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Gain Valuable Insights with Salesforce Wave and the Usage Metrics Pilot

Analytics Cloud

The usage metrics pilot announced by Salesforce in April of 2014 is a fire hose of data about the usage of the app in question. In our experience, the addition of Salesforce Wave to the mix greatly increases the utility of the data. The Wave analytics platform allows you to quickly analyze large datasets to glean incisive insights.

We decided to use our popular app, CalendarAnything, to test usage metrics and Wave. Usage metrics for CalendarAnything make for a large dataset, as two usage records are generated per salesforce instance per day. We must say that Wave lives up to the buzz and allows you to analyze multiple facets of this large dataset with ease. An earlier post by Gordon Arnold sheds light on how exactly our metrics were fed into our wave org.

When analyzing our CalendarAnything data, one aspect of the usage metrics we chose to look at was the version of CalendarAnything out customers were using. We knew that those using older versions of the product could benefit from the increased performance we have worked into recent versions of the app. Usage metrics even provides you with load times of specific pages; so you have a good idea of the performance benefit to be had if a specific customer updates. Our team takes great pride in providing a high level of service to our customers. Contacting customers to make sure that they are getting the most out of our products is part of that philosophy.

The graphs below, which were easy to create in Wave, allowed us to easily target ten customers who would best benefit from an upgrade. We could easily analyze load times and pin-point the exact pages that were heavily used by the customer.

Load times – Most Impacted Customers

Load times - Most Impacted Customers

 

Most visited pages by customer

Most visited pages by customer

On a cautionary note, with the multitude of visualizations available one can easily go down the path of analyzing a lot of metrics. Before spending time on any dataset and analysis its is worth assessing how pertinent, valid and actionable those insights will be. In our case, we had valid data to contact some of our existing customers with upgrades that would improve their experience. These customers are now more inclined to renew their licenses – a direct revenue impact thanks to Salesforce Wave and usage metrics.

 

 

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