Forecasting the Future
As SaaS leaders, a lot is riding on accurate forecasting. We treat all post-sale revenue as recurring, but if it doesn’t reoccur or we overestimate upsells, we may find our companies over-extended. That can mean cutbacks or even layoffs. Miss forecast for more than a quarter and we lose board confidence, making it difficult to secure investors in the future.
Sales frequently invests in enablement activities to train their teams to predict best-case, most-likely, and worst-case within a percentage point +/-. However, Customer Success has traditionally underinvested in training our teams, and forecasting in a common gap. The ability to accurately forecast for CS is not just a tactical advantage but a strategic necessity, so let’s explore how we can better train our teams.
Training Customer Success Teams to Forecast
Foundation in Data Analytics: Too often in an effort to make things uniform, CS teams are relying on Customer Success Platform (CSP) software to auto-calculate things like HealthScores. Then forecasts are auto-generated from that information. For example, some CS Ops person coded it to calculate yellow customers with an 85% likelihood of renewing.
This is similar to how CRMs default to forecasting by sales stages. For example ‘Out for Signature’ might default to a 90% likelihood of closing. But most Salespeople are expected to make manual adjustments to their forecast based on their understanding of the statistical likelihood of the deal getting done, considering all the factors beyond just the sales stage.
CSMs who are given a foundational understanding of data analysis and are given access to historical trends are more likely to be able to override the defaults when they are inaccurate.
Encourage team members to take a LinkedIn Learning, Udemy, or similar class on data analysis.
Then spend an hour or two workshopping together with backward-looking data about the behaviors for three groups of customers, with the goal of establishing the statistical likelihood of renewal:
Those who churn partially or fully
Those who renew for the same
Those who buy more
Select ‘behaviors’ that are most important to your customers, which could be something like time from deal close to go-live.
Engaging the CSMs to do the data analysis to correlate trends in behaviors can be a great learning experience for them. These insights will help them not just give better forecasts but it will also help them prioritize intervention activities when customers are at risk.
2. Relationship Management: When individuals at a company know and trust their CSM they may share news about upcoming changes to the account long before software can pick up on a behavior change. This can be important factors like
Pending mergers or acquisitions
Upcoming leadership changes
New business priorities
Anticipated headcount changes
Renewed executive focus on your solution
Teaching CSMs to ask the right questions to the right people can unlock insights earlier.
3. Scenario Planning: Equip your team with the skills to perform scenario planning. This involves creating various 'what-if' scenarios to anticipate potential changes in customer behavior or market conditions. For example, “What if our key competitor cut prices by 20% would your forecast change?” Such exercises help teams prepare for multiple outcomes, making them more agile in their strategic execution.
4. Sales Training: We would never throw a salesperson out with a quota and no training and expect them to be able to close deals, let alone accurately predict them 1-4 quarters ahead of time. However, for many experienced CSMs owning upsells and cross-sells is new.
For teams with new revenue responsibilities, train them on which buying signals to look for and how to qualify them. Role-playing through parts of the buying process can help them get a better feel for the sales motion, timing, and likely outcome. For example, “The point of contact comes back and says they aren’t signing any deals with Net30 payment terms, what would you do?”
Talking through their funnel regularly with a more seasoned salesperson assigned as a mentor can be very helpful and offers a different perspective than they are likely to get from their CS leader.
5. Understanding Business Metrics: It's essential for customer success teams to understand how their actions influence broader business. The underlying calculations in systems should be understood by everyone and common terms (like ‘red customers’) should be well-defined and documented. This includes training on key performance indicators (KPIs) such as Customer Lifetime Value (CLTV), churn rate, etc. By linking daily activities to these metrics, teams can better understand the impact of their work on the company’s bottom line.
By investing in your customer success team's forecasting abilities, you're not just optimizing for better reporting; you are empowering them to understand and take ownership of their book of business. Accurate forecasting leads to better decision-making and a healthier bottom line. By aligning customer success with top business goals you’ll enhance CS’s strategic influence within the company.
