The Data Analytics Blog

Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.

All Posts

How To Moneyball Your Customer Loyalty Strategy

June 6, 2016 at 2:17 PM

If you at all follow the on-goings of Hollywood, you’ve probably heard of a baseball movie starring Brad Pitt that came out a few years ago. Its name is Moneyball, and it relates an important lesson that is revolutionising customer engagement strategies.

The movie tells the true story of Billy Beane, general manager of baseball team the Oakland Athletics, who’s sick and tired of their lacklustre performance. After a key loss to the New York Yankees, he’s forced to rebuild the team on a limited budget. Instead of going with the obvious picks, he enlists the help of a Yale economics graduate to crunch the numbers and pick a team of statistically strong yet undervalued players. After a few losses, the data-driven approach is proven effective when the Athletics go on to have a 20 game winning streak – the longest in the history of the game.

You’re probably thinking this sounds like your typical feel-good American sports film, with little relevance to your business or professional life. But their approach to building a team based on data analytics can help you build a successful customer loyalty strategy.

Moneyballing your loyalty program means making data work for you

In Moneyball, Brad Pitt’s character uses an approach called sabermetrics to identify statistically strong, yet undervalued players. According to Bill James, baseball writer, statistician and creator of the term, sabermetrics can be summed up as “the search for objective knowledge about baseball.” Applying this to your customer loyalty strategy means searching for objective knowledge about your customers, that is, data based on actual customer behaviour statistics instead of a rough understanding of what marketers think their customers want.

By tapping into Big Data, you can identify key trends in customer behaviour that can help you create a highly personalised loyalty program that caters to each customer’s specific needs and desires. For instance, it’s possible to determine whether your customers would react better to a monetary incentive or one based on travel or subscription to a partner company’s service. And with the added boost of predictive analytics, you can give real-time rewards and discounts based on their purchase history and location.

Discovery Vitality and the FNB eBucks reward program are two great examples of data-driven loyalty programs here in SA.  Both use data to focus on behavioural customer understanding and are two of the country’s most successful loyalty programs. Discovery Vitality is one of the best and most well-known medical aid in the country, yet maintains 4% member growth rate, while eBucks has over 3 million active members who give high customer satisfaction scores. To gain a better behavioural understanding of their customers, these companies combine transactional data with lifestyle segmentation that prioritises needs and motivations over gender, age, or area of residence. Like Billy Beane, the people behind these loyalty programs know the importance of using data and statistics to drive a successful campaign.

Read: How Marketers user Machine Learning to Boost Loyalty

So if you’re assessing your loyalty program and only seeing a fraction of the results you hoped to see, just ask yourself one question – what would Brad Pitt do? He would “moneyball it” and focus on data and statistics to drive his customer loyalty strategy.

If you want to learn more about making the most of your data with predictive analytics, feel free to contact us.

New call-to-action

Image credit: Sony Pictures

Luke Turnbull
Luke Turnbull
Luke Turnbull was the Head of Customer and Lead Analytics at Principa, until the end of 2017, after which he returned to his home country of New Zealand. He worked in the financial services industry since 1995, during which time he worked in process, strategy and operational design across a range of organisations in New Zealand, the United Kingdom and South Africa. Luke had been with Principa for 9 years and led consulting engagements with Principa’s local retail clients across the customer lifecycle, with a particular focus on customer engagement and lead generation.

Latest Posts

Amazon Web Services Vs Microsoft Azure: Which Cloud Provider Should You Host Core Business Systems On?

Deciding on which cloud service to host your core business systems on can be a daunting task. Amazon Web Services (AWS) and Microsoft Azure are two of the biggest players around, while Google Cloud and IBM Cloud are also gaining market-share.

Truth Seeker: How To Avoid Logical Fallacies And Cognitive Biases In Data Science

We have released a new eBook titled Truth Seeker: a guide to avoiding logical fallacies and cognitive biases in data science.

Exploring The Evolution Of Data Science In Banking

We’re looking forward to attending this year’s Evolution of Data Science in Banking conference. The 2019 conference will be held on the 5th and 6th of June at the Indaba Hotel, Fourways, Johannesburg. The event will explore the use of data and analytical techniques to help financial services providers meet regulatory and reporting requirements. Also to be discussed is how running analytics at a product level can provide a more holistic view of customers across their portfolios.