Customer Data & Analytics Blog

Data and Customer Loyalty: Part 1

Ed Wolf | 1 minute read

bridging_the_gap

At the recent Loyalty Expo in Orlando, hundreds of brands and practitioners from various industries came together to discuss best practices and new strategies for increasing the loyalty and engagement of customers. One common thread in the keynotes and sessions was the importance of data to truly understand the customer, and therefore understand how to keep the customer loyal to the brand.

In 2018, data is king. Brands are inundated with it — data from sales channels, digital platforms, call centers, CRM systems, In-store POS, social media, even devices (the “internet of things”) and of course loyalty and reward programs. This data has never been more valuable. But are companies using it correctly? Is this tidal wave of data enabling the insight needed to create valuable, personalized experiences for customers and ultimately promote deeper engagement?

The Data Gap

When it comes to loyalty programs and marketing, generally the answer is too often “no.” A common theme at the Loyalty Expo was that, while marketers recognize the benefit of collecting customer data from their CRM or loyalty, most lack the capacity to interpret and act upon it. Another top challenge mentioned by marketers was personalizing offers, content, and experiences based on behavior — in other words, based on data. There is a wide gap between the data collected and the data used to personalize customer interactions.

This disconnect between what marketers can learn about their customers and the expertise, capability and resources to make that data actionable is a costly one. Competition for customer dollars and attention is fierce, and brands must consistently market to their customers intelligently to keep them engaged and loyal. A customer that leaves a brand is very difficult to win back. But this gap can be bridged by taking the right approach to integrating both data and loyalty.

This is part 1 of 3 in the Data and Customer Loyalty series. Stay tuned for Section 2 on challenges marketers can face when they turn to data for guidance, coming next week.

If you liked this post, check out our other blog post on fixing defunct B2B data analytics with AI.

Topics: Customer Intelligence