Use A.I. To Predict and Prevent Customer Churn... Before It's Too Late.

Posted by Alyssa Verzino on Sep 26, 2018 11:35:00 AM

Rating concept illustrationSavvy Customer Success teams can spot customer churn before it happens, provided they have access to all the systems where the early signs of customer dissatisfaction may hide. Modern A.I. tools can scale up this hard-won skill so even the most novice Customer Success teams can prevent churn and keep clients happy.

There are only two real reasons that customers churn out of a SaaS solution: "natural causes," and a lack of product success.

"Natural causes" is a glib term for changes in the customer over which you have no control, which force the customer to churn. This can include the customer going out of business, the customer being acquired or merging with another business, or a change in leadership at the customer that leaves you with no internal champions for your solution.

Even if you see natural causes coming, there's often very little you can do about them. A newly acquired or newly led customer must be effectively won over again, which is more often a Sales task than a Customer Success initiative.

A lack of product success, on the other hand, is exactly what the Customer Success team is supposed to prevent, and A.I. can help you see a lack of success coming in advance.

Every SaaS solution has usage metrics -- number of emails sent, numbers of sales made, number of accounts created, etc. -- that indicate a steady rate of adoption, or a steady rate of completed transactions. If those metrics aren't steadily progressing, or even declining, that's a sign that your customer isn't continuing to gain value from your solution.

Similarly, if the number of customer support requests spike heavily, that could be a sign the customer is having difficulty using or understanding your solution. By the same token, a sudden, precipitous drop in support cases may indicate that the customer has become frustrated and is no longer trying to work through their issues with your products.

If the number of active user accounts or active logins suddenly drops, that may mean that the customer has abandoned your solution.

Perhaps most telling, if your customer is still in an active implementation cycle, any change in the rate of contact -- a drop in emails, phone calls, or chat sessions -- may show a waning interest or investment in your offerings.

When these changes are sudden or glaring, they can be easy to spot. But when a mixture of these signals occurs, they occur gradually over time, and the change is only noticeable when compared to that of the average customer, it becomes the job of software to spot the trend.

That's where an artificially intelligent virtual assistant can help Customer Success teams spot churn before it starts. An A.I. agent can tap into all the systems and note when any of those metrics deviate from a baseline value or start trending in the wrong direction. When early warning signs start to occur, the agent can prompt a Success team member to contact the customer and address the issue.

Talla is building just such a virtual Success Team assistant. By deeply integrating with your knowledge base and offering API access to all your key systems, the Talla A.I. agent can spot customer churn before it happens and ensure that Customer Success Teams are themselves successful.

If you'd like to learn how A.I. can prevent customer churn, contact Talla today.

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Topics: Customer Success, Artificial Intelligence

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