With a mission to offer bicycles along with every conceivable product associated with them, online retailer Chain Reaction Cycles' catalog includes 20,000 products and up to 70,000 SKUs — everything from wheels, tires and pedals to clothing, accessories, nutrition and training services. Since going online in 2004, the retailer has relied on customers using its navigational tools and search functionality to find what they're looking for.

Recently, however, "We've been focusing on doing a better job on our web site from a segmented, personalized view," said VP of Ecommerce Mark Lilley. "We want to present our customers with product that is relevant to what they want to see."

With the goal of understanding each customer at an individual level, Chain Reaction Cycles deployed a solution from Qubit in January 2015. The retailer can now improve its product presentations based on the type of bike enthusiast a customer is (e.g. mountain biking, road biking, city/commuter, triathlon) as well as whether they are a beginner, intermediate or expert.

"If we know that you're a customer that chooses high-end brands, we can present relevant material, like a brand's new product launch," said Lilley in an interview with Retail TouchPoints.

Machine Learning Supports Ongoing Improvements

The Qubit solution offers a product recommendation engine with machine learning capabilities, which allows it to "learn what is the most engaging next step, or next product, and present that to our customers," said Lilley. "It's learning from itself."

This constant cycle of testing and learning, much of it happening in real time, also is providing valuable insight to Chain Reaction Cycles, as it gains a greater understanding of its customers and their behavior. "It might show that those customers that buy accessories tend to convert at a higher percentage than others, so if we put more accessories on the site we can create a greater ROI," said Lilley.

Other factors affecting customer behavior and sales can be the time of the day and the device the shopper is using to access the site. A customer on a smartphone is likely to be seeking a specific product, while the same customer using a desktop computer would be more open to a leisurely browsing visit.

Chain Reaction Cycles' site optimization and improved user experience efforts, along with incremental revenue through increased sales, has produced big benefits since the Qubit solution was deployed. "We've seen conversion rate increases of 5% to 10% during this period," said Lilley.

Personalization is important to every retailer, but it's particularly vital for those using a flash sales model. "We're not a traditional retailer where people browse with a need to fill; we need to inspire people to buy something they weren't necessarily looking for," explained Matt Fischer, Director of CRM Product Management at Rue La La. "So for us, personalization is key. The only way to get people to come back to our site is if we have relevant content for them. That starts with our communications to get people 'in the door,' and then once they're there, it's about how you carry the personalization through the site experience."

Rue La La also seeks to align its personalization efforts with the route each customer takes to get on the site. "If we acquired someone via a Facebook ad targeting Louis Vuitton, when they land on the site we want to ensure that they get exposure to Louis Vuitton or an equivalent luxury experience," said Fischer. "This is carried forward into their welcome stream and the first set of emails they receive, where we will still be highlighting luxury-style products."

Using Multiple Levels Of Personalization

Overall, Rue La La practices what Fischer terms "personalization at scale" with the help of a platform from Salesforce that was deployed in Q4 of 2015. The retailer has approximately 17 million members and sends more than 7 million emails per day. Of these, 85% are personalized based on the customer's profile, for example the specific Rue La La boutique she shopped most recently.

The remaining 15% are even more personalized, based on triggers related to customer behaviors on the web site. Even traditional email marketing tools such as cart abandonment emails are loaded with recommendations "that are unique to you based on your browsing history, and also referenced by the product that you abandoned," said Fischer in an interview with Retail TouchPoints. "If you left a pair of shoes in your cart, we might provide personal recommendations around similar shoes. We're trying to evolve from just a pure recommendation site to being more consultative."

The retailer also is using behavior-based targeting for more proactive campaigns, such as a win-back campaign aimed at shoppers in danger of lapsing. Emails tested in February 2016, sent to members who had not visited the site recently, were placed into different "buckets" based on affinities these shoppers had already demonstrated.

"Rather than just sending a general email saying 'Hey, it looks like you're lapsing,' we sought to disrupt this with something a bit more relevant to them," said Fischer, adding that these targeted emails were more successful than non-personalized messages at re-activating these wandering consumers.

Personalization already has advanced well beyond simply sending emails that begin "Dear [first name]". Some key principles of the next wave of personalization include:

Consumers' most recent actions are as important as their profiles: While customer activity has always been part of customer segmentation (the holy trinity of Recency, Frequency and Spend), it's now operating in real time or near real time. Personalization is less about a customer's demographics and more about their browsing, transacting, and cart abandoning behavior.

"Marketers still think demographics are important, but I like to quote the VP of product at Netflix, who said there are teenage boys watching Dance Moms and 73-year-old grandmothers watching Breaking Bad," said Graham Cooke, CEO of Qubit. "Demographics are dead. What's been done recently and in the moment, and a retailer's ability to understand those customer behaviors in real time, represents the next generation of what's going to drive the experience economy."

Personalization provides valuable insights to retailers: In addition to yielding higher sales and greater levels of customer engagement, personalization provides priceless information around marketing, merchandising, customer service, fulfillment and other basic operational requirements.

"If a brand knows its customers better, it can understand what problems they are attempting to solve, determine which products and services it offers that could best solve those problems (even if the customer may not have originally recognized how those offerings could best help), and make an offer that isn't just a random discount on an unwanted item, but make an offer that is truly personalized," said RSR Analyst Steve Rowen in an April 2015 blog post. "This is the brass ring of retail."

Personalization is an effective competitive differentiator: Shoppers who feel that a retailer really understands them — including understanding when they want a personal interaction, and when they want to be left alone — will be far less likely to be tempted by a lower price at a competing retailer.

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