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While customer acquisition is a clear part of revenue growth, a less obvious but critically important driver is customer success, as measured by high retention rates. Once you have invested the time and money to acquire a new customer, you lose out on the full revenue potential of that customer if they leave, or churn, earlier than desired. By reducing the revenue headwinds caused by churn, companies with strong levels of customer success grow faster.
To better understand the impact of customer success on the growth of technology and software companies, we developed a set of hypotheses and perspectives on key metrics behind customer success, as well as best practices for reducing churn that we validated with input from leading innovators in venture capital and SaaS. We then dug into our proprietary database, SaaSRadar, which tracks key financial and operational metrics across nearly 200 growth-stage SaaS businesses with revenue between $10 million and $200 million. We used that data to look at how top-quartile performers in revenue growth compare with mean performers across a range of churn and related metrics for each of three customer types: small and midsize businesses (SMBs); SMBs and enterprises; and enterprises (see sidebar, “About the research”).
Companies typically track three churn metrics: customer churn, gross-revenue churn, and net-revenue churn. The most comprehensive of these three metrics is net-revenue churn, as it captures both the dollar value lost from churning customers and the dollar value gained from expansion revenue (which comes from both up-selling and cross-selling to existing customers). Our analysis showed several results:
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The results of our analysis show that top-quartile-growth performers have much lower net-revenue churn than mean performers. The analysis also shows that net-revenue churn improves with larger average contract value (ACV), likely due to more structural churn among SMB customers and higher switching costs associated with larger contracts (Exhibit 1). In particular, between the SMB and the SMBs-and-enterprises customer types, top-quartile performers not only have net-revenue churn that is 14 to 23 percentage points less than mean performers but also have net-revenue churn that is negative in an absolute sense. Negative net-revenue churn means that these top-quartile performers would continue to grow even if they did not acquire any new customers (their ACV expansion in existing accounts is greater than any revenue churn from existing customers).
The difference in net-revenue churn between top-quartile performers and mean performers is less pronounced among companies serving large enterprises—top performers have net-revenue churn that is seven percentage points lower than mean performers. However, because of the size of these contracts, even small differences in net-revenue churn have very real implications for a company’s top line.
Breaking down net-revenue churn into its two primary subcomponents, gross-revenue churn and expansion revenue (also called “antichurn”), reveals that top-quartile-growth performers achieve such low net-revenue churn by outperforming on gross-revenue churn.
While it is true that some of the net-revenue-churn advantage enjoyed by top performers stems from expansion revenue, the majority of the benefit stems from reductions in gross-revenue churn (Exhibit 2). Across all three customer types, the gross-revenue churn of top-quartile-growth performers is about 40 to 50 percent lower than mean performers. In other words, relative to mean performers, top-quartile performers achieve their success more by retaining existing customers than by convincing their customers to buy more or move to higher-priced tiers of the product.
The skew is a little more balanced when serving midmarket customers. Here it is important to excel at both gross-revenue churn and expansion revenue to maintain top-quartile performance. This is likely a result of the “land and expand” strategy that companies with midmarket customers are pursuing, where success at expansion within existing accounts is critical to achieve top-quartile growth.
Coming back to the overall picture, focusing on gross-revenue churn is also more important than focusing on customer churn alone. In other words, it’s important to take into account the fact that not all accounts are created equally—some customers are clearly more valuable than others. Companies with top-quartile growth have lower customer churn than mean performers—from about 10 to 30 percent lower depending on customer type (Exhibit 3). But the bigger gap between top-quartile performers and mean performers, again, lies in their gross-revenue churn, which, as mentioned before, is 40 to 50 percent lower depending on customer type.
One clear implication of these findings is that top-quartile-growth performers know how to protect their base—in other words, they understand how to keep their most important customers for long periods. The second implication is that top-quartile performers realize that there is a healthy level of churn and that losing low-revenue accounts can be acceptable, as long as they protect the core accounts that drive the bulk of their top-line revenue.
Given that gross-revenue churn drives most of the difference between top-quartile-growth performers and mean performers, how can companies effectively lower their gross-revenue churn? In our experience advising SaaS businesses on customer success, there are five areas for companies to focus on.
Top-quartile-growth performers invest in a customer-success model that fits their customer needs (Exhibit 4). At the SMB level, top performers are actually investing less than the mean, as they are more efficient in addressing customer needs. This translates into best-practice digital support as well as products that more seamlessly integrate with existing systems, thereby reducing head-count spend in the customer-success function. Alternatively, companies serving enterprise customers invest more heavily than the mean in customer-success professionals, fitting well with the hands-on expectations of their large deals and customers. The midmarket is a mixed bag, as smaller customers will be served more through a digital model and larger customers will require a more hands-on approach.
The seeds of churn are sown throughout the customer experience, so it’s necessary to have a clear engagement strategy for each leg of the customer journey. During deployment, companies should ensure rapid installation and seamless integration with their customers’ systems. But the best companies solve deployment challenges with great products. Top-quartile-growth performers spend more on R&D and product development than mean performers. They then reap the benefits of this product focus with lower implementation costs and a more positive customer experience at deployment.
As customers then move into the early days of usage, companies should ensure appropriate onboarding and training and also manage work flow actively. Finally, during renewal, companies should identify in advance what accounts are at a high risk for churn and identify and resolve customer issues to ensure a seamless renewal process.
Analytics and predictive modeling can help to both identify drivers of churn and prioritize resources and contact strategy for customers that are at the highest risk and of the greatest value. Analytics and predictive modeling should be employed across three dimensions: key business benefits, technical and feature shortcomings, and pure customer service. Each presents different dynamics and challenges.
For key business benefits, companies should analyze the metrics that matter most to their customers (web traffic, engagement time, or conversion rate, for example). For technical and feature shortcomings, companies should track customer frustration with issues such as bugs and glitches, poor user experience, slow load time, and integration problems. For pure customer service, companies should analyze customer happiness with engagement, response time, and issue resolution across all customer-care channels including phone, email, and live chat.
While predictive analytics will help identify at-risk customers, it is still important to measure a broad range of key performance indicators to keep your customer-success organization accountable to a high standard. As such, consider segmenting your customer-success metrics into three types: lagging indicators, activity indicators, and leading indicators—and having a scorecard to track all three.
Lagging indicators include renewal rate, expansion (again, cross-selling and up-selling existing customers), and advocacy (through case studies and reviews, for example). Activity indicators include a customer’s receptiveness to engaging in activities like interviews, focus groups, and product-feedback surveys. Leading indicators include measures of customer satisfaction, such as net promoter score; adoption, such as the number of seats or features being used; and client engagement, such as the rate of attendance at meetings and events.
Ultimately, the customer-success organization cannot live in a vacuum. One hallmark characteristic of a strong customer-success organization is that customer insights are shared across the entire organization. In that way, the customer-success organization becomes the company’s “learning engine”—relaying their findings from the field to the sales, product, and marketing teams. This feedback loop is critical in allowing for the overall product, value proposition, and delivery model to improve.
In summary, our analysis clearly shows the extent to which a focus on customer success is critical to attaining top-quartile growth. Net-revenue churn is correlated with higher growth. And the key driver behind low net-revenue churn is maintaining low gross-revenue churn. A relentless focus on customer success allows technology and SaaS companies to lower gross-revenue churn and keep it there—complementing the efforts of their sales teams, as well as kicking revenue growth into higher gear. Ultimately, the focus on customer success not only accelerates revenue growth but also creates a more efficient and effective go-to-market organization.