Resources: AI

6 ways to leverage AI for product-led growth

AI can help product managers enhance their product-led growth (PLG) strategies with more automation, deeper personalization, and faster data-driven decision making. Below, we explore how to apply AI to each of the six PLG principles.

Principle 1

Providing a free user experience

This is where any product-led growth strategy has to start—because there is no better sales vehicle than the product itself. Lengthy product demos and follow up sequences take time from sales reps and become friction points for prospects. Instead, teams should let users see the product’s value for themselves, whenever it’s convenient for them.

How to use AI:

With its ability to quickly identify patterns from large datasets, AI can help you determine the right set of features for your freemium product. For example, AI can analyze product usage data from your paid product, identify patterns, and recommend which features to include in your free product.

Ideally, an AI-powered product analytics tool would be able to proactively flag insights like: “Users who engage with X feature Y times in their first three months go on to stay engaged in the product for the remainder of their subscription term.”

Bonus tip

Prediction: The rise of AI will make it more important to have a free product offering.

As sales teams start to use generative AI to power their outreach, the amount of emails and LinkedIn messages could increase exponentially—making these channels even noisier. Companies will need to find new ways to reach prospects, and there’s no better place to engage than inside a free product where people can experience the value of your software for themselves.

Principle 2

Delivering an “aha” moment as soon as possible

Successful product-led growth requires products that immediately let users discover aha moments, which are when they first experience the product’s key benefits. There are multiple ways to ensure users get to aha moments quickly, but a particularly useful one is with an in-app guide that takes the user directly to the experience or feature that leads to the aha moment.

How to use AI:

Although they are extremely powerful, it’s not always simple to produce an aha moment. With AI, though, you can make aha moments happen in more ways—and identify and test them at a much faster pace.

For example, an AI tool can analyze product usage data as well as data on past conversions and upsells and identify potential aha moments. From there, you can quickly test these recommendations by building in-app walkthroughs that introduce users to these features. After that, you can again use AI to analyze behavior data to determine if usage of those features correlates with higher engagement and conversions.

Bonus tip

Use AI to drive more aha moments with personalization

You likely have different types of users who find value in your product in different ways—and therefore have unique aha moments. AI can help you better use information like where a user came from and what they’ve clicked on to create those personalized experiences. It’s not that you couldn’t do this without AI, but AI makes it easier and allows you to identify and implement these insights faster.

Principle 3

Committing to best-in-class usability

A key way to get users to aha moments is to design your free product with optimized usability. The last thing users want is a cluttered or unintuitive digital experience that leaves them unsure about where to go or what to do. As part of ensuring seamless usability, companies should make a point to collect feedback from users about what’s working and what isn’t.

How to use AI:

With an AI-powered product experience platform, AI can help with usability by analyzing user behavior to identify friction points, and even automatically suggesting resources to users based on their behavior.

An advanced tool might even track what resources users select and feed that information back into the model to improve its recommendations in the future. This ability to automatically provide users with the right resources can have a massive impact on their experience with your free product.

Bonus tip

Leverage AI to build hyper-specific onboarding flows

With AI, you can go from a few different in-app onboarding experiences to hundreds—or even thousands. AI tools can analyze a variety of data sources to help craft onboarding flows that are hyper-specific to users’ needs. This could mean that no user is excluded from a personalized first experience with your free product—which is important when it comes to driving virality.

Principle 4

Delighting users to encourage stickiness

Getting users to an aha moment is one thing, but they’re not going to stick around unless they have a reason to. That’s why the best free products keep users coming back and wanting more. Robust feedback collection and product usage data are crucial here, since they can help product teams prioritize the right features and functionality in their roadmap.

How to use AI:

With AI, product managers can sort through and draw insights from more feedback data than they could on their own.

AI tools can quickly categorize feedback into themes and in combination with product usage data, identify where to focus your efforts—whether that means improving what you’ve already built or prioritizing a certain feature in your roadmap. In the end, AI can help product managers better ensure they’re building features and functionality that keep users coming back.

Principle 5

Making purchasing feel like the natural next step

The most forward-thinking product teams design free products that include many key features, while leaving others as part of the subscription model. They also make a point to let users know what they’re missing without the paid version, and make it easy and natural for them to upgrade when they’re ready.

How to use AI:

AI can help product managers get even smarter with in-app messages that encourage users to purchase at the right moments in their journey. For example, an AI tool can analyze usage data from your free product as well as NPS, feedback, and past conversion data to identify moments in the user journey that you might not have flagged on your own.

Similarly, AI and machine learning algorithms can analyze user behavior, company characteristics, and purchase patterns to generate personalized product and feature recommendations. This way, users are exposed to additional functionality that meets their specific needs—which increases their likelihood of purchasing.

Bonus tip

Build personalized and dynamic pricing with AI

Product managers can use AI to run more tests than ever before about which pricing, packaging, and coupons work best for their PLG motion. AI’s ability to quickly analyze massive amounts of data can fuel personalized and dynamic pricing based on a user’s location, company size, the time of year, or other criteria.

Principle 6

Building in virality at every turn

In the end, the goal is to continually surprise and delight users so that they eventually become evangelists for your product. Building in elements of virality helps these super-users spread the word quickly and easily and adds a whole new dimension to your PLG motion. The result is even greater momentum as more and more users discover the value in your product—and let the world know about it.

How to use AI:

Rather than the more traditional purchasing funnel, product-led growth is built on the idea of viral growth loops, also known as the flywheel.

Similar to the other five principles, AI can help product managers analyze behavior data to identify when users are most likely to share the product in their current workflows. From there, you can leverage generative AI to generate any in-app content you’ll use to prompt the user to share and collaborate. It’s still up to you as the product manager to identify the innate virality of your product, but AI tools can help you get to answers and implement virality tactics faster.

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