An analysis of where [Your Client] is being surfaced in AI-generated answers, where competitors are more visible, and which actions are most likely to improve visibility.
Across 55 prompts checked on ChatGPT, Claude, Perplexity, Google AIO, [Your Client] surfaced in roughly 12% of unique answers.
5 competitors were tracked. This page shows the competitive spread at a glance, while the visibility breakdown by intent is shown separately on the following page.
Branded, comparison, and discovery visibility are shown separately because each reflects a different stage of buyer intent and highlights a different visibility gap.
This page highlights the domains most frequently associated with visibility for [Your Client] and the competitors that appear most often in AI-generated responses.
A representative sample from the tracked prompt set. These examples show where the brand is already being surfaced and where competitors continue to control the response.
When [Your Client] is not included in the response, AI engines most often rely on educational broker content, agent-program pages, supplier-diversity proof pages, and YouTube.
Recommendations are prioritized by expected impact and ease of execution, so teams can focus first on the changes most likely to improve visibility.
When [Your Client] is absent, AI engines repeatedly cite educational broker pages and explainers on asset-based brokerage, capacity, and broker evaluation rather than [Your Client]'s own site.
A useful starting point is a focused set of pages addressing the questions buyers ask most often: asset-based vs. non-asset brokerage, asset-backed capacity, how to evaluate an asset-based freight broker, and best-fit use cases. This is the clearest path to improving visibility beyond branded searches.
Armstrong, SPI, Tallgrass, DAT, and similar brands dominate queries about agent programs, onboarding, moving a book of business, and switching brokers.
Create pages covering the agent program overview, switching considerations, onboarding timeline, commission structure, back-office support, and recruiter FAQs so [Your Client] is better represented on these decision-stage topics.
Supplier-diversity prompts are being won by proof-oriented pages, not generic service copy.
Develop a proof-oriented content hub covering WBE certification, procurement readiness, enterprise qualification details, and a dedicated page for WBE-certified freight broker searches.
The remaining recommendations extend the same strategy by strengthening supporting content and improving how key topics are surfaced and understood by AI systems.
[Your Client] already appears in some direct comparison prompts, which suggests comparison content is a practical near-term expansion opportunity.
Develop structured comparison pages for Echo, Coyote, Armstrong, Landstar, and TQL with direct-answer introductions, use-case fit, switching criteria, and FAQ sections.
YouTube is the strongest citation surface when [Your Client] is not included, so video should reinforce the same discovery topics covered by written content.
Pair each major discovery page with a corresponding video on asset-based brokerage, agent programs, supplier diversity, broker evaluation, and switching topics using clear, query-aligned titles.
This appendix outlines the prompt set, engine coverage, and interpretation rules used to keep month-over-month comparisons consistent.
55 prompts were derived from a category template and manual additions, spanning branded, comparison, and discovery-style buyer intent.
4 engines were included in this run: ChatGPT, Claude, Perplexity, Google AIO.
Each prompt was run 1 time, producing 220 total observations across the dataset.
A mention means [Your Client] appears directly in the answer text. This report measures how often the brand is surfaced across tracked buyer-intent prompts.
The AI Visibility Score is the weighted average of mention rate across ChatGPT, Claude, Perplexity, and Google AIO, normalized to a 0–100 scale.
This edition separates branded visibility, comparison visibility, and discovery visibility because each reflects a different stage of the buyer journey.
Source domains are based on cited or linked URLs in responses and are used here to show which surfaces AI systems rely on when [Your Client] is present or absent.
The most meaningful opportunities often come from the gap between strong branded visibility and weaker discovery visibility, rather than from the aggregate score alone.