Artificial Intelligence & Machine Learning Powered Loyalty Programs

With enterprises leveraging machine learning and artificial intelligence to drive better customer experience, loyalty programs are advancing every year.

AI & ML loyalty programs are enabling brands to utilize customer data effectively.

These programs are designed to understand customer purchase behavior through data. 70% of the customers agree that how a company treats them influences their purchase decision. 86% confirm that they will spend extra for a better customer experience. It signifies the importance of delivering an enhanced customer experience.

Let’s understand how AI-based loyalty programs are a win-win for brands and customers.

Why Do AI & ML Powered Loyalty Programs Work?

Businesses have been updating their enterprise loyalty programs with tech that helps them in achieving retention and revenue goals. They want to find a way where customers feel important and recognized. AI & ML add delight to the customer experience.

What makes AI & ML worth investing in is the ability to “act like humans.” From virtually acting like a customer care assistant to using customer data for segmenting, AI can do almost everything better.

Problem-solving, reasoning ability, and identifying customer patterns via AI help enterprises understand what customers exactly want.

Similarly, with machine learning, customer data becomes more meaningful and measurable. Customer data, algorithms, and insights from previous purchase behaviors improve the structure of loyalty programs.

Here are some more benefits of integrating your customer loyalty program with AI & ML

How AI & ML Benefits Customer Loyalty?

Businesses that focus on improving customer experience can increase earnings by 80%. Here are some of the ways brands can leverage artificial intelligence and machine learning to achieve true customer loyalty-

1. Chatbots for Better Customer Assistance

Better customer experience is what brands want to achieve with modern loyalty programs. Customer interaction and solving their problems through communication are among the reasons why some brands do better despite being expensive.

With chatbots facilitating conversations, managing customer relations gets easier.

While focusing on improving customer loyalty, chatbots are designed with pre-planned and personalized data that adds to customer satisfaction.

Chatbots can resolve 80% of customer problems within the first interaction. The chances of customer retention automatically increase with attending to customers on time.

Brands like The North Face have used virtual shopping assistants (Watson) to help customers find what they are looking for.

2. Predictive Insights With ML Algorithms Make Things Easy

Many enterprises use machine learning for predictive analysis based on the buyer’s purchase history and interests.

Brands can find customers who have been consistently buying and how they will behave in the future.

Questions like ‘When is a customer more likely to make a purchase?’ ‘Which customer is likely to return.?’ can be answered faster. Using historical and current data to understand future outcomes helps create better loyalty program models.

Walgreens Balance Reward uses personalization within its loyalty program to deliver suitable offers based on customers’ purchase records and create awareness of promotional events, reward status updates, and more.

3. AI into the VAP (Value, Attrition, and Potential)

Customer Segmentation is vital to understand an audience and break down different customer groups. VAP is an advanced statistical model for creating customer segments. Combining VAP with artificial intelligence makes the segmentation process easier.

Brands can easily measure how likely customers will stay or leave and whether the existing rewards have the potential to perform.

ML-based targeting algorithms segment loyalty members into actionable groups. It suggests strategies to maximize revenue with these customer segments. These benefits include free tier upgrades, bonus rewards, points top-up, and more.

4. AI is Great for Custom Recommendations

Implementing AI to get customer trends is not a recent discovery for brands. For example, Amazon and Netflix have used AI to get what customers look for and the recommendation engine predicts what individuals would like.

AI can quickly understand the data fetched by ML and boost personalized experience in loyalty programs with exactly what customers need. This data is used to provide product and service recommendations to the customers.

5. Deep Data Analytics for Successful Loyalty Programs

When it comes to customer loyalty programs, there is no ‘one-size-fits-all.’ The preferences of what buyers expect from loyalty programs keep changing.

“If a company registers 97% satisfied customers, 3% will still be free agents. They might like the product or services at the moment, but they keep looking for better alternatives.”

A great loyalty program should allow customers to enjoy loyalty benefits depending on their interests. The challenge is how enterprises harness the data to enhance customer experience and loyalty benefits.

This is when deep data analytics comes to the rescue. It helps in making a successful loyalty program.

From purchase association reports, purchase trends, and demand forecasting models to what customers want from similar loyalty programs, data analytics in loyalty programs makes things easy and offers custom recommendations based on real-time and historical data.

Final Words

AI & ML are useful for managing the loyalty programs’ benefits and updations. For example, a customer won’t always want a 20% discount on every occasion. Christmas is different from birthdays and wedding seasons, and so should be the rewards, especially in paid membership loyalty programs.

Customers’ expectations will keep changing, and to provide a better customer experience, companies need to adjust to the changing needs.

Hence, artificial intelligence and machine learning are utilized to keep the process seamless and focused on customers’ preferences. The better insights a brand gets, the more it impacts loyalty management.

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