Who is the client?

Miquido is a software and AI development services company.

They created an AI Development Framework and needed to put it in front of the right people, the practitioners and decision-makers actively involved in real AI implementation.

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What was the problem?

Generic “AI lists” were too broad, which meant outreach reached plenty of people who weren’t actually in the market or actively working with AI in a way that could turn into revenue.

They needed a more accurate way to find and reach real AI practitioners with current, relevant intent.

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The Approach we took:

• Redefined the audience around real activity: Instead of static lists, we focused on people who were actively engaging with AI topics and signals in public channels.
• Collected social intent signals: We identified practitioners through LinkedIn engagement behavior: people actively interacting with AI content, so outreach started with relevance.
• Enriched and filtered aggressively: We processed the dataset through Clay and applied AI filters to validate role relevance, company fit, and activity level, removing contacts that didn’t match the real target.
• Personalized messaging based on what they engaged with: We launched email and LinkedIn outreach that referenced the prospect’s AI engagement context so messages felt timely and specific, not templated.
• Tight feedback loop early: We monitored performance and refined targeting and messaging quickly to increase qualified outcomes.

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Results:

Miquido generated 47 MQLs in the first month from the campaign.

The program also produced three SQLs within the first week, proving the audience strategy was reaching active, high-intent practitioners.