When praised for his contribution to science, Sir Isaac Newton said, simply, “If I have seen further it is by standing on the shoulders of Giants.” Of course he tried to be modest, but he also revealed the divine secret of scientific research: first, gather previous knowledge; second, create your own.
Our SaaS (Software as a Service) assessment series is an example of a Newtonian approach to business analytics and industry research. In it, we leveraged our knowledge of other industries, became customers ourselves of several SaaS platforms, and learned to understand the dynamics of the customer-vendor relationship, all in an effort to gather previous knowledge and create actionable insights for the study.
When we started the study two years ago, there weren’t many prominent or profitable SaaS companies. To borrow from statistics– the sample was small and the data scattered. Not knowing where to begin, we naturally looked to conventional software companies for inspiration. After all, the first S in SaaS stands for “Software,” and many of these companies were considering developing their own SaaS offerings.
It didn’t take long to realize the error of our strategy. Whereas the average software company spends 26% of its revenue on sales, the average expense-to-revenue ratio for SaaS is closer to 40%-50%. Furthermore, we went on to calculate that the similarity in cost allocation patterns between SaaS and software companies is less than 30%. With such a wide gap between the two, conventional software clearly made a poor benchmark dataset for SaaS.
Lo and behold, we found a much more reliable comparison group in telecom and data services companies. With sales cost allocation patterns resembling SaaS’s to the tune of 60%, we had as close a match as we could get. One key difference between the two industries, however, is that most telecom/data services companies cannot replicate the stellar growth enjoyed by SaaS companies. So what drives that SaaS revenue? We gained insight into this question from our knowledge about recurring revenue and customer support in service-related industries. In layman’s terms, periodical cash outflows serve as constant reminders to executives of the need for ROI; and when one has an urge to act, service firms provide support resources to help make it happen. These observations, in turn, helped us design targeted questions around pay frequency and customer support, which led to our conclusion that successful SaaS companies are able to leverage customer service for longer average contractual commitments. In fact, leveraging our previous experience with telecom companies, we could mathematically gauge the health of a SaaS company simply by looking at their price level and mix of customers by payment frequency. Now that’s standing on the shoulders of giants!
Our next round of SaaS assessment is currently under way, and we expect to discover more powerful insights into the typical SaaS coverage model. So stay tuned.
If you are a SaaS sales leader seeking actionable insights to inform your sales strategy, you should participate in our 2012 SaaS Benchmarking Assessment.
Contact Alexander Group’s benchmarking practice.
Originally published by: Ian Zhao