Customer service automation in retail starts with how you handle a return

Marcus ordered a jacket online, received the wrong size, and picked up the phone. An automated voice greeted him, asked for his order number, confirmed the item, checked return eligibility, and initiated a refund to his original payment method, all without a single transfer. When he asked about an exchange, the system offered one and confirmed his preferred size. Two minutes later, a return label was in his inbox and a replacement was on its way.

That experience is table stakes for retail brands competing in an environment where switching costs are essentially zero. According to the National Retail Federation’s¹ (NRF) 2025 Retail Returns Landscape report, 71% of shoppers say that after a poor returns experience, they are less likely to shop with that retailer again, up from 67% in 2024. The report also states that 80% tell friends and family about a bad return experience.

The financial context sharpens the stakes further. U.S. retailers project nearly $850 billion in total merchandise returns in 2025, according to the NRF. That volume is an enormous operational challenge, but it is also a disproportionate loyalty opportunity. Retailers who resolve returns efficiently, without asking customers to repeat themselves or wait in silence for a human to become available, are the ones turning a friction moment into a reason to stay.

Why retail churn keeps climbing despite growing AI investment

Retail churn is a persistent problem, and post-purchase service is consistently among its primary drivers. Research from Bain & Company² has reported that a 5% increase in customer retention can increase profits by 25% to 95%, depending on the industry.

The returns process exposes every weakness in a disconnected operating model:

Voice bots handle the first question, then transfer without context. The customer repeats their order number, their name, and their issue to a human agent who has no record of the previous interaction. The NRF report also shows that 76% of consumers are more likely to choose a return option that provides an instant refund or exchange. Any additional step in the resolution path works directly against that expectation.

Refund execution runs in a separate system from customer communication. The agent confirms the return verbally, but the inventory adjustment and payment reversal run on different timelines. The customer ends the call uncertain about when the money will arrive, which is exactly the uncertainty that drives negative word of mouth.

Fraud checks delay legitimate returns. Without real-time cross-referencing of order history and return patterns, blanket restriction policies frustrate good customers while only partially addressing the 9% of all returns the NRF report identifies as fraudulent.

Human experts absorb the emotional weight of what should be a routine transaction. An agent who has spent the morning logging data and checking policy eligibility arrives at a frustrated customer’s call with depleted capacity for the empathy that would resolve the situation well.

How a connected return journey changes the customer outcome

The returns experience Marcus had at the opening of this article is achievable today, but only when an AI voice agent is connected to back-office execution rather than scripted to gather information and transfer. That connection is the meaningful difference.

In a connected system, the customer’s intent, returning an item, triggers an orchestrated sequence that spans the front and back office at the same time. The voice agent retrieves order details and delivery date, checks the retailer’s return policy against the specific SKU, and if the return qualifies, the back-office layer initiates the refund to the original payment method, triggers the return label, and adjusts inventory, all within the same conversation.[Quebra da Disposição de Texto][Quebra da Disposição de Texto]The human experts only enters the interaction if an exception arises, such as a high-value item requiring manual review or a fraud signal that warrants a judgment call.

The practical value of this structure is that it eliminates the wait state most customers associate with returns. Human experts are freed for interactions where their judgment and warmth change the outcome, and the experience holds up consistently regardless of call volume. That consistency is what loyalty is built on, particularly in a high-churn category where customers have no shortage of alternatives.

Where AI becomes a genuine force multiplier for retail service teams

The human side of returns carries a cost when AI handles only intake. Connected workflows enable AI agents to manage routine steps while human agents use judgment and deliver empathy.

An agent who spent the morning entering order data and checking eligibility arrives at a complex escalation without the mental energy to handle it well. An agent whose AI layer has already resolved that work arrives at the frustrated customer’s call with the full capacity needed to listen and solve the problem.

TP.ai Connect is TP’s human experts + AI orchestration layer for front- and back-office operations. It coordinates people, AI agents and workflows to support customer care and back-office fulfillment.

For retail leaders, the governance layer matters in equal measure. TP.ai Connect provides auditable visibility into operations, with governance and compliance by design. It keeps human experts in control where precision matters.

What the outcome looks like across live deployments

TP.ai Connect reports the following operating outcomes across client environments:

• Up to 80% reduction in QA effort

• Approximately 60% faster deployments

• Approximately 70% frictionless resolution

Every return is a loyalty decision waiting to be made

Customers judge a return experience by whether their problem was resolved quickly and whether they felt treated fairly. A return handled in two minutes by a voice agent that knows their order, checks their eligibility, and executes the refund within the same conversation answers both of those tests. A return that requires a transfer, a repeated order number, and a follow-up call to confirm the refund arrived answers them in the opposite direction.

With 71% of shoppers less likely to return after a poor returns experience, retailers need an operating model that connects AI and human expertise across the journey. TP calls this orchestrated intelligence for what matters most.

In 2026, TP announced that its AI orchestration solution, now presented as TP.ai Connect, was recognized by the Business Intelligence Group’s AI Excellence Awards in the Agentic AI category. TP also continues to strengthen its responsible AI governance foundation through BSI certification for its ISO/IEC 42001:2023 AI Management System, underscoring the operational discipline, management standards, and trust framework clients expect.

See how TP turns your returns process into a retention advantage. Explore TP.ai Connect and learn how TP’s hybrid workforce, combining AI and human operating model, can transform your customer post-purchase experience.

Sources:

1) National Retail Federation’s 2025 Retail Returns Landscape report: 71% of shoppers say that, after a poor returns experience, they are less likely to shop with that retailer again, up from 67% in 2024.

2) Bain & Company: 5% increase in customer retention can increase profits by 25% to 95%, depending on the industry