Company: Intermix
Contact: Don McNichol, director of e-commerce at Intermix
Location: New York, NY
Industry: Retail, Apparel
Annual revenue: Confidential
Number of employees: 100

Quick Read

Today's economy has earnest marketers scrambling for consumer attention, and as inboxes become inundated with more and more marketing messages and ads, the bar continues to inch higher for those attempting to stand out from the clutter.

Women's clothing retailer Intermix has found a straightforward solution: customized email communications that speak to specific customer interests, as determined through those customers' own actions.

Over the past seven months, the company has used iPost's Autotarget recency, frequency, and monetary-value (RFM) analysis platform to identify segments within its customer base and refine its email messages to appeal to each segment individually.

As a result, Intermix has been able to increase both open and clickthrough rates, as well as conversions, leading to a 9% increase in company revenue and 28% growth in its email marketing profitability—all despite a troubled retail market.

Challenge

Founded in 1993, Intermix is a women's clothing retailer with 24 US stores and an e-commerce site that launched in 2005.

Since the launch of that site, the company has frequently used email to alert its entire database of the season's latest "must have" arrivals, sales, and other events.

Though Intermix was profitable, Don McNichol, director of e-commerce, knew there was room to improve. A veteran of the direct mail world, he believed that an RFM (recency, frequency and monetary value) analysis would help to identify segments within the company's customer database; Intermix could then send more targeted, relevant communications to each segment. Doing so, he suspected, would help improve customer relations, increase profit margins, and lower opt-outs.

"I was familiar with RFM from decades of successful application in traditional direct mail marketing and found that those three criteria have been the most reliable predictors of future customer engagement," he said.

Early in 2008, McNichol began searching for a technological solution that would help him to effectively engage in email RFM analysis and test his premise.

Campaign

In June 2008, McNichol signed on to use the Autotarget predictive-analytics solution offered by iPost, based in Novato, CA.

Using Autotarget, McNichol engaged in A/B testing to evaluate customer reception to various products, brands, and discounted offers. On a daily basis, Autotarget analyzed email responses from iPost's email tracking database (including click rate and open rate) and purchase behavior from Intermix's customer database; it then segmented the 150,000-200,000 customers in Intermix's database by level of customer engagement with the brand.

The results revealed three distinct customer segments:

  1. VIPs: 20% of Intermix's customer base were found to have higher disposable incomes and low price sensitivity, opting for the latest trend regardless of cost.
  2. Brand Shoppers: 40% of Intermix's customer base demonstrated medium price sensitivity. Testing confirmed that these customers appreciate a good deal but are also more likely to buy items by specific designers.
  3. Sale Shoppers: The remaining 40% of Intermix clientele were found to be very sensitive to price and often waited for a sale before purchasing.

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Case Study: How a Women's Clothing Retailer Bucked the 2008 Downturn, Upped Revenues via Email

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ABOUT THE AUTHOR

Kimberly Smith is a freelance writer. Reach her via dtkgsmith@gmail.com.

LinkedIn: Kim Smith