$11B Retailer Reduces Promotional Spending 35% with Session AI

By focusing on real-time offers, this hardware accessories retailer achieved significant savings and improved site-wide conversion rates. In its competitive market, the retailer was able to stop most use of sitewide offers and gain a new ability to deliver actions supporting different goals of the business.

A well-known hardware accessories retailer sought to increase efficiency and reduce spending on coupons. With a nine-figure budget for online coupons, the VP of pricing and operations needed better ways to understand their site audience in order to target these discounts. Internal research suggested that paid search was a particularly costly source of traffic when these visitors also claimed coupons.

The company used sitewide 20% discount offers to improve conversions. While this strategy had the short-term benefit of increased sales, the long-term impact was thinner margins and a customer base trained to wait until the next promotion.

The VP of pricing and operations, in collaboration with colleagues in merchandising, finance, marketing, and ecommerce, launched a project to seek customer segmentation options that could have the effect of reducing overall discounting.

With this deep partnership across business leaders, the retailer selected Session AI to reduce overall discounting because of the unique ability of Session AI’s in-session marketing approach to deliver savings. Importantly, Session AI could have an impact regardless of traffic source, product category, seasonality, geography, and customer segment. Even if the traffic was anonymous, in-session marketing could convert with less discounting.

Working with Session AI, the retailer implemented the in-session marketing platform and proved ROI in less than 10 weeks. The new platform segmented visitors in real time according to their likelihood to buy, and the retailer deployed three use cases that targeted the most persuadable group of visitors, the on-the-fence segment.

The three experiences each offered a variation of the 20% coupon that previously was offered to all visitors. One use case deployed a coupon for any cart size, while the other options used cart size thresholds.

All three experiences performed. Each created a lift both in conversion and revenue per visitor, leading to incremental revenue and increased margins in each week that the use cases were deployed. The most impactful use case created a 24% CVR lift and a 17% RPV lift for a small targeted segment of persuadable shoppers. 

The retailer pulled back its sitewide offers so that 20% discounts were no longer offered to the visitors who would convert without discounts. Overall, the average discount for all orders decreased by 35%.

Experiencing such success with in-session marketing, the retailer is exploring additional ways to create value with its new AI capability.

The likely-to-buy segment of eager visitors is not currently receiving on-site offers. The retailer is exploring a cart-size incentive to increase AOV at high margin with these visitors.

Additionally, the retailer is planning to target more of its visitors by deploying in-session marketing for its native mobile app.