How REI Used Web Data To Help Target Product Emails

Like everyone, the email team at outdoor retailer REI was rocked when the COVID-19 pandemic hit three years ago.  

“We were facing a ton of instability in supply chains and an overnight shift in how people were shopping for products,” said Sarah Jenkins, senior program manager of email, REI, speaking at MediaPost’s Email Insider Summit earlier this week.

For one thing, there was a major shift to online shopping. For another, people wanted to go outside, and they needed products for the new forms of outdoor recreation they were trying,” Jenkins continued.   

But it wasn’t easy trying to break through the clutter: “Customers were being exposed to four to 10,000 ads per day — there was a lot of fatigue. How to break through that became a priority for us,” Jenkins noted.  

Then there was this:  “Over time, we started to see friction emerging between best practices and business bottom lines,” she acknowledged.

“Email is so often viewed as really fast and cheap way of getting messaging out to customers to see an immediate return on traffic and demand,” Jenkins explained. “Because of that pressure, we were seeing audience fatigue with the impact of store clickthrough rate as well as our engaged audience size.” 

Jenkins went on: “We often think of top of inbox and top of mind as an increase in in messaging. But we were seeing serious ramifications around doing that at scale."

The team focused on an existing email program that had used products to sustain and engage customers in an activity “that we knew that they were interested in or were likely to be based on our data modeling."

But traffic and revenue around this program were dropping. “We knew the demand was there, so we kept testing our creative and audience targeting, but we weren’t seeing any impact,” Jenkins acknowledged.  

One issue was that these emails were highlighting products that “the merchants and we wanted people to buy, and this wasn’t resonating as strongly with customers.”

So they looked at the data. It was clear that people were getting into outdoor activities they had not bothered with before. In the audience, one member said they started kayacking, while another began running.  

"In order to personalize in email, we often look at one-to-one behavior data on subscribers,” Jenkins stated. "But we realized there was this plethora of data we hadn’t ever really looked at before as an email channel.”

The team  analyzed this data and looked for trend patterns to emerge—

to have all these outdoor enthusiasts whether they were subscribers or not  to tell us what they were likely to start thinking about and to digitally shop for a product or an activity.”

The team analyzed this data and looked for trend patterns to emerge. 

She continued: “Once we identified the macro trends, we layered on behavioral personalization to speak directly to the individual. Behavioral data makes that trend personal.”

All this allowed the REI team to “serve our email subscribers with the most culturally relevant and trending products when all of these data sources were aligning — a time of peak interests.” Jenkins said.  

She added: “By compiling and cross referencing digital, we were able to map consistent trends and we were able to also to spot agile trends as they were happening, and to spot spikes in interest well above historic trends that we wouldn’t have been able to predict.”

As an example, when hiking began to gain traction, REI could version the images and landing pages based on a person’s geography to “better reflect the environment they would be in when they opened the email.” 

What was next? “Once we had dialed in on trends, we started scoring our entire audience based on behavioral flags that would tell us if they were likely to continue engaging with us in email.” 

The team chose to significantly reduce the communications it was sending to the unengaged group, and to make the smaller number they sent more relevant. This actually increased engagement. 

What was the result of all this? The team decreased overall circulation by 21% by weeding out people who were unengaged. There was a 52% increase in demand and 13% increase in traffic. 

“As we get better, we do expect these numbers to continue to rise,” Jenkins said.

The team was also better able to respond to the challenge of external cultural and environment shifts. Case in point: it was set to launch a reindeer email, but California got hit by “awful weather” in the form of an atmospheric river.  “We were able to suppress customers in these areas,” Jenkins said. “A harmless email using product that was trending could come off as insensitive and we would lose brand loyalty.” 

An audience member asked how they sold the email reductions to upper management. 

“It sure was fun,” Jenkins laughed, adding that other stakeholders came around when they saw improvements in email engagement. But it required open communication.   

One surprise was “a strong spike everything that was bear-related.” Jenkins added.. She joked, “It was weird.”

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