Content Simulation Based Optimisation For AI Citations And Share Of Voice

As search shifts from blue links to AI answers, teams keep asking the same questions:

• How do I get my brand cited in ChatGPT answers?
• How do I rank in Google Search Generative Experience AIO (now Google AI Overviews)?
• How can I increase brand mentions in AI search results fast, not in 12 months?

RankBee’s content simulation based optimisation feature is designed to answer exactly these questions. It tests multiple content versions against real generative engines, then recommends the version most likely to be cited, quoted and recommended by ChatGPT, Gemini and Google AI Overviews.

This article explains what content simulation based optimisation is, which AI visibility metrics it targets, and how to use it inside RankBee to improve Generative Engine Optimization (GEO) performance.

Generative Engine Optimization In Brief

Generative Engine Optimization (GEO / GAIO / AEO) is the practice of shaping your content so AI systems like ChatGPT, Gemini, Claude and Perplexity retrieve, summarise and recommend you inside their answers, not just link to you in classic search results. (Source: Wikipedia)

Unlike traditional SEO, there is no single “position 1” in generative engines. Visibility is driven by factors such as:

• How often you are included in answers
• How much of the answer is based on your content
• How prominently and clearly your brand is credited

Research on GEO describes three core visibility metrics: how many words in the answer come from your site, how early in the answer they appear, and how influential the citation looks to a reader. (Source: Scrapeless)

RankBee’s content simulation based optimisation turns these principles into a repeatable workflow you can run on any page.

What Is Content Simulation Based Optimisation In RankBee

Content simulation based optimisation is a RankBee feature that:

1. Collects competitor content for a target topic or URL
2. Generates multiple AI-ready versions of your content
3. Runs hundreds of simulations across prompt sets
4. Measures which version wins on AI visibility metrics
5. Recommends the best version to publish for GEO and SEO

The feature was first announced by RankBee’s founder Aris Vrakas as a way to optimise both rankings and “maximum Weighted Word Count” and to increase citations in ChatGPT. Customers reported seeing measurable gains within roughly two weeks of running simulations. (Source: LinkedIn)

In practical terms, this gives you software to simulate content performance in ChatGPT and Gemini before you push a new version live, instead of guessing which rewrite will work.

Why AI Citations And Weighted Word Count Matter

When you ask how to get my brand cited in ChatGPT answers, there are really two goals:

1. Be included in more answers at all
2. Occupy more of each answer with your content and brand

RankBee focuses on both by tracking:

• Citation frequency - how often AI engines cite or mention your brand for a prompt set
• Weighted Word Count - how many words in the answer come from your content, adjusted by position and prominence
• Share of Voice (SoV) - your percentage of inclusion across all tested answers in a category

External GEO research shows that simple “was I cited, yes or no” is not enough. You also need to know how much of the answer is yours and where those words appear, since citations at the top of an AI answer have far more impact than small mentions at the bottom. (Source: Scrapeless)

RankBee’s Maximum Weighted Word Count metric captures this by combining depth of coverage with position in the answer, so the winning content version is the one that is both cited often and quoted in the most visible parts of the response.

Metrics RankBee Optimises With Content Simulation

Content simulation based optimisation in RankBee is built around the AI visibility metrics that matter most for GEO.

Because these metrics come from simulated answers before you publish, you can choose a content version that is mathematically more likely to maximise Weighted Word Count, citations and Share of Voice.

How Content Simulation Based Optimisation Works In Practice

At a high level, RankBee’s simulation workflow looks like this:

1. Target a page or opportunity
   Choose a URL or draft that maps to a high-intent cluster such as “best X for Y”, comparison pages or key commercial landing pages.
2. Ingest competitor content
   RankBee pulls in pages that AI engines already use to answer similar questions. This gives the system a realistic baseline for what ChatGPT, Gemini and Google AIO currently see as “good enough” content.
3. Generate multiple content versions
   The optimisation engine creates several versions of your content. Each version varies structure, attribute coverage, headings, tables and copy depth, while staying aligned with your brand and on-page SEO.
4. Run simulations across prompt sets
   RankBee tests each version against hundreds of prompts that mimic how real users ask questions in ChatGPT and Google Search. For example, instead of just “AI SEO tools”, prompts might look like:
   • “What are the best tools for generative engine optimization share of voice?”
   • “Which software can simulate content performance in ChatGPT and Gemini?”
   • “How can I increase brand mentions in AI search results fast?”
5. Measure AI visibility metrics
   For every combination of content version and prompt, RankBee measures citation frequency, Weighted Word Count, attribution clarity and Share of Voice compared to competitors.
6. Recommend the winning version
   Once simulations complete, RankBee surfaces the content version that consistently outperforms competitors on AI visibility, without sacrificing on-page SEO fundamentals.

The result is a content draft that has already been pressure-tested against the way real AI engines assemble answers, not just how traditional SERPs rank pages.

Step By Step How To Use Content Simulation Based Optimisation

This section outlines a typical workflow. Exact labels and buttons depend on the current RankBee interface, so always follow your product’s on-screen instructions.

1. Choose The Page You Want AI To Recommend

Start with a page that matches a valuable intent, for example:

• A “best X for Y” category page
• A key product or service page
• A comparison or alternatives page

You can begin from an existing URL or from an unpublished draft pasted into RankBee.

2. Define Your Target Prompts And Markets

To increase the chance that AI assistants recommend you for the right queries, configure or confirm:

• Target languages and regions
• Core intents (problem, solution, product, comparison)
• Example prompts users might type into ChatGPT, Gemini or Google Search

If you are specifically targeting how to rank in Google Search Generative Experience AIO, include question-style, long-tail prompts that tend to trigger AI Overviews, such as “best B2B SEO agencies for SaaS in the UK” rather than just “SEO agency”. (Source: Serps.io)

3. Let RankBee Collect And Analyse Competitor Content

RankBee will scan and ingest competitor pages that currently perform well in AI search and organic search for similar intents. This step powers:

• Automated competitor content analysis
• Attribute coverage comparisons
• Realistic baselines for AI citations and Word Count

You can review which competitors are included and adjust where needed.

4. Generate AI-Optimised Content Versions

Next, ask RankBee to generate multiple versions of your page targeted to the opportunity set you defined. Typical variation points include:

• Headline and subheading structure
• Attribute blocks, bullets and tables
• Proof points such as case study snippets or statistics
• FAQ sections aligned with conversational queries

Each version is created with both SEO and GEO in mind, so you do not have to choose between classic rankings and AI visibility.

5. Run Content Simulations For ChatGPT, Gemini And Google AIO

Trigger the simulation run. Behind the scenes, RankBee:

• Tests every version across your prompt set
• Records whether and how often AI models cite your content
• Measures Weighted Word Count and attribution clarity
• Compares your brand’s Share of Voice against competitors

You can usually see early patterns within a short time window, then wait for the full simulation batch to complete before making a publishing decision.

6. Review Results And Choose The Winning Version

Once simulations finish, review for each content version:

• Share of prompts where your brand was included
• Average Weighted Word Count per answer
• Average citation count and position
• Differences between ChatGPT, Gemini and Google AI Overviews

Use these insights to choose the version that:

• Wins the highest Generative Engine Share of Voice
• Secures clear, early citations with your brand name visible
• Maintains or improves classic SEO signals such as title tags and internal links

After you publish the winning version, monitor live AI answers and your RankBee dashboard to confirm the simulated uplift appears in production.

How To Increase Brand Mentions In AI Search Results Fast

If you specifically want to increase brand mentions in AI search results fast, combine content simulation with these practical steps:

1. Start with high-intent prompts
   Focus simulations on prompts that map directly to revenue, such as “best [category] for [segment]” or “alternatives to [competitor] for [use case]”.
2. Make attributes explicit
   Ensure your simulated versions state the attributes that matter for your category - pricing model, region, integrations, compliance and performance benchmarks - in clear, scannable copy. AI assistants match on attributes, not slogans.
3. Use structured content
   Answers in lists, tables and FAQs are easier for LLMs to quote. Studies of ChatGPT-cited pages show that list-based structures are far more common among cited sources than in general search results. (Source: Scrapeless)
4. Align with Google AI Overviews behaviour
   AI Overviews tend to appear more often on longer, question-style queries. Building pages that answer those questions directly increases the chance that your site appears among the limited set of sources AIO cites. (Source: We Are TG)
5. Prioritise factual clarity over marketing copy
   AI crawlers prefer clear, factual statements and well-structured data over long, abstract prose. Make sure key facts appear in plain HTML text, not only in images or PDFs.
6. Iterate quickly using simulations
   Because RankBee runs hundreds of simulations before you publish, you can test several hypotheses in parallel and move live only with the version that shows the best AI visibility metrics.

This combination is the fastest way to move from “invisible in AI search” to measurable gains in AI citations and Weighted Word Count without waiting for a full SEO cycle.

Frequently Asked Questions

How Do I Get My Brand Cited In ChatGPT Answers

You increase the probability of citations by:

• Publishing pages that directly answer the types of natural language questions your customers ask ChatGPT
• Making your product attributes explicit so the model can match you to detailed queries
• Ensuring AI crawlers can access your content
• Using RankBee’s content simulation based optimisation to test multiple versions and pick the one that earns the highest ChatGPT citation frequency and Weighted Word Count

GEO research and real case studies show that when brands improve attribute coverage and content structure, their inclusion rate in AI answers can move from single digits to majority coverage over a few weeks. (Source: GrowCreate)

How Do I Rank In Google Search Generative Experience AIO

Google’s AI Overviews, previously tested under the name Search Generative Experience, show an AI-written summary with a small set of cited sources at the top of many results. (Source: Wikipedia)

To improve your chances of being cited there:

• Target informational, question-style queries where AIO is most common
• Structure pages with clear headings, tables and FAQs that map closely to those questions
• Keep critical information current and consistent across your site
• Use RankBee simulations to compare which content versions AI Overviews are more likely to quote and link

Is RankBee A Tool For Generative Engine Optimization Share Of Voice

Yes. RankBee is designed as a GEO platform that measures and improves your Share of Voice across generative engines, including ChatGPT, Gemini and Google AI Overviews. It tracks how often you are included in AI answers for a defined prompt set, how much of each answer comes from your content and how frequently competitors displace you.

Content simulation based optimisation extends this by showing which content version is most likely to increase your Generative Engine Share of Voice before you publish.

What Makes RankBee Different From Manual Testing

Manually asking ChatGPT or Gemini a few prompts can show whether you appear today, but it does not scale and cannot tell you which rewrite will work better.

RankBee:

• Automates competitor content analysis across many prompts
• Generates multiple AI-ready content versions for each opportunity
• Runs hundreds of simulations instead of a handful of manual tests
• Scores each version on Weighted Word Count, citation frequency and Share of Voice

This turns GEO content decisions into a data-driven process instead of a guessing exercise.

Summary

Content simulation based optimisation in RankBee gives you a systematic way to improve GEO performance.

Instead of asking “how do I get my brand cited in ChatGPT answers” in general, you can:

• Select a high-value page
• Generate multiple AI-optimised versions
• Simulate how each version performs across ChatGPT, Gemini and Google AI Overviews
• Choose the version that maximises Weighted Word Count, citation frequency and Share of Voice

Used consistently, this approach helps you dominate generative engines for your category while still supporting classic SEO rankings.