What is Product Adoption & How Do You Measure It Properly?
What is Product Adoption?
Product adoption is the process by which people learn about your product or app and start using it to accomplish their goals. Product adoption is usually distinguished from acquisition—while acquisition is about bringing people to your site, adoption is all about turning those visitors into users.
What is Product Adoption?
Product adoption, aka user adoption, consists of the “AHA moment” when users start using your product or site for what you built it to do.
Product adoption can also be expressed as the percentage of first-time users performing a certain set of behaviors. Your mission is to identify these behaviors! What actions do people take that prove they’re getting value?
What’s the difference between Adoption and Acquisition?
Acquisition is about bringing people to your site. It’s all of the ways people learn about the value of your product or app and start using it to accomplish their goals.
Adoption is about turning those visitors into users. It’s a better predictor of long-term product metrics (like LTV, ARR, or retention) than acquisition rate, because it spans the period of time for which the user is activated and retained.
You can acquire thousands of customers, but if they never use the product, you’ll never meet your long-term goals. While it’s important to discover which behaviors correlate with engagement and retention, for the sake of your business you need to find out whether users are actually performing them or not.
Questions to help improve adoption rates for your product and its features
You’ll want to discern which appeals work best for your three types of new customers—the early majority, the late majority, and the laggards. Are they finding the newest features, and are they engaging with them? You also want to know how much existing customers spend on your product throughout their lifecycle—and how often they buy.
How sticky is your product to new users?
Does it appeal to innovators and early adopters?
Which behaviors by potential customers best predict adoption?
Which acquisition channels have the highest adoption rates?
How does the speed of adoption impact your retention rate?
Note that to measure product adoption metrics properly, you likely need a tech stack that can track user behavior, unite qualitative data with quantitative data, then pipe that data to your supporting systems. This stack should include a product analytics solution that makes it possible to understand exactly which behaviors correlate with adoption.
To see why Google Analytics isn’t right for measuring adoption, read our guide here.
The elements of product adoption success metrics
What exactly counts as adoption anyway? While the definition is simple—doing something your website or app was designed to help them do—figuring this out can be tricky!
The “adoption event” should be the action in your product that best indicates a new customer is getting value from the product. For example, pageviews make a poor choice. While they are easy to track and simple to measure, they rarely indicate the value anyone is receiving.
Useful things to track might include:
Conversion rate from signup to first key action taken
Time to value (TTV), or the time it takes to reach a major activation event
Whether users complete an user onboarding flow or tutorial
How closely doing so correlates with frequency of use and feature adoption
Frequency of purchases
A team can also combine metrics from different events to see which mix best represents getting value from the product. By comparing these patterns to cohorts with the highest retention, you can see which adoption behaviors best predict retention.
Learn about which Product Metrics to use when. Read our guide.
HelloSign is a product that lets users sign documents digitally. Upon signup, a user might do one of the following:
Upload a document
Request a signature
Add a team member
Turn on an integration
Or best of all, upgrade to a paid plan!
Each of these actions may count as adoption. So what’s important to find out is how many times did action X happen, how often did action Y occur, and which of these activities best correlates to retention and LTV.
Why increasing product adoption is critical to your business
The simple answer is that a higher adoption rate = a larger user base. That’s why adoption is the key criteria for success in product & feature launches.
Adoption is all about the first few experiences with the product.It’s critical to figure out which actions provide new users value, and then encourage new users to repeat these actions soon after acquisition.
Marketing success does not equal adoption success. Simply bringing in thousands of new users doesn’t count. They need to be doing the right things!
A slight increase in product adoption makes a big difference. When users are successful from the start, their value begins increasing earlier AND their value also accumulates over longer periods of time.
Strong product adoption rates are favorable for retention. This means people who discover your product tend to stay around longer, spend more money while they’re there, and drive predictable revenue for your business.
In fact, product adoption impacts nearly every key growth metric:
Customer lifetime value (CLV)
Cost per lead
Cost per customer (CPC)
Average user MRR
And more. This influence only grows over time! Once you know what counts as “adoption” in your product, you can measure the gains when you increase product adoption rate.
What areas of your product should you focus on to increase adoption?
To repeat, adoption is about getting users to that first “a-ha” moment. To do that, teams usually focus on the following elements of their product:
Customer onboarding can help get new users oriented so they can find value quickly.
Product design can help active new users find key features and complete actions that drive adoption.
In-product messaging and tutorials can provide guidance to your product for people as they start using it.
Customer success workflows can make sure any roadblocks to adoption are quickly addressed and solved.
Behavioral data also helps product teams learn from their customers, plan updates to their website or platform, enhance popular features, sunset unpopular ones, and improve the overall user experience.
Want to learn how to make your product stand out? Read our complete guide to product differentiation.
Freshworks is a customer engagement platform that supports over 150,000 organizations. Here’s how they used Heap to diagnose low feature adoption and quickly fix it!
Data was incomplete and hard to understand without a technical background.
Access was limited to those who could write complex queries.
The engineering team was overloaded with ad hoc requests.
After adopting Heap
Teams were able to see user behavior in real time without the help of engineering. Heap revealed that adoption and usage of the Ticket Templates feature was low.
Freshworks solved their problem by introducing an in-app message that explained the Ticket Templates feature. Heap funnels tracked which users created and applied templates after viewing the tour. They found adoption had increased by 20%!
Read the entire Freshworks case study here.
This kind of improvement can be made across every feature, having a profound impact on overall adoption rate and stickiness.
The ideal stack for increasing product adoption
While a product analytics platform is essential to product adoption, the ideal stack includes several other solutions that help you roll out changes driven by user behavior.
Marketing automation software. Platforms like Marketo and HubSpot help you target users with product-related campaigns, onboarding flows, and timely tips on using your solution. When users read and act on the messaging in these campaigns, they are likely to find value more quickly which improves both product and feature adoption rates.
Product-led growth platforms. Solutions like Appcues and WalkMe help show notifications and customer feedback right in your product, so you can offer guides and tours that help people learn how to use it quickly. You can continuously collect feedback from people already using your product and incorporate feedback from your most valuable customer segments into your roadmap, so you can ensure users aren’t missing the features you’ve launched for them.
Interested in Product-Led Growth? Read our complete guide to learn more!
Testing and experimentation platforms. Tools like Optimizely and AB Tasty help you conduct efficient, regular testing, and quickly gauge the impact of new products, features, and website changes. This way, you can focus primarily on tasks likely to increase adoption rate.
Customer feedback tools. Solutions like Delighted and UserVoice help you survey people who have already adopted your product, so you can take action easily on responses from your most engaged customer base. Quickly survey many customers simultaneously, wherever they’re most likely to reply, in order to get the data you need to make maximum-value updates to your website or app.
Customer support solutions. Customer support platforms like Intercom and Drift help you segment and triage customers to reduce churn. This lets you learn from users who have already adopted your product and make changes to your roadmap that are likely to increase adoption in the future.
Why is product analytics critical for improving product adoption?
Above all these tools is the need for a great Product Analytics solution. Really, improving a product is largely about repeating this process:
Identify the behaviors that best predict long-term value.
Launch and test improvements that encourage those behaviors.
Measure the effectiveness of each of these changes to the customer journey.
Product analytics is what makes all this possible! It’s what allows you to track user behavior across your whole product.
What product analytics features are most important for improving product adoption?
There are plenty of product analytics tools out there. Which ones will help you improve product adoption? We’d recommend you choose a tool with the following features:
1. Automatic Event Tracking
To understand exactly which behaviors drive adoption, you must be able to track them all.
Some product analytics platforms only allow you to manually track events and behaviors. This requires selecting them all in advance, and you’ll need engineers to write code during implementation.
See the problem? You won’t know which actions and behaviors drive adoption before you can analyze all of them in a single place.
Automatic event tracking solves this dilemma! You install a single snippet of code, just once. No engineering help is necessary.. You can examine anything, anytime you want.
2. Data Science
If you have to spend all your time digging through your data, you’ll never find the information you need. These days, good product analytics tools come with data-science-driven features that can analyze your data for you and point you to the areas that need attention.
3. Session Replay
Session replays are precise recreations of what specific users did within your digital experiences, so you can add qualitative context to your quantitative data. Replays are indispensable for building funnels, defining events and investigating important moments of friction.
And most important—when the replays are available within your analytics platform, there’s no need for the added complexity of exporting data to third-party applications.
4. Robust integrations
You’ll want to combine marketing, sales, testing, and customer success team data with product analytics to see the full picture.
In a good tool, APIs and popular integrations will come pre-built, so it’s easy to share normalized product analytics data with apps like Marketo, Intercom, Fullstory, and more.
How does Heap help with adoption?
We’re biased, but we believe Heap is the best analytics tool to help with adoption. Why?
Heap’s autocapture gives you a complete and trustworthy dataset. Because manual tracking requires advance planning and uses valuable engineering time, autocapture is a must for getting the most use out of any product analytics tool.
Heap offers Integrated Session Replays to understand the “why” behind the “what.” Unlike other tools, with Heap you get Session Replay built into your analytics And most important—when the replays are available within your analytics platform, there’s no need for the added complexity of exporting data to third-party applications. With Heap, your session recordings are cued to the exact moments you want to know more about. Just click!
Heap has a powerful data science layer that helps find insights for you. Heap Illuminate searches your dataset to automatically spotlight the insights that lead to the biggest business results—even on untracked events.
Some of Heap’s data science features include:
Top Events displays how well paths with different events convert to the next step.
Journeys compare multiple goal paths, as well as the impact of optional steps in a funnel.
Step Suggestions automatically surface untracked events that exhibit significant dropoff.
Effort Analysis helps quantify the difficulty of steps in the journey.
Group Suggestions identify user cohorts that correlate best with outcomes
With a full understanding of your customers’ digital journeys, you can quickly improve conversion, retention, and customer delight.
Interested in finding alternatives to Fullstory? Read our complete guide!
Just getting users to sign up isn’t enough to fuel the long-term success of your company. For consistently strong growth and customer retention, you need to:
Understand your product adoption rate
Know all of the behavioral factors contributing to it
Take effective action based on those insights.
Let us show you more about how Heap enables greater product adoption!
Getting started is easy
Interested in a demo of Heap’s Product Analytics platform? We’d love to chat with you!