We replayed the full digital journey of a Pair of Thieves customer. Screen-by-screen, we captured how value is delivered today at every step of a customer’s journey.
The findings? While markdowns are necessary to clear inventory, they are still treated tactically: static, untargeted, and often wasted on customers who would have purchased anyway, while training others to wait and eroding brand equity.
The opportunity? The same products you need to clear are leveraged to deliver personalized and optimized offers to each customer based on their individual preferences, intent, and willingness to pay.
While the GUILD loyalty program exists, it isn’t being leveraged to deliver personalized offers as "secret sales" and as part of the "early access to holiday deals" to deepen engagement or increase customer lifetime value (LTV). Members are treated as one segment, missing the opportunity to tailor rewards that drive incremental behavior.
The sale section shows 53 products discounted at 20% off. These markdowns are applied indiscriminately, leading to significant expense, training customers to wait for discounts, and eroding both margin and brand equity.
Individual products are discounted steeply regardless of the customer. Offers are static and untargeted — often given to customers who would have purchased anyway — rather than being personalized based on willingness to pay or purchase history.
When a customer adds an item to their cart, there is a rule-based response — no tailored incentive based on their willingness to pay. This misses the chance to capture intent in the moment and increase conversion before customers drop off.
Once on the cart page, every shopper sees the same static view regardless of loyalty status, purchase history, or willingness to pay. This leaves one of the most critical points in the journey underutilized, rather than using personalized offers to nudge checkout, increase basket size, or prevent abandonment.
Turn Every Interaction Into Impact.
Drive conversions and profits by delivering the right recommendation — personalized and optimized in real-time — at every moment that matters.
