D.O. Cava

A research system assisted by AI to track the sparkling market and transform dispersed changes into positioning decisions

D.O. Cava communicates a category, an origin, a regulation, a production fabric and a culture. The challenge was to observe how the stories of sparkling wines, consumption, wine tourism and sustainability evolved without losing its own criteria or copying external trends.

Karmina AI Studio implemented a Benchmark Scout with stable methodology, cited sources and expert review. The AI collected and compared; the team contextualized regulatory, cultural and commercial differences.

Main CTA: Build a live benchmark CTA Secondary: Discover the Benchmark Scout

Summary Fact Sheet

• Organization: D.O. Cava
• Sector: food, territory and institution
• Challenge: following an international market by maintaining origin, regulation and context
• Principal Agent: Benchmark Scout
• Complementary agents: Market Scout · Social Listener
• Service: strategy and research assisted by AI
• AI layer: benchmark agents, market research and social listening
• Human role: methodology, sectoral interpretation, source validation and decision-making

El challenge

A good benchmark not only asks what others do, but what it means to us.

Comparisons can mix denominations, brands, distributors, territories and creators as if they were equivalent actors. They can also confuse a visible campaign with a real market change.

The challenge was to maintain comparable criteria over time and distinguish between signal, example, data and hypothesis.

The starting point

A matrix was built with stable fields: market, actor, category, occasion of consumption, territory, public, message, format, channel, source, date and degree of confidence. Regulated categories and terms of origin required a specific layer of validation.

The system was not to produce an infinite list, but a periodic reading that would make changes and gaps visible.

The Karmina AI Studio approach

The solution combined:

• Benchmark Scout to keep the comparison.
• Market Scout to further the relevant changes.
• Social Listener to detect emerging conversations and languages.
• An expert review to relate signals with regulation, origin and strategy.

Each conclusion had to link with evidence and clearly distinguish the fact from the interpretation.

How it worked

1. Definition of business questions and comparable criteria.
2. Periodic collection of approved sources.
3. Standardization of markets, actors and categories.
4. Check for changes over the previous period.
5. Review of false equivalents and regulatory specifications.
6. Providing an executive summary with evidence and possible decisions.