Frequently Asked Questions

GEO (Generative Engine Optimization) focuses on how your brand appears in AI-generated answers — the responses produced by ChatGPT, Perplexity, Google AI Overviews, and similar engines. Traditional SEO optimizes for ranked links on a search results page. GEO measures your visibility inside the AI response itself: are you mentioned? Are you recommended? What sentiment surrounds your brand?

GEO is a developing subdiscipline of SEO — it shares the same foundation (E-E-A-T, technical indexability) but introduces its own target variable: Citation Rate. A brand can be cited in AI answers without receiving a single click, creating a new type of visibility that SEO metrics don’t capture. AEO (Answer Engine Optimization) is used interchangeably with GEO.

Google’s AI features (AI Overviews, AI Mode) do pull from the same index as traditional search — that part is true. But ChatGPT, Perplexity, and other AI engines have their own data pipelines, training data, and citation logic that are completely independent of Google’s index.

Our monitoring data shows only about 11% domain overlap between what different AI engines cite for the same query. A brand that ranks well in Google AI Overviews may be completely absent from ChatGPT’s responses, and vice versa. You need multi-engine monitoring to see the full picture — which is exactly what ARPAI GEO provides.

The numbers are already massive and growing fast. Google AI Overviews reaches 2.5 billion users per month. Google AI Mode processes over 1 billion queries per month and is doubling each quarter. ChatGPT has 900 million weekly active users.

The challenge is that most analytics platforms (including Google Analytics) report AI-referred traffic as “direct” or “organic” — making it invisible in your dashboards. This is why we built the AI Traffic Pixel: it correctly identifies visitors coming from AI engines so you can see the real numbers.

The system generates 15 search queries based on your business — 10 category queries without your brand name and 5 branded queries. Each query is formulated across 8 different buying intents (informational, comparison, recommendation, etc.) to cover how real users actually ask questions.

All queries are sent simultaneously to every major AI engine. The responses are collected, and each mention of your brand is cross-validated for accuracy using a dual-layer system: an AI cross-check evaluates context, then a code-level bidirectional substring match verifies the brand name. Raw AI responses contain 15–30% false positives — this validation eliminates them. The entire process takes 3–5 minutes and produces a full report with share-of-voice, visibility scores, citation rates, sentiment analysis, competitor rankings, and per-engine breakdowns.

ARPAI GEO monitors all major generative AI engines simultaneously. The specific engine list is updated as the market evolves — new engines are added as they gain meaningful market share, and deprecated engines are phased out.

Every monitoring report includes per-engine breakdowns so you can see exactly how each engine treats your brand. This is critical because engines often disagree: a brand may have 80% visibility on one engine and 0% on another.

Raw AI responses contain 15–30% false positives — hallucinated brand names, incorrect attributions, and fabricated mentions. We address this with a dual-layer validation system.

First, an AI cross-check evaluates each mention in context: does it actually refer to your brand, or is it a coincidental string match or hallucination? Second, a code-level bidirectional substring match verifies the brand name against the full response text. Every validated mention includes an audit trail showing why it was accepted or rejected.

Share of Voice (SOV) — how often your brand is mentioned relative to competitors across all responses. Visibility Score — weighted measure of mention quality, position, and prominence. Citation Rate — percentage of responses that cite or link to your domain. Sentiment — whether mentions are positive, neutral, or negative.

All metrics are available per engine, per query, and tracked over time so you can measure the impact of your optimization efforts.

ARPAI GEO provides a complete toolkit for the optimization cycle: Source Analysis maps which platforms AI engines cite in your market — so you know where to focus your content. GEO Strategy generates a prioritized action plan based on your monitoring data. AI Webmaster audits your site for AI readiness. Content Engine writes AI-optimized articles with the signals that increase citation probability. Hypothesis testing lets you statistically verify whether specific changes actually moved your metrics.

The cycle is iterative: monitor → identify gaps → take action → monitor again to measure impact.

Technical fixes (schema markup, structured data, site architecture) can show impact within 1–2 monitoring cycles. Content-based optimizations typically take longer as AI engines need to discover and index new content.

Perplexity updates in real time — publishing on an authoritative platform can reflect within hours. Google AI picks up changes within days. Typical result: measurable visibility increase within 2–4 weeks of publishing GEO-optimized content on high-authority platforms.

Yes, significantly. Brand monitoring tracks your company’s overall visibility across AI engines — how your brand as a whole is perceived and recommended.

Product monitoring focuses on a specific offering: it generates product-specific queries, identifies direct product competitors (not just brand competitors), tracks product-level pricing mentions, and measures visibility for that particular product in its category. A company might have strong brand visibility but weak visibility for a specific product line — product monitoring surfaces this.

Brand monitoring and product monitoring are $12 per run. Other operations are priced individually: articles at $6, strategies and audits at $3–$5, chatbot consultations at $0.50. The AI Traffic Pixel is free.

There are no subscriptions, no annual contracts, and no per-seat pricing. Your balance never expires. You top up any amount from $25 to $1,000 and use it at your own pace. Run more checks during active optimization, scale down when stable — you control your spending completely.

A typical small business with one location running weekly brand monitoring, biweekly product checks for a few products, and occasional audits and strategy runs spends roughly $150–170 per month.

This compares to $99–398/month for competitor tools that offer fewer engines, fewer queries, and no content or optimization features. Your actual spend depends entirely on your activity level — you control it completely.

A lightweight JavaScript snippet (under 1KB) that you add to your website. It detects visitors from 12 AI sources by analyzing referrer headers and UTM parameters. Most analytics platforms misclassify AI traffic as “direct” or “organic” — the pixel makes it visible in your ARPAI GEO dashboard.

No personal data is collected. No measurable impact on page speed or Core Web Vitals. For conversion tracking, call arpaiConversion('purchase', 99.99) on your confirmation page to see revenue attribution by AI engine.

The pixel sets two cookies: _arpai_vid (visitor ID, 12-month expiry) and _arpai_src (source attribution, 30-day expiry). These cookies contain randomly generated session identifiers — no personal data, no email addresses, no browsing history.

As with any cookie-setting technology, website owners are responsible for including the pixel in their cookie consent management. If consent is required under GDPR or similar regulations, the pixel should be loaded only after the visitor provides consent.

For the monitoring platform: your company URL, monitoring settings, analysis results, generated content, and audit reports. All of this is data you explicitly create through your use of the platform.

For the AI Traffic Pixel: page URLs visited by AI-referred traffic, the AI engine source, and anonymized session identifiers. No personal data, no email addresses, no browsing profiles. All monitoring data, reports, and content are completely private to your account — no data sharing, no public benchmarks, and no way for another user to see your results.

72 countries and 44 languages. You can set monitoring at the country, region, or city level, and queries are generated in the target language to match how local users actually search.

AI engine responses vary significantly by location and language. A brand that’s well-represented in English responses may be absent in German or Japanese responses for the same queries. You can create multiple monitoring locations within a single project, each with its own metrics, competitor analysis, and trend tracking.