The Brand Advantage Over Amazon? Individual Customer Relationships

'Amazon is an expert at tying into 'easy' culture — but not loyalty culture,' says Sitecore's Joe Henriques.

Amidst shrinking shopping malls and closures from big-box retailers like Toys ‘R Us, it’s easy to see why brands are afraid of Amazon: Retail is certainly changing, and the e-commerce behemoth is seemingly everywhere.

But as Joe Henriques, VP of Global Strategic Partnerships at Sitecore, points out, with its low prices and fast delivery, “Amazon is an expert at tying into ‘easy’ culture — not loyalty culture.” And therein lies the opportunity for brands who aren’t afraid to re-envision customer experience.

GeoMarketing: If Amazon represents the death of the American shopping mall, what does this means for the individual brands you work with, like L’Oréal? How can they compete, and what will customer engagement evolve to look like?

Joe Henriques: Look, Amazon is a behemoth. We get it. But Amazon is an expert at tying into the “easy” culture — not the loyalty experience culture.

Amazon is not exactly saying, “how do I beat brands?” Instead, they’re worried about how to make someone go to Amazon, buy products in a very quick fashion, and not have to deal with lines at shopping mall, parking a car, et cetera. They’re asking, “How do I make that easy, and how do I make the return process easy? [That’s what] they do incredibly well, and that’s why we talk about the end of the shopping mall as the preferred shopping experience.

But now, in my view, brands have the opportunity to say, “How do I make a relationship with the consumer?” That’s their opportunity. If they don’t want to buy into that, they are going to be beat by Amazon.

In my opinion, this relationship is built from three things: One, collecting data and knowing your customer. And you can’t just take data and not provide the customer anything in return — so you have to have that partnership with that data sharing activity.

Two, you have to have the capability — whether through machine learning or just learning in general, if you’re a smaller brand — to use that data to react on the fly, in real-time, to respond to immediate [customer] needs as well.

Then, finally, you have to go beyond the transaction. It’s about creating a loyal relationship to [the brand] that not only leads to re-buying, but also evangelizing the brand across their network.

How have you helped brick-and-mortar retailers create these “beyond the transaction” relationships in your work at Sitecore?

Let’s use a Sitecore customer that sells pet supplies for an example. They have about 400 stores. They’re competing with PetSmart, Petco, and a bit with Amazon, too, in terms of delivering dog food.

They knew [that winning business] was going to be about customer experience. They came to us and said, “How do I make the in-store experience better?” Forget digital in and of itself for a second; it’s just one part of the way to do that.

So, they introduced in-store pickup, and they’re planning an option to have things brought out curb side. More importantly, they’re going to start utilizing digital technology to enhance the experience while shopping in the store. So not only do you have to think about cash registers, but you think about the experience of buying product in the aisle.

Also, [it’s important to incorporate] the fact that the store has your information can know things about you while you’re in the aisle. Saying, for example, if we know you’re a cat person, we can serve you video content related to cats [or] a new brand of cat food to try — to make it about you.

You mentioned machine learning earlier. In terms of online-to-offline marketing — and building this personal relationships — where and how does AI fit in? 

People get AI and machine learning confused, too. They’re two different things. But the big challenge for marketers today is collecting all of this [customer] data and then harnessing it. What’s the next step?

Well, the next step is you have to apply some sort of machine learning to get the [most] out of it and to make it actionable. One thing we’re doing with it is to make recommendations to a marketer about how they could be optimizing their revenue based on the goals and the engagement values they’re trying to put forth. What engagement are you looking for? What goals are you looking to achieve? [Our platform] can tell you the proper segment for achieving those goals.

We’ll also tell marketers about [how to optimize] what they’re currently doing from the machine learning on our side.

AI is the next iteration of that — which will be automated personalization. That’s where we’re heading.

No one’s really there yet. And I’ll be honest with you, I don’t know if the market is there just yet. But now is the time to think about it; that’s what we’re going to see soon.

About The Author
Lauryn Chamberlain Lauryn Chamberlain @laurynchamberla

Lauryn Chamberlain is the Associate Editor of A New York City based journalist, she specializes in stories related to retail, dining, hospitality, and travel.