Consumer Electronics / E-commerce

How GadgetHub grew AI visibility across markets

An online consumer electronics retailer noticed AI models favored larger competitors in product recommendations — and used Aivius's 6-step GEO engine to grow AI visibility and earn citations from multiple AI models.

Illustrative customer analytics dashboard.

Illustrative scenario. This case study is a composite based on typical outcomes for consumer electronics brands using Aivius. Specific metrics are directional, not exact.

Customer overview

CompanyGadgetHub
IndustryConsumer Electronics / E-commerce
ScaleOnline retailer, multiple markets
ChallengeAI models favored larger competitors when shoppers asked for product recommendations, leaving GadgetHub absent from AI answers across key buying-decision prompts

GadgetHub sells gadgets and tech products online to shoppers across multiple markets. When the team started asking AI models for product recommendations in their own category, they kept seeing larger competitors cited — and rarely themselves. They had no way to measure how often AI models mentioned them, which prompts mattered, or why rivals dominated the answers. Without a baseline, every content change was a guess.

Solution: Steps 1, 3, and 5 of the 6-step GEO engine

1

Market Competition Analysis

Aivius benchmarked GadgetHub's AI Share of Recommendation against key competitors. This revealed exactly where larger rivals were being cited in AI answers — and which high-intent buying prompts GadgetHub was missing entirely.

3

Prompt Research

The Prompt Research Tool surfaced the electronics-related prompts shoppers actually ask across AI models — from "best wireless earbuds under $100" to "which robot vacuum is worth it." GadgetHub prioritized the prompts with the strongest buying intent for immediate action.

5

Off-page Optimization

Aivius helped GadgetHub build off-page presence on tech review forums and Reddit — the sources AI models frequently cite. By earning mentions where shoppers research gadgets, GadgetHub expanded the citation-worthy footprint AI crawlers could draw on.

Implementation timeline

Month 1 — Benchmark AI share
Measured GadgetHub's AI Share of Recommendation against larger competitors and identified the high-intent buying prompts where rivals were being cited instead.
Month 2 — Research electronics prompts
Mapped the electronics-related prompts shoppers ask across AI models and prioritized the ones with the strongest buying intent for optimization.
Month 3-5 — Optimize content & build off-page presence
Optimized product content for AI crawlers with structured Q&A and citation-friendly summaries, while building off-page presence on tech review forums and Reddit.
Month 6 — Results measured
Grew AI visibility significantly, expanded presence across multiple markets, and earned citations from multiple AI models on buying-decision prompts.

Results

Grew
AI visibility significantly
Multiple
Markets with improved presence
★★★★★

"Aivius showed us exactly where AI search was underserving our category. We could see which buying prompts shoppers asked, which competitors got cited, and where we were invisible. That clarity let us focus on the content and off-page signals that actually moved the needle."

Head of Digital
GadgetHub

Get similar results for your brand

See how much AI visibility you're missing across your markets — and how to fix it with the 6-step GEO engine.

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