HOW VINEYARD VINES USES ANALYTICS TO WIN OVER CUSTOMERS
by Dave Sutton
When brothers Shep and Ian Murray cut their ties with corporate America to start a little company on Martha’s Vineyard in 1998, their motivation was clear: “We’re making neckties so we don’t have to wear them.”1
Little did they know that the business they founded, Vineyard Vines, would become a darling of the fashion industry and a household brand name around the country.
Today, the company best known for its smiling pink whale logo offers much more than its signature neckwear. It manufactures a full line of “exclusive, yet attainable” clothing and accessories for men, women, and children. That “little” privately held business has grown tremendously since its launch and currently has more than 90 physical retail locations and a highly successful e-commerce business.
I met the team at Vineyard Vines while doing research about data-driven marketing technologies for my book, Marketing, Interrupted, and learned firsthand about the company’s beginnings and what has made it so successful today. From the very beginning, the Murray brothers adopted a guiding principle to authentically connect with and deeply understand the unique needs of their customers. This principle has always been a priority for the leadership team at Vineyard Vines and it is still top of mind today. It is clear that the current VP of Marketing, Lindsey Worster, is committed to this principle, as she told me: “We are all about getting the right message, about the right product, at the right time to our customer—targeted, relevant, and authentic communication is our primary goal.”
Of course, this type of real-time, one-to-one marketing is easier said than done.
As Vineyard Vines has rapidly grown its customer base, the size of its customer database has expanded, too. Terabytes of data have been captured. Hundreds of attributes, encompassing customer profiles, preferences, and buying behaviors, must be parsed into actionable insights in order to deliver a highly personalized experience. Like many competitors in the apparel industry, Vineyard Vines has kept its operations lean in order to preserve operating margins. This means that it simply does not have the human resources to perform the onerous data analysis and behavioral segmentation needed to inform true one-to-one marketing. So, over the years, the retailer fell into the trap of relying on traditional “batch-and-blast” types of communications to reach its customers, promote products, and make offers. Of course, that trade-off was inconsistent with the guiding principles of the founders, but it was perceived to be the only way to keep the cash register ringing. But, Worster acknowledged, “With the batch-and-blast campaigns, we were sending the exact same message and static images to millions of people, and that just isn’t the best way to communicate with customers.”
In July 2016, the e-commerce team at Vineyard Vines set out to find a solution to help it keep pace with its dynamic customer base and stay true to its principles of authentic, relevant, and personalized communications. What team members were looking for was a retailer-agnostic platform that would integrate their online customer and products data to enable true one-to-one, personalized messaging. As we all know, Amazon has the technology to do this, but it’s proprietary and not available to retailers.
Enter Fayez Mohamood and his team at Bluecore, a retail marketing automation platform. The solution that Fayez and his team have developed correlates customer behaviors and their interactions with the retailer’s online product catalog. From these analytics, Bluecore dynamically builds intelligent, triggered campaigns that can be run across email and social media channels or be used to optimize search-engine marketing. At the heart of the solution sits an AI-driven decisioning engine that determines the timing and content of the next best campaign to send to individual shoppers. The decisioning engine takes the data about the customers’ interactions with specific products and decides what products to target next for each customer, based on its understanding of the individual and the collective wisdom of all customers. It understands which customers have price sensitivities (and therefore are motivated by discounts), what items an individual customer has viewed, what those items have in common with other items the customer engaged with, which products are replenishable items and at what cadence a specific customer replenishes them, which activities predict an upcoming purchase, the right time to contact a specific customer, a customers’ lifetime value and activity, and so on.
Initially, Vineyard Vines deployed the technology to tackle obvious challenges like triggering emails for abandoned shopping carts, abandoned searches, and abandoned browses. After seeing increases in revenue per email (RPE) on those initial customer messaging efforts, the marketing team decided to expand its use of the dynamic decisioning capabilities of the platform—what Bluecore refers to as “predictive audiences.” This part of the platform enables Vineyard Vines to send dynamic, personalized messaging based on a customer’s online behaviors, purchase transactions, and their relative level of personal engagement with the brand.
Next, the marketing team quickly set about using the platform to automate campaigns for specific use cases where personalization and relevancy had always been a challenge, including:
- notifying customers when high-demand products were back in stock
- communicating last-chance offers on stock-out items
- running holiday-specific and special event campaigns
- predicting when a customer may be at risk of unsubscribing
The days of batch-and-blast campaigns for Vineyards Vines may soon be over, as to date the campaign results with the new decisioning engine have been exceeding expectations. Consider the following campaign examples:
Holiday campaigns expand reach without sacrificing relevance
The Vineyard Vines team increased the reach for its annual St. Patrick’s Day email campaign from 3,000 recipients in 2017 to more than 239,000 in 2018, while maintaining a highly personalized approach. This holiday-themed product campaign targeted two specific audiences: customers who had previously viewed the holiday-themed apparel and customers with a high affinity toward the product. The open rate for emails generated from the new platform was up 68% and the RPE increased by 572% over the prior year, when a batch-and-blast approach had been used. For the annual Easter campaign, the marketing team used the platform to target not only customers who had browsed Easter-related products previously but also expanded the list of recipients to include customers who had a high affinity toward the products. In this case, the number of recipients jumped from 5,000 to 150,000, open rates were up 77%, and RPE was up 759% over the prior year’s results.
A seasonal campaign generates outsized ROI through enhanced cross-channel marketing
The social media team at Vineyard Vines used the decisioning engine to determine which customers are unlikely to open or click emails and then targeted those customers on Facebook instead. This cross-channel move resulted in a 182% ROI. Based on its initial success, the team plans to extend this approach to even more channels. First up is an anti-churn campaign that targets at-risk customers through direct mail. The team believes this campaign will offer a powerful opportunity to reengage with these customers in a new way.
A women’s performance campaign far outperforms expectations
The goal of this campaign was to introduce a new women’s performance collection to customers who would have a high affinity for the product line based on predictive models. Since this was a brand-new product launch, the team didn’t have any historical purchase behavior to use as a guide for segmentation, so Bluecore was used to close that gap. The target audience was customers who had a high or very high product affinity for Vineyard Vines’s brand-new women’s performance leggings. Using the new decisioning engine, the campaign generated 124% higher RPE than the average Vineyard Vines women’s campaign.
The decisioning engine helps find new customer segments
The Vineyard Vines team is using the “audience insights” module of Bluecore to reveal retail-focused insights for specific groups of customers. In terms of customer needs, the ability to map customers to different life cycle stages helped the Vineyard Vines team home in on which priority customers to target, such as those who are at risk of opting out of direct marketing communications and losing touch with the brand. Looking at engagement with products, the team found “hidden gems,” or products with low traffic but high conversion rates. This insight clued the team in on the products to which they should drive more traffic through targeted campaigns. When the marketing team combined the intelligence from audience insights with predictive decisioning, the results were impressive. For example, after finding that several kids’ products landed in the “hidden gems” category, the team decided to create a “Kids’ Weekly Best Sellers” campaign to drive more traffic to those products. It targeted customers who had previously browsed kids’ products, had a high-to-medium likelihood of opening emails, and were unlikely to unsubscribe. Within the first 24 hours, the campaign brought in an 81% higher revenue per email than the traditional batch-and-blast kids’ email campaigns.
What can other companies learn from Vineyard Vines’s success? A few best practices stand out:
- Engage with customers on a one-to-one level. It’s no longer a “nice-to-have”—customers expect it.
- Overhaul your batch-and-blast approach to email marketing by integrating behavioral data and predictive algorithms to make high-volume campaign sends that are unique to each recipient.
- Provide your loyal customers with the best experience at every touchpoint.
- Target customers in a personalized manner across more than just email, and determine the best channel mix for each customer.
- Gain a deeper understanding of customers and products. View detailed audience insights to better understand customer health and engagement with products.
Without tools like Bluecore, retailers don’t have a clear or accessible understanding of what products customers are interacting with or the commonalities across products that a single customer has engaged with. They also don’t know the minute that a product’s status changes. Consider the occasions when a product decreases in value, goes out of stock, or is back in stock again—all of these events should trigger action by the retailer. Most retailers struggle to understand how and why a customer engages with a product unless the customer buys it or abandons the cart. Today, there’s so much more that can be done to better serve customers and to ultimately make your company more successful.
Vineyard Vines uses its customers’ data to connect with them authentically using real-time, one-to-one marketing. Understanding what this company has learned through its analytics and AI efforts can help you improve your marketing campaigns to reengage customers and increase revenue.
✓ Moving past batch-and-blast messages that sent the same text and images to millions, Vineyard Vines looked to authentic, relevant, and personalized communications through a retail marketing automation platform. This platform created triggered campaigns based on an AI-driven decisioning engine that determined the timing and content delivered for each shopper.
✓ The company also expanded into “predictive audiences,” which enabled the company to send personalized messages based on the customers’ online behaviors, purchase transactions, and level of personal engagement with the brand.
✓ The Vineyard Vines example illuminates a few additional best practices: Provide your customers with the best experiences at every touchpoint; determine the best channel mix for each customer; and view detailed audience insights to understand customer health and engagement with products.
Adapted from content posted on hbr.org, June 8, 2018 (product #H04DRC).