2021 was a critical time for airlines to make up for lost travel and capitalize on recovery momentum after nearly two years of reduced bookings and activity. Travel was on the upswing and airlines and hotels needed an edge in capturing that demand.1
Cue Loyalty Currency Retailing, selling loyalty programs points/miles to members to generate immediate revenue and long-term engagement. Since 80% of members who buy points/miles do so to reach a core reward like a flight or stay, incentivizing members to purchase at a key time in their travel consideration journey can increase bookings.2
As travel was rebounding, we recognized this opportunity to help our airline and hotel partners secure a bigger share of travel recovery. With this as our goal, we approached one of our North American airline partners to create a profitable campaign that would significantly increase demand for their program miles, especially amongst members who had never before purchased miles. Our task at hand: design a campaign to not only boost bookings by incentivizing mileage purchases, but also acquire new customers who have never purchased before.
The key to success for our partner’s campaign hinged on the strength of our predictive models to identify and attract new mileage purchasers. Targeting the right member and personalizing the offer served to them were critical to achieving our goal.
To target new buyers, we built a Buy Acquisition Model to predict which members were most likely to transact. Thanks to our data partnership, we leveraged a comprehensive data set—pulling in input variables such as recent flight activity, past earnings, redemption patterns, and mileage purchase behaviors—to produce propensity to transact scores for each member.
With the right members targeted, we could focus on personalizing each offer we put in front of them. Through prior testing, we knew that certain offer types resonate more depending on the member, including those who had never purchased miles before. As such, the promotion was designed with a mix of bonuses and discounts.
Next, we added a further layer of optimization through our Average Transaction Size (ATS) Model. Our ATS model, which is informed by historical purchase behavior and our own aggregate member profile data, predicts how many miles each member would buy and which offer to assign to them in order to drive conversions while maximizing their purchase.
In all, we went to market with 18 customized offers based on member segment and time of purchase—a testament to the precision of predictive modeling and our offer design process for this campaign.
Building machine learning models to identify which members to target and how to optimize the offers presented to them, resulting in significant loyalty currency demand during a vital travel period for our partner.
So much so, that the campaign closed out well above forecast. Mileage purchases exceeded expectations, and moreover, 73% of members who purchased miles during the campaign did so for the first time,3 successfully achieving the partner’s goal of acquiring new customers. In addition, lapsed program members made up 20% of transactors as a whole, proving the power that Loyalty Currency Retailing has in driving member engagement.4
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Sources
1. 2021 Deloitte holiday travel survey, November 2021.
2. Why Buy survey, November 2021.
3. Data from promotion with NA Airline partner, November 2021.