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CHANEL

An AI search dashboard, regional research and a reporting framework that make it easier for business, PR and retail teams to understand what people see when they ask about the brand.

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The CHANEL AI search dashboard example built by DLVX, with engine comparisons, prompt detail and a technical audit

Delivered dashboard example. Its figures and generated answers are illustrative, not CHANEL performance results.

The brief connected three questions: what AI says about the brand, which sources shape those answers, and what each regional team can do with that information.

  • Working dashboard example
  • English and Thai research
  • Reporting framework for business, PR and retail

Inside the work.

Make the answer inspectable.

We built a dashboard example with an overview of AI visibility, comparisons across engines and a prompt-level view of answers, sentiment and cited sources. Competitive share of voice and technical audit sections put the different parts of the research in one interface.

A concrete interface to explore and discuss, with sample figures clearly identified wherever they appear.

A closer look at the delivered dashboard example
A detail from the delivered dashboard example. All figures in this screen are illustrative.

Start with the questions people ask.

The research brought together brand and category questions, the answers returned by AI search, the competitors named and the sources cited. English and Thai questions gave the regional discussion a local starting point, alongside dated Thailand signals and event and trend research.

A research structure that keeps the question, language, answer and source together, so a recommendation can be traced back to what prompted it.

From a question to a useful decision

  1. AskRecord the question, market and language.
  2. InspectKeep the answer, named brands and sources together.
  3. InterpretExplain what the finding means for the team.
  4. ActTurn the finding into a specific next step.
Workflow illustration based on the project scope.

Give each team a useful next step.

We shaped the reporting around how the work would be used. Business needs the wider competitive picture. PR needs to understand the publications and sources influencing answers. Retail needs the local questions and signals that can inform conversations with customers.

A framework connecting findings, sources, interpretation and recommended actions, rather than leaving the team with a score alone.

What the team gained.

Dashboard, research and reporting framework delivered for the regional discussion.

  • A working interface

    The dashboard made the research structure tangible, from the overview to individual prompts and sources.

  • A shared reporting language

    Business, PR and retail could discuss the same findings through the lens of their own work.

This case covers the dashboard example, research and reporting framework. Dashboard sample figures are illustrative. It does not present a regional production rollout or measured commercial uplift.

Need to turn search and AI research into a tool your team can use?

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