One of the key uses for portal analytics of course is reporting on who’s doing what in the portal.
As we all know these reports are used to calculate portal ROI, to determine the value of portal assets, or to correlate partner portal behavior to revenue generation performance. However, reporting is a static snapshot in time, providing a rear-view picture of what has happened.
Activated Analytics for On-Demand Engagement
In an Experience-As-A-Service (XaaS) platform such as Webinfinity’s, analytics drive on-demand activity and engagement. We all have a limited experience of this phenomenon in our personal lives when the next (hopefully relevant) action is presented as a result of something we have clicked or viewed. In a XaaS environment, all activity is driven by personalized intelligence. Real-time analytics help to drive a relevant flow of what the partner would want to see or experience based on what they are doing, or not doing. Activated analytics drive a highly relevant digital “conversation”.
Some example activated analytics scenarios:
- Analytics show that specific users aren’t subscribing to key collections of assets. An on-demand action might be to send a communication to the user regarding their knowledge of subscriptions. Or perhaps to auto-subscribe them to a topic they have been searching on frequently.
- We see that specific users have viewed an incentive, but haven’t yet registered a deal that takes advantage of that incentive payout. An on-demand action might be to send a communication about other partners having received X value in rebates from the incentive. Or to provide a simple “what’s possible to earn” calculation.
- After sending a partner communication, we of course would like to know which partners have viewed the communication and which have not. This analysis would activate different digital pathways, orchestrated differently depending on those who viewed, those who viewed and took action, and those who didn’t view. Each digital engagement pathway is relevant to the user on topic, as well as on task.
Can you imagine the above scenarios being driven by experience rules that are automatically activated by the analytics? That is the goal of an experience as a service environment.