In one of his blogs Avinash Kaushik makes a very important distinction between reporting and analysis. Reporting is a series of metrics and data points and analysis(typically) is the inferences and recommendations that are then made on that data. By definition most analytical tools lean heavily into reporting and this makes it very easy for them to crossover into data puke territory. At MineWhat we’ve included a few features that will help you avoid just this.
Viewing data in the right context is key to ensuring that you are always focussing on useful data. A spike in purchases on your store means little unless you know the story behind it, maybe there were a series of bulk purchases or the local league game caused a surge in traffic to your store. The event overlay feature on MineWhat lets you upload different events, for example a series of print ads you ran in your local daily. These events are then overlaid on a trendline so you can see how they affected your sales.
Human analysis on the data
The value of a good analyst is in the inferences they make on the data and the actions they recommend based on this. Avinash Kaushik sums this up well “Dashboards are not reports. Don’t data puke. Include insights. Include recommendations for actions. Include business impact.” On MineWhat users can add their comments and recommendations to the reports available on the app.
In eCommerce not all things are made equal, some categories might have a lot more products than others. As a result of this these categories will always appear at the top of most sales and traffic reports. Unless there’s some form of normalization on the data, you might end up not noticing interesting patterns like a smaller category having a higher conversion rate. In addition to normalization by conversion rate on MineWhat you can also normalize the data by the number of products in the group