Ecommerce

Answer order and returns questions from Shopify and Redo.

Support volume grows with order volume. The answer usually sits in Shopify or in the Redo return, and a person goes and finds it. Prana IQ maps the ticket types and names what an agent may draft first.

Shopify Redo Order status Returns

The problem

01

Tier-1 tickets outrun the people answering them.

The storefront and the returns portal both work. The gap is the lookup. Every repeat question costs a person a context switch, and the answer was already sitting in one of two systems.

What eats the queue

  • Order state lives in Shopify. The return lives in Redo.
  • The same questions repeat: where is it, can I exchange it, will it fit.
  • Policy edges get answered differently depending on who is on shift.
  • Macros go stale, so the team rewrites the same reply by hand.

What this closes

  • The agent resolves the ticket to the right Shopify order.
  • Returns and exchanges read from Redo, not from memory.
  • Answers stay grounded in your policy and your sizing reference.
  • A person reviews the draft. Nobody retypes the same reply twice.

What we build

02

Drafts grounded in the order, not in a guess.

An agent that reads the ticket, resolves the order, and writes a reply in your voice. It does not send on its own.

What we built

Ticket resolved to the Shopify order, including exchange orders
Return and exchange state read from Redo
Escalation queue for policy edges and anything outside standard cases
Reply drafts a person approves before they go out

2-week discovery

03

We name the ticket types before we build anything.

The audit is a specific map of this stack, the ticket mix, the policy edges, and the review gate. It is not a generic strategy deck.

1

Inventory

List Shopify, Redo, and every place a policy answer currently lives. Name who owns each login.

2

Trace

Walk one week of tickets from first message to resolution. Mark every manual lookup.

3

Sort

Separate what an agent may draft from what always goes to a person, and write down the policy edges.

4

Find

Name the ticket types to ground first, what stays manual, and what the build takes.

Proof

04

What we built for the support queue.

What we built

We built the agent that answers from the order instead of from memory. It resolves the ticket to the right Shopify order, including exchange orders, reads return and exchange state from Redo, and drafts the reply in your voice against your policy and your sizing reference.

It runs with the gate in place. The agent drafts, with a human review step before anything goes out, and policy edges escalate to a person rather than being guessed.

FAQ

05

Common questions

Two weeks. We map Shopify, Redo and your macros, then trace one week of tickets from first message to resolution. You get the ticket map and the build plan for your stack.

Shopify and Redo first. Shopify holds the order and the fulfilment state. Redo holds the return and the exchange. Both are built-in toolsets on the Prana IQ platform, so discovery starts with the systems you already run.

No. It drafts, with a human review step before anything goes out. Tools flagged for approval pause for a human before they run.

Least-privilege access. Credentials stay in your control. We sign an NDA and work inside your compliance requirements. We do not copy production logins into a shared vault we own.

It escalates. Discovery names the ticket types an agent may draft, the ones that always go to a person, and the policy edges where only your team decides.

Other use cases

06

What else we build

Ready to map the ticket path?

Book a call. We will show you the two-week scope for Shopify, Redo, and the questions your team answers twice.

Book a call See platform trust

An example build on the hosted Prana IQ platform.