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Sep 12, 2013
Case Study

Email Marketing: Clothing retailer lifts average open rate 40% via customer segmentation campaign

SUMMARY: Engaging customers through email campaigns is a craft. As a marketer, you understand the importance of appealing to your customers' behaviors, but what behaviors are most important to hone in on? Which area of focus will result in the most success for your company?

This case study illustrates how a women's e-commerce retail site, SwayChic, optimized its email campaigns by tuning them to different segments of customers, ultimately increasing revenue as well as clickthrough and open rates.
by Allison Banko, Reporter

CHALLENGE

SwayChic is the e-commerce store for a California-based women’s fashion retailer, Sway. The brand features six brick-and-mortar store fronts speckled throughout Northern California, and it's through these stores Sway's associates organically collect customer email addresses.

Sway team members entice customers to provide their addresses at the point of sale with alluring website promotions, including coupons and gift card giveaways.

Plus, SwayChic isn't only the online presence of Sway. The site is a unifier of the six physical locations, too.

"We were just trying to make it go full circle, and a lot of people wanted to be a part of that," said Cheyanne Sequoyia-Mackay, Project Manager, SwayChic. "We got lucky."

SwayChic had already been utilizing an email service provider, but email marketing efforts had plateaued and the company was no longer experiencing positive results. The brand longed for a new strategy in its email marketing to increase traffic and more fully engage its loyal customers.

The challenge was to maximize revenue from existing customers through optimized email campaigns.

Step #1. Examine pre-existing data

SwayChic's campaign wasn't sprouted from scratch.

Because of the team's existing email service provider, SwayChic already had access to select data, serving as a base point. Sequoyia-Mackay explained she had already been tracking general patterns to see which days produced the best open rates for email sends.

Through previous testing, she discovered emails sent on Tuesdays triggered more customer engagement than emails sent on Wednesdays, for example. While this sort of data was certainly valuable, SwayChic needed to get deeper into the metrics to reap results.

Step #2. Test for characteristic engagement patterns

Coming into this process, SwayChic wanted to:
  1. Maximize revenue

  2. Avoid spending hours comparing data

The next step encompassed collaborating with a predicative technology vendor who could give SwayChic a better glimpse of its customer engagement.

However, at the same time, the vendor had to be able to present that data in a way that was clear and easy to apply optimized email efforts. SwayChic didn’t want just a slew of data the team had to exhaust time analyzing.

Newly harvested data was to be focused on behavioral features, testing 30 to 50 attributes including:
  • Days with the highest open rates

  • Time of day with the highest open rates

  • Customers' past purchases

  • Clickthrough rates

  • Time of actual conversions

Timing

SwayChic already possessed the data on which days opened best, but it needed to delve deeper to see what time of day stimulated the highest engagement.

To test this, customers were divvyed up, organized to receive an email at different times of the day. Starting out, a certain percentage of customers were sent an email in the early morning, while additional groups were sent the same email either in the late morning, afternoon or evening.

Behavior, with a heavy focus on ROI

In each group, typical ESP elements (open rates, clickthrough, etc.) for those time slots were collected and examined. However, these items were collected with a focus on how they tied back to SwayChic’s revenue, so it wasn't just run-of-the-mill A/B testing.

Data was presented in a way that highlighted how much revenue SwayChic was generating at the particular tracked times. The trick was looking at those behavioral patterns that resulted in transactions.

Perhaps a customer would open her email in the morning on her way to work, but she wouldn't have time to buy the clothing right then (input credit card information, shipping info, billing address). So, she may go back to it in the evening to make her purchase.

Because the overriding goal centered on ROI, these behavioral patterns of when the conversion actually took place overruled all other data. So, in the situation above, though the open rate may show activity in the morning, the transaction took place in the evening so it would be most beneficial to engage this customer in the future with an evening email.

Step #3. Segment customers, then customize

After initial testing, SwayChic was able to segment its customers based on the behavioral data collected.

One aspect of the segmentation was the creation of an optimized email schedule revolving around the highest engagement days and times. Customers were divided into following slotted groups:
  • 5 a.m.

  • 10 a.m.

  • 5 p.m.

If their engagement behaviors change, the vendor's technology allows for customers to be automatically shifted into the better performing group.

"Honestly, we keep adding more to our evening group," Sequoyia-Mackay said. "That's apparently when our customer opens the emails the most."

SwayChic also collected behavioral tidbits of customers in terms of their purchase histories with the brand, enabling for the customization of what's in the email, too.

For example:
  • One-time buyers

  • Three-time buyers

  • Buyers who are no longer engaged

By collecting that data, SwayChic was able to launch a retention-based campaign, specifically targeting those customers who are no longer engaged with a "We miss you" email in hopes of reengagement.

Eventually, Sequoyia-Mackay said, SwayChic plans on launching incentive-based campaigns to target those different types of buyers. She outlined some possible ideas such as offering product recommendations to the three-time buyers or free shipping for the one-time buyers.

"Those campaigns haven't launched yet, but they're on the horizon and we're really excited about them," she said.



RESULTS

SwayChic unveiled 12 optimized email campaigns per month and experienced the following results:
  • Increased average open rate by 40%

  • Doubled average clickthrough

  • Tripled revenue for each campaign

"Marketing for us is really, really based on timing and making sure that you can follow a customer’s behavior," Sequoyia-Mackay explained. "It's helped us really hone in and keep a keener eye on how to recognize those behaviors and utilize them to make more money."

Aside from successful metrics, Sequoyia-Mackay explained the campaign has helped SwayChic fine-tune its marketing voice to better build relationships with customers — something extremely delicate in its industry.

"In fashion, it's a really big deal," she said. "It's great if you can market well to someone, but you have to market in a way that doesn't sacrifice who you are as a company."

Creative Samples

  1. Email graphic targeted at buyers who are no longer engaged

  2. Email graphic for "back in time" campaign

  3. Email graphic for "chill out" campaign

Sources

SwayChic

Retention Science — SwayChic’s email marketing analytics vendor

Related Resources

Email Marketing: 142% higher open rate, 15% bigger list from retailer's strategy

Data Overload? Segmentation, Strategy Tests Increase ROI 377%

7 Useful Email Strategies for Consumer Marketers

Email Makeover: 7 Email Optimization Tactics to Boost Revenue

'Mind Type' Segmenting Lifts Email Donations 42.5%: 6 Steps to Find Subscribers' Underlying Motivations


See Also:

Comments about this Case Study

Sep 12, 2013 - Hunter Boyle of AWeber says:
Great case study Allison. Kudos to the SwayChic team for using segmentation, analytics and testing in a very effective way. Tripling revenue is a huge win! Thanks for sharing the details. Cheers -- Hunter



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