Woolworths-commissioned research suggested around one-third of supermarket loyalty members actively linked to points programs had never redeemed points; not for flights, holidays, coffee makers – nothing at all.
There are now more programs than ever and deciphering their value is often impossible, given varying redemption rates for the same points depending on how they are used. This has led to ‘points fatigue’ with many customers signed up to points programs confessing to not using them. Woolworth’s research found that for 68% of customers, money off their normal supermarket shopping was the preferred option, with only nine-per-cent preferring a points-based scheme.
Based on customer feedback, a rebranded program was designed to give customers money off their shopping, quickly and automatically.
Customers would earn Woolworths Dollars in the course of their regular shop, and once their balance reaches $10, that amount would be taken off their next shop.
When Woolworths decided to revitalise its customer loyalty program, Celina Farrell helped architect what the new program would look like, putting Woolworth’s customers first.
With Woolworths investing in Salesforce capability, the team were able to automate more personalised loyalty offers. Customers want choice and range is a key driver of the decision on where to shop. However, many are drowning in a sea of irrelevant choices.
“For years as marketers, we’ve been led to believe we were personalising our experience because we were sending communications to segments of customers that looked the same. But the truth is, it doesn’t matter whether your demographics look the same. Ultimately, (they) are still very different people.”
Director of loyalty and data at Woolworths
The new approach allowed a much more sophisticated understanding of the individual needs of Woolworth’s customers. Using one of the most advanced algorithms in the world, Woolworths send customers a weekly catalogue of hyper-personalised offers.
Woolworths, with the help of Quantium, created a personalisation engine to fuel the supermarket’s email marketing efforts. The team began with 20 trillion data records and put them through a Gradient Boosted Machine learning model, with the end goal being highly-targeted offers. In order to do this, the model crunched the data for every customer looking at the products they did and didn’t buy at every price point in history.
Scan rates have increased as more customers swipe their card at the checkout. There has also been a 16% increase in email open rates while opt-outs have gone down significantly. The number of members has also increased, while Net Promoter Scores are on the rise.
Working with the Woolworths Loyalty team (now WooliesX), Celina helped achieve two core objectives: growing the database of 10+ million customers and improving the value of customers within the program.