ROUVY identifies significant microconversions through High-Value Modelling

The Challenge

ROUVY is an indoor cycling software company that is used by professional and hobby cyclist. The main goal of their performance team is to acquire new users and their main challenge is to understand user behavior before trial. For this purposes ROUVY uses microconversions without statistic information about significance of microconversions on the main conversions. This could cause ineffective Google Ads budget allocation to the wrong microconversions.

The Approach

ROUVY uses BigQuery as a data warehouse with all information about users and website and app data. To evaluate significance of each microconversions ROUVY, in cooperation with Optimics, use High-Value Modelling to evaluate significance of each conversion.

The solution is based on linear regression that give ROUVY information about microconversions that significantly influence number of main conversion.

The whole solution uses Collab as a notebook to run all of the preparation and computation phases.

The Results

ROUVY uses 12 microconversions to motivate and stimulate users to accomplish main conversion. Outcome of High-Value Modelling shows us that only 2 of them have significant impact on main conversion.

This information allows ROUVY to properly allocate Google Ads budget during next indoor cycling season.

“We started with this project to deeply understand what microconversions we should use to acquire new users. Outcome of this project we will use in upcoming season to properly allocate our Google Ads budget.”

–Barbora Petříková, Performance Director, ROUVY

Primary Marketing Objective

• Grow number of main conversion

Featured Product Area

• High-Value Modelling (Linear regression)

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