When it comes to software as a service, like with any other service or product, there are a number of statistical sources and metrics which professionals are wont to observe closely during the service or product’s lifespan. The thing is, though, that there are some statistics which must be watched and some that are less important. It’s not really obvious in many cases which is which, so, understandably, often too many statistics or simply the wrong statistics are being factored when overall metrics are taken.
Common sense will not indicate the right answer to this – common sense tells us the world is flat. Only by consulting with UX professionals who work closely with the SaaS industry can we accurately determine what statistics truly matter the most.
An SaaS and UX professional will say that first, it depends on the model of SaaS being presented. With a “freemium” model, there is one outstanding statistic that is more important than any other, and that is the rate of conversion. With a freemium business model, users are granted either trial access to software, or are given a somewhat crippled lifetime free product, with the option to buy into a better model.
The rate of conversion in this case is the amount of users who upgrade to the paid platform when either the free trial ends, or of their own volition as the appeal of paid features lures them over.
With ad-powered models, the most important statistic to watch is going to be the ratio of ad clicks to user access of the software. While views generate steady revenue if the software has steady use, if the ads are not being clicked, advertisers may pull their ads in time. This probably means the ads are poorly targeting the demographic, and if this is the primary source of revenue, then this must be monitored closely.
When it comes to flat subscription models, the rates of conversion to higher tier accounts, as well as rate of kept customers are both important statistics to keep an eye on. If customers do not continually re-subscribe, or feel unmotivated to upgrade to costlier accounts, something is probably wrong somewhere. It may be that the benefits, like with freemium models, of more expensive accoutns are not enough to stimulate conversion. It may be that users find a free software that meets the needs of their existing paid account, and therefore it may be time to sweeten the pot for them, as it were.
Ultimately, though, with any type of SaaS model, two of the greatest statistics of global importance are referral rates, where users recommend your service or product to others, and the ratio of incremental overhead generated by customers.
With freemium, this overhead is even more crucial than with others, as paid users may be supporting multiple free users, which drives up the cost of service, causing a greater rift and lower conversion rate. For others, it is a matter of maintaining proper profitability margins while keeping prices overall realistic from the beginning. With ads, it’s also sensitive because ads are not as predictable as subscriptions, and therefore if overhead is high, there is a chance of random periods of loss rather than gain from the service to the company.
Out of all the statistics that can be measured, these provide the greatest window into any metaphysical glitches in the software and user experience, as well as the effectiveness of the business model and the meta-model any given company develops.
While other statistics have their moments of importance, these should always take precedence at any given time metrics are taken.