We know that across the world of SaaS, businesses are generating a ton of data through customer interactions and product usage, every day.
This data, when harnessed effectively, can be a game-changer for Customer Success Managers (CSMs) seeking to better serve and retain their customers.
One of the most valuable types of data, especially in SaaS, is product usage data, which holds huge potential for predictive analytics.
But, despite most companies knowing abstractly that product usage data is valuable, many are not using it to its full potential.
Let's dive into the value of product usage data for CSMs, particularly in the context of predictive analytics.
Product Usage Data Is Key to a Holistic Picture Within Predictive Analytics
Predictive analytics involves using historical data to make more informed predictions about future outcomes.
With a stronger analysis of patterns and trends, CSMs can gain even more insights into customer behavior and then identify potential risks or opportunities before they materialize.
This proactive approach enables CSMs to take timely actions to combat churn, drive adoption, and maximize customer satisfaction.
And without that valuable product usage data?
Predictive analytics are limited in scope and value. They’re typically not actionable for CSMs who are savvy at having deeper product usage conversations with customers.
And without actionable insights and suggestions, there’s not much reason to even bother with predictive analytics.
So let’s start with the basics- what is product usage data?
Product usage data refers to the info collected about how customers interact with a product or service.
It includes data points such as feature usage, time spent on specific functionalities, user preferences in the app, and more.
With such a broad range of usage categories and activities, product usage data can be amassed quickly!
When assuming your company is collecting this data properly, the next hurdle is to figure out what to do with it.
Here's why product usage data is simply too invaluable for CSMs to overlook:
1. Early identification of at-risk customers is a major value add:
By better monitoring product usage data, CSMs can easily identify usage patterns that indicate potential churn risks.
A sudden drop in feature utilization, decreased engagement, or prolonged periods of inactivity might signal customer dissatisfaction, or worse - apathy.
With this information, CSMs can proactively reach out to at-risk customers, understand their concerns, and provide more targeted assistance to re-engage with them.
2. Customer engagement becomes more personalized:
Product usage data provides CSMs with a deeper understanding of how customers are using a product or service.
This insight enables CSMs to tailor their engagements and demonstrate the value of specific features or functionalities that align with the customer's goals.
By delivering personalized, data-driven recommendations, CSMs can foster deeper customer relationships and drive increased product adoption rates.
3. CSMs can better anticipate what customers need:
Predictive analytics revved up by product usage data allows CSMs to anticipate customer needs.
They can then act proactively rather than reactively.
By identifying usage patterns and trends, CSMs can then jump to predict when customers might require additional training, varied features, or upgrades.
Proactively addressing these needs helps to solidify customer satisfaction and strengthen retention rates.
These can then drive revenue growth for the business as a whole.
4. Product improvement in SaaS is a team sport:
We know that product usage data’s primary purpose is to better your product.
That’s why product management and engineering teams institute product analytics in the first place. But we also know that product improvement is a team sport...Everyone across your company should feel responsible for it.
It shouldn't be thought of as an island that only the product and engineering teams live on.
By analyzing usage patterns and feature adoption rates, CSMs can better work with product managers to find areas for improvement or innovation.
This symbiotic relationship between CSMs and product teams ensures that customer feedback and preferences are incorporated into future product iterations.
This leads to enhanced customer experiences across the board and an even better product-market fit.
5. CSMs can actively measure and report on the ROI of their activities:
Accurate measurement of return on investment (ROI) is a vital aspect of any business, especially in the SaaS realm.
By using product usage data, CSMs can assess the value customers derive from the product and link it to their business objectives.
This data-driven approach lets CSMs demonstrate the real impact of their efforts, identify areas for improvement, and drive metrics such as retention, upsells, and cross-sells.
Tingono Makes Utilizing Product Usage Data Effortless
In the era of data-driven decision-making, product usage data is a goldmine for CSMs.
Leveraging this data empowers CSMs to become proactive advocates for their customers, driving customer success and retention.
It’s too valuable to go untouched and unturned by your GTM teams.
And we’ve got an idea on something that just might make this a touch easier for you...
What we’re working hard on here at Tingono!
Using Tingono’s AI-powered platform, CSMs can easily identify their at-risk customers, enhance engagement, anticipate needs, contribute to product development, and measure ROI much more effectively.
Tingono makes it much simpler to make sense of that wealth of product usage data you have. For many companies, it’s too overwhelming to make sense of.
But with AI, machines do the heavy lifting of analyzing this valuable data. Insights are easier to understand and can be proven with evidence. And those insights are easier to act on!
As businesses increasingly prioritize customer-centricity, CSMs armed with product usage data and predictive analytics are poised to do better (and more) for their customers.
And that’s really everyone’s goal, right?
Oh, and by the way, product usage data is not the only type of data your business collects. Check out a previous post by our Co-Founder and CTO, Sami Kaipa, on the various types of data Tingono uses to help you become churn-proof.
So if you’re ready to fire up your product usage and other data sources to do more, we want to talk to you.
