AI agents for customer support teams in retail

A parcel scan goes quiet at the depot and the first anyone hears is the third email from the shopper, because checking Royal Mail, Evri, and DPD scan histories order by order is nobody's scheduled job and it slides behind the live queue.

→An agent checks carrier status on every open order each morning, flags the parcels that have stalled past their window, and drafts the delivery update for your approval, so the shopper hears from you first.

Returns requests arrive in the shared inbox with no order number, a photo of the wrong item, and a policy that changed for the Christmas window, so each one takes a long read to work out whether it is eligible at all.

→An agent matches each return to the order and the policy in force on that date, sorts clear cases from doubtful ones, and attaches its reasoning, so you only decide the ones that genuinely need a person.

Faulty-goods claims stall at the supplier because the photos, receipt, and purchase date arrive in separate emails, and nobody keeps a list of which supplier claims are still waiting on a reply.

→An agent collects the evidence into one case record, drafts the supplier claim, and checks the open-claims list every week, so nothing sits unanswered and nobody chases from memory.

The same shopper writes in a third time about one order while the first two tickets sit unanswered behind the live queue, and the complaint reaches the area manager before it reaches the shift lead.

→An agent watches reply targets and repeat contacts through the day, flags tickets before they breach, and posts a short summary of the history to Slack so the right person steps in at the right moment.