The Right Way to Quantify Customer Success

True customer success stems from your ability to quantify, measure, and replicate the behavior of happy customers.
Categories Articles, SaaS

There’s a big problem with the goals customer success teams set for themselves. The metrics we focus on are retention, cross sells, and upsells. Those are the big three that measure the impact customer success has on your company’s bottom line, and thus they are the accepted method for evaluating customer success teams.

The problem is by tying our goals directly to the revenue of our own company, we lose sight of the mandate implied by our title – customer success. We focus on maximizing our own profitability, not on helping our customers to gain value from the product we’ve sold them.

Churn and upsell opportunities are actually derivatives of the value your customer finds in your product. The key to improving the quality of your customer experience is to align organizational goals and KPI’s with the value proposition of the business. The first step toward that alignment is to effectively identify and quantify the reasons your customers bought your product in the first place.

The key to improving the quality of your customer experience is to align organizational goals and KPI’s with the value proposition of the business.

By quantifying the benefits your customers gain from your product, your customer success team will be able to identify the handful of features in the product that lead to value. That knowledge helps you design onboarding and training plans around those core features, which both shortens a customer’s time-to-value and increases the utility they gain from your product.

That’s the right mentality for customer success. By structuring our goals around maximizing the utility of our product, we create satisfied and engaged customers — which in turn leads to reduced churn and an increase in upsell and cross sell opportunities.

I’ll use my own experience at InsightSquared as a concrete illustration of this point. We still measure churn, upsells, and cross sells like everyone else (these are unquestionably vital metrics for a SaaS company to stay on top of), but we’re shifting our focus to the metrics that are direct indicators of how effectively customers are using our product.

We structure our approach to customer success around a few core questions:

What are the common themes for why customers bought?

If you don’t at least have a subjective answer to this question, your company is in trouble.

Very early stage startups may get a wide range of answers to this as they strive to find product-market fit, but the majority of companies should be able to pick out 3-4 common use cases across all their customers for each product.

In the case of InsightSquared (which sells sales and staffing analytics software), the answer for every customer boils down to this: InsightSquared makes it easier for me to increase sales and manage my team.

This broad stroke is all you need to start figuring out how to quantify customer success. It’s the broad foundation you can build more granular analysis on — you don’t want to get more technical until this value proposition is rock solid.

How do you quantify success?

This next step is significantly harder for some companies than for others.

In our case, answering it was pretty straightforward (there are advantages to working for an analytics company) — we identified key sales metrics that correlate with customer success and established benchmarks for the returns our average customers see against those key metrics.

Here’s a sample of a few of those benchmarks:

In the first year with InsightSquared our average customers will see improvements of:

For companies with 200 employees or fewer:

  • 5% increase in dollar value win rate (won dollars/total dollars in pipeline)
  • 50% increase in monthly bookings
  • 22% increase in monthly bookings per employee
  • 61% increase in ASP
  • 16% increase in number of deals won
  • 33% increase in opportunities created

For companies with more than 200 employees:

  • A 7% increase in dollar value win rate (won dollars/total dollars in pipeline)
  • A 12% increase in bookings
  • A 13% increase in ASP for the entire sales team
  • A 19% increase in ASP per employee

Not all products lend themselves so neatly to being able to quantify what success looks like, but the fact remains: If you want to optimize your ability to retain and upsell customers, you have to establish quantitative benchmarks for their success.

Otherwise, you’re just guessing at whether they’re getting a good return from your product or not, and you won’t be able to create a scalable process for onboarding, training, and managing new customers.

What product features contribute the most to success on our benchmarks?

It’s rare that your product will be the only solution your customer has found to address a major business pain — so the challenge for customer success teams is to parse out how much of a direct contribution their product has had in solving the customer’s challenges.

Continuing with InsightSquared as an example: We can show that companies tend to see an increase on key metrics in their first year with us, but who’s to say those increases aren’t in part due to leadership changes, or the release of a new product, or any number of other variables?

Our approach to this problem is to conduct multivariate segmentation analysis. In short, we divide customers into groups and batch together the ones who have shown the greatest increase on one metric or another.

I’ll use team-wide average sales price, to simplify the explanation. Once we’ve identified the group of customers that see the greatest increase in team ASP, we can parse through their usage metrics to find similarities in how that specific cohort uses the product.

We also home in on the right use cases by looking at companies who have failed to achieve the standard returns we’d expect them to see, and look for the common threads in their behavior that represent a failure to use the product in the right way.

By cohorting across the entire customer base in this manner, it’s possible to pick out the specific features and use cases that are tied most closely to improvements in our customers’ key performance metrics.

That insight is extremely powerful for structuring the way we handle our onboarding, training, and support.

How can we structure our onboarding, training, and management to ensure customer success?

This is the point where analysis turns into action. We take the information we’ve gleaned on what features are most likely to contribute to the metrics that matter for our customers, and focus our calories in the early stages of the customer lifecycle to ensure the customer uses those features.

We sell a complex, B2B product, so we take an iterative approach to onboarding. Knowing which customers have derived the most value and the least value from the product allow us to develop specific training plans that shorten implementation time and create a direct path to value in the product.

We wouldn’t be able to do that without having done the math ahead of time to know what that path looks like for each customer cohort.

This may sound biased coming from a Customer Analytics Specialist, but true customer success stems from your ability to quantify, measure, and replicate the behavior of happy customers.

I’ve outlined the approach we take here at InsightSquared — I hope it starts a conversation around how we can move the focus of customer success teams back to actual customer success.

Dan McDade
Dan McDade
Dan McDade is the Customer Analytics Specialist at InsightSquared. He uses advanced statistical analytics and predictive modeling to analyze customer behaviors.
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