How teams improve AI visibility with Findable
Real examples of how teams find where they are missing in AI answers, fix it, and improve how their brand is represented.
These case studies are illustrative scenarios based on real platform usage patterns, not customer endorsements.Free. No credit card required.
Customer Stories
How teams use Findable across industries
How teams use Findable to understand AI visibility, uncover competitors, map trusted sources, and prioritize what to improve next.
A global executive education institution
Findable mapped how AI engines describe Executive Education, who they cite, and which questions a brand needs to own.
- 10 prompts analyzed across AI engines
- 7 competitors surfaced
- 190 unique cited domains mapped
A behavioral healthcare software provider
Findable mapped how AI engines describe Healthcare SaaS, who they cite, and which questions a brand needs to own.
- 10 prompts analyzed across AI engines
- 7 competitors surfaced
- 499 unique cited domains mapped
A healthcare services organization
Findable mapped how AI engines describe Healthcare Services, who they cite, and which questions a brand needs to own.
- 10 prompts analyzed across AI engines
- 5 competitors surfaced
- 233 unique cited domains mapped
A property management technology company
Findable mapped how AI engines describe PropTech, who they cite, and which questions a brand needs to own.
- 10 prompts analyzed across AI engines
- 2 competitors surfaced
- 513 unique cited domains mapped
A global retail and sporting goods brand
Findable mapped how AI engines describe Retail & Sporting Goods, who they cite, and which questions a brand needs to own.
- 10 prompts analyzed across AI engines
- 7 competitors surfaced
- 314 unique cited domains mapped
A fashion and apparel brand
Findable mapped how AI engines describe Fashion & Apparel, who they cite, and which questions a brand needs to own.
- 10 prompts analyzed across AI engines
- 7 competitors surfaced
- 303 unique cited domains mapped
A business advisory firm
Findable mapped how AI engines describe Business Advisory, who they cite, and which questions a brand needs to own.
- 10 prompts analyzed across AI engines
- 7 competitors surfaced
- 282 unique cited domains mapped
See what changed and how visibility improved.
AI visibility is a new discipline. Unlike traditional SEO or paid media, it requires understanding how language models interpret, summarize, and recommend brands based on patterns in their training data and live retrieval sources. These scenarios illustrate how teams approach this challenge.
Scenario-based case studies
Real-world examples of how teams use Findable to improve their AI visibility
How a SaaS founder monitors AI visibility during product launch
A founder launching a workflow automation tool had no visibility into how AI platforms described tools in their category.
- Monitored which prompts mentioned the product category
- Tracked how AI platforms positioned competitors in software comparisons
Increased clarity on category positioning in AI answers, with baseline data to guide go-to-market messaging.
How an agency establishes AI visibility baselines for clients
An agency onboarding an HR software client had no documented view of how AI platforms currently described the client's product.
- Reviewed AI visibility across multiple platforms
- Benchmarked client presence against competitors in the same space
Improved client reporting with a documented baseline for tracking AI visibility progress throughout the engagement.
How a marketing team monitors AI visibility alongside SEO
A project management company's marketing team saw strong SEO performance but had no data on how their brand appeared in AI-generated responses.
- Reviewed brand presence in AI answers across platforms
- Compared AI visibility data alongside existing SEO metrics
Clearer view of brand discoverability across both search and AI channels, supporting strategy for AI as a visibility channel.
How leadership teams get a unified view of AI visibility
A VP of Marketing needed to brief the executive team but had no consolidated view of how the brand appeared across major AI platforms.
- Reviewed unified dashboard showing visibility across ChatGPT, Perplexity, Gemini, and Claude
- Identified platform-specific gaps
Improved executive alignment with a clear, consolidated summary of AI visibility across all major platforms.
How a sustainable apparel brand compares AI visibility with competitors
The marketing team wanted to understand how their brand appeared alongside competitors when users asked AI about sustainable clothing.
- Compared brand vs
- competitor descriptions across AI platforms
- Reviewed relative visibility across different query types
Improved positioning by identifying specific prompts where competitors were chosen instead of the brand.
How a B2B team monitors brand sentiment across AI platforms
A B2B software company had no insight into the tone and language AI platforms used when describing their brand.
- Reviewed sentiment patterns across AI platforms
- Tracked how the brand was characterized in different query types
Improved brand consistency across AI platforms by identifying and addressing tone and messaging gaps.
How an agency documents AI visibility trends for client reporting
An agency needed to show their client clear evidence of how AI visibility had evolved during their engagement.
- Reviewed historical AI visibility data
- Compared how AI responses changed over time across different platforms
Clearer client reports showing visibility trends, making AI visibility progress easy for stakeholders to understand.
How a consulting firm tracks AI visibility over time
A managing partner wanted to monitor how AI platforms described the firm over time and detect any changes in positioning.
- Tracked specific queries over time
- Reviewed how AI responses evolved and documented visibility trends
Increased visibility tracking accuracy, supporting internal reporting and early detection of shifts in AI brand representation.
How a freelance AI visibility expert helps clients control how AI describes them
Clients needed to know if AI tools accurately described their services. Inaccurate or missing mentions were costing them discovery opportunities.
- Compared how ChatGPT, Perplexity, and Gemini described each client's services
- Identified inconsistencies and missing mentions across platforms
More consistent brand mentions across AI platforms, with clearer representation in key service-related prompts.
How a consultant tracks how AI describes client services
An independent marketing consultant's clients wanted to know if AI platforms recommended their businesses for relevant queries.
- Reviewed client mentions across ChatGPT, Perplexity, and Gemini using real buyer-style queries
- Identified where clients were missing
Clearer AI presence for clients, with adjusted content and positioning that improved representation in AI answers.
These are repeatable patterns across different industries and teams.
What these scenarios show
AI visibility can be measured and improved
Competitors often appear where your brand is missing
Fixing gaps improves how your brand is represented
Visibility improves over time with consistent updates
These are real scenarios based on how teams use Findable to improve AI visibility.
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