A shopper can like your product, trust your brand, and be ready to buy—yet still leave because one simple question remains unanswered.
They may wonder whether a dress runs small, whether a supplement is suitable for sensitive skin, whether a spare part fits their model, or whether an item will arrive before a birthday. These questions rarely feel dramatic, but they create hesitation at the most important moment in the customer journey.
An AI agent for eCommerce can reduce that hesitation by answering product questions instantly, using your catalog, product pages, policies, and business rules. Instead of waiting for an email reply or searching through multiple pages, shoppers get relevant guidance when they are most likely to act.
Here are seven common product questions that stop customers from buying—and how a well-configured AI agent can answer them.
1. “Which size should I choose?”
Sizing uncertainty is one of the biggest barriers in fashion, footwear, sports equipment, and furniture. A shopper may like a product but hesitate because choosing the wrong size means waiting for a return, exchanging the product, or missing an event.
Size charts help, but they do not always solve the problem. Customers often need guidance based on how the product fits: Is it oversized? Does it stretch? Should they size down? Is it shorter than standard?
A good eCommerce AI agent can answer:
“This jacket has a tailored fit. If you usually wear a medium but prefer extra room for layering, choose a large.”
It can also ask a useful follow-up question, such as whether the customer prefers a fitted or relaxed style. This turns a static size chart into a helpful conversation that reflects the customer’s actual concern.
The key is reliable source material. The assistant should use your size guide, product descriptions, return notes, and merchant instructions—not make assumptions from general product knowledge.
2. “Is this product right for me?”
Customers rarely search for a product using the exact words in your title. They search based on their goal or situation:
“Which moisturizer is best for dry winter skin?”
“What laptop should I buy for video editing?”
“Which stroller is easiest for public transport?”
“What mattress is better for back pain?”
“Which coffee machine is easiest for beginners?”
A category page can show several options, but it may not explain why one product is more suitable than another. That leaves customers to interpret specifications, reviews, and prices themselves.
An AI agent can turn a broad question into a short recommendation process:
“Are you mainly preparing espresso, filter coffee, or both?” “Do you prefer a compact machine or a larger model?” “Is ease of cleaning important?”
After two or three clarifying questions, the assistant can suggest relevant products from your catalog and explain the reasoning in simple terms.
That reasoning matters. “Here is our best-selling espresso machine” is not as persuasive as:
“This model is a good fit because you want espresso, have limited counter space, and prefer minimal maintenance. It has a built-in grinder and a removable water tank.”
This is where an AI agent becomes more useful than a basic chatbot. It can guide product discovery instead of simply repeating a FAQ.
3. “Is it compatible with what I already have?”
Compatibility questions affect many categories, including electronics, home improvement, automotive parts, software, accessories, and replacement components.
A customer might ask:
“Will this case fit the latest phone model?”
“Is this strap compatible with my watch?”
“Does this part work with my dishwasher?”
“Can I use this accessory with the previous version?”
“Is this plugin compatible with my current platform?”
These questions are high-risk because a wrong answer can cause a return, complaint, or poor review. Customers therefore tend to pause until they feel certain.
An eCommerce AI agent can check compatibility information from your product documentation, specifications, SKU relationships, or merchant-provided guides. It can also avoid overconfident answers when the information is incomplete.
For example:
“This strap is compatible with the 42 mm version listed in your product description. It is not compatible with the older 38 mm model. If you share your exact model number, I can help you confirm.”
That answer is useful for two reasons: it gives the customer a practical next step, and it avoids inventing certainty where none exists.
For Liliwi, this kind of accuracy depends on the merchant’s own data. Liliwi is positioned around training an AI agent with business-specific information so it can support customers using the store’s content and rules.
4. “Is it in stock—and when will it arrive?”
Availability and delivery timing are decisive questions, especially when the purchase is urgent.
A generic “In stock” label may not answer the shopper’s real concern. They may need to know:
Is the right size available?
Can it be delivered to their country?
Is express shipping possible?
Will it arrive before a particular date?
What happens if they order today?
Is a pre-order available if the item is sold out?
An AI agent connected to store information can answer these questions in context rather than sending the customer to a separate shipping page.
For example:
“The blue version in size M is currently available. Standard delivery to France is listed as 2–4 business days, while express delivery is 1–2 business days.”
If the item is unavailable, the agent can preserve the sale by suggesting an alternative:
“That color is currently out of stock. The same model is available in navy and black, and the product page indicates that the same size and material apply.”
This is a valuable distinction between a chatbot that says “Please check the product page” and an agent that helps the shopper recover from a potential dead end.
Liliwi’s eCommerce positioning includes answering stock questions and supporting store actions within the shopping journey.
5. “What makes this product different from the others?”
Choice overload can be just as damaging as missing information. A customer may compare three similar products and still not understand which one is right for them.
The problem is common with:
Multiple product tiers
Similar-looking variants
Good/better/best pricing
Technical products
Products with small but important differences
Bundles, subscriptions, and accessories
A basic comparison table can help, but customers often do not want to study every row. They want a short explanation in plain language.
An AI agent can compare products based on the customer’s priorities:
“The Essential plan is best if you only need basic tracking. The Pro version adds advanced reporting and team access. Based on what you told me about managing three users, Pro is the more suitable option.”
For a physical product, the agent might say:
“Model A is lighter and easier to travel with. Model B has a larger capacity and longer battery life. If portability is your main priority, choose Model A. If you need longer use between charges, Model B is the better choice.”
The assistant should also know when not to compare. It should not criticize competitors, invent performance claims, or suggest that one product is better without source-based reasoning.
How to prepare your store
You do not need to automate every conversation at once. Start with the questions that create the most hesitation in your category.
For many stores, that means:
Review recent support tickets, customer emails, and live-chat transcripts.
Identify recurring product questions related to sizing, compatibility, stock, delivery, comparisons, price, and returns.
Make sure product descriptions and policies contain clear, current information.
Write simple merchant instructions for how the assistant should respond.
Test the assistant with difficult customer scenarios before launching.
Add escalation rules for exceptions, sensitive requests, and cases that require a human.
The better your source content and rules, the more useful your AI agent will be.
From unanswered questions to confident purchases
Shoppers do not always abandon a store because the product is wrong. Sometimes they leave because they cannot confirm that it is right.
By answering sizing, suitability, compatibility, stock, comparison, value, and return questions instantly, an AI agent helps customers move from hesitation to confidence.
