I am working through an example and thinking about a SaaS/PaaS company that processes data for large corporations.
What does this company do? Large corporations can upload GBs of data that this company’s technology will clean, sort, and output in an industry-standard format for a price. Add-on features include data analysis (some ML), pushing it to different databases, etc. that a customer can purchase later on.
What are the KPIs that a PM would focus on for such a business? There aren’t high volumes of customers and this is aimed at large corporations.
One KPI could be revenue (MRR/ARR). Should one track how many of these customers were up-sold premium features? Or time spent on the platform, data processed by the platform?
In this context, sales cycles are long and contracts are signed for a minimum of a year/often multiple years. Because of this, it’s hard to attribute any piece of work to a commercial result so sales/revenue/upgrades aren’t great performance indicators for a team to track.
Time spent or data processed might be okay indicators (and often the best you can get) , but the gold standard is measuring the value that clients get from your data/service.
This depends on the context, but if your software is generating recommendations of customers to target, then you’d want to measure the incremental revenue that the client drove from your recommendations. If you’re doing AI to save users time, then you want to estimate the actual time saved; etc.
The reason for doing this is to align your product goals with your clients goals. In a B2B context, upgrade/renewal decisions are made based on value, so if you’re already driving and measuring it, you and your commercial teams will have a much easier life.