MAKE DATA ACTIONABLE
DO MORE WITH LOCATIONS
JAY: Influenced by Fast Casual Restaurant
A fast casual Mexican chain wants to promote their new daily specials menu through their app. Jay uses the app for loyalty points and most often eats there on his lunch hour. The Mexican chain sends Jay a push notification when he’s predicted to be in the area for $2 off an entree from the daily specials menu.
RICK: Influenced by Local Fitness Studio
Rick has a busy career and cancelled his “standard” gym membership a few months ago. Since then he has enjoyed trying niche gyms near his residence. One niche fitness studio references data from class attendance, class instructors and visit frequency to deliver tailored message to Rick. They'd like to welcome him back with a free first month and waived activation fee. By creating custom audience segments, the studio is able to reach back out to any users who have taken a class but never signed up after their free trial.
SANDRA: Influenced by Holiday Retailer
Sandra is a frequent shopper at Big Box stores for groceries, gifts, and more. Last year was the first year she shopped online for Black Friday sales. One holiday retailer understands buyer tendencies and behaviors through the types of products guests have viewed online. They set up a campaign targeted toward Sandra's audience segment for an extra 10% off on select items that have been viewed online. This year, Sandra's total amount in her shopping cart is 45% higher when using the coupon code from the targeted campaign.
Take Your Messaging to the
Identify patterns in customer behaviors and locations to predict when, where, and what your customers will buy from you and your competition. Our first-in-class predictive location tools allow you to reach your customers ahead of time when they might be headed to your location or a competitor's.
Say farewell to goodbyes with Customer Look-Alike Targeting
Your customers are more alike than you think. Recognize at-risk behavior patterns and re-engage with customers who are following the path of similar users to attrition. Prevent customer churn before it’s too late using Customer Look-Alike Targeting.