This post was originally published on UX Matters.
The ultimate challenge for any product leader is to ensure that customers not only try, but keep using your product over time. This is the heart of a product-led growth (PLG) strategy. A great product can be a fast path to revenues, brand loyalty, word-of-mouth, and durable business growth.
Product-led growth is a go-to-market (GTM) approach that transforms the way we design products and deliver them to market. PLG is about putting the product at the forefront of the customer journey to drive conversions, retention, adoption, and expansion by delivering an immersive product experience. Plus, in today’s software as a service (SaaS) environment, in which free trials, freemium experiences, and self-service onboarding are quickly becoming increasingly popular, it’s not a question of whether your company will adopt a PLG strategy, but when your company will adopt this model. While PLG is not trivial to implement, it leads to stronger economic units such as net dollar retention (NDR or NRR), gross revenue retention (GRR), and customer acquisition cost (CAC). PLG can help you unlock organic expansion and growth.
Of course, all of this starts with a great product. So how can you build a product that people love? The hero in this story is product analysis, which provides insights that inform and back your product decisions, enabling you to lead a product team with confidence. These in-product reports reveal how well your time and energy investments are paying off. When you do product analysis right, it can help you build a world-class product experience for your customers.
If you aspire to be a data-driven product manager or leader, read on. Here are the five essential product-analysis approaches that you can use for better decision-making and roadmapping.
1. Adoption Analysis
Whether you want to examine new launches or existing features, adoption analysis shows how each feature of your product is paying off in revenues. Since higher adoption rates lead to higher retention, it’s important to examine how well your adoption efforts are paying off. Nearly 60% of SaaS leaders say customer renewals are a high priority, so understanding adoption is essential.
Adoption analysis shows you which users are embracing and adopting your product’s features. What’s more, it reveals which features they’re adopting and which they’re not. Adoption analysis also makes it easy to see what customer segments or user groups are not adopting your product—and you can use that information to create a plan to drive higher adoption.
2. Retention Analysis
Retention is critical because recurring revenue models rely on long-term customers for a product to survive and thrive in the marketplace. Many users walk away from a product after using it just once. For example, users abandon one in four mobile apps after just one use. Retention analysis can change that.
With retention analysis, you can see which features are reducing churn and increasing long-term growth. For example, by setting up a baseline and monitoring your product’s features over time, it’s easy to identify how your product—and the strategic moves you make—create long-term, durable growth. You can also map out expected time-to-value (TTV). From there, you’ll have the foundation to back and measure decisions that accelerate adoption, usage, and conversions. Finally, you can base all of your retention-roadmap decisions on data. That means you’ll see how features or enhancements are turning into long-term, product-led growth. Plus, you can use that proof to secure even more support from stakeholders.
3. Path and Funnel Analysis
With path and funnel analysis, you can spot and eliminate any friction points that are keeping users from taking the actions you want them to take. Path and funnel analysis visually maps how users and product-qualified leads (PQLs) are moving through your product.
At the same time, you can use funnel analysis to see where users are getting lost. For instance, if users are reaching a purchase page and dropping off in significant numbers, you may want to dig into the reasons they’re getting spooked. Once you adjust your product to solve the problem, you can use funnel analysis to understand the impact of your changes.
4. Targeted User-Engagement Analysis
The most successful product teams nudge their users to take the actions on their platform that they know would limit their frustrations and lead to success. They do this by predicting pitfalls that would thwart user engagement and fostering user engagement at strategic points within the user’s in-app experience.
User-engagement analysis is a clear-cut tool for smoothing out friction in a product experience. For instance, if you see that users are dropping off before engaging with a new feature, you might be able to encourage user interactions by inserting an in-app guide at a strategic point. Targeted user-engagement analysis lets you track how often users are viewing, interacting with, and completing specific engagements.
5. User Sentiment and Feedback Analysis
Before you can analyze user sentiment and feedback, you must collect the data. The better you understand your users, the easier it is to craft a product experience that they’ll love. That’s the power of user sentiment and feedback analysis.
User sentiment and feedback analysis looks at your users’ valuable, qualitative feedback, enables you to learn about the feelings your users hold about your product, and packages the data in a way that lets you use it to drive better outcomes. In addition to helping you keep your product decisions laser-focused on your users’ needs, this type of research and analysis shows users that you care about their opinions. It’s also a clear way of identifying your users’ biggest challenges, so you’ll know how to deliver a better product experience.
In the next decade, our products themselves will become the primary tools that enterprise software vendors use in driving and analyzing compelling customer experiences. The next wave of successful software companies will use their products to monitor and engage their prospects and customers contextually.
Product organizations will have to adapt to take on increasing responsibility for customer experiences, as well as the customer-acquisition process. In doing so, they’ll deliver the user experiences that are necessary to succeed in the customer-experience era.
That said, to succeed with a product-led, GTM strategy, SaaS companies must embrace an organization-wide strategic mindset that enables their team to engage prospects in using their product, early in the customer-acquisition process, then guide them through their in-product journeys.
It can often feel like this is mostly a guessing game, full of hedged bets and hopes. The truth is that there is plenty of data available for product managers to make insightful, impactful decisions on behalf of their users to drive repeatable, durable growth through a fully realized, product-led growth strategy. The key is when and where to gather and use that data.
When the question is How can I grow my business? product analytics is a rich resource for answers.