Why Feature Adoption Matters More Than Ever in Today's Competitive Market

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Discovering and integrating new features can be a game changer for any product, but getting users to adopt these features can be a daunting task.

Feature adoption is the art of introducing users to individual features and capturing their attention without being intrusive or overwhelming. The end goal is to encourage them to engage, activate, and use these features, and provide them with support documentation on how to use them daily to showcase a feature’s full value. Feature adoption is a key to overall product adoption, showcasing your product’s total value and keeping customers aware of all newly released features.

Successful feature adoption is essential for keeping your product relevant and competitive in today's ever-changing marketplace. It requires a deep understanding of user behavior and a well-thought-out plan to introduce new features in a way that aligns with your user's needs and preferences.?

In this edition, we explore the art and science of feature adoption, uncovering the secrets behind successful adoption strategies and the tools used to increase user engagement.

The Feature Adoption Funnel

Users go through a process from the moment they first encounter a feature, begin exploring it, and eventually use it consistently. These steps include:

1. Exposed: This is the stage where a user is first introduced to a feature. They become aware of it either by exploring independently or through onboarding cues such as guided tours, pop-ups, and alerts.
2. Activated: The activated stage is where a user takes the first step towards using a feature, such as importing their data or inviting their team members.
3. Used: At this stage, a user has tried out a feature for the first time to see how it works. This point is ideal for follow-ups, and here’s where you can suggest a conversation with your product experts or offer users discounts and product credits to help them get started.
4. Used Again: This is the final stage of the feature adoption funnel, where a user tries out a feature again to better understand how it works or make it part of their workflow.

Let’s look at an example to give more context to this feature adoption funnel.

In this example, you start with a user cohort of 2,000 new users who signed up for your product in March, and you want to understand feature adoption for this segment of users.

Of those 2,000 users, 800 clicked on an in-app pop-up that led them to a walkthrough of the specific feature you’re analyzing. Your feature’s exposure rate is 40%.

Using Whatfix Analytics, you see that out of the 800 users exposed to a specific feature, 700 of them activated the feature – i.e. they set up a dashboard, imported data, invited a co-worker, or met specific criteria your team has set for achieving your “activation” goal. This means your activation rate for your March new user cohort is 35% (700 / 2,000), and your exposure-to-activation rate is 87.5% (700 / 800).

Next, you want to see how many users who activated the feature actually used it. For simple features, “activation” and “used” may be the same. For more complex features, tasks, and workflows, you’ll need to create the criteria for accomplishing the “used” goal. For the sake of this example, let’s say that 400 users who activated the feature used it. That means your overall feature used rate is 20% (400 / 2,000), and your activation-to-used rate is 57% (400 / 700).

Finally, you want to measure repeat feature usage to determine your “used again” rate. The used again metric is extremely important to overall product stickiness and overall user adoption. This shows that users are returning to use the feature multiple times, understand how to use it, and have realized value from implementing it into their workflows. For this example, let’s say that 200 users used the feature one or more times, which means your overall “used again” rate is 10% (200 / 2000), and your used-to-used again rate is 50% (200 / 400).

You can see the full feature adoption funnel analysis data in the table below:

Throughout the feature adoption process, you need to keep your time-to-value short by simplifying your product’s UI and using a straightforward onboarding experience to determine how users can get started with your product quickly.

Feature Adoption vs. Feature Discovery

On the surface, they seem quite similar. However, feature discovery and feature adoption are two different approaches to your product adoption strategy.

• Feature discovery is the process of making users aware of new or underused features, while adoption only ensues when your users start trying out these features.
• Feature discovery includes all the effort a product team makes to put their product’s features in front of their users, eventually leading to feature adoption.

The Importance of Feature Adoption

Overall adoption is the big-picture goal of product teams, but feature adoption is the path that takes you there—you need to encourage users to try out your product’s functionality, find them helpful, and slowly expand their usage.

1. Feature adoption drives renewals, retention, and upsells

Your users are more likely to stick around when they find and start using features that solve their pain points, fit into their workflows, and integrate with the rest of the tools they use.

2. Drives overall product adoption and stickiness

Marketers and growth engineers obsess so much about acquiring new users, signups, and free trials that they forget they’re essentially vanity metrics—the signal-to-noise ratio is relatively poor and a significant number of the new users you bring into the door will churn without trying out your product enough to see what it offers.

Instead, feature adoption offers an alternative to a blind focus on vanity metrics.?

Why? When users try out specific features and use them long enough to get value out of them, they’re more likely to stick with your product, make it part of their workflow, and eventually explore other features that may be tangential to their desired use case.

3. Empowers product teams to capture and analyze user behavior data and feedback

Feature adoption serves as a rich source of behavior analytics and insights that help product teams understand their users’ usage patterns, see which features they engage with the most, and then figure out how to optimize the entire product’s UX to fit their customers’ needs.

Feature Adoption Metrics to Track

Feature adoption metrics measure specific data points that show your customers’ sentiment towards your product and help you keep tabs on your growth efforts without referring to your spreadsheets often.

Here are feature-specific adoption KPIs and metrics to capture, benchmark, track, and improve on:

• Overall feature adoption rate: Feature adoption rate refers to the percentage of active users who use a particular functionality in your product. To calculate your feature adoption rate, divide the monthly active users who tried out the feature in question by the total number of logins or active users during the same duration.
• Feature adoption by user cohort or segment: It’s similar to the aforementioned, but in this case, refers to the percentage of a specific batch of users who started using a particular feature. You can segment users in various ways, from the acquisition date, pricing tier, company size, user persona, or any other metric you can extract from your database.
• Exposed rate: The number of users who have been exposed to a new feature. An example is how many users saw a pop-up promoting a new feature.?
• Activation rate: The number of users who have met the criteria for activating a feature. This typically means they have gone through a feature introduction and walkthrough and have started to engage with that feature. Examples include importing data or creating a dashboard.
• Used rate: The number of users who have met the criteria for “using” a feature. “Activation” and “used” may be the same for simple products but differs for more complex features and workflows.
• Used again rate: The number of users who have met the “used” criteria more than once for a specific feature.
• Frequency of feature use: While it’s important that users initially engage with a new feature, that doesn’t matter if they fail to use it in their day-to-day. This metric expands on the overall feature adoption rate and answers the question, “how often is a feature being used?”
• Time-to-first use: Time-to-first use measures how long it takes a user to try out a feature for the first time after signing up. This metric is important for understanding what features are being adopted first, which are seen as more critical by users, and so forth.
• Time-to-adoption rate: Time-to-adopt measures how long it takes your customers to use specific features after signing up and completing your product onboarding. This metric will explore the relationship between user onboarding flows and individual feature adoption success.

How to Increase Feature Adoption

While feature adoption may not seem simple, there is a blueprint: observe how your users currently use your product, learn what they expect instead, and then close that expectation-reality gap as un-chaotically as possible with in-app guidance and help support. You can repeat this cycle by using a product analytics tool to experiment and make data-driven product tweaks.

1. Build features that solve user problems

It’s a simple problem, but many products seem to run into this issue.

No amount of growth gimmicks, onboarding tricks, or conversion tactics can help a bad or underwhelming product. It may generate enough growth to keep your product team working on it, but users fail to stick around, with high churn and low NPS.

According to CB Insights, poor product-market fit is the second-biggest (35%) reason startups fail—surpassed only by running out of money. Your development process needs to be tied directly to product feedback to ensure you’re investing your engineering and marketing resources, building features that solve your user's pain points, and which (not surprisingly) they’re willing to use and pay for.

2. Create a robust, omnichannel new feature announcement strategy

If you launch a new feature and only mention it in passing on a new monthly feature update blog or newsletter, users will fail to even know you’ve released a new feature.

Instead, you can attack a new feature announcement like the priority media campaign it is. Ideas to promote new features include:

• Organic and sponsored social media posts on Facebook, Twitter, and niche communities that target your users.
• Sponsorships and shoutouts from industry influencers that introduce your product to their social network, subscribers, or online communities— and it works whether it’s a SaaS feature, a service, or just a resource you’re launching. For example, Ahrefs promoted their recently launched Blogging for Business course to the Demand Curve Newsletter, a community of 65k founders and marketers at companies like Stripe, Webflow, and Dropbox. That segment of potential customers is several times more likely to check out their curriculum, review it on social media, and promote it even further;
• In-app banners, pop-ups, and alerts to announce features. Linear always has a link to new releases of their issue tracking tool—it’s prominent on their homepage and visitors can’t miss it.
• Optional step-by-step walkthroughs that explain how new features work in <1 minute
• Loyalty campaigns—ask users to share your launch posts, or forward your email to their network to get several months’ worth of subscriptions

The best time to promote a new feature is right after you launch it, so go all out, engage your network, sponsored third-parties that your budget permits, and every channel possible right away.

Continue reading about how to increase feature adoption and how to drive feature adoption with a digital adoption platform (DAP) here.

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