Analysing SaaS user behaviour

Behaviour analytics tools can play a crucial role in business planning, says Rajesh Ranjan

Understanding user behaviour in Software-as-a-Service (SaaS) applications helps software companies serve their customers better and price themselves competitively. The benefit of SaaS for the channel is the ability to offer alternatives, but where do these alternatives come from? Is it from the product management team, or is it from competitor features?

Google Analytics and other measurement tools that gather measurable data have changed the landscape. The engineering team now has access to rich data on how an application is being used, and this is changing the thought and validation processes.

Data has driven decisions for years, for various purposes. Today's technology helps us capture metrics on user behaviour, which the product management and engineering teams can use for analysis and to validate their success.

However, what we measure and when we measure it are not easy questions to answer. You might start with one area, and on analysing it you may discover there are other areas you must measure in order to understand user behaviour. This may also change how we measure the success of engineering teams as well.

This is not the motive, right? The motive here is to make sure your end user has a good experience – good enough to remain with you and to help you propagate your business.

So, how do you do this? You cannot do it from the outside; your application needs to learn and it should have features that allow you to analyse the user interaction, which features are used and when they are used.

Analytics, audit trails, application logs and user clicks are some of the means, but it varies from system to system – and what works for one may not work for others. For example, what works for a mobile application may not work for a web-based application and vice versa.

Different users will use different features, based on their licenses and needs. So the features and the administration of those features go into forming a specific configuration.

An application should allow the user to customise how he or she wants the feature to work, within given parameters. The application itself, or other supporting tools, will analyse the pattern of use and generate appropriate reports to help you analyse.

Data can be in the form of logs, events, or notifications that are custom-designed for easy analysis. Applications must ensure that the privacy of users is maintained and that the analysed data is not misused.

Another way to do this is to ask users for feedback on application features, and co-relate this to their usage pattern to check what is needed and when. Engaging users by getting feedback from them and creating a customer ecosystem has helped many SaaS solution providers.

You can engage your customers and finalise the product roadmap before the implementation begins, but this can create some nasty surprises as well. Users can be your product managers and sharpest critics at the same time.

User behaviour analysis will not only help shape the product road map, it also means that collected and measured user behaviour can play an active part in your planning and review.

After all, data doesn't lie. User behaviour, along with application monitoring, will help you better understand the datacentre, peak load and provisioning for the system if needed to manage the scale. It helps manage the load, predict the lean times, and also predict when it is time to make another sales call to the customer.

Rajesh Ranjan is programme director of engineering services at MindTree