AI VISIBILITY ENGINEERING

Your US competitors are winning AI citations — and you have no systematic data on where, how often, or what's driving it

GEO Competitor Gap Analysis is the competitive intelligence foundation every serious AI visibility programme requires. Ignited Nepal tests 30 industry queries across ChatGPT, Perplexity, Google AI Overviews, Gemini, and Claude against three to five of your direct US competitors, documents every citation instance, builds a competitor citation matrix with frequency scores by engine and query type, audits the signals driving those citations, and delivers a prioritised action plan to close the gap. If your competitors are appearing in AI-generated responses and you are not — or if you are starting AI visibility work and need a competitive baseline — this is where it begins.

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This is for you if

The US B2B company that has seen competitors cited in AI responses for its category

The company about to launch AI visibility investment that needs a competitive baseline first

The marketing or demand generation team that needs competitive AI intelligence for strategy

The growth leader who suspects the AI citation gap is affecting pipeline

What's broken

You are making AI visibility decisions without a competitive picture

The US market has more AI visibility competition than any other. In most B2B and technology categories, multiple competitors have built meaningful citation authority on at least some engines and for at least some query types. Deciding where to focus AI visibility investment without knowing the specific competitive landscape in your category — which competitors are most entrenched, on which engines, for which queries, through which signals — is a significant allocation risk. The GEO Competitor Gap Analysis eliminates that risk by replacing assumption with data.

You have no engine-level competitive breakdown

A competitor that dominates ChatGPT responses for your category may be weak on Perplexity. A competitor that appears consistently in Google AI Overviews may be entirely absent from Claude. The query types that surface each competitor can differ substantially by engine. Without testing all five engines with the same query set, you do not know whether your competitors' AI citation advantage is broad and entrenched or narrow and concentrated — and that distinction determines the entire shape of your competitive response.

The signals driving competitor citations are invisible without a dedicated audit

US B2B and technology companies that appear consistently in AI-generated responses typically got there through some combination of Wikipedia coverage, press mentions in authoritative technology and business publications, G2 and Capterra category presence, schema implementation, analyst report citations, and entity data consistency. Each of these signals has a different acquisition timeline and a different level of current competition. Without a signal audit that maps what each competitor holds versus what you hold, you cannot prioritise your response. You cannot tell whether the gap is three months of concerted effort or eighteen months of sustained work.

Observations about competitor AI presence are not actionable without frequency data

Noticing that a competitor appeared in a ChatGPT response tells you that they have some AI citation presence. It tells you nothing about how consistently they appear across engines, whether their position is strengthening or thin, or whether they hold that position for the full range of queries your buyers ask. Frequency data from a 30-query, five-engine sweep changes observations into intelligence. That distinction is the gap between knowing you have a problem and knowing what the problem actually is.

What we engineer

What we deliver

30-Query Test Set

30 queries built from awareness, consideration, and comparison stages in your specific US B2B or technology category, using the query phrasing US buyers actually use when consulting AI engines during vendor research

5-Engine Citation Sweep

all 30 queries tested across ChatGPT, Perplexity, Google AI Overviews, Gemini, and Claude, with every citation instance documented by engine, query type, and frequency across repeat testing

Competitor Citation Matrix

a structured matrix showing each competitor's citation frequency by engine and query category, with frequency scores producing a direct, comparable view of the competitive citation landscape across your full set of three to five competitors

Gap Analysis

a clear identification of where each competitor holds citation authority that your brand currently lacks, structured by engine, by query stage, and by the scale and consistency of the gap

Signal Audit

a comparison of the signals driving each competitor's citations versus your current signal position, covering Wikipedia coverage and depth, press and media mentions in authoritative US technology and business publications, G2 and Capterra category presence, schema implementation, analyst report citations, backlinks from AI-relevant authoritative sources, and entity data consistency

Prioritised Action Plan

a ranked implementation sequence ordering gaps by citation opportunity, competitor weakness, and implementation effort, giving your team a clear, evidence-based starting point and a sequenced roadmap for closing the competitive citation gap

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Common questions

Frequently asked questions

What is GEO Competitor Gap Analysis?

GEO Competitor Gap Analysis is an audit that identifies which competitors are being cited in AI-generated responses in your US market, at what frequency, on which engines, for which query types, and through which specific signals. The output — a competitor citation matrix, gap analysis, signal audit, and prioritised action plan — gives you the competitive intelligence foundation needed to invest in AI visibility with direction rather than guesswork.

Why is GEO competitive analysis different from traditional SEO competitor analysis?

GEO competitive analysis measures citation frequency in AI-generated responses, which is driven by a different set of signals than search rankings. Wikipedia coverage, press mentions in authoritative publications, G2 and Capterra category presence, analyst report citations, and entity data consistency drive AI citations in ways that do not map cleanly onto traditional SEO metrics like domain rating, backlink count, or keyword rankings. A competitor can dominate your category in Perplexity responses while ranking below you in Google search. SEO tools do not surface this, and SEO competitor audits do not tell you what is driving AI citation gaps.

What does the 30-query test cover?

The 30-query test covers three stages of the US B2B buyer journey: awareness queries (category and problem-framing language buyers use before they have a vendor in mind), consideration queries (recommendation and shortlist requests), and comparison queries (direct head-to-head and "alternatives to" formats). The specific queries are built from your category, your competitive set, and the query patterns US buyers actually use in AI engines — the "best enterprise X platform," "X vs Y for mid-market," and "how to evaluate a Y vendor" formats that drive the most commercially relevant AI citations in B2B technology categories.

How long does the analysis take?

GEO Competitor Gap Analysis for US clients is delivered within seven to ten working days of the briefing session. Competitor and query finalisation takes one to two days, the five-engine sweep runs over three to four days, and the citation matrix, signal audit, and action plan are produced and reviewed over the final three to four days. The deliverable is a complete, actionable document — not a preliminary findings report.

What does GEO Competitor Gap Analysis cost?

GEO Competitor Gap Analysis for US businesses is priced from USD $3,500, covering three to five competitors, 30 queries, the five-engine sweep, the competitor citation matrix, the gap analysis, the signal audit, and the prioritised action plan. Pricing varies with the number of competitors included and the depth of signal audit required for complex or crowded categories. Contact us for a proposal based on your specific competitive set and market segment.

What happens after the analysis is delivered?

The action plan from the GEO Competitor Gap Analysis is built to feed directly into an AI visibility programme — either executed by your internal team or by Ignited Nepal. Most US clients use the output to prioritise their first ninety days of signal-building work, knowing exactly which gaps have the highest citation return, which competitor advantages are most vulnerable, and which engine represents their fastest path to competitive parity. The analysis is a standalone deliverable with no obligation to continue.

Our team

The people behind the work

Not a black box. Real specialists you can call, with their names on the work.

Niraj Raut

Founder — Ecommerce SEO

Keshab Joshi

PPC Expert

Hawrry Bhattarai

Google Ads Expert

Arogya Rijal

SaaS SEO Expert

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The US AI citation competitive landscape in your category already exists — get the map before your competitors do

The GEO Competitor Gap Analysis tests 30 queries across five AI engines, maps every competitor citation across the full engine set, audits every signal gap against your current position, and delivers a ranked action plan that tells you what to close first, what to close next, and what the twelve-month signal-building roadmap looks like. Seven to ten working days from briefing to delivery.

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