In this case study we explain the approach used by Smart Pricer to determine Classictic customer’s willingness to pay by using A/B testing. The Case study shows the used approach in details and presents the final recommendations for Classictic based on A/B testing results.
Classictic had been working with a historically grown fee base of fixed fees per venue. The web portal operator asked Smart Pricer to optimize its fee structure to achieve a revenue increase. We approached the task with a historical data analysis of Classictic. Then we created three price groups to test the willingness to pay. At the end we applied the test results in optimal price points per venue and geolocation.
+100% price increase in certain geolocations
For some venues and certain geolocations, the demand is highly inelastic to price.
+100k€ annual revenue increase for 7 venues
Overall, we conducted 14 tests for 7 venues over 4 months
+200-250k€ total potential annual revenue incerase
Based on the achieved results, the total potential annual revenue increase for all venues is in the range of ~200-250 kEUR
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