Customer service automation
AI voice agents and conversational AI can support common customer queries, triage requests and route customers to the right next step.
Retail and eCommerce
Resolve order and returns queries with less manual handling
ETT connects order status, returns eligibility and service escalation to the systems that can actually resolve the request. Capacity is designed against your peak demand, and anything outside policy routes to a person.
Where we start
The workflows we lead with in this sector
Proposed use cases based on how this work is usually organized. None of these is a published client result.
Order status
Answering “where is my order” from the order management and carrier systems rather than a static FAQ, and saying plainly when the answer is not yet known.
Return eligibility
Checking the policy against the actual order — date, item, condition flag, channel — and either starting the return or explaining why it does not qualify.
Service escalation
Recognizing when a case needs a person and handing it over with the order, the history and what has already been tried, so the customer does not start again.
How it would be measured
Measures to agree before anything is built
A baseline taken after the fact is not a baseline. These are the measures we would ask you to agree, and what each one means, so the before-and-after comparison holds up.
| Measure | What it means |
|---|---|
| Resolution rate | Interactions where the customer's request was completed, not merely answered. |
| Repeat contact | Contacts from the same customer about the same order within an agreed window, typically seven days. |
| Handling time | Time from first contact to resolution, measured for automated and assisted paths separately. |
| Customer satisfaction | Post-interaction score, reported separately for handled and escalated cases. |
Who this is for
Customer Service Director or Head of eCommerce Operations, with the contact-center lead and whoever owns the order management platform.
What has to be true first
- API access to order management, returns and carrier tracking
- Current returns policy in a form a system can apply, including the exceptions
- An agreed peak-demand profile to design capacity against
The challenge
What teams in this sector face
Retail teams often operate under constant service pressure.
Customers expect quick answers across calls, chat, email and digital channels. They want order updates, return support, stock information, loyalty help and personalized responses without long waits or repeated handovers.
Behind the scenes, the work is rarely simple. Order data, warehouse systems, CRM records, POS platforms, contact center tools and customer service processes do not always connect cleanly. That creates friction for teams and frustration for customers.
ETT helps retail organizations identify where AI and automation can reduce that friction, connect the right systems and turn customer interactions into useful business action.
Where AI can support
Practical use cases
Order tracking and WISMO handling
AI can help customers get updates on order status, delivery progress and next steps without relying on manual agent handling.
Returns and refunds workflows
Automation can support repeatable returns, refund checks, approvals, updates and internal routing across connected systems.
Inventory and product queries
AI can help surface product, stock or store information from the relevant systems and present it in a more useful way.
Customer conversation insight
Calls, chats and support messages can reveal recurring issues, service gaps, sentiment trends and opportunities to improve retail operations.
Example workflow
Example workflow: from customer query to action
One request, end to end. Each stage shows what happens and the ETT solution behind it, with people kept in control wherever judgement is needed.
Illustrative workflow. The actions, integrations and controls are defined for each deployment. This is not a customer result.
- 01Customer queryConversational AI and Voice Automation
- 02Intent recognitionConversational AI and Voice Automation
- 03System checkData and Analytics for AI
- 04Workflow triggerAgentic AI and Automation
- 05Customer updateConversational AI and Voice Automation
- 06Insight capturedData and Analytics for AI
Each stage in detail below, with the systems involved and where a person stays in control.
Customer query
A shopper asks about an order, a return or stock by voice or chat. Capacity is designed against your measured peak-day volumes and agreed in the contract, so demand spikes are planned for rather than hoped through.
Typical technologiesPolyAIWeb & app chatContact center
How ETT helpsConversational AI and Voice AutomationIntent recognition
The agent works out what they actually need, and which systems and policies the request touches. One sentence becomes a structured, routable request.
Typical technologiesOpenAIGetVocal AI
How ETT helpsConversational AI and Voice AutomationSystem check
It checks order status, stock or returns eligibility live across OMS, CRM and the warehouse, with no agent chasing tabs. The customer gets a real answer, not a callback.
Typical technologiesOMS / WMSCRMDatabricks
How ETT helpsData and Analytics for AIWorkflow trigger
The right action fires: a return is started, a replacement ordered or a refund queued, inside your systems of record. The conversation finally does something.
Typical technologiesUiPathPayment & OMS APIs
How ETT helpsAgentic AI and AutomationCustomer update
The shopper gets a clear, accurate update straight away, and complex cases hand off to an agent with the context attached. Nobody has to repeat themselves.
Typical technologiesPolyAIEmail / SMS
How ETT helpsConversational AI and Voice AutomationInsight captured
The interaction becomes data, so recurring issues, sentiment and service gaps surface and operations can fix the root cause. Every contact makes the next one less likely.
Typical technologiesDatabricksAnalytics dashboards
How ETT helpsData and Analytics for AIWhen it cannot complete
The order cannot be found, the returns policy has no clear answer, or the carrier feed is down. The customer is told plainly what is not known, the case is handed to an agent with the full history, and no eligibility decision is guessed at.
Where to start
One query type, end to end, sized for peak
Start with the highest-volume query — usually order status. We design it against your actual peak-day volumes, connect it to the systems that resolve it, and measure resolution and repeat contact rather than deflection alone. Volume limits are set by the design and the contract, not asserted as unlimited.
The solutions involved
- Conversational AI and Voice AutomationFor handling high-volume customer queries, order updates, delivery requests and repeatable service interactions.
- Agentic AI and AutomationFor connecting customer interactions to workflows, approvals, system updates and internal routing.
- Data and Analytics for AIFor turning customer conversations, order data and service activity into clearer insight.
- vCISO for AIFor governance, voice data privacy, customer data protection, payment-related workflows and AI risk controls.
- AI Strategy and DeliveryFor identifying which retail use cases should be prioritized and how AI should move from pilot to production.
Analect: fewer tokens, less storage, proven on your documents.
ExploreFAQs
Common questions
How can AI automation support retail customer service?
It can help retail teams handle common queries, triage requests, provide order updates, route issues and support agents with better context.
What are “where is my order” queries?
WISMO stands for 'Where is my order?' These are common delivery status queries that can create high volumes of contact for retail and eCommerce teams.
Can AI help with returns and refunds?
Yes. AI and workflow automation can support repeatable parts of returns and refund processes, such as gathering information, checking order details, routing approvals and updating customers.
Does retail AI need to integrate with existing systems?
Yes. It is most useful when it connects with systems such as CRM, order management, warehouse management, POS, contact center tools and customer support platforms.
Can conversational AI replace retail customer service teams?
No. It should support teams by handling suitable repeatable interactions, improving routing and escalating more complex or sensitive cases to people.
Ready to reduce friction across your retail operations?
Request an AI session to explore where AI automation could support customer service, order queries, returns, workflows and operational insight across your retail environment.
Around four minutes. Indicative guidance based on your answers.