Data Model

The Data Model for recurring revenue businesses.

The Model

The modern Data Model for recurring revenue is represented as a bowtie, aligning all Revenue capabilities with a consistent set of metrics.

This contrasts with the typical 'sales funnel' or 'marketing funnel' that many Revenue teams historically have used to measure their performance across a sales process; that funnel has distinct shortcomings for enabling a recurring revenue model.

Key Elements

The Metrics

The Data Model for recurring revenue is comprised of three types of metrics:

(i) Volume metrics

Volume metrics are typically what revenue teams are most familiar with. These metrics often include measuring the following (or similar): prospects, MQLs, SQLs, SALs, commit (closed won), onboarded, ARR, and LTV. The exact metrics used will vary based on stage of the company (e.g., product-led growth companies with smaller contracts may be using monthly contracts, in which case they will focus on MRR rather than ARR). [Footnote 1]

(ii) Time metrics

The Time metric most often used by Revenue teams is the length of the sales cycle. Others often measured are time to go-live and average length of contract. For a more sophisticated, granular view that can help pinpoint where issues are happening in the sales cycle, revenue teams should be measuring the average time between each sales stages, rather than the length of the entire sales cycle, so that they can determine which parts of the sales cycle need further improvement.

(iii) Conversion metrics

Conversion metrics examine how many leads or opportunities move from one stage to the next. There are a few classic metrics used by many Revenue teams, such as Lead-to-Opportunity and Opportunity-to-Close. But similar to the case with volume and time metrics, Revenue leaders should be examining these at a more granular level in order to diagnose where improvements should be made. After the customer commitment, teams typically look at overall churn level, but they should examine this more closely, instead looking at onboarding churn and usage churn, which will typically have very different rates. Similarly, in the area of customer upsell, CS leaders should be looking at this on a more granular level as well, by measuring renewal rate (to the same decision makers), resell rate (to new decision makers), upsell rate, and cross-sell rate.

An important note that becomes clear when Revenue leaders start to visualize and apply the Data Model is that there is a strong emphasis on detailed Customer Success (post-sale) metrics, beyond what most companies measure. The reason for this is that improvements in the customer success stages of a recurring revenue have a compound impact on revenue. For more information on compound impact, see here.

The Principles

Full Funnel

The typical buyer’s journey that a B2B customer goes through is often thought of as the general phases of awareness, education, and then selection of the right solution for their business. Similarly, the typical sales process that B2B Revenue teams use to work with their customers often focuses on those three phases. But once the customer makes their selection, that is not the end of the customer journey; it’s actually the very beginning.

In this way, recurring revenue teams typically make the mistake of focusing primarily on their own sales process to get to the commitment from the customer, ignoring the rest of the customer journey where the customer is focused on achieving their desired impact. The sales process for a SaaS product may take just a few months, while the length of a successful relationship with that customer may last many years. Therefore, rather than a narrowing 'funnel' that ends with the customer commitment, the proper process and model for recurring revenue is far better represented by a bowtie, with the customer commitment in the middle.

Closed Loop

The modern Data Model, when properly applied, operates as a closed loop system, which means that there is a loop that feeds back into the beginning of the model in order to inform it and improve it over time. In this case, a classic example of the closed loop is determining who your best customers are in the later stages of the bowtie, and then feeding that information into the beginning of the bowtie, where your Marketing team can be informed of these customers and try to go find more prospective customers that are similar.

Customer Centric

There is a fundamental rule that drives sustainable growth for successful recurring revenue businesses: recurring revenue is the result of recurring impact. Examining the idea of impact further, there are two kinds of impact: emotional impact (e.g., making a report easier to build, or giving a manager more visibility into the activities of their team) and rational impact (e.g., increase revenue or decreasing costs). Revenue teams must think in these customer-centric terms, truly understanding what impact their customers are trying to achieve. [Footnote 2]

This way of thinking should be reflected in the sales process as well. Many companies think in terms of prospects, MQLs, qualified opportunities. Instead, the sales process should be thought of in terms of the customer: expressing interest, engaged with us, committed to a solution, ready to activate, achieving recurring impact, and growing further to achieving maximum impact. When we start to use this customer-centric mindset and terminology, we start to act in the best interest of our customers, helping them achieve recurring impact, in turn yielding recurring revenue over time.

Recurring revenue is the result of recurring impact.


  1. The typical 'sales funnel' or 'marketing funnel' does not serve the needs of recurring revenue business models.
  2. The Bowtie is a more accurate way to model the inner workings of a recurring revenue engine and reflect the principles that define it.
  3. Companies are placing an outsized emphasis on the first half of the Bowtie, leading to a heavy focus on winning more deals; most companies have a great opportunity for growth by more closely examining and measuring their metrics after the customer has made a commitment.
  4. Most revenue organizations have plenty of data at their fingertips, but are getting lost when it comes to how to interpret it. This results in the incorrect identification of the problems, and therefore the wrong actions being taken to remediate the issues.
  5. Recurring revenue models can be optimized as follows:
    a) In the first half of the Bowtie, drive exponential growth by making small improvements at each of the key moments in the customer acquisition process
    b) In the second half of the Bowtie, drive compound growth by making small improvements at each of the key moments in the customer success process (such as renewal, cross-sell, and upsell)

The Model in Action

Visualizing the Bowtie

The typical “funnel” needs to be reimagined in order to serve the needs of recurring revenue organizations.

Visualization of the ROM Operating Model in action


Terminology Used

Volume metrics. The number of leads, opportunities, or accounts you have at the beginning of each stage
Conversion metrics. The conversion rate of leads, opportunities or account from one stage to the next; indicates how effectively you are demonstrating the value of your product
Time metrics. How much time on average passes from one stage to the next; indicates how quickly you are helping customers move through your sales process


Source 1. Schrage, M. (2017, April 18). What Most Companies Miss About Customer Lifetime Value. Harvard Business Review.
Source 2. van der Kooij, J. and Persofsky, J. (2021, March 23). The Rise of Customer Success as a Profit Center. Winning By Design.
Source 3. van der Kooij, J.J. (2018) The SaaS Sales Method: Sales as a Science.
Source 4. Miller, A., Vonwiller, B., & Weed, P. (2016, October 26). Grow Fast or Die Slow: Focusing on Customer Success to Drive Growth. McKinsey.
Source 5. Lorem ipsum dolor sit amet, consectetur.


Note 1. Refer to SaaS Metrics 2.0 for a thorough overview of typical volume metrics and their definitions.
Note 2. For more on emotional and rational impact, see here.