Source-led article
Brand Positioning Now a Key AI Search Variable, Semrush Reports
Artificial intelligence (AI) search engines are fundamentally changing how brands achieve visibility online, according to a recent analysis by Semrush. The report emphasizes that AI systems no longer just rank web pages but instead construct a comprehensive understanding of a brand based on signals gathered from across the internet. This shift makes consistent and relevant brand positioning a crucial factor for success in AI-driven search environments.
Traditionally, search engine optimization (SEO) focused heavily on content volume and technical optimizations. While these aspects remain important, Semrush’s findings suggest that AI’s ability to form an implicit judgment about a brand’s identity, credibility, and relevance means that a well-defined brand positioning strategy is now paramount. AI determines whether to recommend a brand by assessing what it does, who it serves, and its overall relevance to a user’s query.
How AI Perceives Brands
AI systems develop a probabilistic understanding of brands by analyzing vast amounts of data. This includes a brand’s own website, press coverage, customer reviews, mentions from partners, social media content, and forum discussions. All these diverse data points contribute to a single, albeit implicit, judgment about what the brand stands for, its areas of expertise, and its trustworthiness within specific contexts.
The report cites an example where ChatGPT, when asked for the best WordPress hosting providers for small businesses, did not mention WordPress.com, despite its obvious relevance. This could be influenced by how ChatGPT interprets “WordPress hosting” or by underlying perceptions AI has formed about the brand. This highlights that if AI associates a particular perception with a brand, it might not surface it even for seemingly relevant queries, indicating the depth of AI’s brand interpretation.
Semrush’s Search Visibility Framework
To help brands navigate this evolving landscape, Semrush has developed a search visibility framework. This framework organizes the brand signals that AI systems use into four actionable layers: Discoverability, Clarity, Authority, and Trust. Each layer addresses a specific question AI implicitly asks about a brand:
- Can it find you? (Discoverability)
- Does it understand you correctly? (Clarity)
- Does it consider you qualified? (Authority)
- Does it trust you enough to recommend you? (Trust)
Achieving success at each of these layers requires a strong, well-articulated brand positioning strategy. The initial step for any brand is to assess its current AI perception and determine if it is being recommended in critical areas.
Auditing AI Brand Perception
Brands can begin by manually checking how they are perceived by open AI platforms like ChatGPT, Perplexity, and Gemini, using structured prompts across different categories. However, AI answers are dynamic and personalized, meaning a manual check provides only a directional snapshot. For ongoing tracking, Semrush recommends using its AI Visibility Toolkit.
The toolkit’s workflow involves three key reports:
Key facts:
| Feature | Description |
|---|---|
| AI Search Shift | AI ranks brands, not just pages, based on overall perception. |
| Brand Positioning | Consistent, clear positioning is now crucial for AI visibility. |
| Semrush Framework | Four layers: Discoverability, Clarity, Authority, Trust. |
| AI Visibility Toolkit | Helps audit and manage brand perception through Brand Performance, Perception, and Narrative Drivers reports. |
Brand Performance report: Provides a high-level overview, including AI Share of Voice compared to competitors and an AI sentiment score. For example, WordPress.com, while a category leader, had only 60% favorable sentiment, suggesting underlying perceptions that might limit AI recommendations.
2. Perception report: Details specific positive and negative perceptions AI holds about a brand, broken down by feature category. This helps identify strengths to highlight and outdated or negative perceptions that need correction.
3. Narrative Drivers report: Reveals high-intent queries featuring the brand and the external sources AI uses, guiding content creation and external platform engagement strategies.
Managing Brand Positioning in AI Search
Semrush outlines a three-part process for managing brand perceptions in AI search: clearly defining brand positioning, making it visible on proprietary sites, and reinforcing it externally. Many brands lack a clear positioning, leading to ambiguity that AI systems reflect in their recommendations.
Before undertaking any content work, brands must solidify their core positioning. This should then be compared against the insights from AI audits using the Brand Performance and Perception reports. Brands need to ask whether AI understands their key positioning attributes, communicates them consistently, and does so favorably. Case studies from Semrush, such as rtCamp (a WordPress design agency) and WorkLounge (a coworking space), illustrate how internal positioning often differs from AI’s external perception, necessitating strategic adjustments.
For India’s growing digital landscape and startup ecosystem, understanding and actively managing brand positioning in the context of AI search is becoming increasingly vital. As AI tools become more integrated into search and discovery, businesses in India will need to adapt their digital marketing and SEO strategies to ensure their brands are accurately and favorably represented by these advanced systems.