IBM Watson
Customer Loyalty Revisited with Advanced Personalization
September 19, 2018 | Written by: Brett Wachter
Categorized: IBM Watson
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Customer loyalty has become an ever more complex and nuanced discipline. Consumers might stick with a brand because of product quality and price breaks, but they also expect something more than just a transactional relationship. Knowing that companies collect their personal information, consumers want to see that data be the foundation of smart, personalized — bordering on emotional — experiences and connections. Offering a loyal customer an early-bird discount on a variety of sneakers no longer cuts it. Today, a company has to think about anticipating a customer’s excitement about the impending release of their favorite type of sneaker and delivering a compelling back story about its creation and design — that’s the kind of bond brands need to form.
It’s time to revisit customer loyalty. Traditional loyalty programs aren’t dead; they just need to reach a new level, especially if your brand wants to compete with transactional giants such as Amazon and Jet.com. Deep insights on customers not only inform personalized conversations and tailored content, but they also help you better understand your loyal shoppers so you can foster more beneficial relationships. They’ll embrace your brand — often publicly on social media — if you can demonstrate that you “connect” beneficially with them and can even anticipate their wants and needs.
Today, to sustain customer loyalty, retailers have to move beyond typical transactions in their digital channels and create new experiences that are remarkably different — and more compelling — than those of their competitors. Through tailored conversations and stories, brands can make a unique mark and cement themselves as the preferred retailer for particular transactions.
Recently, we worked with a major U.S. retailer that was trying to personalize the shopping experience it offered its young-adult customer base in 1,200 physical stores and many e-commerce channels. Due to geography and education, customer tastes varied widely. By reinventing its customer experience platform with IBM iX, the retailer now offers customized content that is specific to each location and thus appeals to the sensibilities of each customer niche — a level of personalization that is strengthening brand loyalty and increasing sales.
Artificial intelligence enables this level of personalization. A deeper, AI-driven approach allows retailers to gain insight on customers from the usual sources (think: demographic and geographic data), while behavioral data reveals how customers react to certain content. The nuanced feedback empowers retailers to either continue their successful outreach or study what went wrong and try an approach that resonates better with their most valued clients.
Excavating Customer Data
Going a step further, retailers can aggregate customer data from all of their channels and touchpoints to create a single data model that yields a broad and useful cross-section of information, which helps score and shape each customer relationship. The data reveals how often a customer buys, their need for quality products, price threshold, level of social interaction about your brand and other brands, as well as overall loyalty. The next technological plateau is analyzing that customer data in real time and reacting with personalized interactions that light a spark.
This melding of demographic, geographic, behavioral and other data forms a retailer’s customized insight models. These are quite insightful, but the process doesn’t end there. A retailer can learn even more from the data by running it through deeper cognitive analysis — often in collaboration with an experienced technology partner.
For example, IBM Watson analyzes the psychographic data of customers from a major automobile manufacturer to discern their personalities. This insight may well provide insight into the step they might take when their automotive lease expires. A customer with an open personality might accept information about new cars because he likes new things and wants to know all of his options. The highly conscientiousness customer typically wants only details about their financial relationship with the manufacturer, such as the cost of an extended lease or a new car.
We’re also working with a popular grocery store chain that’s reimagining its relationships with customers by combining its loyalty, marketing and commerce efforts into one platform. Despite having more than 3,000 stores, this grocer recognizes competition is still fierce. By digitally engaging consumers with responsive, personalized content that emphasizes the freshness of its food, for example, the grocer is forging mutually beneficial relationships, understanding what customers value most and using specialized content to optimize the relationship through a range of commerce channels.
Like the retailer, the grocer recognizes loyalty efforts must transcend transactions. These companies want to tell stories that make each customer feel as if the brand is talking directly to her or him. Both companies are using integrated engagement platforms that incorporate every aspect of their respective brands and connect e-commerce with physical stores. Coupled with high-level automation tools that can deliver individualized content at scale, brands have the technological foundation to consummate meaningful relationships with their customers.
And as with any strong relationship, the connection between a brand and its customers will build over time, deepening with each gratifying interaction so that retailers know exactly what consumers need and the best way to respond.
Learn more about how IBM transforms customer loyalty with AI.
Lead Account Partner, IBM iX
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