Product analytics for healthtech

Healthtech represents a new way to address everything from personal mental health to the inefficiencies of the healthcare system. 

But, without the right level of insight, healthtech companies may be overcome by the challenges of growing a niche solution—namely, retaining an engaged user base for a delicate use case. 

Our guiding question: How can product analytics help the healthtech category? 

Why healthtech needs product analytics

Mental and physical health have been at the forefront of the public eye for the past few years. This has not only spurred digital transformation in the space, but also made way for digital disruptors to offer solutions focused just as much on user experience as they are on privacy and scalability.

A collection of McKinsey articles provides insight on this, covering how “health technology continues to push the boundaries of how healthcare is delivered and has the power to create breakthroughs in our understanding of disease.” Tellingly, the collection hits on everything from building a sustainable business in the space to how companies are recapturing value from engagement with their apps.

This dual focus highlights why product analytics is so critical in the healthtech sector: Companies have a long history of legacy solutions and processes to disrupt and big opportunities to capture consumer behavior for other insights. Healthtech companies can put tools in the hands of more traditional companies that will support digital transformation and build applications that both adapt to consumer behavior and report on behaviors and preferences for the wider healthcare sector. 

It’s altogether unsurprising that healthtech received a record $14B in funding in 2020, up from $7.4 in 2019. 

With the public embracing healthtech, it’s created more space for science-backed support in niche areas that weren’t previously supported by traditional healthcare systems. Men’s sexual health, PTSD, and virtual therapy are all prime examples. According to Deloitte, funding like this for “products and solutions that address well-being and care delivery, along with open, secure data and interoperable platforms” will stay strong through 2021 and beyond.

Product analytics means healthtech companies can assess how people are using their solutions, where the gaps are, and how to make the connection more personal than ever before.

This is an important shift beyond tech. In the past, you’d have to search pretty hard to find someone who specialized in what you needed, and it wasn’t a guarantee to find them in your area, either. Now, tech is doing what it does best: connecting people with niche needs with those who have niche solutions in a more personal way.

Product analytics means healthtech companies can assess how people are using their solutions, where the gaps are, and how to make the connection more personal than ever before. 

Metrics that matter for healthtech

The qualities that have made healthtech boom are also the category’s biggest challenges. Growing a user base for niche tech is hard, and retaining them is even harder considering how personal physical and mental healthcare is. 

That said, it’s been a relatively introspective year for consumers. COVID has had a big impact on how people connect and how they understand their own personal experiences and needs. 

We’ve seen usage for healthtech apps go up—and with that comes positive trends in your typical product metrics like acquisition, activation, engagement, and retention. But in what ways do these metrics vary for healthtech companies, and how should they be used differently to assess everything from engagement to stickiness in this special field?

Acquisition

Acquisition metrics are about finding the right users for niche products and even specific programs within the product. Acquisition for healthtech products doesn’t look too different from that of other apps—except that humanization and social proof may be even more important. 

Ultimately, acquisition for healthtech products is about creating testing: combining quantitative and qualitative data to experiment with the messaging, targeting, and even channels that work best. 

Analyzing acquisition via product analytics can help answer questions like:

• Which channel do most users come from?
• Does a free trial move the needle on conversions, or is it more about social proof?
• On average, how much does it cost to acquire new users from each channel?

Activation

Activation metrics are all about finding (and optimizing for) where your users find their first “value moment.” For a bit more detail, check out this quote from our guide to product analytics: 

“Depending on your product, a user journey might look very different. To get to the value moment for the first time, some user flows require registration, verification, adding friends, or entering credit card information before a user can “activate” and experience the product’s value for the first time. This initial journey to value is critical: the more quickly you can get your users to value, and the more you can signal during that journey what value is to come, the better the chances they’ll stick around for more value moments.”

For healthtech applications, the value moment could be something like a user/patient completing their first therapy session or using their first discount for medication. 

With product analytics, you can answer specific activation questions like:

• What is the average time to the first value moment? 
• Which events are most likely to lead to that value moment?
• How many pieces of content does a user engage with before reaching activation? 

Engagement

Product engagement metrics measure how users interact with your product. In turn, analyzing engagement metrics can show you where the product gets the most usage, which content has the highest consumption, and where features are being underutilized. 

In a phrase, engagement metrics help you identify where to double down in the app and where user flows and education may have some gaps. 

For healthtech applications, engagement is almost more important than retention. You want to be sure people are using the product responsibly and that you’re doing everything you can to make it a responsible app, both for emotional and physical health. Mental health apps often have a community aspect, which makes engagement metrics even more important as you look at how users interact with one another, who can be considered “high value” users from a community perspective, and where you need to safeguard against trolls. 

Some of the questions you can answer with engagement metrics include: 

• Which content gets the highest views and interactions?
• How do in-app events impact the likelihood of engaging with community?
• Are users engaging 1-1 with each other? How and how often? 

Retention

Retention metrics indicate how many users experience enough value in your product to keep coming back to use it. 

Getting into the weeds with retention analytics means you can better understand how long users stick around, which events make them more likely to return, and which users (based on both behavior and demographics) are likely to return. 

Retention analytics may look different for healthtech since drop off is both more of a binary decision (“Yes, I’ll see a therapist this week” or “No, I won’t”) and more of a personal decision. Healthtech products should be built around how a user is feeling instead of trying to always optimize for return usage. It should be a much more personalized messaging journey, making product analytics even more critical for healthtech than for other types of applications.

Some of the questions you can answer with retention analytics include: 

• How many users return within 30 days after their first therapy session?
• What percentage of users complete a therapy session on a weekly basis?
• Does engagement with community members translate into higher retention over time? 

How to tie it all together

Unlike other industries—which look to replicate existing processes and interaction in a digital-first, user-friendly format—healthtech is kind of starting from scratch for optimizing user experience. That’s why you shouldn’t take any action in a vacuum. 

While we outline a handful of specific metrics to track consistently, remember that no single metric should be treated as the end-all-be-all of growth.

Identifying specific metrics to track is the right first step in data-driven product development. But, whenever possible, you should be asking open-ended questions of your data rather than looking for validation of a preconceived theory. That’s why it’s so important to advance your product analytics maturity as you grow your product. You’ll only be able to build a better healthtech product by understanding user behavior—improving user experiences accordingly. 

We’ve said it before, and we’ll say it again: Whether you’re already measuring advanced product metrics or just getting started with a product analytics tool, you should aim to iterate on your product analytics strategy the same way you do on your product.