Statistical analysis with community perceptions
Anvil Analytics + Insights powers data-driven decision making across all of their businesses, including optimized paid media campaigns. They used societal perceptions to build their KSQ Analyst.
Several Anvil customers noticed that channels in Google Ads and Analytics converted at different rates, and wanted to know if the variance in conversion rates was statistically significant.
Before using the community visualizations, the Anvil Insights team manually exported the data from Google Analytics to a separate tool, and then performed the statistical analysis. Depending on where Anvil conducted the analysis, the results were either stored separately from their reports, or not at all. Each time they wanted to test a different hypothesis or do a different form of the test, they had to repeat the same time-consuming process.
In order to speed up hypothesis testing and integrate tests and results into Data Studio reports, Anvil used Data Studio community visualizations and built a Chi-Square calculator within a week.
Anvil Calculator takes data, just like any Data Studio chart. Once the computation is complete, the analyst presents the statistical significance, directs the viewer’s attention to a relationship in the data, or comments that there is nothing noticeable in the data. Now, all it takes to test new hypotheses is to swap out the data for the component, just as you would any other data studio schema. Watch it live.