Your Email Marketing Battle Plan for 2017

Your Email Marketing Battle Plan for 2017

Last Thursday, people sat down with family and friends to celebrate Thanksgiving and eat their hearts out. Whether the tradition is to eat turkey, tofurkey, or chinese takeout, one things is for certain, most of the people who are busily enjoying a large meal on Thursday are ready to shop on Black Friday and Cyber Monday.  In early October, National Retail Federation released their forecasted numbers for 2016. While the 2015 holiday season didn’t perform as well as estimated, increasing 3.2% over the previous year, they’re forecasting in-store sales to increase 3.6% to $655.8 billion. Moreover, NRF is forecasting non-store (online sales) to increase a whopping 7-10% to as much as $117 billion.

At this point, retailers are in full swing, running promotions, stocking up for Black Friday and Cyber Monday, and organizing their team to execute flawlessly. What retailers may be forgetting is how to handle this influx of customers after the holiday season is done and gone. With more consumers turning to online shopping as the quickest and easiest way to get their holiday shopping done, retailers can enjoy more visibility online and more opportunities to turn browsing shoppers into loyal customers. However; retailers need a game plan quarterbacked by two key strategies in order to succeed: retention and predictive marketing.

Retention marketing, also known as lifecycle marketing, helps retailers speak to consumers wherever they may be in the buying lifecycle, from an onsite visitor to a one-time customer, to a high value, loyal customer. The 2016 Retention Marketing Report states that retailers have embraced the idea of retention marketing, with a 55% increase in retailers budgeting 30% or more to marketing to existing customers. The main channel for retention marketing, is, of course, email marketing. Interestingly, we found that retailers who are winning in the retail space and seeing a competitive edge are employing predictive data on top of their retention marketing strategies.

In fact, in the 2016 Predictive Marketing Report, we found that, anecdotally, retailers who have invested in predictive marketing are seeing increases across the board from sales, to engagement, and even inventory management. These findings jive with what we’re seeing in the industry. A recent Forrester Report states “predictive marketers are 2.9x more likely to report revenue growth rates higher than the industry average.” Additionally, Salesforce Marketing Cloud found that 79% of top-performing marketing teams are using predictive intelligence to inform their marketing communication and strategy.

So how does all of this fit together? The first step to get started with retention marketing or to add predictive marketing is getting access to your data in an actionable way. Having access to product, purchase, and customer data in your email marketing platform allows you to start slicing and dicing your customer list by key features, such as, last order date, products purchased, geographic location (for in-store promotions), etc. This enables retailers to ensure they’re not sending Harry, who lives in Montana, promotions for women’s bathing suits in the middle of winter or Joan, who lives in Florida, promotions for a brand new snow shovel.  Once retailers have set up foundational retention marketing campaigns - first purchase series, abandoned shopping cart campaigns, browse abandonment campaigns, and a best customer series - it’s time to sprinkle in predictive data and create predictive campaigns.

Predictive marketing can take form in a few different ways in the world of email marketing.  If you’re just getting started, I recommend starting with the low hanging fruit. One of the easiest steps you can take is enabling dynamic product recommendations for your existing email campaigns. Dynamic product recommendations are populated based on buying trends of the individual person and the trends seen in the retailer’s aggregate customer base. This one addition creates a more personalized experience for each customer. 

Once dynamic product recommendations are added, it’s time to move on to using predictive data - predicted replenishment date (for consumable products), predicted gender, predicted order date for a predictive win-back campaign, etc  - to trigger and build out campaigns.. Depending on your industry, certain campaigns and promotions may work better than others.

PREDICTED REPLENISHMENT DATE

  1. com, an IR1000 retailer (#617), a web-only retailer of coffee, tea, and related products, created a replenishment campaign based on predicted replenishment date. This campaign, pictured on the right, triggers based on each customer’s buying cadence. This campaign’s revenue per email (RPE) is $0.73. Note: The industry average is $0.11.

Similarly, Artbeads.com, also an IR1000 retailer (#550), a bead and jewelry-supply online retailer, created a replenishment campaign based on predicted replenishment date and has seen a 161% increase in opens from this particular campaign.

In both instances, the retailers are leveraging dynamic product recommendations in their emails, as well as relying on the predicted replenishment date to trigger the campaign. 

PREDICTED GENDER

For US based stores, we’re able to predict with a 99% confidence rate the gender of each customer in your database. This data can be extremely useful when you’re creating your promotional calendar. While the promotion might be the same, the copy and products your pushing may vary based on gender. Additionally, you can employ this information to create suppression lists, so Harry will no longer get promotional campaigns for women’s swimsuits. This not only helps create a more curated and personalized experience for your customers, but cut down on unsubscribes and spam reports.

PREDICTED ORDER DATE

Predicted order date can be used in a number of ways, but primarily we tend to focus on creating a predicted win-back campaign. A static win-back campaign uses a set number of days past the purchase date as their trigger date, generally retailers will look at their average latency period to help determine the timeframe; however, this approach leaves room for error. For any customer who has purchased 3 or more times, retailers can employ predicted order date to create a predictive win-back campaign. This campaign is triggered based on the predicted order date for each customer.

SurfStitch, Australia’s number one surf and lifestyle brand, created a predicted win-back campaign. Running both a static for 1-2 time buyers, and predictive campaign for 3+ buyers, SurfStitch has seen a 72% decrease in churning customers.  To top it off, SurfStitch capitalized on their existing copy and creative when creating

Pennington & Bailes, Windsor Circle’s green pants provider, also created a predictive win-back series. They have seen a 62% lift in opens and a 137% lift in clicks from their predictive win-back series when compared to their static win-back campaign.

Retailers are just beginning to scratch the surface of what predictive marketing can do. As consumers demand a seamless experience across devices, regardless of whether they shop in-stores or online, it’s imperative that retailers create the curated, personalized experience consumers are looking for. To learn more about predictive marketing, download the 2016 Predictive Marketing Report and make sure to keep your customers after the holiday rush.

 

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Friday, 10 July 2020