// AI_Search_Fixes_04

    Get your products assistants recommended by AI.

    Assistants recommend competitor products for questions your catalogue answers perfectly well. Product attributes that decide the match — sizing, materials, compatibility, certifications — exist in images, widgets or variant selectors rather than readable text and structured data.

    This page is for ecommerce brands whose products are absent from assistant shortlists. Assistants recommend competitor products for questions your catalogue answers perfectly well. Product attributes that decide the match — sizing, materials, compatibility, certifications — exist in images, widgets or variant selectors rather than readable text and structured data. The work below is the sequence we run when a client brings us this exact problem: diagnose against evidence rather than assumption, fix the underlying cause rather than the symptom, and measure the result on product mention count across a fixed recommendation probe set.

    // Key_Takeaways

    • Assistants recommend competitor products for questions your catalogue answers perfectly well.
    • Product attributes that decide the match — sizing, materials, compatibility, certifications — exist in images, widgets or variant selectors rather than readable text and structured data.
    • What changes: your products get named in shortlist answers with the correct attributes attached, and the collection pages behind them capture the follow-up click.
    • How we prove it: product mention count across a fixed recommendation probe set.

    Product attributes that decide the match — sizing, materials, compatibility, certifications — exist in images, widgets or variant selectors rather than readable text and structured data.

    — Arise GEO, Get your products recommended by AI assistants

    Your products get named in shortlist answers with the correct attributes attached, and the collection pages behind them capture the follow-up click.

    — Arise GEO, Get your products recommended by AI assistants
    24 hours
    Scoped response
    $4,500
    Forensic audit
    90 days
    Execution plan
    180-day
    Money-back window
    // Symptom

    What this looks like from the inside

    Assistants recommend competitor products for questions your catalogue answers perfectly well. It is usually noticed late, because the reporting most teams have was built for a search landscape where the click was the only outcome worth counting. Product attributes that decide the match — sizing, materials, compatibility, certifications — exist in images, widgets or variant selectors rather than readable text and structured data.

    • Evidence gathered before any recommendation
    • Cause separated from symptom
    • Scope agreed in writing before work starts
    • No engagement recommended if the data does not support one
    // Method

    How we actually fix it

    Four steps, run in order. Each one produces an artefact you keep, whether or not you continue with us.

    • Audit attribute coverage across product templates against the questions buyers actually ask
    • Move decisive attributes into on-page text and Product schema
    • Build constraint-shaped collection pages that answer the buying question directly
    • Re-probe recommendation queries and track product-level mentions
    // Outcome

    What changes when it works

    Your products get named in shortlist answers with the correct attributes attached, and the collection pages behind them capture the follow-up click. We report against product mention count across a fixed recommendation probe set. — set as a baseline before anything ships, so the effect of the work is separable from seasonality and from everything else running in parallel.

    • Baseline captured before work begins
    • Matched before-and-after measurement windows
    • Reporting by segment, not in aggregate
    • Findings documented whether positive or not
    // Start here

    The cheapest way to find out

    Run the free AI visibility check first. It takes a minute, needs no signup beyond an email, and tells you whether this is genuinely your problem before anyone talks about a fee. If it is, the forensic audit is $4,500 and covers the full diagnosis with a 90-day execution plan.

    • Free visibility check, instant results
    • $4,500 forensic audit with 90-day plan
    • 24-hour scoped response on enquiries
    • 180-day money-back window on retainers
    // The_Contract

    The 180-day money-back guarantee.

    We can promise this because our methodology already works. Hundreds of pages now sit in position #1 across our clients' catalogs. The risk shouldn't be on you — it's on us.

    • 01We run the full 10-stage audit and deliver a sequenced 90-day plan.
    • 02You implement our recommendations (or hire us to implement them).
    • 03If you don't see measurable ranking and revenue improvement in 3–6 months — we refund you. In full.
    Lock in your audit slot →
    // Frequently_Asked

    Questions about this engagement.

    How do I get my products recommended by ChatGPT?+

    Product attributes that decide the match — sizing, materials, compatibility, certifications — exist in images, widgets or variant selectors rather than readable text and structured data. The practical answer is to diagnose before acting: audit attribute coverage across product templates against the questions buyers actually ask, then move decisive attributes into on-page text and Product schema. Your products get named in shortlist answers with the correct attributes attached, and the collection pages behind them capture the follow-up click.

    How long does this take to show results?+

    Long-tail and comparison questions typically move within 30–90 days of the fix shipping. Broad category questions take longer because they depend on corroboration accumulating outside your own site, which you influence but do not control.

    What does it cost?+

    The forensic audit is $4,500 and includes the full diagnosis plus a prioritised 90-day plan you can execute yourself. Ongoing engagements are scoped per brand. Implement our plan and if you do not see movement in 3–6 months, we refund our fees in full.

    Can we do this in-house?+

    Often, yes — and the audit is deliberately written so you can. Most teams have the capability but lack the diagnostic layer and the measurement, which is what makes the work land on the right pages in the right order.

    How do you measure success here?+

    Product mention count across a fixed recommendation probe set. Baselines are captured before anything ships and reported by segment, so improvement is attributable rather than assumed.

    Is this different from regular SEO?+

    It shares the technical groundwork but changes the target. Classic SEO competes for a position in a list of links; this competes to be the source a model uses and names, which rewards explicit data, honest qualifiers, named expertise and independent corroboration.

    Get your products recommended by AI assistants — start with the free check.

    Audits scoped within 24 hours. Results within 90 days, or your money back.

    Request Your Audit →