AUTONOMOUS BID MANAGEMENT SYSTEM
THE CHALLENGEOur client, a US-based ecommerce player, was facing a squeeze on profitability, given rising cost of acquisition through digital marketing on one hand, and having to drop prices due to competitive pressures on the other hand.
OUR APPROACHTypically, digital marketing spend is evaluated by looking at profitability per transaction. Our approach was to not only look at profitability but also use customer lifetime value (CLV) as the basis of evaluating profits and determining the cost of acquisition.
THE METHODOLOGYOur data scientist examined the cost of acquisition through the lens of Customer Life Time Value (CLV)
- Customer transactional behavior analyzed to segment customers.
- Customer segmentation and historical transaction data used to build a model to predict the expected CLV of new acquisitions.
- Expected CLV correlated with digital marketing ads.
Rules Engine was deployed to include the above parameters and autonomously change bids within digital marketing channels.
The final algorithm also tracked the effect of changes on digital marketing performance to continuously improve rules for bidding.