March 11, 2014, 1:49 PM

A wholesaler aims to use online shopper behavior to make better predictions

O’Neill Clothing is already using predictive analytics to recommend products on its consumer-facing site, and aims to use the data in wider ways.

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The ability of e-retailers to accurately predict what consumers are seeking could help wholesalers as well, at least going by the experiences and plans of O’Neill Clothing, a surf apparel and gear seller owned by La Jolla Group Inc.

O’Neill has begun to use web-hosted predictive analytics software from Reflektion to improve the product recommendations it offers online shoppers. Here is how it works: A customer visits the site and the e-retailer tracks her activity via cookies, or bits of software code. Based on what that shopper browsed—say, a woman’s T-shirt—and how she arrived at the site, the technology can match her to shoppers with similar demographics (gender and location, for example) and preferred styles (she might like purple stripes, for instance).

“Imagine this happening thousands of times a day,” says La Jolla CEO Daniel Neukomm, suggesting the data accumulated can lead to better product recommendations. The tool also can advise the retailer when to offer “dynamic” discounts on product prices based on that shopper behavior, he says.

So far, the tool has helped boost the e-retailer’s conversion rate by 50%, to an average of “above 2%,” he says.

The tool could also help O’Neill better craft its wholesale offerings to retailers, whether larger operations such as Macy’s Inc. (No. 12 in the Internet Retailer Top 500 Guide, Pacific Sunwear of California Inc. (also known at PacSun, and No. 290 in the Top 500) or mom-and-pop surf shops. That’s because “we are in the business of making buy recommendations to retailers,” Neukomm says. In fact, no more than 10% of O’Neill’s revenue comes from business-to-consumer retail; the rest is wholesale, he says.

The brand primarily serves consumers between the ages of 14 and 24, he says, an age group that is especially responsive to fast-moving trends. He says the data collected via the Reflektion tool could anticipate and describe emerging trends. “After we’ve cycled through the data for a number of seasons, we can add some trend recognition” to the wholesale abilities, he says. That’s important because retailers are often making their apparel buys months before they go on sale, potentially giving an advantage to a wholesaler with more information about what’s likely to be popular in the season ahead.

Reflektion says its pricing varies by how often a customer uses the platform but runs approximately $8,000 per month.

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