Tom Teylor
Which customer data do I no longer need?
This will be one of the most important questions retailers face. When it comes to personalization, demographic data like gender, age, income and even in some cases first name, last name or email address will fall by the wayside. In addition, as third-party cookies go away, so too will retailers’ reliance on cross-domain tracking.
Which customer data is now most relevant?
The biggest shift we see is toward behavioral data that gives retailers contextual clues about a customer’s visit as they enter and browse a store. This includes:
- First-party data: First-party cookies collected on retailers’ own websites are here to stay. In the possible absence of third-party data, we expect retailers to make larger investments in first-party data to improve site conversion and retention metrics.
- Zero-party data: This is explicit data customers share with retailers through surveys, quizzes, membership registration forms, etc. We’re personally big fans of questionnaires that ask consumers about their shopping preferences. Retailers can use their answers to create a guided shopping experience personalized to each consumer’s needs.
- Second-party data: This is data collected and owned directly by merchants and shared with other merchants. We expect to see an expansion of data cooperatives to help retailers make wise use of second-party data.
Winning the data diet game will mean creating richer customer experiences with the least amount of data. We recommend retailers look for vendors that create personalized shopping journeys with first- and zero-party data. Also look for ones who use “cold start” — a type of machine learning that describes how fast an algorithm can learn with little to no data. For transparency’s sake, we believe vendors will offer retailers the ability to explain why and how things are being personalized. That can include using language like, “You’re being shown this item because blue is your favorite color.”
In addition, as one data source might go away, look for new explicit data sources to take its place. One possibility: visual artificial intelligence that allows consumers to receive personalized outfit recommendations. This expands retailers’ opportunity to present cross-sells and upsells in a consumer-driven way.
One of the best examples we’ve seen of personalization on a data diet is from Princess Polly, an online fashion boutique. It used explicit zero-party data (a quiz asking about customers’ favorite styles and categories) and implicit first-party data (site browsing history) to create a highly personalized year-in-review landing page experience, complete with cross-sell and upsell opportunities and information about each customer’s loyalty tier status.
With more data privacy regulation on the horizon and companies like Apple making data privacy a part of their corporate strategy, the time is now to do more with less data. Retailers that get creative with their data diet will win the day.
