A shopper is looking at a lamp they like. The price is right and the photos look good. But they can't tell whether it will fit on the shelf they have in mind, because nowhere does it say how tall it is.

In a physical shop they'd sort that out in ten seconds: pick it up, or ask someone. Online, they have to find the answer on their own. If they can't, they probably won't buy.

It's based on a real case from the Baymard Institute's usability testing: a shopper gave up on a lamp because she couldn't work out its height from the photos.

What happens when a question goes unanswered

Baymard has spent years watching real people shop online, and it describes three reactions when someone can't find what they need on a product page:

  • They leave the page, and sometimes the store.
  • They look for the answer elsewhere: another site, a forum, Google. From there, it's easy to end up buying somewhere else.
  • They guess. Sometimes they guess right. When they don't, disappointment follows, and in some cases a return that could have been avoided.

That last one is the most expensive, because the sale looked done. Something similar happens when the detail is there but wrong: in a Salsify survey of more than 2,700 shoppers in the US, Canada and the UK, carried out in October 2025, 45% had returned an online purchase because the product information was wrong or misleading.

The most striking thing in Baymard's testing is how often the product would have suited the person. The sale was lost over a fixable problem with the page, such as a detail that was missing or hard to find.

The questions that come up most

They vary with what you sell, but nearly all of them fall into a few groups:

  • Size and fit. "Will it fit if I'm usually a medium?", "Will it go in a 40 cm cupboard?"
  • Compatibility. "Does it work with my coffee machine?", "Will it work with my phone?"
  • Use. "Is it OK for trail running?", "Can it go in the dishwasher?"
  • Differences. "What does this one have that the one €20 cheaper doesn't?"
  • Availability. "Do you still have it in blue?", "Will it arrive before Friday?"

Notice that hardly any of these are solved by a nicer description. They're solved by specifics: a measurement, a list of compatible models, a plain sentence about what the product isn't for.

How to find out what your customers are asking

You don't have to guess. Most stores already have the clues, scattered across different places:

  • The messages you get. Emails, WhatsApp, social media. If several people have asked you the same thing, many more probably had the same question and left without asking.
  • Return reasons. "Not what I expected" nearly always hides a question the product page didn't answer.
  • Reviews. Comments like "I thought it would be bigger" tell you exactly which detail is missing.
  • Your store's search. What people search for and don't find, or search for in words your product pages never use.

An afternoon going through these four sources usually produces a short list of questions that keep coming back. Those are the ones costing you the most sales.

What to do about them

First, put the answer where the question comes up. If people ask about sizing, the answer belongs next to the size selector, not on an FAQ page nobody visits.

Second, fill the gaps in your catalogue. A measurement missing from one product page is usually missing from all the similar ones, so it's worth checking them by product family. How to prepare your catalogue for AI covers which details to have and how to organise them.

Third, spell out the differences between similar products. When someone is torn between two, they usually have the details of both; what they don't know is which one suits them. That's what helping customers choose is about.

And fourth, give people a way to ask there and then. A contact form that gets a reply the next day is too late, because the question comes up while the shopper is on the page.

Where a shopping assistant fits

That's what assistants like SmartShop AI are for. The shopper types their question in your store and gets an answer straight away, based on your catalogue: measurements, materials, which sizes and colours are left.

There's one limit worth being clear about: it's built to answer only from what's in your catalogue. If a detail isn't in your catalogue, it has nowhere to get it from. So the two go together: complete your product data, and give shoppers somewhere to ask.

It also works the other way round. From the Growth plan up, your dashboard shows what shoppers look for and can't find, so the questions they ask the assistant tell you which product page to improve.

In the end, every unanswered question is one the shopper would have asked out loud in a physical shop. Listening to them is one of the cheapest ways to sell more.