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Shopping Research is a feature in ChatGPT that acts as a personalized shopping assistant.
Simply describe what you’re looking for, such as “a lightweight laptop for travel”, and ChatGPT gathers product details, reviews, specs, prices, and comparisons from the web.
You can refine the results by marking products as “Not interested” or “More like this”, helping ChatGPT understand your preferences.
At the end, you receive a custom buyer’s guide that explains the pros, cons, and trade-offs of each option, making your purchase process easier and more informed.
Entity-based SEO helps AI systems understand who a company is, what it offers, and how it relates to other concepts in an industry. For B2B organizations, strengthening entity signals and semantic relationships increases the likelihood of being recognized as an authoritative source in AI-generated search results.
Implementing WebMCP is streamlined through the Google Chrome Labs toolkit. Developers have two primary paths:
toolname and tooldescription attributes to existing HTML <form> tags.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.
Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) are closely related strategies, but they serve different purposes in how content is discovered and used by AI technologies.
llms.txt) to guide how AI systems interpret and prioritize your content.In short:
AEO helps you be the answer in AI search results. GEO helps you be the source that generative AI platforms trust and cite.
Together, these strategies are essential for maximizing visibility in an AI-first search landscape.
AI search performance metrics are the new frontier for digital marketers. As generative engines like Gemini and Search Generative Experience (SGE) redefine how users find information, relying solely on legacy SEO tracking is no longer enough. To succeed, you must measure how AI models perceive, rank, and cite your content.
1. Subjective ImpressionThis metric evaluates how well your content answers user queries compared to competitors. AI models assess the relevance, completeness, and accuracy of your content. A high score signifies that your content provides comprehensive answers that LLMs deem most helpful to the user.
2. Position ScoreSimilar to traditional SERP rankings, the Position Score measures how high your website ranks within the AI’s generated response. Calculated by your average ranking position (1st, 2nd, 3rd), a higher position directly correlates with increased user trust and higher click-through potential from AI citations.
3. Share of Voice (SoV)In the context of GEO, Share of Voice measures the percentage of queries where your website is mentioned or cited in the AI's response. A dominant SoV indicates broad topical authority and ensures your brand remains "top of mind" for the AI across various related search strings.
4. Consistency ScoreBecause users interact with various models (Perplexity, ChatGPT, Gemini), the Consistency Score is vital. It tracks the similarity of your rankings and mentions across multiple platforms. High consistency ensures that your brand’s authority is recognized universally, regardless of the specific AI model used.
Compliance with the EU AI Act is fundamental to our search strategy. We help brands adapt to the new 2026 transparency obligations, ensuring their content is properly labeled and that their recommendation systems meet limited-risk standards—protecting both their reputation and visibility in international markets.
**Brand Mentions that drive action.** RankWit.ai continuously monitors the web for mentions of your brand, products, and campaigns across sources like news, blogs, forums, and social media. Each mention is analyzed for sentiment, authority, and relevance, so you can see not just where you’re discussed, but how it affects SEO and brand health.
**What you get:**
- **Real-time detection** of new mentions across a broad publisher set.
- **Sentiment and context** analysis to understand tone and potential risk or opportunity.
- **Impact ranking** that prioritizes high-value mentions by engagement potential, source credibility, and audience size.
- **Topic enrichment** to surface related keywords and content angles for optimization.
- **Alerts and digests** so you stay informed without noise.
**How to use Brand Mentions effectively**
1. **Set your brand and product keywords** to ensure comprehensive coverage.
2. **Filter by sentiment, platform, and authority** to focus on the signals that matter most.
3. **Action directly from the platform**: draft outreach, respond to feedback, or create content based on real conversations.
4. **Leverage insights for SEO**: identify backlink opportunities and topical gaps to strengthen content strategy.
5. **Track trends over time** to spot seasonal spikes and measure the impact of campaigns.
**Workflow quick-start**: enable Brand Mentions, configure keywords, set thresholds, and connect to your CRM or CMS for rapid response. For a guided tour, visit our [Try it now](/features) page and see Brand Mentions in action.
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.