A product manager continuously strives to improve a product and deliver a competitive product experience. One way to achieve this goal is by understanding which features are most valuable to users and which ones may need improvement or removal. Feature adoption lets you handle these aspects of product growth and management. It allows product managers to measure the success of the new features to improve the overall product. With feature adoption analytics, you can encourage and enable users to use a product’s new or existing features.
This article on feature adoption metrics is all you need to understand its importance and learn how to measure it. It explains the feature adoption funnel stages and how to implement them. Finally, you can grab the strategies and practical tips to improve feature adoption rates. So let’s get to it.
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What is feature adoption?
Feature adoption means your user is introduced to your product’s new feature and decides to use it. Feature adoption is a complete process of analyzing and identifying key drivers of product growth and scaling a business. It also helps in understanding the value a customer gets after using your product.
By analyzing feature adoption, companies can get insights into how well features of a product are performing and what features require improvement. It also helps companies determine which features to include in their product development.
It also indicates how much value your users get from a specific feature. Product managers use different metrics and tools to measure certain feature adoption rates.
It also indicates how much value your users get from a specific feature. Product managers use different metrics and tools to measure certain feature adoption rates.
How to measure feature adoption?
You can use the following formula to calculate the feature adoption rate:
Why is feature adoption important?
Feature adoption allows companies to make critical business decisions that impact product development, marketing, and sales. It is essential for product-based businesses because of the following reasons:
- Identify strengths and weaknesses in a product – Feature adoption helps you identify the features performing well and underperforming. A low feature adoption rate indicates the feature lacks value or users need more awareness. It also helps in creating relevant features that best serve the customers.
- Increases product engagement – Consistent product usage significantly indicates users’ engagement. An engaged user is less likely to churn. It means the users are getting what they want in your product. Thus, customer acquisition improves.
- Improves product via feedback from users – Feature adoption is user feedback that you can use to improve your product. Removing friction from your user experience leads to feature awareness. You can also get customer feedback via surveys, focus groups, and usability testing.
- Improves customer retention – Users can move to another solution if a product fails to deliver on its promise. User retention plays a big role here, as retaining existing customers is easier than acquiring new customers. Moreover, selling to an existing customer (60-70% success rate) is more likely to be successful than selling to a new customer (5-20% success rate).
- Drives customer satisfaction – Customers who enjoy a product’s perceived value are likelier to stay loyal to the company long-term. Moreover, feature adoption can be a great way to upscale your product by introducing features that your customers might look for in the competitors’ products. Feature adoption leads to product growth. When old features are upgraded and the latest features are introduced, it fulfills the evolving needs of the user base.
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How is feature adoption different from product adoption?
Although both are related to the product, feature and product adoption differ. They provide unique information about a SaaS product. Product adoption is about the overall product usage covering all the features a product offers its users. It provides a high-level view of the performance of the product. It targets the complete user base of a product.
Product adoption is a rather complex process involving various stages: awareness, interest, evaluation, trial, and adoption. A product’s design, marketing, and positioning all play a role in encouraging customers to adopt it. You can calculate it by using the following formula:
On the other hand, feature adoption speaks for a specific feature within a product. It indicates the particular feature’s performance. Depending on your product, you can have multiple feature adoption rates compared to the product adoption rate, which is a single measure.
For example, a customer adopts a social media platform traversing the various stages of the product adoption process. Then a new feature, such as live streaming, becomes available. The same customer (now user) will have to go through another process (feature adoption) of learning about the new feature, evaluating it, trying it out, and eventually deciding whether to adopt it into their regular product usage.
Related: Post Launch Analysis: What to Do After You’ve Launched
Five key feature adoption metrics
Features adoption metrics are equally important for pr
oduct and customer success managers. To get a 360-degree view of a feature’s performance, feature adoption analytics are tracked from the following four angles. The following five metrics help product managers in driving and tracking various KPIs related to feature adoption:
1. Breadth of Adoption – Usage Rate
Determining the scope of adoption is a critical element of performing feature adoption analysis. The usage rate of a feature tells about the percentage of users actively using it. Find answers to the following questions to measure the breadth of adoption:
- Is a feature adopted across the entire customer base or by a specific customer segment?
- Is the new feature targeted towards a particular customer persona’s need?
2. Depth of Adoption – Engagement Rate
Depth of adoption translates into the engagement rate associated with a particular feature. It tells how much time the customers spend interacting or using a feature. Moreover, you can ask the following questions to measure this:
- How often do the customers use a particular feature?
- What goals are users achieving with the use of a feature?
- How often do they use a feature to complete a task?
- Do the new features add to the stickiness ratio of the overall product?
3. Time to Adopt – Conversion Rate
As the name suggests, this metric indicates the time it takes for a customer to try the new feature. How long does it take for a user to get familiar with a new feature? Quick time to adoption indicates the new features meet the user’s needs and thus relieve existing pain. It is proportional to the feature conversion rate because it measures the percentage of users who use a feature to achieve a goal or complete a task.
A long time to adopt might indicate either of the following issues:
- Complex UI
- Users are not aware of the feature
- Technical issues
- The feature doesn’t meet any user’s need
4. Duration of Feature Adoption – Retention Rate
It measures the percentage of users who continue to use the new feature over time. How long users use a feature is an essential metric for analyzing feature performance. In addition, it tells about the usage behavior related to a feature.
- Do users try it only a few times or continue using it over extended periods?
- Does the feature impact the customer retention rate, or has it maxed out its value delivery and needs an upgrade or replacement (new feature)?
5. Feature Adoption Rate
Feature adoption rate refers to the rate at which users adopt and begin using a new feature or product. This metric is often used to measure the success of a product launch or update. A high feature adoption rate indicates that users find the new feature valuable and use it frequently. In contrast, a low adoption rate may indicate that the feature is not meeting user needs or is too difficult to use. Companies often track feature adoption rates to gain insights into improving their products and increasing user engagement.
How to measure feature adoption across the funnel
To help companies understand feature adoption, Justin Butlion has developed a product analytics framework called the feature adoption funnel. It’s a four-step funnel to measure the basic usage metrics of every feature in a product. By breaking down the feature adoption process, businesses can better identify the areas for improvement. You can optimize feature adoption with detailed knowledge about user behavior throughout the various stages of the funnel.
All the steps of this funnel are explained below:
1. Exposed – Awareness Stage
The first step of the funnel measures the percentage of users exposed to a feature. This is where you look at how many users know a specific feature exists. Releasing a feature is not enough; the most it can do is sit in your software without users knowing its existence. To understand how many people interacted with a feature, you need to measure how many users have viewed the feature page. It’s best to get a yes / no response, as Justin Butlion states.
For example, if 500 out of the 1000 users that signed up in January viewed the product’s feature page, the exposure rate would be 50%. Raising discoverability and awareness of a feature can improve the exposure rate.
2. Activated – Activation Stage
The second step measures the number of users that activate a product or feature. This step only applies to the features that require activation from the user to perform an action. For example, downloading a report in .pdf format doesn’t require activation.
Since the features can be disabled, simply looking at the number of users with an active feature is not a true representation of the activation rate. To measure the accurate activation rate, use an event-based tracking tool like Usermaven. Companies should make a historical record of user activation data. It’ll allow them to find when the feature was enabled for the first time.
For instance, if 400 people activated a feature out of 500 sign-ups, the activation rate would be (400 / 1000) x 100 = 40%. Moreover, January’s “exposure to activation rate” would be (400 / 500) x 100 = 80%.
3. Used – Engagement Stage
In the third step of the funnel, you measure the percentage of users that have used the feature (at least once). Feature users vary widely across the tool. The aim is to get a yes / no answer about whether a feature is used once or not.
To continue our example, if only 100 people used a feature out of the 400 activations, the usage rate is (100 / 1000) x 100 = 10%. And the “activated to used rate” will be (100 / 400) x 100 = 25%. It is interesting to note that some feature activations are feature usage. In such a case, you can skip the third step of the funnel.
4. Used Again – Retention Stage
The last step of the funnel measures the repeated use of a feature. It’s a general indicator to understand whether a user that tries a feature once will likely use it again. You can skip this step if you have a feature that does not require repeat use through the feature adoption funnel. In the case of our example, if 50 users use a feature repeatedly, then the “used percentage again” would be (50 / 100) x 100 = 50%, and the overall used again rate would be (50 / 1000) x 100 = 5%.
Related: What Is User Activation in SaaS And How To Improve It
How to improve feature discovery and adoption rates
You have measured the feature adoption rate, but how will you improve it if it’s not good enough? Below are some of the ways you can use to optimize and help the users to adopt new features:
1. Promote and announce new features via announcements
The best way to drive feature ado
ption is by telling your customer it exists. You can use announcements to promote features at the feature launch. New feature announcements can be internal (targeted toward existing customers) and external (aimed at prospective users). Some of the widely known ways to make feature announcements include:
- Feature release announcements let the users know about the upcoming release of a feature update. It creates curiosity and anticipation among the product users to be excited about something new.
- Paid and organic social media campaigns are tools to let the world know about a new feature and drive the adoption rate. Posts about the benefits of the feature encourage the users to use your feature. As a by-product, new users can come flocking in to try the product because of the new feature and decide to stay.
- Send email newsletters to put the new feature in front of prospective users already in the feature adoption funnel. You can include a call-to-action (CTA) to redirect them to the feature or login page.
- Blogs allow you to discuss a detailed feature that is challenging to comprehend via notifications and social media posts.
- In-app messages reach the users using appealing alerts as they use the product. You can use different formats of in-app messaging, such as product/feature tours, widgets, chatbots, tooltips, and models, which help drive adoption.
- Release notes allow you to explain the technical aspects of the changes made in the latest feature within your product, including bug fixes. They also keep a track record of the overall feature adoption efforts.
2. Collect user feedback to determine the feature’s value
To ensure a new feature release is taken by storm, do the homework before its launch. Instead of launching a new feature across your entire user base, run it through beta testing. It allows real users to access the feature under a production environment to highlight bugs or issues. It’s a great way to collect user feedback, refine the final feature release, and improve the value of your product in customers’ eyes.
Another great way to ensure your feature is foolproof is by conducting user or usability testing. It’s one of the stages of the design process that tests the product on real users to create a human-centric product. It gives insight into your target audience’s behavior regarding the functions and interface of the product.
You can also conduct user surveys to determine how customers benefit from a feature or if they are moving to a competitor tool for a feature your product lacks.
More feature adoption strategies:
- Use interactive walkthroughs and product tours to drive feature discovery. Walkthrough videos are an engaging way to introduce new features where users can visualize and see how a feature works. Additionally, videos are less time-consuming and interactive channels you must incorporate in announcement campaigns.
- Organize webinars to explain the new features to existing users. To target high-value customers and power users, you can conduct webinars where subject matter experts can explain the features personally and address any queries related to the feature, improving the feature onboarding immensely.
- Use secondary onboarding to unlock more advanced features. Secondary onboarding adds another layer of in-app experience by onboarding ‘activated’ users to the secondary features. It’s an opportunity to show the features your users have yet to use but exist in your product. With secondary onboarding, users can realize a product’s full potential, resulting in product stickiness.
Start your feature adoption tracking with Usermaven
Feature adoption metrics can deliver a top-notch product experience. You can leverage and track several product adoption metrics with Usermaven’s feature adoption analytics and see who’s effortlessly using your new product features. It can compare your product’s most and least used features to help you make data-backed decisions in the feature development process.
With Feature Audit Report, you get detailed information about user behavior while interacting with your product and feature. For example, you can determine how many users are slipping away and take action to retain them.
Moreover, you can Segment by Audience to enjoy feature engagement reports by custom audiences. Try Usermaven for free and see for yourself how it complements your product.
Frequently Asked Questions:
1. What is feature adoption?
Feature adoption means users start using a new feature that has been added to a product. It can be described as a process through which users understand the value of a new feature and begin using it.
2. What is the difference between product adoption and feature adoption?
Although related product and feature adoption are two different processes applicable to a single product, product adoption is when customers start using a new product and adopt it if it delivers value. While feature adoption refers to the process by which users of an already adopted product begin using a new feature within a product. Feature adoption can be considered a subset of product adoption.
3. Why does feature adoption matter?
Feature adoption is an important aspect of product development, marketing, and management because of the following reasons:
- It helps companies identify and prioritize developing the most valuable features for their customers. Thus, it is a great tool for understanding the product market fit.
- Leads to increased revenue. A high feature adoption rate means more customers are willing to pay for these features, which you can offer as part of a premium subscription plan.
- Allows companies to unlock product differentiation and gain competitive advantage. By understanding which features are being adopted by customers and which are not, companies can understand how their product differs from the competition and what makes it unique.
- Using feature adoption analysis, companies can drive user engagement and increase retention.
4. How does onboarding impact product and feature adoption?
With a well-designed onboarding process, users can better understand what a product offers and how to use its features, boosting engagement and satisfaction. Conversely, a poor onboarding experience can make it difficult for users to understand the product and its features, leading to confusion, frustration, and, eventually, a high churn rate.
5. How to Measure Feature Adoption?
To measure the feature adoption r
ate, use the following formula:
Feature Adoption Rate (%) = (# of active users of a feature in a given period / total # of user logins in a given period) x 100
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