Predictive Analytics

Predictive analytics, a broad term describing a variety of statistical techniques to predict future events, is one of the most efficient and effective ways to mine marketing data intelligently.

Having access to predictive analytics creates a strategic opportunity for marketers to reach customers by zeroing in on what customers are most likely to do and allows retailers to trigger email campaigns based on these predicted actions. Predictive data helps retailers strengthen customer retention by sending the right email to the right person at the right time.

Pennington & Bailes | Predictive Analytics | Windsor Circle

Actionable Predictive Data Fields

Windsor Circle’s Retention Analytics Suite produces a number of key predictive data fields that are used to power personalized, automated marketing based on:

  • Predicted Order Date – customer’s personal purchasing habits
  • Replenishment Re-order Date – when the product they purchased will run out
  • Product Recommendations – related items to the product a customer has most recently purchased
  • Hot Combo – items that are typically purchased together

The ability to pair predicted order date with any number of other data fields, allows retailers to send timely product recommendations, replenishment emails, and even win-back campaigns.

Tell Your Customers What They Need Before They Even Know

CoffeeForLess-Windsor-Circle-Replenishment-Campaign, a member of our Million Dollar Circle, leverages predictive data to run their automated replenishment emails (seen to the left).

Windsor Circle automatically pulls a predicted order date for customers who have made 3 or more purchases and then triggers a replenishment email based on an individual's buying behavior.

In this example email, the empty square to the left is a smart image that populates an product image based on the products a customer is receiving the replenishment email about. CoffeeForLess uses the remainder of the page to recommend other products that the customer may find interesting.


 Pinpoint At Risk Customers Earlier

While using the predicted order date field to trigger product recommendations and replenishment emails is the most obvious solution, SurfStitch, Australia's top surf and apparel retailer, uses predicted order date to pinpoint customers who may be churning. Normally, win-back campaigns are sent based on static dates such as 60, 90, and 120 days since the last purchase.

As shown below, with access to an individual's purchase history and predicted order date, SurfStitch automatically deploys a win-back series to customers based on their individual buying habits. SurfStitch has seen a decrease in churn by 72% over a 6 month period from this innovative win-back email series.


Learn more about using predictive analytics in your email marketing strategy with a FREE demo today.