Shoppers ask instead of search.
Instead of typing “tumbler 30 oz” and scrolling, a shopper types what they need: “something that keeps coffee hot on my commute and fits my car.”
The short version.
The assistant does the research.
It reads the item pages for the shopper, compares them against the request and comes back with a short list and a grounded reason for each pick.
It can only suggest what it understands.
A great product with a vague page is hard to recommend. If the facts aren't inputted where the assistant looks, it can't match them to the shopper’s question.
What a shopper sees, and what Sparky reads.
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Attributes: the facts it filters on
Structured dataCapacity, material, dishwasher safe. To a shopper these are details. To the assistant they're the filter. A blank field reads as “unknown”, and unknown items tend to get left out.
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Claims: what it can repeat
Answerable content“Fits most cup holders” in a bullet is hard to check against “fits my car.” Put the claim in plain words, with the number that backs it, in a field the assistant can match.
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Proof: what it can point to
Reviews & Q&AAssistants lean on what other shoppers said. Reviews and answered questions give it something to cite when it recommends you, and unanswered ones leave a gap.
Search versus ask.
SearchAsk an assistant
The shopper typesKeywords/PhrasesDescribe your situation and what you are solving for
Who reads the listingsThe shopper, scrolling a gridThe assistant, before the shopper sees anything
What comes backPages of resultsA few picks, each with a cited reason
What helps you show upKeywords, sales history, adsComplete facts that match the need
A blank field meansNot much, if the photos do the workThe assistant can't confirm it, so it may ignore your item
The words, in plain English.
- Assistant
- A chat you can ask questions in, like Sparky in the Walmart app. It answers and suggests; you still decide and buy.
- Agent
- An assistant that takes steps for you, not just answers: comparing options, building a cart, reordering. “Agentic” just means “able to act.”
- Structured attribution data
- Facts stored in labeled fields (capacity: 30 oz) rather than buried in a paragraph. It's the easiest thing for software to read with confidence.
- Answerable content
- Copy that answers the questions shoppers ask, in their words, with the specifics: “fits cup holders up to 3.2 in wide,” not “fits most.”
- Grounding
- The assistant sticking to what it can find on the page, so it doesn't make things up. It's why a blank field turns into a “can't confirm.”
- Adaptive Content
- Seasons turn, trends spike, categories shift, and stale copy gets left behind. We keep your listings in step with the market and update copy whenever demand moves.
What we do about it.
Ask the questions your shoppers ask
We run the real questions in your category and record why items come back to understand your gaps.
Fill the fields that decide it
An attribute audit against the category spec, item by item, ranked by the questions each blank field doesn't answer.
Rewrite claims so they can be matched
Titles, key features, and descriptions written around real use cases and shopper questions, in the shopper’s words, so AI agents can match your product to intent.
Build the proof
Review programs for thin items and answers for the questions already sitting on your pages unanswered.
Keep the basics winning
An assistant won't push an item that's out of stock or losing the Buy Box. In-stock and offer health stay key to our strategy.
Watch and adapt
We watch the signals (trends, competitors, category shifts) and update your copy the moment they move, so your listings always match how people and AI agents search.
Ask us what Sparky says about you.
We'll run the questions your shoppers ask, and show you where your items drop out.
hello@lunyr.ai
Bentonville, Arkansas
Not quite your setup?
The other three practices.