My Favorite Analytical Tool for a SaaS or Recurring Revenue Business

For my very first post, I wanted to write about what I consider to be the most useful analytical tool that exists in a SaaS business. At DiscoverOrg, we call it the ACV Database. At my prior firm, where I was first exposed to the concept, we called it Spend Rate. The concept is extremely simple, powerful, and malleable, providing a framework for cohort analyses, retention rates, and calculating upsell/downsell, among other things.

Think of the ACV database as a flat file. In the left most column are your unique customer identifiers. These can be names or numbers, however you want to view the data. We use SFDC Account IDs so that we can do lookups on other data as necessary. The important point here is to use an identifier that is at the level of your customer hierarchy that you want to count. I find that account level or even higher works best, depending upon how you use your data.

Across the top row are dates. We build ours monthly, but quarterly can work as well. In the cells are the ACVs of each customer for each of the time periods. The ACV for each period must be calculated by using the start date and end date of the all of the contracts for that customer. So this is not simply an output of all of your opportunities, but is instead the summation of all of the opportunities for each customer at any point in time. If you use close dates instead of start dates, you'll end up double counting ACV if you have early renewals.

Read left to right then, you can see the history of any individual customer. When they came onboard (the time period when the ACV went from $0 to a positive value), if/when they added or lost value over their tenure (if the ACV went up or down), and when/if they churned (when the ACV goes from a positive value to $0). You can also see when/if they were won back post churn (positive value to $0 to positive value). Read from top to bottom, the ACVs should sum to your firm's total ACV at any point in time. Combined, you can view the history of the firm: how many customers the firm had at any time, what was the total ACV of any slice of the data at any point in time, and how many customers had ACV that went up, went down to some positive value, went down to $0, or stayed flat.

Because you have a minimum of 3 factors (customer counts, ACV, and time) in one file, the ACV Database can be used for ACV and logo cohort analyses, retention analyses (what was the ACV and/or logo count one year ago and what of that value remains?), and easy filtering and sorting to determine things like number customers over a certain size or ACV added over time to a certain subset. We also append other data to the Account IDs like customer segment or firmographic information. This allows us to perform the same types of analyses I've already mentioned, but slice the data more ways (e.g. what was the ratio of customers in segment X with employee size Y that increased their ACV YoY to those that decreased and how is that different than 6 months ago).

That's it in a nutshell. The ACV Database is simple to build and maintain, allows for both macro and micro views of your business and is flexible enough to scale as you add other characteristics to your account data.

Thanks for reading, and feel free to reach out if you have questions.