When a shopper steps inside a store, their gaze fixed on the return counter while awkwardly carrying a crumpled box under their arm, the spotlight shifts to the retailer. This is their moment to shine or falter. The way a store handles this crucial interaction can turn a simple return into a golden opportunity to secure a customer's loyalty and significantly enhance the customer's lifetime value (CLV).
With AI-powered technology, retailers can ensure a return system is pleasant, secure, and predictable. The right platform can shape every return experience into one that encourages additional shopping while mitigating the risk of loss.
It’s understandable to think that if a shopper has a bad return experience, they’re prone to go elsewhere. A study from the Reverse Logistics Association echoes that theory, finding:
Ensuring customers have a positive experience directly impacts loyalty, and technology can boost the return experience and keep them loyal.
The right platform can shape every return experience into one that encourages additional shopping while mitigating the risk of loss.
To understand what a customer wants in a return is to know the shopper personally — a task where AI and predictive analytics step into the limelight. Appriss Retail champions a forward-thinking approach: leverage technology to stay a step ahead of customer behavior, rather than merely responding to it.
Predictive analytics harnesses the power of shopper feedback and data from past transactions to tailor the return process to individual needs. This approach not only pinpoints what customers are looking for but also anticipates their future expectations, refining its insights with every piece of feedback.
A more front-facing factor of the shopper experience in-store and online is how retailers support associates and call centers. Technology can help managers coach and bridge this interaction.
AI-powered platforms can analyze interactions between employees and customers to identify any gaps in training or highlight associates in need of additional help. The technology effectively helps managers coach associates. Other support measures include:
Prioritize the customer experience. Coach associates on how to listen first, handle customer complaints, and resolve issues stress-free.
To understand what a customer wants in a return is to know the shopper personally — a task where AI and predictive analytics step into the limelight.
There are several tactics retailers can deploy to keep both associates and shoppers happy during a return. Data analytics that integrate shopper insights into the return process, along with AI and automation to personalize customer interactions, are delivering a positive impact on returns.
Utilizing mobile apps and digital platforms can help train associates via modules and offer real-time feedback, while also aiding more personalized and less rigid return policies.
At the heart of this transformation is technology. It's not just about smoothing out bumps in the road; it's about paving entirely new pathways to loyalty. With every thoughtful interaction and tailored return policy, technology is not just supporting a better return experience — it's creating a legion of loyal shoppers, one positive return at a time.