With a diverse portfolio of consumers, PACCAR Parts' loyalty program experienced growth plateau in digital engagement and offer redemptions. Fleet characteristics like truck age, fleet size, owner/operator etc. drove the product preference and buying patterns at individual customer level. A recommendation system powered by machine learning was built to recognize individual customer characteristics and analyzed the engagement and purchase behaviors to personalize offer content across digital touch points. Hyper-personalized offers were delivered through our "SAVINGS IN OVERDRIVE" and "GET IN GEAR" campaigns and the program achieved positive year over year redemption growth for the first time in the last six months.
Fleet characteristics like truck age, fleet size, owner/operator etc. drove the product preference and buying patterns of our loyalty members. Hyper-personalized offers demonstrating unique knowledge of each of our member's specific fleet characteristics could drive engagement and sales.