Product Usage: The Key to Customer Retention

Nathan Ricks
Nathan Ricks

With decreased budgets across the entire tech industry, acquiring new customers is more difficult now than ever.

Because of this, management teams are increasingly turning to their CSMs, sales reps, and product-led growth (PLG) teams to not only retain the customers they have but upsell them as well.

This is a big responsibility to carry out, and these teams are having to do it driving blind. Blind because these teams often don’t have access to the data that is most correlated with customer retention: product usage.

What is Product Usage?

You might think this question has a simple answer, but you’ll soon realize that “product usage” includes a wide range of data that can be analyzed.

The core of product usage starts with the primary questions: who, what, when, and how.

Who - Which accounts are using the product the most? Who within those accounts are the power users? Who hasn’t been engaging as much?

What - What features of the product are they (individually or in aggregate) engaging with? What are they not using? What is their level of engagement or usage?

When - When are they logging in? How often are they logging in? How much time do they spend in the product when they do log in?

How - How are they engaging with the product? What behaviors do they exhibit when they engage with certain features? What roadblocks are they hitting?

Why is Product Usage Data Important?

First and foremost, product usage - usage frequency, in particular - is important in predicting customer retention.

There are several studies that suggest that the level of product usage is the most correlated factor with whether or not a customer renews. A higher level of usage indicates that the customer is getting value from the product and is likely satisfied. And the opposite is true for a lower level of usage.

But usage frequency isn’t the whole picture. When combined with the other data points we discussed above, you get a much greater level of predictive power.

For example, you can start to answer questions like:

  • Is low engagement during the onboarding phase indicative of churn down the road?
  • Is the size or industry of the customer correlated with product usage?
  • Did product usage decrease when the customer hit roadblocks or reported bugs?
  • Is product usage correlated with the account executive who sold the deal?
  • Which personas are engaging the most?
  • What features are being used by XYZ persona? Or which personas are using XYZ feature?
  • Are there certain cohorts of customers that exhibit different usage patterns?

Being able to answer these questions will give you significant insights into the business, your product, and your customers to help increase retention.

What Do You Do With These Insights?

These insights can be used by a variety of teams including customer success, sales, and PLG teams.

Customer Success

With these insights in hand, CSMs can approach customers with significantly better questions and resources which will help ensure customer retention.

These questions could include:

  • I noticed you haven’t had a chance to try the feature in the product. I think you’d gain a lot of value from it for XYZ reasons. Want to do a quick call so I can show you how to use it?
  • It seems like you haven’t logged in in a few weeks. Are you hitting any roadblocks?
  • Your usage of XYZ feature has been high. What are you liking about it? What problems is it solving for you?

Any CSM knows that getting answers to these questions increases the probability of renewal and upsell tremendously.


By having insight into what happens after a sale is made, the sales team can adjust the companies and personas they target (their ICP) in order to increase retention down the line.

For example:

  • If certain industries or company sizes are showing high amounts of product usage, it would be wise to dig into the reasons and potentially target those types of accounts more.
  • If certain personas or departments are showing high initial engagement that then falls off after a few months, maybe the use case for the product is different than anticipated and other types of personas should be targeted.
  • If there is a correlation between customers with low usage and the account executive that made the sale, you should probably find out why that’s the case.

Even if you’re a startup with few customers who have made it to the one-year renewal mark, simply knowing that product usage is highly correlated with renewal can help the sales team adjust mid-flight.

PLG Teams

Product-led growth often entails the use of a freemium product to attract new customers. Of course, the real bet is that these customers of the free product will want to upgrade to paid products with more features.

The timing and messaging you use with these customers - whether through sales reps or automated marketing messages - can have a big influence on whether they upgrade.

For example:

  • If you notice that a freemium user isn’t using a feature that tends to be the real selling point of your product, sending an automated email to encourage them to use it would be wise.
  • If it’s been a few weeks since they logged in, it might be worth sending them product demo videos or customer case studies so they can discover more use cases.
  • Sending them congrats emails for reaching milestones or using certain features shows that you’re paying attention and care about their success.

These personalized messages based on product usage will clearly contribute to them eventually upgrading.

How Do You Get This Data?

I’ve been yapping about all the benefits of product usage data for renewal and upsell, but it begs the question of where to get this data.

Traditionally, these customer-facing teams would need to turn to their engineers to query for this data. That’s because product usage data is often stuck in a product database such as PostgreSQL, MongoDB, or MySQL and requires specific permissions and skills to be able to access it.

A slow process with many headaches along the way.

This is where Polytomic comes in.

Our tool allows anyone, including non-technical folks, to be able to sync product usage data from the product database into the CRM.

That way, the CSMs and sales reps can see directly in Salesforce or HubSpot the last time a customer logged into the product, which features they’re engaging with, and whether they’ve reported bugs within the product.

With the data now in the CRM, managers can run reports and do further analytics to spot trends and derive insights that can be used by CSMs in their outreach, sales teams in their targeting, and the product team in their roadmap, all with the goal of customer retention.

If that sounds interesting to you, we’d love to give you a demo of the product!

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