Backpacks under $100: what nine Cuebase AI searches returned

JanSport appeared in six answers. Laptop fit was the gap.

We ran three backpack questions through Cuebase’s ChatGPT tracking, three times each. JanSport appeared in all three general-backpack answers and all three commuting answers. It appeared in none of the answers that asked for a 15-inch laptop fit.

That is the useful part of a visibility report: seeing which buying question needs a closer look. The overall mention rate was 67%. The laptop question showed 0%.

The three questions we tracked

Each prompt kept the budget below $100 and named the US as the destination. We changed one buying need: everyday use, laptop fit, or commuting.

1. What is a good everyday backpack under $100 available in the US?
2. What is a good everyday backpack under $100 that fits a 15-inch laptop and is available in the US?
3. What is a good everyday backpack under $100 for commuting to work, available in the US?

We chose JanSport as the baseline and tracked Osprey, The North Face, Herschel, and Fjallraven alongside it. Those five names define the comparison. They do not cover every brand the answers could recommend.

What Cuebase found

Cuebase counted eleven brand appearances across this tracked set: six for JanSport, three for Osprey, and two for Herschel. JanSport’s share was therefore 6 ÷ 11, or 54.5%. That is a share of these tracked mentions, not a share of backpack sales or all AI recommendations.

The screenshot rounds the figures to whole percentages. Its average-position figure describes first appearance among tracked brands. It is not a universal product rank.

The overall number hid a missing buying question

The last column lists names found across each prompt’s three responses. A listed brand did not necessarily appear in every response.

The next step is to inspect the laptop question, not assume the product lacks a laptop sleeve. JanSport’s own SuperBreak Plus listing describes a padded sleeve for a 15-inch laptop. That fact was available in the manufacturer’s product listing reviewed for this article. Our small test cannot explain why the brand was absent from those answers.

For your store, use Cuebase’s Queries to win table to find a weak question. Then check the relevant product page and source evidence. Correct an unclear or missing fact if you find one. If the facts are already clear, keep observing before making a speculative edit.

A brand mention did not mean a link to the US store

Five answers contained a link to JanSport’s European SuperBreak collection. None linked to the tracked jansport.com domain. Cuebase therefore reported a 0% citation rate for that domain, alongside the 67% brand mention rate.

Both numbers are useful. One says the brand appeared; the other says the specific website was not cited. Naming the US in a prompt did not ensure that every returned link was a US storefront. We also recorded links to retailer, marketplace, publisher, and blog pages.

Check the destination before treating a citation as a route to your checkout. We have not verified that every suggested item was in stock, below $100, or deliverable to the US. The budget was a test condition, not a verified price claim about every result.

The answers also exposed a gap in our competitor list

MATEIN appeared in seven of the nine answers, including all three laptop-fit answers. It was outside our initial five-brand comparison. Cuebase’s laptop row showed no tracked top rival because none of those five brands appeared in that row’s answers.

An empty rival cell does not mean there were no recommendations. Review the answer evidence when you choose competitors, and expand the next tracking set when a relevant name keeps appearing. Keep the original set’s results separate so the share-of-voice denominator remains clear.

Run the same workflow for your Shopify store

1. Add a small question set

   Open Share of Voice in Cuebase. Add a general product question, an important attribute question, and a use-case question. Keep their wording fixed. Our ten-question worksheet gives you a starting set.

2. Choose the competitors and domains

   Add names shoppers genuinely compare with your store. Check the domains, including regional differences. Your chosen list determines the share-of-voice comparison.

3. Run a probe and inspect the weak query

   Use Run first probe, or Run probe now when a report already exists. Read results by engine and question before drawing a conclusion from the headline percentage.

4. Connect the finding to catalog work

   Open the relevant product in Catalog Readiness. Check the flagged fields, verify the facts, and review suggestions before applying changes. Use our first-ten product guide to choose a manageable batch.

Method and evidence

We used Cuebase’s existing live probe runner, brand detector, and report calculations in an isolated research workspace. No merchant account or catalog was changed. The screenshot renders the actual app view with the saved results; it is a read-only research capture.

All nine requests succeeded on 12 October 2026, with provider timestamps from 11:54:14 to 11:54:23 UTC. We used Cuebase’s ChatGPT engine through DataForSEO’s LLM Responses API. The returned model was gpt-4.1-mini-2025-04-14, with web search enabled and a 400-token output cap. The requests used English prompts with a US destination; no separate tester-location control was set.

Three rounds in a short time window show a limited snapshot, not long-term stability. The answer cap also limits how many products can appear. We did not test other engines, measure clicks or sales, or change product pages. No visibility gain or cause is claimed.

For the definitions behind the report, read our guide to AI share of voice.