AI Chatbot Development for E-commerce
Deflecting a ticket is not the same as answering the question.
Most e-commerce support volume is order status, returns, sizing, and delivery timing. A chatbot that cannot look up a real order just delays the ticket. We build assistants that authenticate the customer, query your store, and resolve the request — or hand off with the full context already gathered.
- In your content
- GroundedIn your content
- Availability
- 24/7Availability
- Every question
- LoggedEvery question
Typical stack
- Next.js
- OpenAI
- RAG
- Intercom
- Webhooks
What this handles for e-commerce brands
- Answer order status and tracking questions with a live lookup against your store
- Initiate returns and exchanges, generating labels within your policy rules
- Answer sizing, materials, compatibility, and care questions from product data
- Recover abandoned carts by answering the specific objection blocking checkout
The bulk of routine tickets resolved instantly, with agents handling only what genuinely needs them.
The e-commerce problem underneath it
E-commerce volume scales faster than the team handling it. Support tickets, returns, supplier updates, product content, and channel reconciliation all grow linearly with orders — and all of them are largely mechanical. AI systems absorb that growth without proportional hiring.
- The same 'where is my order' question dominates support volume around the clock
- Returns and exchanges involve several systems and a lot of copy-paste
- Product descriptions and attributes are a bottleneck on every new range
- Inventory and pricing live in different places across marketplaces and your store
Inside an AI chatbot
We ground the bot in your actual content and give it firm boundaries. It answers what it can support with a source, captures context for anything else, and escalates to a person with the full conversation attached. We also instrument what people ask, because that log is one of the most useful research assets a business can have.
- Retrieval-grounded answers drawn from your site, docs, and policy content
- Lead capture that reads as a natural part of the conversation
- Live handoff to human agents with full conversation context carried over
- Order, booking, and account lookups via authenticated API calls
- Multilingual support with automatic language detection
- Conversation analytics highlighting the gaps in your content
What ships with the engagement
- Embeddable widget matched to your brand styling
- Grounding corpus with a refresh process for content changes
- Escalation rules and routing into your support tooling
- Conversation dashboard with search and tagging
- Monthly gap report showing questions the bot could not answer
AI Chatbot Development for E-commerce — questions
- How does it verify a customer before showing order details?
- Order number plus email or postcode, matching the verification your support team already uses. Logged-in customers on your storefront are identified from the session, so no verification step is needed at all.
- Can it process a refund?
- Within limits you set — value thresholds, time windows, product categories. Anything outside them is prepared for an agent with the case already assembled, so approving it takes one click rather than an investigation.
- How do you stop it inventing answers?
- It answers only from retrieved content, and when retrieval comes back empty it says it does not know and offers a handoff. We test this explicitly with questions we know are not covered in the corpus.
- Can it hand over to a real person?
- Yes, into Intercom, Zendesk, Crisp, or a plain shared inbox — carrying the whole conversation so the customer does not repeat themselves.
AI Chatbot Development in other sectors
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