For years, I felt like one of the deck officers on a Federation Starship, charting the unknown and exploring brave new worlds. I earned my stripes under the watchful eyes of the James T. Kirks and Jean-Luc Picards of the SaaS era, leaders like Marc Benioff, Frank van Veenendaal, Phil Barker and Maria Martinez.
Customer success was everything to me … a role, a team, a creed. Our focus on the customer helped us plot every course, navigate every murky nebula, and compel engineering to flood the warp core if we needed to move faster to make a customer successful.
When it came time to pilot my own starship, I knew I needed a company with a similarly trained crew and the same navigation charts. However, I needed an opportunity to explore a frontier where no one had gone before. I found the right ship in XANT. I’m on the boundary of that frontier with the company’s Predictive Cloud.
Applying predictive forecasting to customer success
In May 2015, just as I was joining InsideSales, we acquired the incredible predictive forecasting technology called HD Forecast. I was excited at that time to harness that technology to predict our renewals more accurately.
Any customer success professional knows that hitting a renewal forecast is not the prime directive for a customer success team. The primary goal of a customer success organization in a SaaS company is to aid the customer in deriving value from your product.
Customers achieving business value beyond the cost of the license subscription are typically happy, willing to be a reference, and likely to renew to continue to receive the value you are delivering. Happy customers tend to multiply like Tribbles. You’ll need a bigger starship as a result of the success.
Customers who receive no value, or when the value barely covers the cost of the license, are going to find it very difficult to stick around at renewal time. They can be as ornery as a Klingon and as cold as Khan’s abandoned crew on Ceti Alpha VI.
Important milestones on the customer journey
Deriving value is no accident. Most SaaS products require energy from both the customer and the provider. It takes effort to continuously deliver secure, stable and innovative products. It takes similar effort to administer, train and use this innovation effectively.
To highlight these mutual responsibilities, the best SaaS companies prescribe a journey for their customers the moment they start their subscription. Typical milestones on this journey include implementation, onboarding, periodic training and measurement of value.
This journey is very linear as it progresses toward the time of renewal. Many of the milestones are highly quantifiable. Qualitative elements are also important when gauging customer delight through this process.
While I am no data scientist, I did enough research into machine learning and the predictive sciences before I joined InsideSales to know that these customer journey attributes would lend themselves to high degrees of correlation in a predictive model. This is my new frontier.
Now I stand on the bridge looking out into an infinite starscape. Instead of a warp drive, our ship is powered by the Predictive Cloud. Billions of data points from successful and unsuccessful customer journeys are being crunched by some of the most brilliant blue-shirted science officers ever gathered aboard any starship.
They’ll test and retest multiple algorithms and models. Eventually, we’ll have a model we can start testing on actual customers, large or small, no matter where they are in their respective journeys.
A proactive, data-driven approach
Armed with predictive insights, our customer success team can engage more efficiently and effectively to resolve the challenges and issues that would have otherwise impacted the customer’s ability to create value.
We’ll be able to open support tickets on behalf of customers before they even know their app is having an issue. We can suggest training to a team that may have just gone through some abnormally high turnover, even before the customer success manager ever receives a request for training.
If we see numerous customers beginning to struggle with a new feature, we can launch a webinar to help answer questions and improve adoption. The best part is, the model continues to learn and improve with each action we take and each reaction of a customer.
In a few short months, I’m optimistic we’ll be the best practitioners of data-driven engagement in the universe.
Helmsman, one-quarter impulse power. Take us out of space dock …
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