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Full-Funnel Marketing Automation

Designed and optimized paid acquisition campaigns with data-led experimentation and AI-assisted insights.

Author: Team ValeffDate: April 09, 2026Time: 04:45 PM IST6 min read
AutomationAIWeb Dev
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The results

Data-driven paid campaign optimization with structured experimentation and automation.

31%

Lower cost per qualified lead

2.2x

ROAS improvement in 10 weeks

MoM

Consistent pipeline growth trend

How we solved the problem

Context

Paid acquisition was active but unstable, with inconsistent return between campaigns and audiences.

The team needed a repeatable experimentation system instead of one-off optimization attempts.

The challenge

  • High ad spend with fluctuating lead quality and ROI.
  • No reliable visibility into where the funnel leaked intent.
  • Creative and audience tests lacked structure and learning loops.

Execution

1. Rebuilt campaign architecture by funnel intent

  • Split campaigns by awareness, consideration, and conversion objectives.
  • Aligned messaging and landing pages to stage-specific user intent.

2. Operationalized experimentation cadence

  • Introduced weekly testing cycles for creatives, offers, and page variants.
  • Tracked learning velocity, not just winner/loser outcomes.

3. Closed the loop with downstream conversion data

  • Synced CRM qualification signals back into campaign optimization logic.
  • Prioritized spend toward channels driving revenue-quality leads.

What changed

  • Cost per qualified lead reduced by 31% while maintaining volume.
  • ROAS improved 2.2x over a focused 10-week optimization window.
  • Pipeline growth became consistent month-over-month.

What's next

  • Deploy creative fatigue prediction to refresh assets proactively.
  • Extend funnel scoring to include sales cycle velocity.
    Full-Funnel Marketing Automation