Case studies
See how product-level AI visibility audits reveal where products appear, disappear, or are misunderstood in AI-led buyer journeys.
These case studies focus on measurement. They show what Odyssiant can uncover from an audit: buyer-stage visibility, product-theme gaps, prompt-level strengths and weaknesses, evidence quality, and the actions that should be prioritised next.
Equans wanted to know how its Carbon Shift decarbonisation proposition appeared in AI-led buyer research. Odyssiant mapped visibility across awareness, consideration, evaluation and decision-stage prompts, showing where Carbon Shift was strong, where competitors led, and how to shape the buyer journey earlier.
- •Evaluation: 65 → 81
- •Decision: 32 → 49
- •26 prompts improved
- •4 buyer stages audited
An ongoing case study in how Odyssiant uses its own platform to measure, improve and retest its visibility across AI-generated answers. Since 10 April, our overall score has moved from 17 to 26, with 34 individual AI answers improving across consideration, evaluation and decision-stage prompts.
- •Overall score: 17 → 26
- •34 AI answers improved
- •Audit window: 10 Apr – 31 May
- •4 engines tested in latest run
NatWest is a major UK financial-services brand, and investment products are strategically important. But a product-level AI visibility audit showed that NatWest Investment Accounts were almost invisible at the awareness stage and under pressure from better-surfaced investment platforms.
- •122 buyer prompts tested
- •99% answers scored
- •4 buyer stages audited
- •Overall score: 26/100
EE One performed more strongly than many products in AI-led buyer research, especially when buyers compared named broadband and mobile bundle alternatives. But the audit also revealed weak spots in awareness-stage prompts, consumer-protection questions, and ambiguous household-plan language.
- •75 buyer prompts tested
- •100% answers scored
- •4 buyer stages audited
- •Overall score: 60/100
Revolut Business led its competitor set in answer-driven competitive analysis, but a product-level AI visibility audit showed a major awareness-stage gap. Across 516 prompts and four AI engines, the product was strongest when named directly and weakest when buyers asked broad multi-currency account questions.
- •516 buyer prompts tested
- •92% answers scored
- •4 AI engines tested
- •Overall score: 29/100
SAP is one of the world's best-known enterprise software brands. But a product-level AI visibility audit showed a sharp difference between brand recognition and product discoverability across AI-led ERP buying journeys.
- •153 buyer prompts tested
- •100% answers scored
- •4 buyer stages audited
- •Overall score: 40/100
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