RAG for eCommerce

Reduce support bottlenecks with retrieval-augmented chatbots

RAG combines search with AI so your chatbot answers from your product catalog, policies, and order data. The result is faster resolutions, fewer repetitive tickets, and more confident shoppers.

24/7 supportPolicy-accurate answersGuided escalations
RAG for eCommerce

Common bottlenecks

Where support queues pile up

  • Order status and shipping ETA updates.
  • Returns, exchanges, and refund clarifications.
  • Product fit, compatibility, and stock questions.
  • Promo code issues and cart troubleshooting.

Why RAG works

Answers grounded in storefront data

  • Pulls from product pages, FAQs, and policy docs.
  • Uses order systems for personalized updates.
  • Escalates when confidence is low or a human is needed.
  • Keeps the tone consistent across channels.
RAG for eCommerce

Customer experience

What a helpful RAG chatbot can handle

Shopping guidance

Compare products, recommend alternatives, and answer sizing or compatibility questions without drifting from your catalog.

Post-purchase support

Provide order updates, start returns, and explain warranty steps with the right policy attached to each request.

Always-on help

Offer 24/7 answers and hand off to a human for exceptions.

Operational impact

Signals workload is shrinking

  • Higher self-serve resolution rates.
  • Shorter average handle time for agents.
  • Better CSAT with fewer repeat contacts.

Conversion impact

Where it helps revenue

  • Fewer abandoned carts after quick answers.
  • Higher AOV from guided recommendations.
  • More confident repeat purchases.

Data needed

Connect the right sources

  • Product catalog and variant data.
  • Returns, shipping, and warranty policies.
  • Order management updates and FAQs.

Implementation path

A practical rollout plan

  1. 1. Map use cases. Identify top support questions and data needed.
  2. 2. Prepare sources. Clean policy docs, product data, and FAQs.
  3. 3. Add guardrails. Define escalation triggers and tone guidelines.
  4. 4. Measure outcomes. Track deflection, CSAT, and conversion impact.
RAG for eCommerce

Working with Net17

How we help teams build RAG chatbots

Net17 helps businesses design and implement RAG chatbots that align with their storefront stack, data sources, and support workflows. If you want a practical assessment or a pilot, we can map what success looks like for your team.

Talk to the teamShare your current help desk workflow and data sources.