What is Product Adoption?
Product adoption, or user adoption, is the moment when users start to use your product or site’s features to accomplish the goals it was built to help with. At a basic level, adoption can be expressed by the percentage of users who perform a certain set of behaviors after discovering your product for the first time. To truly dig in and understand product usage and adoption, however, you’ll need to identify what those behaviors are. What actions do people take that show they’re getting the value you intended your product to give them?
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.
In general, adoption spans a period in which the user is activated and retained, making it a better predictor of long-term product metrics (like LTV, ARR, or retention) than acquisition rate. You can acquire thousands of customers, but if they never actually start using the product, they’ll never help you meet those long-term goals.
To measure product adoption in a way that lets you take action to improve it, you’ll need to consider several factors:
- How sticky your product is to new users
- Which behaviors correlate with engagement and retention and whether users perform them
- Which pre-adoption behaviors best predict adoption
- Which acquisition channels have the highest adoption rates
- How the speed of adoption impacts your retention rate
- Whether users are finding and engaging with new features
- How often and how much users are spending on your product throughout their lifecycle
You won’t be able to improve the adoption rate of your product—or its individual features—without fully understanding these underlying elements of product adoption. To break down the many behaviors that drive adoption and measure them properly, you’ll need to invest in a tech stack that can track user behavior, pipe that data to other systems, and empower your product team to build and test meaningful improvements to your products. This stack should include a product analytics solution that makes it possible to understand exactly which behaviors correlate with adoption.
The elements of product adoption success metrics
Companies measure product adoption by tracking the behaviors that indicate that a customer is using a product to achieve the goals the product is designed for.
Figuring out what exactly counts as adoption can be tricky. In general, the “adoption event” should be the action in your product that best indicates that a user is getting value from the product — that they’re doing something your website or app was designed to help them do.
It can be tempting to use metrics like pageviews to measure adoption — pageviews are easy to track and simple to measure — but metrics like these rarely indicate whether a user is getting value from your product. Better is to measure the number of people who take the actions that matter in your product. That number is a far more reliable indicator of retention and ongoing usage.
For example, a user of HelloSign (a product that lets users sign documents digitally) might perform several key actions after signup: uploading a document, requesting a signature, adding a team member, turning on an integration, or upgrading to a paid plan. Depending on the level of granularity one is interested, each of these may count as adoption. By tracking all of these actions, including how many times they happened and how often they occurred, a team can figure out which most correlates to retention or LTV. Or a team can combine metrics from different events to figure how which mix best captures getting value from the product.
As you define your own product adoption metrics, you’ll probably want to track the following:
- 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
By looking at these patterns and comparing them to cohorts with the highest retention, the product team can clearly see which adoption behaviors most predict retention.
Why product adoption is critical to your business
Once you know what counts as “adoption” in your product, you can see how product adoption impacts nearly every key growth metric, like customer lifetime value (CLV), average MRR per user, and churn. This influence only grows over time — the higher your product adoption rate, the larger your user base will be. Adoption is almost universally the success criteria for product or feature launches, which makes it a top priority for product managers (even more than retention).
Even top-notch marketing programs that bring in thousands of new users won’t ensure the product team meets their adoption goals. Because adoption is all about the first few experiences with the product, it’s important to understand which actions provide new users value and get them to repeat them soon after acquisition.
A slight increase in product adoption makes a big difference. When users are successful from the start, their value begins increasing earlier and accumulating over longer periods of time.
Strong product adoption rates means the people who discover your product are more likely to stay around for longer, spend more, and drive predictable revenue. But before realizing these benefits, companies must invest in the technology that drives these improvements.
How product analytics can be used to measure and improve adoption
Product analytics make it possible to identify the behaviors that best predict long-term value, launch and test product improvement that encourage those behaviors, and measure the effectiveness of each change. Platforms like Heap track user behavior in your product or website and uncover insights that will power your entire product adoption strategy.
Product improvements that are likely to increase adoption
Armed with product analytics and a clear definition of what product adoption means to your team, you can begin to launch and test improvements to:
Customer onboarding, which helps new users get oriented and start finding value quickly
- Product design, which helps newly acquired active users find important features and complete key actions that drive adoption
- In-product messaging and tutorials, which provide clear guidance to your product for people as they start using it
- Customer success workflows that make sure any roadblocks to adoption are quickly addressed and solved
Behavioral data also helps the product team plan improvements to their website or platform. allowing them to improve the overall user experience and individual features and improvements based on the behaviors that existing customers take.
How Freshworks improves adoption and customer success with product analytics
Freshworks — a customer engagement platform that supports over 150,000 organizations — used Heap to uncover the reason for low feature adoption and quickly fix the issue.
They started using the platform to better analyze user behavior in their SaaS product. They had an in-house data lake, but the data was incomplete and hard to understand without a technical background. Access to it was limited to those who could write complex queries, leaving the engineering team overloaded with ad hoc requests.
After adopting Heap, the Freshworks team was able to see user behavior in real time without the help of engineering. They used Heap’s product analytics to find that adoption and usage of its Ticket Templates feature was low, and solved the problem by introducing an in-app message that explained the feature. They then used Heap funnels to track which users created and applied templates after viewing the tour—adoption had increased by 20%.
This kind of improvement can be made across every feature, having a profound impact on overall adoption rate and stickiness. 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.
The importance of tracking all events automatically
To understand exactly which behaviors drive adoption, you must be able to track them all. However, not all product analytics platforms do this automatically. Some only allow you to manually track selected events, or user behaviors, by writing code during implementation. The problem is, you won’t know which actions and behaviors drive product adoption before you can analyze all of them in a single place.
Heap autocapture solves this problem by capturing all user data from the beginning using a single snippet of code, once. By tracking every interaction, Heap makes it easy for product teams to see the big picture and quickly start iterating on new features and functionality that might drive adoption.
The ideal stack for increasing product adoption
Heap’s product analytics platform was built to integrate easily with other business applications so nearly every tool in your stack can be used to affect user behavior and increase adoption. As users adopt your product and its features, you’ll need to examine marketing, sales, testing, and customer success team data and combine it with product analytics to see the full picture.
Because Heap’s approach to product adoption is built upon exploring data and testing hypotheses, information must flow from system to system seamlessly. The Heap’s APIs and pre-built integrations then make it easy to share normalized data in apps like Marketo, Intercom, Fullstory, and more. For companies who combine data from across the company in a data warehouse, Heap Connect is a managed ETL that lets teams easily pipe data into Redshift, BigQuery, or Snowflake.
Below are a few examples of SaaS solutions to include in your stack:
Marketing automation software
Platforms like Marketo and HubSpot helps 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 give users tours, show notifications, and get customer feedback right in your product — guides to your product that help people learn how to use it quickly. You also can use them to continuously collect feedback from people already using your product, incorporate feedback from your most valuable customer segments into your roadmap, and make sure users aren’t missing the features you’ve launched for them.
Testing and experimentation platforms
Tools like Optimizely and AB Tasty help you quickly gauge the impact of a new product, new feature, or website change. Efficient, regular testing makes it possible to focus only features and improvements that are likely to move the needle on your adoption rate.
Customer feedback tools
Solutions like Delighted and UserVoice make it easy to understand user satisfaction and take action on it. While these tools survey people who have already adopted your product, they give you the data you need to make updates to your website or app that are likely to provide more value (and increase adoption) for future users. They allow you to quickly send out surveys to many customers at once, wherever they’re most likely to reply, and act on responses from your most engaged customer base.
Customer support solutions
Customer support platforms like Intercom and Drift help you segment and triage customers to reduce churn. Like customer feedback tools, these solutions allow you to learn from users who have already adopted your product and make changes to your roadmap that are likely to increase adoption in the future.
With all of your tools working seamlessly together, you can quickly implement new features and campaigns and see how they impact product adoption.
Splunk’s product team subscribes to a philosophy known as The Scientific Method of Product Development. It anchors on hypothesis-driven approach, where changes are rigorously tested and the results used to quickly decide whether they’ll have a positive impact on their customers. Read the Splunk case study to learn how they use Heap’s behavioral analytics to build a best-in-class product.
Getting users to sign up isn’t enough to fuel the long-term success of your company. To realize your goal of consistently strong growth and customer retention, you need to understand your product adoption rate and all of the behavioral factors that go into it, then take action based on those insights. Learn more about how Heap enables greater product adoption by requesting a demo, or sign up to start using Heap for free.