Are you the same consumer you were in January 2020? Have your shopping patterns changed? Do you make the same number of trips to the same stores and buy the same items in the same amounts? Do you shop online exactly as much as you did before the COVID-19 pandemic? For nearly everyone the answer is a clear and resounding “No!” But the retailers you shop at probably don’t see this. While they understand it intuitively, they likely have a static view of customer personas based more on art than science.
Retailers should have been rethinking their approach to customer persona development already, to support retail of the future. But the global pandemic is a massive catalyst for change and provides a dramatic, real-time example of why dynamic and data-driven customer personas are essential. Rapid change and uncertainty have had significant impacts on buying behavior almost overnight. As we collectively adapt to a changed world, truly knowing your customer is now more important than ever.
While customer personas are used widely among retailers, they are often under-analyzed and narrowly focused. Many times, personas are based on managers’ understanding of shopper stereotypes or qualitative insights from a handful of focus groups. Other times, customer personas might be pieced together from existing sources across the organization, which may not be accurate or meaningful.
Many organizations do take a more analytical approach to persona development based on quantitative surveys, but these often fail to connect back to actionable data owned by the retailer. Moreover, even approaches focused on actionable data—like a recency/frequency approach – are missing an understanding of underlying needs, which is critical to discovering a customer’s core intent and engaging them in authentic ways.
Crafting a Customer Persona
Personas not only evolve as external circumstances shift, but individual customers can also represent different personas at different points in time. Developing personas in a way that enables retailers to reorient their business requires a deep understanding of customer behavior using an analytical approach that augments existing data and insights. It also requires ongoing analysis that captures the dynamic nature of personas to ensure that retailers accurately understand their customers even as needs and preferences change.
A customer persona makeover is about more than just how personas are derived; it’s also about how personas are used. Personas miss the point entirely when they are narrowly focused on identifying audiences for marketing messages. Persona use needs to move beyond the campaign team. An effective customer persona represents customers with a similar underlying need for that moment, which might vary based on not only who the customer is, but also on the context of their shopping trip and where they are in the customer journey. When retailers understand personas well, they deliver not just marketing messages or offers, but an entire reorientation of the business toward the core intent of purchase, including product assortment, pricing, services, in-store experiences, and online interactions.
To understand the promise of this approach, consider the grocery segment, where most consumers use multiple stores to fill their grocery needs. Imagine a consumer—Kelly—who is health- and sustainability-conscious. She does her everyday food shopping at a natural food chain, where she prefers a curated assortment so she can explore what meets her core needs. Kelly enjoys discovering new products that match her farm-to-kitchen lifestyle and wants to interact with store associates that can provide more information on product sustainability.
However, Kelly might shop a bulk discount chain for stock-up trips on staples. In these trips, she appreciates convenience and value so things like shopping lists, basket-driven discounts, buy-online-pickup-in-store, and cashier-less checkout are appealing. Understanding Kelly’s persona gives each grocer a view of the core intent behind her trips, which enables them to develop unique experiences, products, and processes that create value for Kelly in very different ways.
Or consider an athletic footwear retailer who may have many shoppers for many different activities. While many may be casual purchasers of sneakers, without a true understanding of personas, the retailer might miss meaningful opportunities to engage its customers. For instance, at first glance, Shelia — a teenager who buys a pair of basketball shoes online — may be seen as a stand-alone transaction. However, through data-driven insights, the retailer could discover that Shelia’s transactions moved from in-store to online even after the store reopened following the shutdown, alerting the retailer that her behavior has changed. In addition, the use of a discount code from the local basketball team’s website promotion can prompt customized online offers for the local team’s branded gear.
The same retailer could also miss an opportunity when a man in his early 20s — Ken — purchases a pair of Adidas indoor-soccer shoes. While many next-best offers may recommend shin guards and socks, through the scanning of a coupon from the back of a Liverpool match ticket, the retailer can discover that this is a lifestyle purchase and recommend a Mohamad Salah shirt, matching shorts, and a discount to the next match.
In these examples, retailers are leveraging AI-driven solutions to automatically look across all customer data sources to discover and reveal insights about their most highly differentiated digital personas.
Today, retailer understanding of customers is point-of-sale driven, but that must change to support customer-driven retail of the future. Retailers should look for a customer insights solution to help them shift to a point-of-context-driven understanding that is dynamic and rooted in robust analytics. The right analytics solution can not only track rapidly changing shifts in customer behavior but also discover the core intent of consumer purchases, which retailers can then use to reorient products, services, and experiences.