Deriving the value of discounts, referrals, and loyalty through insights-led engagement

With easy access to information and multiple brand alternatives at their fingertips, the new generation of customers can easily shift their purchases from one brand to another. 

But studies show that 72% of customers are more likely to be loyal to a brand if they offer a personalized experience with additional rewards and benefits. 

The global loyalty management market is expected to surpass US$24 billion USD by the end of 2029, and there will be even more competition in the market than ever before. Unless your approach to customer engagement and loyalty is unique, survival will be tough. 

There is a pressing need to break through the clutter and connect with your customers in a way that gives value to them. This is why using insights-led engagement is essential.  

Data helps you understand your customers better. But knowing which insights to use is a foundational step to successful customer engagement.

Here are the three types of insights modern marketers need, to understand their customers holistically:

To understand your customers’ attributes, behaviors, and preferences. 

To understand what your customers’ journeys on your platform look like.

To understand how your customers respond to your campaigns and communication.

Once you know the insights you want to pull from, you must segment your customers based on the data you have about them.

Customer segmentation is critical for establishing which customers you need to engage with and how.

But since traditional segmentation methods are limited by incorrectly weighted factors and pre-existing biases, using more deeper ways to segment is a better approach. These include segmentation based on affinity, behavior, purchase path, and RFM segmentation.

RFM in particular accounts for the “Recency (R), Frequency (F), and Monetary (M) value” of each customer to generate valuable insights. Hence it is one of the best ways to understand where customers are in their purchase journey, their willingness to purchase, and eventually their CLV.

Customers who show similar behavior on R, F, and M scores and RFM aggregate scores, are grouped into the same RFM segments. 

Based on the customer segments, you can tailor your engagement strategies such as the following:

These customers have visited your website/app most recently, visit most often, and spend the highest. They promote your products and can be early adopters of your new launches. 

These customers have visited recently, visit often, and spend a large amount. They are highly responsive to your promotions. 

These customers have spent a significant amount on your website/app and have visited you many times.

These are recent customers who spent a good amount with your brand and have the chance of becoming your loyal customers. 

These customers have visited most recently, but do not visit often, and have not spent much.

These customers have average recency, frequency, and monetary scores but the potential to buy more, and more often. You need to convert them into loyal customers.

These customers have visited you the most recently, and also visit you often, but have not spent much. This indicates purchase hesitancy based on price and that they are looking for the best deals. 

These customers have spent a good amount with your brand but a long time ago and haven’t visited recently. You need to bring back these customers. 

These customers have below-average recency, frequency, and monetary scores, and are about to disappear. You need to reactivate them as soon as possible. 

These are customers whose last visit was a long time back and who have not spent much on your website/app.

These customers have the lowest recency, frequency, and monetary scores.

We’re in the digital age of engagement, and customers can navigate their own buyer journey like never before. To stay ahead of your competitors and ensure customer retention you need to slice and dice your data into insights and craft bespoke customer engagement strategies. 

Fortunately for you, an AI-based customer engagement platform like MoEngage can enable you to segment your data, derive insights, and truly personalise your approach to customer engagement. 

To know more about the current landscape of insights-led engagement, check out The State of Insights-led Engagement Report 2022 | Europe Edition.

Author Bio: Falguni is the Partner Content Manager for EU and NA at MoEngage. She is passionate about writing various types of content, from epigrams and micropoetry to long-form B2B thought leadership articles. Having spent her life living in different parts of the world, she is always fascinated with travelling, meeting new people, and learning about their cultures.