• by TJ Gentle , October 7, 2014

It’s been a while since something changed in the way we approach online retail.

The formula goes something like this:

Get as many people to the site as possible. Show them popular items. Serve up related products. Send them as many emails as they’ll put up with. Then show them more related products.

It’s a good formula. It’s effective. But something’s missing.

We live in a world that gets more highly personalized with each iteration … of every app … on all platforms. Our devices call us by our first names. So do the sites where we buy shoes, designer underwear, and baby formula. They show us items similar to the things we’ve looked at before.  

And that’s the problem. We’ve expected customers to find what they want on their own since the internet became shoppable. Web retailers consider their job done after they’ve served up “related products” and “popular items.” 

Compare that to the experience of going into a store, talking with an expert who really knows the products, and having her point you toward the most comfortable pair of shoes you’ve ever worn. Suddenly, “you might also like” doesn’t sound so personal.

If you’ve been given great advice, you know how rewarding it is. You feel a connection with the salesperson – like she actually knew you. Like she wanted you to get just what you were looking for. My guess is that you didn’t feel “sold to.” It’s not just a matter of convenience. It’s a desire to be served as though your satisfaction is that store’s highest priority.

Now is the right time for that kind of personalized service to make it to web retail. It should become the way we expect web retailers to treat us. It’s not based on customer behavior. 

Personalization, in this world of tech-savvy shoppers who’ve seen the wizard behind the curtain of web retail, is based on prescriptive analytics – not reactive analytics. You can’t prescribe personal choices for a customer by showing him popular products or the click paths other customers have followed.

If we’re to make the connection between what specific customers want and what we show them, we need knowledge of what they really like. So how do we find out?

Ask them

Why not? Every good customer service representative starts with “How may I help you?” Focus on the customer and how he perceives his own needs.

This is where good retailers set themselves apart. How well they focus on the customer’s needs determines how likely they are to gain return shoppers.

Netflix uses data from subscribers’ viewing history to recommend shows that are similar to what they’ve already demonstrated an interest in. They were one of the first to actually listen to customers’ input about what they liked and didn’t like. When you rank a show, Netflix’s recommendation engine learns what you prefer — and you’ll see more relevant content.

Warby Parker uses related products, but doesn’t rely on crowdsourced data. Instead, they’ve ranked their glasses according to style. If you look at the Mitchell, for example, you’ll probably also like the Wilkie. They’re similar. Once a shopper creates an account, he’ll be sent an email featuring those related glasses. A key feature is Warby Parker’s use of engaging copy to relate to the customer on a personal level. We all like friendly, knowledgeable salespeople who aren’t pushy.

Prescriptive personalization is the most important trend in web retail. Get it right, and it’ll show.

Combining data patterns and adding product knowledge will be key as recommendations become even more personal. Retailers who get it right will be able to prescribe products more effectively — and become even more useful to customers.