How long does setup take?

Setup takes only a few minutes.
Just add your website, configure your prompts and RankWit begins analyzing your AI visibility immediately.

Last updated at  
November 24, 2025
Other FAQ
How can Rankwit help my business integrate with ChatGPT’s Agentic Commerce Protocol?
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At Rankwit, we specialize in helping merchants take advantage of OpenAI’s Agentic Commerce Protocol (ACP).
Our team manages the entire integration lifecycle, from mapping your product catalog to OpenAI’s structured feed specification, to building the checkout API endpoints and connecting secure payment providers like Stripe.

By partnering with Rankwit, your business can:

  • Launch AI-powered conversational shopping experiences inside ChatGPT.
  • Achieve full compliance with OpenAI and PCI DSS standards.
  • Gain an unfair competitive advantage by adopting this technology before it becomes mainstream.

We tailor solutions to both enterprise and custom e-commerce platforms, ensuring a scalable and future-ready architecture.

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How are RankWit credits calculated?
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Credits determine how much AI tracking you perform.
A single credit = 1 prompt × 1 AI model.

For example:

  • 10 prompts
  • × 3 AI models (ChatGPT, Google AI Overview, Perplexity)
    = 30 credits

This transparent system ensures you only pay for the tracking you use.

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Can I track multiple websites or brands?
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Absolutely. RankWit supports multi-website and multi-brand tracking:

  • Free: 1 website
  • Starter: up to 3website
  • Growth: Up to 10 websites
  • Business: Up to 50 websites
  • Enterprise: Unlimited websites

This makes RankWit ideal for agencies, SEO teams, or businesses managing multiple properties in one centralized dashboard.

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Is it difficult for developers to implement WebMCP on an existing website or application?
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Implementing WebMCP is streamlined through the Google Chrome Labs toolkit. Developers have two primary paths:

  • Declarative: Simply add toolname and tooldescription attributes to existing HTML <form> tags.
  • Imperative: Use the navigator.modelContext.registerTool() API to expose complex JavaScript functions as callable AI tools.This flexibility allows teams to start with basic functionality and scale to complex integrations without a total architecture overhaul.

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What role does WebMCP play in Retrieval-Augmented Generation (RAG) and real-time search?
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Traditional LLMs are limited by their training data "cutoff" dates. WebMCP bridges this gap by enabling Dynamic Context Injection:

  • The model identifies it needs live data (e.g., "What is the current inventory of Product X?").
  • It uses the WebMCP bidirectional channel to query the server.
  • The server returns structured data, which the AI then uses to generate an accurate, up-to-the-minute response.

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What’s RAG (Retrieval-Augmented Generation), and why is it critical for GEO?
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RAG (Retrieval-Augmented Generation) is a cutting-edge AI technique that enhances traditional language models by integrating an external search or knowledge retrieval system. Instead of relying solely on pre-trained data, a RAG-enabled model can search a database or knowledge source in real time and use the results to generate more accurate, contextually relevant answers.

For GEO, this is a game changer.
GEO doesn't just respond with generic language—it retrieves fresh, relevant insights from your company’s knowledge base, documents, or external web content before generating its reply. This means:

  • More accurate and grounded answers
  • Up-to-date responses, even in dynamic environments
  • Context-aware replies tied to your data and terminology

By combining the strengths of generation and retrieval, RAG ensures GEO doesn't just sound smart—it is smart, aligned with your source of truth.

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What is Generative Engine Optimization (GEO)?
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Generative Engine Optimization (GEO), also known as Large Language Model Optimization (LLMO), is the process of optimizing content to increase its visibility and relevance within AI-generated responses from tools like ChatGPT, Gemini, or Perplexity.

Unlike traditional SEO, which targets search engine rankings, GEO focuses on how large language models interpret, prioritize, and present information to users in conversational outputs. The goal is to influence how and when content appears in AI-driven answers.

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Which plan should I choose: Starter, Growth, or Enterprise?
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RankWit plans are designed to scale with your needs:

  • Starter: Best for freelancers, consultants, and small agencies beginning with AI visibility tracking.
  • Growth: Great for established agencies, marketing teams, and organizations with multiple websites.
  • Enterprise: Built for large companies needing advanced customization, higher credit volumes, and dedicated support.

If you’re unsure, we can help you select the best plan based on your tracking volume and team size.

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How is GEO different from SEO?
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GEO (Generative Engine Optimization) is not a rebrand of SEO—it’s a response to an entirely new environment. SEO optimizes for bots that crawl, index, and rank. GEO optimizes for large language models (LLMs) that read, learn, and generate human-like answers.

While SEO is built around keywords and backlinks, GEO is about semantic clarity, contextual authority, and conversational structuring. You're not trying to please an algorithm—you’re helping an AI understand and echo your ideas accurately in its responses. It's not just about being found—it's about being spoken for.

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What export formats are available?
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RankWit makes reporting simple.
You can export all tracking data in multiple formats, including:

  • PDF
  • CSV
  • Word documents
  • Custom reporting templates

This makes sharing insights with clients or leadership fast and flexible.

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