Discover Customer Personas, Don’t Build Them
Netflix’s celebrated “recommendation engine” understandably gets considerable attention. Yet what's little known is that Netflix appeals to viewers not just by suggesting titles, but by showing each subscriber different cover art of the same title that are most likely to appeal to them.
With a score of different covers emphasizing one aspect of a movie over another, “we don't have one product, but over 100 million different products,” said a machine learning manager on the Netflix Tech Blog.
Netflix’s use of sophisticated algorithms and large data sets to create distinct subscriber personas is even more important in retail, as consumers increasingly look for brands that appeal more to their personal values and goals. To build loyalty, retailers need customer personas that reflect their customers on a more granular level and relate to their personal goals.
Many retailers rely on qualitative methods to create personas through focus groups and research. Yet these are limited for personalization since they don't help in knowing individual customers, their goals and intent.
Fortunately, there are now ways to extend such qualitative personas with quantitative methods that use machine learning to relate to the specific beliefs and needs of individual customers.
Advanced artificial intelligence can now blend behavioral and psychographic insights along with purchasing history, spending habits, in-store shopping activity, social media, and real-world interactions via smartphones and other Internet of Things (IoT) devices. When combined, it’s now possible to discover sophisticated personas that can help retailers meet individual customer needs as they arise. As the CTO of a leading retailer once said, “The customer’s intent right now is the pinnacle of personalization.”
Hidden in data, discovered personas offer exciting new ways for retailers to narrow in on customer likes and proclivities, and design personalized campaigns and shopping journeys to suit them.
It’s a task best done through machine learning, as it would be impossible for humans to sort through relevant data, discover constantly shifting shopping patterns, and then test their reliability and validity. So even when retailers start with qualitative notions of a persona, they can extend them through quantitative means by analyzing information to discover winning customer personas.
Discovering personas in data invites tantalizing possibilities to move closer to the Netflix model of bespoke customer experiences. Campaigns can be created for individual segments that target customers based on time of year, a particular holiday, as well as demographics.
Customer engagement can be persona-based. Just as one Netflix customer will see a different version of cover art than another, so too can one retail customer interested in a product see a different offer than another. Offers can be more contextualized. If a retailer knows a particular customer in a sporting goods store looking for running shoes actually runs marathons, other products and services — or experiences — could be offered during that person’s in-store or web visit that would appeal to them.
Once discovered personas influence sales, a retailer’s job is not over. As individual needs, desires and market conditions alter, personas should not remain static. Personas should be dynamic, shifting with societal conditions and be flexible enough to be updated on the fly in response to the latest internet meme.
Over time, persona discovery may become so sophisticated that one persona defines a specific person. Pinpoint marketing engagement would zero in on exactly what a particular consumer wants at the precise time in the customer journey.
But for now, better personas through discovery can recall that familiar feeling from the pre-digital age, when we trusted local merchants because they knew us and what we liked. Doing so will create a tighter bond between a retailer and its customers.
Suman Mahalanabis is director of product management, digital software and solutions group at Tata Consultancy Services, an IT services, consulting and business solutions organization that has been partnering with the world’s largest businesses in their transformation journeys for the last 50 years.
Suman Mahalanabis is Director of Product Management, Digital Software & Solutions Group at Tata Consultancy Services, an IT services, consulting and business solutions organisation that has been partnering with the world’s largest businesses in their transformation journeys for the last 50 years.