One of the most common responses we hear when asking potential customers any number of questions regarding their customer data during a discovery call is “If I had to guess…” followed by an answer that may or may not be accurate. We ask customer success, product marketing, and product management leaders things like:
- What is your most used feature during a trial?
- How many support tickets do your enterprise clients submit a month?
- Where in your software do most of your users run into trouble?
The teams we speak with never seem to really know the answers, and if they do, it can take some serious manual work to figure it out. In the age of automation, there is no reason these answers should not be readily available in a convenient, usable way. Clear, accurate, and actionable customer data is imperative for all departments in an organization so they can be more informed throughout the scope of their work.
In many cases, simply having more data won’t solve your business problems, but having a way to easily read and disseminate what that data is telling you will allow you to act in a more informed manner. In the SaaS landscape, there are a number of solutions that will provide immense amounts of data to your organization, with many focusing on only specific data types. There are tools that will show you every single user who is currently using your product at that given time, tools that will track every interaction a user has with your platform, and even tools that track how much you’re using other tools. With such an abundance of information available, no one should ever “guess” at an answer again. So why do we continue to hear that they are?
Rather than collecting piles of data, your team needs actionable insights so they can make informed decisions about how to do their job smarter. They’ll need to understand how datasets affect one another and discover trends and patterns so they can adjust accordingly.
Here’s an example:
A Customer Success Manager has a customer churn and is debriefing the Head of Customer Success on why. Without understanding the data, the manager’s answer could be, “Well, they were experiencing some bugs” or “I don’t know they didn’t use it very often,” putting the emphasis of blame on the customer. Contrary to popular belief, most customers actually leave for a reason, not just randomly out of the blue. And there is often plenty of time to intervene to save customers from churning.
Having a platform in place that easily allows you to dissect the meaningful data you’ve gathered could lead to a conversation that instead goes like this: “Well looking at the data, I see that they didn’t leverage some core features at all during their initial onboarding, which appears to have resulted in a poor health score. On top of that, it appears they gave us a 5 on our latest NPS survey and no one reached out to rectify their issues.”
Instead of having to guess at why the company churned, they now have an informed view of what led to that action. This ultimately will allow teams to map those key actions customers should be taking and replicate that across their users.
So, STOP GUESSING at what makes your customers successful. Sign up for a demo to see how UserIQ can help remove the guesswork and help you customers become successful.