Clutch emphasizes personalization in customer loyalty

Today’s loyalty programs go beyond a monetary reward and strive to create an emotional connection with their customer base. However, to develop a lasting customer relationship, data – especially good data – is essential.

Poor data management can not only impact customer experience, but also operations. The ability to centralize information in a single view of the customer allows the business to begin implementing loyalty rewards rules.

“We want our platform to support a self-service capability,” says Joe Pino, vice president of strategy and solutions, for Clutch. “The ability for business users to create a great experience for their customers without having to engage with technology product teams is critical.”

Personalization in customer loyalty takes center stage
Personalization of customer loyalty programs is at the heart of today’s market, and the ability to impact customer loyalty is paramount for the people who drive and manage these customer loyalty programs.
“Personalization isn’t just about putting someone’s name on an email,” says Pino. “It’s not just about remembering their favorite color, but applying it to every engagement you have with that client.”

With all the data available, brands should drive personalization practices. Consumers are foregoing more personalized data in hopes that the brand will use this information to improve the customer’s buying and shopping experience.

Pino explains that the data tracked by Clutch is analyzed using rules-based logic. When to send the welcome email, when to send the thank you, and which product to promote are all examples of how machine learning uses collected data.

According to Pino, “Clutch systems are in place to make the marketer’s life easier while simultaneously optimizing the customer experience.”

Regardless of how the customer engages, whether through email only or fully involved in the loyalty program, personalization must be conducted on each of the platforms on which they interact. Questions can be answered from when to communicate to customs to what to communicate and even when not to communicate with them. Relationship building is first and foremost.

Pino insists, “Even your best customer doesn’t shop every day, so why are you trying to get them to buy every day?”

AI and Machine Learning Power Loyalty Programs
While many companies have some form of customer loyalty program or strategy, most are in the early or middle stages of developing personalization with their customers. “Everyone knows he should,” Pino says. “But even those who do it well have opportunities to grow across all channels. Personalization is more than just an offer, more than just an email. It needs to be at every touchpoint. Whether it’s as simple as a transaction notification or a receipt they receive after a purchase. »

While marketers know there is a need for personalization, choosing the right technology to implement this strategy is a crucial starting point. A popular technology playing a big role in personalization is artificial intelligence (AI) and machine learning.

According to Pino, machine learning and AI are useful for developing rule-based logic. We are moving away from standard one-size-fits-all communications. Instead of a general email to all customers after 90 days, machine learning can help create highly targeted forms of communication for the best outcome.
Pino adds: “The models are self-learning in the product. Machines start learning as soon as we put data into the product. »

AI and machine learning are also being used to improve personalization efforts and have a measurable impact on customer loyalty. At Clutch, they use machine learning around lifecycle management to measure at-risk customers.

Pino explains, “You don’t always email a customer after 90 days, hey we missed you. Our risk indicator is personalized, so one person may be at risk after day 21 and another client is at risk on day 75. It becomes truly personalized, so the tactics you engage in with the client are also.

Tracking customer churn has a similar benefit. Machine learning can measure inactive customers and inform the brand when it’s best to drop communications with that customer. There is no need to waste effort where it has no impact.

Now is the time to link segmentation, personalization and personalization to customer retention strategies.
Pino emphasizes the importance of touching all touchpoints. Knowing where the customer is in their journey, when they do and do not buy, what they buy and what they do not buy, is essential to then link this information to other experiences.

“If you don’t segment, you miss an opportunity,” says Pino. “If you don’t understand your customer’s behavior, you’re not going to achieve the personalization and you’re not going to deliver on the promise that customers expect these days.”

Brands measure the success of personalization efforts
“Customer lifetime value is the number one metric you can track,” says Pino.

Additionally, with customer engagement being a priority, it’s important for brands to look at churn rates or if customers are opting out of communications. One of the key KPIs to track is lifetime spend, as well as the increase or decrease in overall customer value at each touchpoint.

Personalization can start simple. There is always room to grow.
Setting the right goals is one of the biggest challenges of loyalty personalization. A business may have all the right tools, but for a true loyalty strategy, it needs a plan and the right technology in place to execute that plan.

Pino insists on the importance of just starting. “Get a plan and a vision of where you want to go. Start somewhere and you can always grow. Personalization is big business that can start simple and grow, especially with the addition of artificial intelligence and machine learning. »

To learn more about Pino’s and Clutch perspectives, watch the video interview here.

Joseph P. Harris