So many companies, particularly in information technology, have moved to a subscription model in large part because the recurring revenue model is so attractive both from a cash flow perspective, in part from a business valuation perspective, and, most importantly, it is what Wall Street and Venture Capitalists are valuing most these days. The downside of the subscription model is that the customers have to be using the system and seeing on going value from the product or service or they will opt out of the renewal and that much of the cash flow from a sale are deferred to later years during the subscription renewal process. With the subscription model, the emphasis is on making sure your existing customers renew for next year and again and again down the road. This is a new and different sales process that requires an organization that goes beyond the hunting organizations of the past.
Traditionally, Software sales organizations are focused on getting the deal, getting the signed contract, closing the new customer. If something like a software product sat on the shelf and was never used (so called “shelf-ware” in the software business), it was of new concern because the vast majority of the revenue was in the sale. There was only a small amount of revenue from an annual service contract. If the customer didn’t use the software, they might drop the service contract but, in reality, that didn’t happen that often and it certainly didn’t happen for a few years because they still believed they would use the software product “as soon as they get the resources available” which was never a high enough priority.
This issue of shelf-ware became a bigger and bigger issue with CIOs and CFOs just as financial markets were pushing software and other companies to adopt subscription models to provide more regular cash flows. For VCs, the renewal rates became the best predictor of product quality and true product market fit. High quality products that people use and want to keep using is a very strong indication of a winner that is worthy of investment. The implication for this is that there is better alignment between the software company and its customers. Software purchased (signed up for) has to be used and their customer needs to be satisfied with it or they just won’t renew. Since software companies are, essentially, not making any money on the software initials sale after the high costs of customer acquisition (marketing, sales support, commissions, etc.) but are only rewarded if the customer renews year after year they have a big vested interest in the software getting installed successfully, getting rolled out and used with the customers being satisfied such that they don’t look for another solution. Finally, it also gives incentive for the software company to continue the development of the package enhancing the software value over time so they can defend their revenue stream against new entrants.
The challenge for management is not just looking at things like customer satisfaction and Net Promoter Score surveys how to make sure products are being used, it is about tools for being able to monitor the product usage, proactive intervention when usage patterns do not appear to match expectations and identifying and adding new use cases for the product or service to address.
How is this achieved? We have worked with a number of clients on this problem lately. How we addressed it was that we have created metrics represented by graphs and reports and triggers that can look at these patterns of product usage and support tickets. For example, one client with a SaaS model had a good mathematical model on how users would use storage over time. As a totally made up example, if you offered a CRM package, you could imagine how that for every paid user, there would be .8 logins per day, the addition of 15 leads, 1 opportunity conversion, etc. At the most basic level, if that usage wasn’t achieved within a certain confidence level, there might be cause for alarm. Similarly, with help desk tickets too many is bad but then again too few is bad too. Too few might mean that they aren’t pushing the limits of the system to get the greatest benefit from it. Too many tickets (and too many that are resolved as being feature requests rather than true bugs) might mean that they are pushing up against the limits of the system or dissatisfied with the quality or available training or ease of use. All this data is fed into custom tables/custom modules within the CRM.
With these metrics of customer usage, we also looked at customer touch points in how much contact the client’s team had with the customer and at what level. This goes beyond the ideas of simply sending customer satisfaction surveys but real contacts with key people at different levels in the organization. These calls (who in the client organization that makes them and to whom in their client’s organization they are made to) are drive off a number of things including a traditional ABC analysis looking at the most significant customers, as well as, the usage metrics and help desk ticket data. For example, if it is a small account and they are clearly getting a lot of use from the system the company would determine that they are at a low probability and low financial downside risk of being lost. That kind of customer can get “less love” than a Fortune 500 enterprise that represents a large opportunity for expansion of use that might not be using the system to its fullest. That kind of client is clearly worth a lot “more love”. That type of client might require senior level face to face contact and and regularly scheduled meetings to ensure that the renewal is on track and to push for expansion of the system’s use.