Sales
AI shopping assistant for your e-shop
Connect a chat assistant to your product catalog, sizing guides and shipping policy, so it answers from your own information first instead of guessing. Let it help shoppers compare products, find the right size and check delivery options. Show clearly that it is AI, hand over to a person for anything unusual, and review its conversations every week.
Effort:
Medium
Time saved:
Often 20–40% fewer pre-sale chats for your team (estimate; test it)
The problem today
Shoppers leave when they cannot quickly find out whether a product fits, works with what they already own or arrives in time. Large online retailers already run AI assistants that answer these questions around the clock. For a small e-shop, the affordable version is an off-the-shelf chat tool that reads your catalog and policies and passes harder questions to your team.
How it works, in plain words
Think of it as a new sales assistant who has read all your product pages and policies, and answers only from them.
What goes in: your product catalog, size guides, shipping and returns policy, and the questions shoppers ask most.
What the AI does: when a shopper types a question, it searches your own pages first, picks the relevant facts and writes a short answer, often with a link to the right product.
What a person checks: someone on your team reads a sample of chats every week, fixes wrong or missing information and takes over any chat handed on.
What comes out: faster answers in the chat window of your e-shop, fewer repeat emails and a clear list of gaps in your product data.
It only knows what you have written down, and it should never promise discounts, stock or delivery dates your system has not confirmed.
How it could work for businesses like yours
Illustrative examples, not client case studies.
A 15-person sportswear e-shop in Larissa
The team answers the same size and delivery questions by chat and email every evening. They would connect a chat assistant to their catalog and a new size guide, and route returns and complaints to a person. Over a three-month pilot they would track the share of chats solved without handover and whether size-related returns fall.
A 4-person digital agency in Patras that runs e-shops for clients
Several of its clients ask for "a chatbot" without having clean product data. The agency would make a short data clean-up the first step of every setup and test the assistant on 30 real questions per client before launch. A realistic first target could be correct answers to most of those test questions, checked by the client.
A family olive oil producer in Kalamata selling abroad
Buyers from Germany and the Netherlands ask about harvest dates, acidity and shipping costs, often outside Greek office hours. The producer would load product sheets and shipping rules in Greek, English and German, and pass wholesale requests to the owner. They would measure response time and how many foreign inquiries turn into orders.
How to do it, step by step
Collect the questions shoppers ask before buying. Go through chats, emails and phone notes from the last two months. Separate pre-sale questions (size, compatibility, materials, delivery) from after-sale ones.
Clean up your product data. The assistant is only as good as your catalog. Fill in missing sizes, materials, dimensions and stock status, and write a short sizing or compatibility guide where returns are common.
Choose a tool that answers from your content. Pick an e-shop chat tool that searches your own pages and documents first, then answers (this approach is called RAG). Switch off answers on topics you have not covered.
Set clear limits and a handover. Write down what it must never do, such as promise discounts, give medical advice or confirm stock it cannot see. Add a visible "talk to a person" option and say when your team replies.
Test with real questions before launch. Ask it 30–50 real questions in Greek and English, including tricky ones and Greeklish. Fix the catalog or the rules wherever it gets something wrong.
Run a 6–8 week pilot. Track how many chats it resolves, how many it hands over and whether returns for wrong size or wrong product go down. Read a sample of conversations every week.
Tools to consider
Tidio (Lyro): chat widget for small e-shops with an AI agent that answers from your FAQ and pages, and works with Shopify and WooCommerce. Caveat: check the quality of its Greek answers on your own questions before you go live.
Intercom (Fin): AI agent that answers from your help content and hands over to your team in the same inbox. Caveat: it is built for larger support teams, so it may be more than a small shop needs.
Shopify Inbox: chat for Shopify stores, with Shopify Magic suggested replies that can use product and order details. Caveat: it mainly suggests answers to your team rather than running conversations alone, and it works only on Shopify.
Data protection and GDPR
Shoppers type names, addresses, order numbers and sometimes health details into chat. Choose a tool with a data processing agreement, EU hosting or lawful transfers, and clear retention settings. Ask only for what the answer needs, and never ask for card details in chat. Tell visitors plainly that they are talking to an AI chatbot; the EU AI Act's transparency duties for such systems phase in through 2026–2027, and being clear now builds trust. Update your privacy notice to mention the chat tool. Check with your DPO or legal advisor before launch.
Mistakes to avoid
Launching on a messy catalog, so the assistant gives wrong sizes or confirms products that are out of stock.
Hiding the human option, which frustrates shoppers with unusual questions and loses the sale.
Never reading the conversations, so the same wrong answer repeats for weeks.