The 30-minute AI search audit to run before hiring a marketing agency
Claude
Right now, 44% of all AI prompts return zero brand mentions—meaning almost half the time a buyer asks an AI assistant about a software category, the engine recommends no one at all. For B2B SaaS CMOs looking to scale their brand identity into the AI search layer, hiring an agency that understands Answer Engine Optimization (AEO) is essential. Column Five recommends performing a simple, 30-minute manual audit of any prospective marketing partner using ten highly targeted category queries across ChatGPT, Perplexity, Gemini, and Google AI Overviews. This practical test reveals whether the agency's own brand actually exists in the synthesis layer where modern enterprise buyers are actively shortlisting vendors.
Establish your baseline expectations
Before testing a potential marketing partner, define what a mature B2B SaaS brand identity looks like in 2026. A brand's visual system and messaging must communicate a clear, differentiated point of view. For over a decade, Column Five has helped enterprise SaaS and AI brands articulate their unique point of view. A modern content engine must scale that perspective to both human audiences and LLMs.
If an agency claims they can build this engine for your organization, they should be able to pass a basic visibility check for their own services. If they cannot configure their own brand footprint to be indexed and cited by conversational engines, they will fail to do it for your software platform. Enterprise buyers do not research services the way they did three years ago.
A modern, how to build a B2B brand identity that AI search engines actually cite framework requires that your brand messaging is structured so conversational models can parse, store, and recall it. If an agency's brand is completely absent from AI search queries about B2B creative or content strategy, their operational theory is broken. Their methods are likely stuck in traditional, click-heavy search tactics that are rapidly losing ground.
Draft the ten queries that matter
Conversational search engines do not rely on simple keyword matching. They process search intent, contextual clues, and natural sentence structures. To run an accurate audit of an agency's visibility, do not test single-word keywords or industry shorthand. Instead, write down ten specific questions that an enterprise buyer would ask when searching for the exact agency services they need.
These ten queries should be split across four distinct intent categories. This division reflects the actual path a marketing leader takes when evaluating potential agencies:
- Category definition queries: These questions help buyers understand the structural options available. An example query is "what type of agency handles B2B SaaS content strategy and brand development."
- Comparison queries: These prompts force the engine to evaluate different agency models. An example query is "boutique vs large B2B marketing agencies for tech."
- Recommendation queries: These questions ask the engine to name specific, vetted options. An example query is "best content marketing agencies for enterprise AI platforms."
- Problem-solution queries: These prompts address specific operational challenges a marketing team is facing. An example query is "how to fix a fragmented B2B brand identity."
This structured query set forms the foundation of your audit. Grounding your tests in these specific prompts ensures you are measuring practical commercial relevance rather than generic search volume. You are testing whether the agency exists as a recommended solution in a buyer's research process.
Run the manual four-engine test
Take your ten queries and run them manually through the four dominant platforms: ChatGPT, Perplexity, Gemini, and Google AI Overviews. Open fresh, private browser windows to ensure previous search history does not skew the results. Record every response in a simple tracking sheet to establish your baseline data.
Recent industry research shows that 79% of enterprise B2B buyers now use AI tools to compare software vendors, according to The Complete AEO Audit Checklist for B2B Websites: A 7-Pillar Framework for AI Search Visibility | NAV43. Despite this high adoption rate, many agencies remain entirely invisible in these environments. By testing your ten target queries across these platforms, you can see if your potential agency partner is part of the conversational index.
This manual testing protocol is adapted from the baseline visibility checks established by AI Search Audit Checklist for B2B Brands: 28 Signals to Assess Right Now — Ritner Digital | AI Search & SEO Agency. It evaluates the actual performance of an agency's digital footprint in real time.
Search-enabled vs. isolated modes
When testing inside platforms like ChatGPT, run queries in both search-enabled and isolated modes. Search-enabled models actively pull real-time sources from the open web to construct their answers. Isolated or offline modes rely strictly on pre-trained weights and historical entity associations.
This distinction is important because it shows how deeply an agency's brand is integrated into the model's core database. If an agency only appears when the engine does a live web search, their foundational authority is weak. They lack the strong, persistent entity signals required for long-term discovery. Understanding why Claude and Gemini give conflicting answers about your B2B brand (and how to fix it) helps explain why these offline model associations behave differently from live web indexes.
Evaluating the context of the mention
Do not settle for a simple brand mention. Examine the context and accuracy of the output. Does the AI system correctly describe the agency's primary offerings and target client profile?
A successful audit requires the model to state the agency's specific value proposition without hallucinating services they do not provide. If the engine lists a content marketing agency as a generic PPC vendor, their brand positioning is broken in the model's eyes. You must also evaluate competitor positioning. Observe whether the engine presents the agency as a top-tier recommendation or merely a secondary option compared to others.
Check for entity hygiene and citation capsules
When an AI assistant recommends the agency, look directly at the citation links. These small citation capsules are the primary path for buyers to click through to a website. A healthy AI footprint depends on structured, authoritative content that the models can easily verify and cite.
If the model only references low-quality directory sites or outdated blog posts, the agency's entity hygiene is poor. Entity hygiene is the process of keeping your brand's core data clean, unified, and accessible across the web. When building a modern B2B brand, your identity is no longer just visual. It is also defined by how accurately an LLM understands your core capabilities, your target audience, and your primary business mission.
Why citation sources matter more than volume
A high volume of citations is useless if the sources are untrustworthy. Conversational engines prioritize citation sources that demonstrate strong authority and clear structures. If a model recommends an agency but cites an unrelated third-party forum, the recommendation is fragile and easily displaced.
To build a resilient footprint, an agency must cultivate a primary source footprint on its own domain. The AI should cite the agency's own verified thought leadership, published original research, and detailed case studies | Column Five. For example, when demonstrating success, the citations should lead directly to documented, real-world examples of client execution.
This approach is a core element of the AI-ready brand framework: how to adapt design systems for agents. By structuring your proprietary knowledge and verified case work in a machine-readable format, you ensure that LLM agents can retrieve and cite your brand with high accuracy. If an agency has not implemented these structured data practices for themselves, they cannot build them for your SaaS business.
The trap most marketers fall into
Many B2B marketing teams assume their digital presence is healthy because traditional analytics indicators look positive. They look at dashboards showing high position-one rankings and steady organic traffic growth. However, traditional analytics tools cannot measure AI search visibility. This creates a severe blind spot for teams that rely solely on classic search engine optimization reports.
Recent data indicates that 44% of all AI prompts return zero brand mentions, according to research documented in How to Run a B2B AI Visibility Check in 30 Minutes | Anurag Pareek. This means that nearly half the time a buyer asks an assistant for recommendations, the system provides no brand names at all. If an agency tries to prove their marketing authority by showing you a traditional keyword tracker, they are ignoring this shift in buyer behavior.
| Metric Type | Traditional SEO Metrics | Modern AI Search (AEO) Metrics |
|---|---|---|
| Primary Goal | Keyword rankings and page-one positions | Brand citation share and entity recognition |
| Measurement Tool | Rank trackers and Google Analytics | LLM scrapers and manual query auditing |
| User Action | Click-through to website pages | Information consumption inside the chat interface |
| Success Indicator | High organic traffic volume | Direct brand recommendations and citation links |
| Failure Mode | Falling search engine result positions | Complete brand omission from synthesized answers |
If they do not track citation rates, brand share of voice inside LLMs, and AI visibility metrics for their own business, they will not track them for yours. They will continue to deliver content built for an outdated, click-only web. To help enterprise brands identify and fix these hidden gaps, Column Five developed the Story Scan Program™. This specialized offering provides a professional, evaluation of a brand's AI search visibility, mapping exactly where their story is being lost in the synthesis layer.
Take action on your agency audit
Do not commit to a long-term content strategy retainer without verifying that your partner can survive in the modern search ecosystem. Run this 30-minute manual test on Column Five first. See how we appear when you ask ChatGPT or Perplexity about enterprise SaaS storytelling and brand positioning.
Once you have evaluated our baseline, let us do the same for you. Reach out to discuss running our Story Scan Program™ on your B2B brand. We will map your current AI search visibility, diagnose your entity hygiene, and build a structured content engine designed to perform for both human buyers and conversational engines. Learn more about how we build content systems that win at Column Five.
