to-5 scale from ‘very unsatisfied’ to ‘very satisfied’. Again, satisfaction points to loyalty and a positive user experience. What’s more, if customers are willing to fill out CSAT and NPS surveys, they’re often also willing to provide qualitative responses to more in-depth questions, where they can explicitly tell you what they do and don’t like.

In-app pop-ups are a great way to solicit this kind of feedback, so long as you’re not bothering your users with them too often.

9. Customer churn and retention

Customer churn and retention are two sides of the same coin, really. In a given timeframe, churn is the number of customers you lose, and retention describes the number that sticks around. Obviously, the higher your retention rate (and the lower your churn rate), the better you’re doing. But be aware that no company has a 100% retention rate.

The thing is, just generating these two numbers for a report is kinda useless unless you use the rest of the metrics in this list to understand why churn and retention are the way they are.

And that brings us nicely to our final point…

What to do with all that insight?

Tracking various bar charts, statistics, and retention rates is a waste of time if all you’re going to do is parrot the figures up and down the line to various teams. No one will really care about a bunch of meaningless statistics.

Or, in other words, data is pretty useless if you don’t put it to work.

Product analytics tools are fantastic resources when they’re in the right hands, but not everyone is naturally attuned to decoding the meaning behind the numbers. To that end, we’d recommend leaning on a data scientist to dig into the stats and pull out the story of the customer journey.

Buried in those product adoption metrics will be your next steps. It might be that people can’t understand how to complete a core action, or maybe they’re bamboozled by hand-holdy tutorial screens and run a mile? Maybe they’re using the tool perfectly, every single day, but ditch it the second their free trial ends? Or perhaps there’s a really cool unused feature that 90% of your users never even touch?

All of these little data-based stories will tell you what your next product update should look like, and that will define your product adoption strategy on your roadmap. It might be that you were prioritizing a feature that – on closer inspection – is much less important than that one big change that’ll massively boost your onboarding completion rate, retention, or customer lifetime value.

Whatever the case, product adoption metrics should form an integral part of your continuous discovery process. Dig into the data, and it’ll show you what needs to happen now, next, and later.