Robert Statsky

Creating a forecast for CS in B2B SaaS can get quite overwhelming. There is a ton of data and analytics to pick through. Ultimately, everyone wants to know the same thing:

1. How many customer are renewing?
2. What are they paying?
3. How close are we to our targets?

I’ve found most forecasting models at B2B companies are built for the sales use-case and are then just adapted or ignored for the CS use-case. It’s probably because in a basic sense most people are just looking at the churn percentage, the NRR or the GRR.

There might be some metrics like CSAT or NPS looked at as well, but I have not seen very sophisticated forecasting for CS.

In most of my roles, I’ve been the most senior CS hire, so nothing has been established yet. Or worse you come into a scenario where you hold CSMs accountable to metrics but they have absolutely no way of tracking them at all.

At the minimum, run through the exercise of asking yourself what is important for the org. If this has been established already and you’re a CS leader coming into an organization with some basic infrastructure I would suggest working to understand how the data is collected and reported on. Don’t come in and immediately tell everyone they are wrong and then put your system in place. That will be an uphill battle you’ll ultimately lose and you won’t make any friends along the way.

Understand how you are being measured/evaluated and what the expectations are, and then work hard to track against those metrics. If your targets are logo retention (GRR), NRR and increasing the NPS score you should first build out a dashboard to track all of those in a digestible way. Then build out targets for your CSMs to ensure they are focused on those as well.

After that develop an engagement model that drives towards those metrics. This will help ensure the entire organization you’ve built is moving in the right direction. You’ll have the systems in place, and everyone will have a trackable and easy way to understand what goals they are driving towards. You can then assign KPIs to the team afterwards.

While all of this seems to make sense on paper it is much more difficult in terms of implementation. Most organizations, especially startups in the B2B SaaS space have messy data and disjointed systems.

So it is much harder in practice. To ensure longevity in your position, learn to work with the systems you have, learn to track and work against the targets put in front of you, and build credibility before you blow everything up.

Forecasting GRR (Logo Retention)

To start, work with two forecasting stages for your customer base:

1. Commit: This will renew, or I believe I can get them to renew.
2. Pipeline: This will churn, or this might not renew and there’s a strong justification why.

If you’ve created these two simple categories you can very easily figure out best what your forecast could look like, and then you can begin to layer on additional factors.

Next Steps

1. Have your CSMs categorize their entire book of business for a given quarter (assuming you’re on an annual subscription cycle and track metrics quarterly)
2. Once you have the GRR forecasted, have the CSMs place a dollar value with how much revenue they anticipate to bring in. That will give you a sense of the NRR.
3. Depending upon how close you are to goal, determine where to focus your time to make the most amount of impact.

This is basic 101 forecasting, but from what I’ve seen, most CS organizations do not even have this in place in a meaningful way. Roll this out before you build anything else out more sophisticated. If you have a monthly subscription cadence, you’ll need to come up with a different forecasting strategy (but that’s a separate topic).

As always here is what Chat GPT has to say:

Forecasting net revenue retention (NRR) and gross revenue retention (GRR), also known as logo retention, is essential for a B2B SaaS company to understand revenue growth and customer retention trends accurately. Here’s a strategic approach to forecasting these metrics:

1. Gather Historical Data:

• Collect historical data on revenue from existing customers, including churn, expansion revenue, and upsells/downsells.
• Analyze past performance trends to identify patterns and drivers of revenue retention.

2. Define Key Metrics:

• Clearly define net revenue retention and gross revenue retention metrics.
• Net revenue retention measures the change in revenue from existing customers, accounting for churn, contraction, and expansion.
• Gross revenue retention focuses solely on the percentage of revenue retained from existing customers, regardless of expansion or contraction.

3. Segment Customers:

• Segment customers based on subscription plans, contract terms, industry, or other relevant criteria.
• Analyze revenue retention rates and contributions from different customer segments to identify trends and opportunities.

4. Analyze Churn and Expansion:

• Analyze customer churn rates, including voluntary and involuntary churn.
• Evaluate expansion revenue from upsells, cross-sells, and upgrades to existing customers.

5. Consider Contractual Factors:

• Account for contract renewals, upgrades, and downgrades in your forecasting model.
• Consider the impact of contract lengths, pricing changes, and billing cycles on revenue retention.

6. Factor in Seasonality and Market Trends:

• Consider seasonality and market trends that may influence customer behavior and revenue retention rates.
• Adjust forecasts accordingly to account for fluctuations in demand or economic conditions.

7. Utilize Predictive Analytics:

• Leverage predictive analytics and machine learning algorithms to forecast future revenue retention rates.
• Incorporate historical data, customer characteristics, and external factors to generate more accurate predictions.

8. Collaborate with Sales and Finance:

• Collaborate with the Sales and Finance teams to align on revenue forecasts and growth targets.
• Share insights on revenue retention trends and factors influencing revenue performance.

9. Monitor and Adjust Regularly:

• Continuously monitor actual revenue performance against forecasted metrics.
• Adjust forecasts and strategies as needed based on real-time data and market dynamics.

10. Communicate Insights:

• Communicate revenue retention forecasts and insights to key stakeholders, including executives and investors.
• Provide regular updates on progress, trends, and potential risks or opportunities.

11. Iterate and Improve:

• Continuously iterate on your forecasting methodology based on feedback and performance.
• Incorporate new data sources, technologies, and best practices to improve accuracy and reliability.

By following these best practices, you can develop robust forecasts for net revenue retention and gross revenue retention, enabling your B2B SaaS company to make informed decisions and drive sustainable revenue growth.