8 tips to spark customer loyalty using data

Below are eight tips that will help organizations focus on sparking lasting customer loyalty.

1. Build a solid data foundation and experimentation framework

Creating connected experiences requires a deep understanding of both customer needs and data. Organizations that get this right see positive results. While capturing and rewarding customer behavior in the moment is important, businesses also need to prove to their customers the value of long-term loyalty.   

By establishing a strong data foundation, and then building an experimentation framework on top of it, retailers can actively test different hypotheses concurrently; this test-and-learn approach enables businesses to pivot rapidly. And speed to pivot means speed to revenue. 

2. Use predictive behavior metrics to pivot and personalize

Our own research finds  many consumers aren’t all that loyal to the loyalty programs they have joined:  

• 93% of consumers have active loyalty program memberships, yet only 33% are happy with their current programs and 36% feel the value they receive doesn’t reflect the worth of their personal data. 

• Customers are typically enrolled in up to 14 different membership and loyalty programs with as many brands, but they’re actively leveraging only six. And within those six programs, purchasing behavior tends to be driven by price. 

  That behavior causes brand longevity to suffer, so retailers have to use predictive behavior metrics to connect with those loyal customers by catering to their specific, immediate needs through personalization.

3. Deeply understand your customers and their needs

When retailers design and create for everyone, they’re designing and creating for no one. Behavioral statistics show that 64% of shoppers are men and 72% of online shoppers are women. Retailers must make sure they cater to the persona their brand is tailored for. What’s more, retailers must also ensure that data is stored securely, used ethically, and harnessed thoughtfully to link in-store and online experiences.   

Data is going to help retailers create transparency and help consumers understand why they're being shown certain offers, why they're being shown certain data and how that data is being used.

4. Level up customer service by using data and AI

Data from customer service interactions, such as chat logs and call transcripts, provide insights into common customer concerns. Collecting this data, using AI to learn from it, and starting to address those needs — perhaps through a bot — can help retailers improve customer support processes and address recurring issues promptly.

When customers have a good service experience, 89% of them are more inclined to buy from the same company again.

5. Getting personal is good for both customers and the business

See what happens when data is used to deliver highly personalized experiences.  

Nate buys a pair of black gloves online, but when he receives his order, they’re the wrong size.

When he calls customer service, two things could happen:

“Hi Nate. Are you calling about your recent purchase of black gloves?"

Or:

"Hi, how can I help you today?"

The first response is so personalized it creates a wow moment for Nate. He can immediately see the connectivity of his online purchase and his offline conversation with the customer service rep — and he can skip having to provide his order number and other details.

Hyper-personalization dramatically changes the customer’s experience for the better, and it makes it easier for the customer service rep to interact more positively and intentionally.

6. Inject a human touch into data-driven customer interactions

When people think about data, they tend to think about automation, artificial intelligence and other non-human elements. Yet retailers can truly excel in customer service by including an emotional intelligence aspect.

If a consumer makes a purchase and receives the wrong item, but it’s easy to exchange or return it, they will more likely remember the ease of the experience than dwell on receiving the wrong item — especially if the experience includes a human touch. 

Difficult and impersonal interactions will only drive consumers away. So, look for opportunities to build a human element into customer experiences.

7. Power all experiences through a single source with MACH

Having fewer touches for a consumer to interact with a brand is very important, and MACH (microservices, API-first, cloud-native SaaS, headless) technology can become a vehicle for reducing the amount of stress for the customer. 

Take something as simple as updating holiday hours. The information is updated in one place, and MACH technology moves that content through all of the retailer’s different digital experiences. It's better for the user and improves the efficiency of internal teams.

8. Make the move from monolith to headless

Global enterprises tend to have multiple digital properties, such as numerous websites for different countries, each in a unique language.

The challenge is bringing all of those digital properties together into one component library that will allow them to deliver a consistent experience, no matter where it’s taking place.

While a lift-and-shift impacts customer service (because the company won’t always have a fully functioning site), MACH is a step-by-step approach to transformation. An experienced MACH partner will perform optimizations to ensure there’s business value in the data once it has landed in the company’s cloud environment.