As part of the digital shopping experience, AI-centered loyalty programmes have been enhancing customer stickiness. Such personalised loyalty programmes are linked with individual shopping patterns, and rewards or discounts can be customised and aligned with customer interests and what they value most. AI solutions are capable of analysing purchase history, browsing patterns and individual profiles to provide individualised offers and rewards.
Gamification Edge
To increase retention of customers and encourage repeat purchases, AI can gamify the loyalty programmes by encouraging referrals or social media participation and provide associated graded rewards. Companies are able to prevent churns and promote repeat purchases with the help of analytics and proactively send offers to customers that would lead to sales.
Hilton Honors uses AI to provide personalised offers, room upgrades and tailored experiences to its loyalty programme members. Customers of American Airlines, who are part of its loyalty programme, have been offered personalised promotions and dynamic offers over the years. The airline is now looking at ways to use AI in more granular ways. Domino’s Pizza offers discounts and rewards to its loyalty programme members using its AI-powered virtual assistant. Starbucks Rewards is able to use its AI tool to make personalised offers based on customer analytics.
Bigbasket and Flipkart use AI extensively to analyse purchasing patterns to offer personalised recommendations. They provide discounts and rewards through their loyalty programme to attract the attention of their consumers to spend more on their products. Swiggy, the food delivery app, monitors order history, frequency and value of orders to incentivise customers to place further orders. Oyo personalised the guest experience through its AI-driven loyalty programme. It offers attractive pricing based on the past preferences with the view to get repeat bookings.
While the AI-led loyalty programme can bring immense returns to the company, it is not easy to conceive and implement. The tech infrastructure and the data required to implement it may not be affordable by all companies. Customised offerings have also raised privacy as a matter of concern for consumers whose data are used to arrive at recommendations.
Therefore, a systematic and regular data collection and management is an essential first step. Loyalty programmes should be personalised and using predictive analytics, offers should be dynamic making them relevant for the individuals. Redemption of offers should be seamless whether online or offline; the user experience should be thoughtfully designed.
Ongoing evaluation of loyalty programmes with respect to key parameters that matters to the business is essential. This would include metrics such as retention rate, customer lifetime value, and offer redemption rate. Regular monitoring of these parameters would provide valuable insights on tweaking the loyalty programme from time to time in order to derive better results.
