Though many companies view saas customer success as a support line used for calming and potentially saving angry customers, each company should realize that retention is based solely on telemetry and a mathematical equation rather than feeling.
This guide provides evidence against the assumption that you can save an account by checking in on customers through friendly means and instead shares the actual data models, automated triggers, and technology stacks that can drive revenue growth in a recurring revenue model.
Mathematically Evaluating SaaS Customer Success
Many businesses today estimate the health of their accounts on their own gut feelings and simple email open rates.
This method of evaluating customer account health fails to deliver accurate results at scale. In contrast, organizations with a customer success unit as a revenue engine will evaluate data and understand that by tracking net revenue retention (NRR), the organization is determining its absolute financial limits.
SaaS Customer Success Targets by Segment
A NRR of 90% could be the end of an enterprise but a normal range for a small business. Based on data from the marketplace there are extreme shifts between performance medians based upon the segment/type of company. For example, enterprise companies may expect to have an NRR of 112% and an annual churn around 6.8%.
Mid-markets may target 103% NRR and 1%-3% monthly churn. The targets for small business (SMB) and Product-Led Growth (PLG) are lower than enterprise. SMB sits at approximately 95% NRR and PLG at 98% NRR respectively with a potential annual churn of up to 16.4%. You cannot apply an enterprise metric around an SMB product.
Using a Weighted Health Score Formula
There are multiple factors that should contribute to an assessment of customer health; therefore, do not rely on a single metric. A well-constructed weighted customer health score should include four components, and each component should be balanced within the formula to mitigate against bias. Each of the four component weights is as follows:
Usage: 35% (frequency, feature depth, and active days)
Engagement: 25% (ticket volume and meeting attendance)
Commercial: 20% (license utilization and payment history)
Qualitative: 20% (feedback surveys). Both types of qualitative data will contribute to the overall score of the team's success. All quality feedback should originate from sources which are familiar with the team.
Quantitative feedback for saas customer success is calculated using a score of 1-100. A score of 80 or greater is green, which means that the account is considered "in good standing" because it has met all of the time-to-first-value expectations. Scores between 60 and 79 are yellow and are subject to a 72-hour mandatory follow-up from the team. A score of less than 60 is red, which means that immediate intervention must occur within 24 hours of receiving the score and that the assigned owner must take action.
Workflows for Revenue Protection
The highest performing teams will proactively automate various outreach operations with targeted, automated follow-up sequences. You should build any relevant data trigger into a human operator activity to ensure that you have taken proactive measures to stop potential revenue loss before it occurs.
Activation Sequences and Time to First Value
Accounts can be lost or retained in the first month of the contract. The most critical metric for determining success or failure is the time to first value (TTFV). Data indicates that individuals who achieve a major success within the first 30 days of using their product have a 68 percent higher chance of renewing their contract than those who do not achieve TTFV in the first 30 days.
For an effective sequence, 80 percent of users should have their product set up and active within the first 14 days after activation. If not, an escalation task should be created immediately to the success team for follow-up action.
Monitoring for Silent Failures and Champion Exits
Customers do not typically provide a notice that they tend to stop using your product. Instead, they explicitly stop using your product with no explanation for their departure. Advanced monitoring sequences should be actively monitoring for silent usage declines after initial activation. If usage falls below 60 percent of the last 12-week baseline, a warning should be issued immediately. Tracking when a champion buyer, or most influential user (primary buyer or top user) fails to log into the system is a key early warning sign of a potential increase in churn.
How SaaS Customer Success Software Aligns with ACV
When choosing saas customer success software, your annual contract value (ACV) and CRM’s depth are the primary focus — not the generic feature lists. Dedicated software deployments report average net retention rates (NRR) approaching 100% while operating manual account management typically exhibits a 94% NRR.
High-Volume and Small Business Software Solutions
For ACVs below $5k, use a platform that provides automation to handle high volume very efficiently. A few examples of the platforms that meet this need include Totango, Planhat, and Vitally. These platforms are quick to implement and provide either zero-cost or low-cost licensing to help you start tracking accounts. Typically, the total cost of ownership for these platforms ranges between $0-25,000 per year.
Mid-Market Software Solutions
For companies with an ACV of $5,000-$50,000, enhanced renewal forecasting and in-app guidance become paramount. ChurnZero, Vitally and Planhat primarily address these needs. Annual service costs of these platforms are typically between $12,000-$50,000 with high levels of functionality for tracking complex health data for teams of 10-15 users.
Enterprise CRM Environments
For companies with ACVs greater than $50,000, the need for bi-directional Salesforce syncing and a complete 360-degree data view becomes critical. Gainsight and Catalyst are two examples of platforms that provide this functionality. Gainsight has consistently been identified as the enterprise standard with annual service costs ranging from $50,000-$150,000+ depending on the level of implementation complexity. With these types of solutions, they must align with the company’s larger revenue operations.
The Final Verdict About Retention
Retention is a science and needs to be executed clinically. Staring at a spreadsheet with a list of ‘friendly’ account managers waiting to save deals is not a viable retention strategy. Highest performing software companies only operate on strict mathematical thresholds. Coupling your contract value to your software stack allows you to enforce strict 24/7 response times for dropping health scores and daily track usage decay. Retaining customers becomes predictable revenues instead of guesswork.
Strategic Operations Q&A
What is the response time structure for intervention?
Align your response times to the numerical health score. When a score drops below 60, the response time is set to 24 hours. If the score is a medium-risk score, the response time is set to 72 hours maximum. Without this set time limit, no amount of waiting will allow your team to respond quickly enough to save the account.
How will you identify severe churn threat based on product usage?
When usage drops below 60% of the account's baseline versus the historical maximum (last 12 weeks), you have an increased churn threat. Sudden drops in daily active users, plus the presence of non-failing errors occurring, say 3+ times per day, can indicate an imminent cancellation.
Why do the basic metrics fail to provide a good predictive model of renewal?
Basic metrics (i.e., open rates of the customer’s emails, tickets opened, etc.) provide little insight but rather measure noise. A customer may log in daily just to complain about an issue caused by a feature malfunctioning. Measuring true saas customer success health scoring requires combining both usage depth and commercial signals, such as license utilization, in order to accurately assess if a customer truly sees value from the product(s).
How do you connect account expansion with usage data?
An expansion opportunity is evidenced by specific usage triggers. If an account uses more than 85% of their purchased seats or is nearing the limit of their storage (data), this should trigger an alert to your team so upgrades can be initiated before the next billing cycle.
