Challenge
A luxury brand wanted to drive second purchases with customers who had converted within the last 18 months by offering a targeted group a personalized and elevated Cash Back rate instead of the brand’s typical rates.
CASE STUDY Drive 2nd purchase with targeted Cash Back
Solution
- Rakuten launched a targeted campaign to dynamically serve two different elevated Cash Back rates, 8% and 10% respectively, alongside their 2% base rate. The Dynamic Cash Back strategy allowed the brand to optimize for engagement and extra incentive on peak days.
- Using our proprietary data, Rakuten targeted members who purchased within an 18-month time period.
- Targeted media in the form of solo email, app pushes, and banners were served to drive campaign awareness and engagement with the audience.
Key Learnings
- Targeting with personalized, elevated Cash Back drove significant lifts across core metrics defined as: trips, shoppers, buyers, and sales per audience.
- Buyers who made the second purchase had a strong above Average Order Value.
- Campaign was efficient, delivering 4x ROAS.
- The CPA impacted average order value at a rate of 4.29x.
- Media drove additional performance lifts when paired with increased Cash Back rates. When media was introduced, the 8% test group performed stronger than the 2% base, despite the base also running promotions and media.
- Layering the campaign over sale and promo events boosted volume and encouraged second purchases among the target audience of previous buyers.
Results
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Serving a personalized, elevated Cash Back reward through a targeted campaign drove strong lifts across core audience performance metrics.
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Media drove high awareness and engagement with the reactivation audience.
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Push Notification open rate 2.70%, 1.3x above the rate associated with base rate or mass send
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Solo email click rate 1.64%, 7.8x above the rate associated with base rate or mass send
Percentages on Y axes are the percentages of the total targeted audience. The control group is large enough to give an accurate representation of BAU (business as usual) and the test group to target as many audience members as possible. These charts allow us to compare the control and test group(s) as if they were the same audience size.
Targeted audiences are curated and customized for the brand based on machine learning algorithms that take into account Rakuten member's preference as well as recent and past shopping and purchase pattern, including shopping behavior across competitors.
Learn how Rakuten merchants turn rewards into revenue and brand loyalty
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Shutterfly proves Cash Back is an effective performance lever
