“If you’re going to send an email to somebody, you want to send emails to people that are likely to click — and purchase,” says Jeff Ekblad, vice president of marketing at music instrument and equipment retailer Sweetwater.
Ekblad uses artificial intelligence customer engagement vendor Blueshift’s “create predictive model,” which Sweetwater uses to plan promotional strategy around its products. The model uses machine learning to predict whether a consumer will click on a marketing email.
Marketers need to collect data so it can be used for personal recommendations and predict future shopping behaviors, says Michael Renz, global retail technology leader at consulting firm Ernst & Young.
“That helps create a personalized shopping experience,” Renz says. Without automating certain tasks, retailers stand to lose to retailers that are investing now, he says.
“I can see who’s ready to engage via email and I can then target the people who didn’t open the email,” Sweetwater’s Ekblad says.
Sweetwater created a predictive audience called “likely to click,” within Blueshift, for consumers that were likely to click on a link within the email to Sweetwater.com, Ekblad says.
“We used this predictive audience to supplement our normal engaged audiences,” he says.
It worked. Sweetwater increased clicks from emails by 25% month over month in September 2022 compared with August 2022, he says.
Sweetwater is No. 72 in the Top 1000, Digital Commerce 360’s database ranking the largest North American online retailers by web sales.
Classify tags result in increased clicks, online sales
Classify tags on products like “guitar vintage,” has more context than “guitar,” Ekblad says. Sweetwater has built about 150 customer classify tags and attached these to its inSync blog articles and videos. The classify tags dive deeper into customer interests than categories alone, he says.
Sweetwater’s customer data platform (CDP) funneled these classify tags into Blueshift. This helped further match content to consumers, resulting in a 13% increase in clicks and a 40% increase month over month in purchases. A CDP is marketing software that collects first-party customer data to build a single view of each customer.
Sweetwater is currently merging 150 classify tags from its internal CDP to Blueshift. It will also create a ranking system of which classify tags are most popular.
It can launch automated email campaigns based on classify tags. These email campaigns can segment its email list based on shoppers who made purchases with those classify tags and email them other products in that category.
Personalized product recommendations
Throughout 2022, Sweetwater continued to build personalized product recommendations in email marketing campaigns.
As a result, email click-through rates for the retailer’s weekly deals and promotions emails increased 10% month over month. Online purchases attributed to emails increased 16% month over month, Ekblad says.
After success with its weekly emails, Sweetwater expanded product recommendations into additional promotional and category-focused email marketing campaigns that were category-focused.
The software makes recommendations based on factors such as personal viewing history, and items related but not limited to:
- Viewed products
- Category interests
- Customer classify tags
- Promotional offers
- Product financing eligibility
- Inventory availability
Why do shoppers abandon their carts?
Sweetwater also wanted to appeal to shoppers who abandoned their carts. A/B testing — also known as split testing — allows Sweetwater to test a percentage of its shoppers with two email campaigns to see which results in more opens or clicks. The retailer may test different images or language and compare which consumers responded to more.
In July 2022, Sweetwater ran its first A/B test, which compared article and video Blueshift recommendations in its weekly content newsletter inSync, resulting in a 31.5% increase in click-through rate for the number of consumers who opened the email compared with the other email. Order rate increased 39%, he says. Order rate is the total orders relative to the number of consumers who opened the message. Sweetwater conducted the A/B tests over the course of several weeks, Ekblad says. Previously, Sweetwater hand-selected what content to include in emails, he says. Blueshift’s AI-generated recommendations are more effective, he says.
Other tested changes include removing text promoting an active deal when there wasn’t one. “It was cluttering the email which decreasing the visual impact of items that had actual deals available,” Ekblad says. Another changed the call to action button during checkout from “checkout now” vs. “go to cart.”
The retailer plans to roll out messages based on customer preferences, he says. Sweetwater plans to test email campaigns with articles and video content related to items in their shopping cart items. The software will test how promotional headlines, color and design elements, messaging and other emails elements appeal to shoppers.
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