JD.com and Alibaba create indexes to identify Chinese shoppers’ spending trends, which help retailers gain insight.
Wondering the types of products I'm interested in? Just ask me!
Lately I’ve been seeing the resurgence of a trend that emerged a few years ago but then fell by the wayside: Offering consumers a list of personas to choose from when shopping an e-commerce site.
It’s an interesting marketing tactic that might help take some of the guesswork out of personalization. It also can give a shopper a sense of ownership of her e-commerce experience—enabling her to get involved and tell a retailer the types of items, cross-sells and up-sells she actually might be interested in purchasing.
Take Organize.com’s site. In its She hub, shoppers can choose from a list of female personas: The Career Girl offers wall calendars and planners; The Mom, a babysitter checklist; and Girl’s Night Out, wine glasses and fun party games.
Neiman Marcus uses personas with its StyleRadar feature. Updated weekly, StyleRadar offers a dozen or so types of people, personas in essence, that shoppers can subscribe to and then shop from, comment on and receive e-mail updates from. For example, shoppers can choose Indie Chic as well as a city, such as Chicago or Dallas, as a persona.
Personalization vendors and web site operators have used a behind-the-scenes version of this tactic for years, choosing personas on behalf of customers based on their web browsing or shopping behavior. Some build a profile for customers based on their actions as individuals on an e-commerce site. Others create profiles based on the activity of all shoppers, then base suggestions on the profile the shopper seems to fit into given her current behavior.
But why not ask shoppers to define themselves? Personas seem to be a straightforward way of presenting higher-converting, more relevant recommendations and to get shoppers involved.
I presume many of you reading this are thinking that it is one thing to gather data from individuals’ personas but that acting on that data adds a whole other set of complexities. I realize it may take work to centralize the data and create a way to make it useful. But, if it is going to give you extremely accurate (what can be more accurate than a shopper telling you what she is interested in?) information about what a shopper wants to buy, isn’t the result with the effort?
A travel site's auto personalization system may see a visitor is looking at sunny beach destinations and show them a slew of tropical islands, but if a consumer can choose a Honeymooners or Just Married persona, the site can offer resorts with Honeymoon suites, special extras and discounts for couples and even upsell with activites for newlyweds. Another site might recognize a consumer is looking at wine glasses and show her martini glasses and other types of stemware. But if that shopper chooses the Girl’s Night Out persona, it would know to market fun table settings and party platters as well.
After all, there’s a lot more to a Girl’s Night Out than wine glasses—and all the required gear could amount to many sales for e-retailers.