The power of analytics

Two web services with very different target audiences, Slideshare and Square, have decided to offer analytics to their users. Slideshare allows users to share presentations, presumably to tell the world that the uploader is an expert in whatever subject; Square is a mobile payments service that allows retailers to extract information from the application.

Using analytics can boost users’ loyalty: simply hand them a resume of their use of a particular application. In the case of Slideshare, we’re not just talking about the number of people that have accessed their presentations, but also details such as their origin, the division between access via search engines or links, as well as the pages the presentation has been used on, along with other data that can provide users with a lot of information about how their material is being used.

LinkedIn, which owns Slideshare, knows about the value of analytics: for some time now it has been sending messages to its users that include information about how many people have accessed your profile; and if you want to know more, sign up to the premium service. LinkedIn’s analytics are a key factor in persuading its users to sign up for a pay service to improve their chances of finding work. Slideshare’s analytics were, until now, only available to subscribers.

In the case of Square, we are talking about retail outlets and vendors of all types that have decided to replace their POS with an app consisting of a small reader with a magnetic band (Square has recently overhauled the service to allow chip cards, which are widely used around the world, but are still relatively unusual in the United States), and that from now on can be used to access information about what products have been sold via it, at what times, seasonal trends, customer profiles, etc., all of which is very useful for small establishments that until now would have found this level of analysis very hard to manage.

The reality is that analytics are an increasingly important way of winning customer loyalty and perceptions of value associated with the service. This is a relatively simply thing to offer, and relatively simple to use, allowing clients to decide on what level of analysis they wish to apply or that they feel able to handle, and then set about making sense of any trends they might see.

Once they are familiar with the dynamics of their business (which they may already have been, and have seen their conclusions confirmed by the analysis), users then become “slaves” to their data, and are constantly referring to benchmarks and working to maintain those levels. Once users have become accustomed to using an analytic tool, they rarely change, especially as this will likely mean losing all information acquired up to now.

Analytics are a relatively simple way of offering a premium service to paying users, as well as earning their loyalty by providing them with something that when all is said and done, we obtain in a perfectly natural way by processing data activity in our application. We can expect to see similar offers in other areas.

(En español, aquí)