How Room & Board makes data personal

Kimberly Ruthenbeck

Creating the online equivalent of the in-store experience, one that hinges on associate interaction, is a challenge for any retailer. So for home furniture chain Room & Board, the idea that impersonal data could create a more personalized experience was a foreign one.

The success, according to Kimberly Ruthenbeck, Room & Board's director of Web experience, is the marriage of online and in-store data that creates a solution that neither platform was able to offer on its own. Through data and predictive decisions provided by Salesforce, Room & Board has been able to improve on the store associate's ability to offer suggestions, pair items and sell accessories. That, in turn, has yielded higher conversion rates and larger orders.

FierceRetailIT: Home furnishings have a unique set of challenges when it comes to e-commerce. What prompted you to implement predictive decisions?

Kimberly Ruthenbeck: We see ourselves as very personal and the decision-making as very personal. We always had this thought that you have to speak to a person to get a great recommendation. We obviously don't have that opportunity on the website, so there was definitely an acclimation period in terms of accepting the fact that data could do that for us. One of the positive things about it was that we were bringing in data from multiple sources, so not only bringing in Web data, but we were bringing in all of the data from our store purchases too.

We're seeing the collective of what people are doing with our products in order to make those great recommendations, so it's not just Web data. We started out slowly, to see what the successes were, and we have found more places to use recommendations and the predictive decisions than I ever thought we could.

After [a customer has] added an item to the cart, we go ahead and make suggestions there. Then we added [recommendations] to our product page, and now we're adding it to a category page, we've added it to our mobile site and we're currently in the process of adding it to email. And the emails that we're adding it to are all of our predictive emails. Not our global emails, but the ones where we're actually sending people information based on what we know about them and their browsing. We're putting recommendations into those emails and across the board on all of these, we're seeing really great engagement and conversion.

FierceRetailIT: Can you share some more details about how you ramped up and what kind of results you saw?

Kimberly Ruthenbeck: When somebody interacts with the predictive decisions, when they've clicked on an item and actually bought the item, we see two times the conversion rate. So people are actually going in and buying the item that was suggested to them. And then we have significantly more people who actually interact with it and convert. It's taking them on the journey like a design associate would if [they] were face to face and walking through the store talking about other [items] they should be thinking about. And the great thing about the data is that we know exactly who you are and what you've been doing in your personal life. Not everybody on that page is getting the same recommendation.

We have seen the average order value be about $150 more than our average order value for the customers that engage with the predictive decisions. Not only are the orders higher, but there's a higher conversion rate. When they interact with the predictive decisions, they convert six times better than the average person on the site.

The average order value is 16 percent higher for Web visitors who engage with predictive decisions-powered content.

The direct conversion from customers who engage with predictive decisions-powered content and then click to buy within the predictive content module is 150 percent higher than the site average.

The technology gets better and better over time. The data gets better, the algorithms get better. Predictive intelligence-influenced revenue keeps growing. Thirty-seven percent of visitors who engaged with predictive decisions-powered content have purchased from one of our channels—either in-store or on the Web, and 53 percent convert offline.

FierceRetailIT: So it's bringing shoppers into the store, as well?

Kimberly Ruthenbeck: We can see it from a multi-channel perspective, [too]. Of the people who engage with predictive decisions, 37 percent will purchase from one of our channels, 53 percent of those will purchase from an offline channel. We're not showing their conversion on the site, but we know that they're purchasing in other locations. It's creating an offline engagement.

FierceRetailIT: How far along are you in implementing this program?

Kimberly Ruthenbeck: We're about a year [in] now, and that's only because we chose to go this slow. We chose to add it in incremental ways and that was an internal decision. We wanted to see how it was working and our comfort level with it. Then, we saw the success and recognized it was positively influencing the interactions and not getting in the way—that it was really good.

FierceRetailIT: So what's next? How far can you go with it?

Kimberly Ruthenbeck: I think we've got a few more places—more emails that we can put it on. We still have an implementation on our category pages to do, and from a site perspective there are a lot of places where we see it's applicable. Currently, we're only using it on our predictive or behavior-based email. There may be more opportunity on other emails. We're adding it to our Web order confirmation, so when you place an order we'll be adding it to that email.

At this point, we've covered the decision-making process. But there's a step before that which is "inspiration," and we have some ideas of using the predictive decisions data to help serve up actual photography or room settings that might inspire versus [offering] items. That's a different process for the customer, they're just coming to look and gather ideas. Maybe there are ways that we can inspire them with great room setting photography when they're not at a place of choosing between two [products] or an add-on to a sale.

That's the really big next step.

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