A retailer approaches Axtria with a common problem – their existing Loyalty program is not yielding results in terms of customer usage. Only a small number of card-holders are swiping their membership cards and new sign-ups were limited.
Axtria’s team analyzed the problem from various angles and came up with a set of hypotheses:
- Data from various sources being used for targeting of campaigns may not be clean
- Segments used for targeting are no longer valid and have to be reconstructed
- Targeting algorithms need reconstruction to identify the right offers for the right customers
- The entire Loyalty Program point system needs to be re-designed
Two weeks later, all four hypotheses tested positive. The team then systematically went about solving for each of the above.
First, the data was cleansed and a new data mart was created with appropriate governance rules in place. Next, new customer segments were created, one based on RFM (recency, frequency and monetary value) and the other based on long-term buying behavior. After that, statistical response models using logistic regression were created to address CPG vendor concerns around disappointing campaign response rates. Finally, Axtria redesigned the existing Loyalty program by simplifying the point conversion system and tightening the spending rules for point accumulation. Strategies were designed to win back lapsed customers and the top percentile of valuable customers were identified and targeted with personalized offers to increase the retailer’s share of wallet.
Using Axtria’s newly designed system, our Retail client increased response rates for new campaigns, grew redemption rates from 0.3% to 8%, and increased comp store sales +2% VYA. We also trained our client’s internal team to cleanse the data, refresh the segments and run the models, ensuring a smooth transition.
Axtria also built a set of customized reports for the central headquarters of the retailer which helps them monitor their business on a day to day basis.