How Air Rebuilt Paid Efficiency and Restored MQL Growth

The Overarching Challenge

Air’s paid acquisition engine had begun to stall.

Spend continued to rise, but efficiency was slipping. Cost per lead climbed while lead quality became increasingly inconsistent. Native targeting within paid platforms struggled to reach the right mix of creative decision-makers, and the team lacked confidence that their budget was being allocated to audiences that resembled their best-performing users.

The problem was not volume. It was signal.

Air needed a way to regain control of audience quality without sacrificing reach — and to prove that paid campaigns were driving meaningful pipeline, not just surface-level engagement.

How Air Rebuilt Paid Efficiency with Primer

Air approached the problem as a system challenge, not a channel problem. Their strategy combined audience precision with disciplined measurement and creative iteration, structured across three pillars.

Pillar 1 · Rebuild Audience Quality (Top-of-Funnel Control)

Goal: Ensure paid traffic reflects high-fit users, not just high volume.

Air replaced broad platform targeting with Primer-built ICP audiences derived from firmographic and role-based filters. These audiences mirrored the profiles of Air’s highest-converting customers and excluded low-fit segments that had previously inflated CPL.

Result: CPL dropped by 50% as spend shifted toward users with higher relevance and intent.

Why it worked: The algorithm was no longer optimizing for cheap clicks. It learned from audiences that reflected real buying potential.

Pillar 2 · Reinforce Demand with Measurable Lift (Mid-Funnel Precision)

Goal: Convert attention into qualified demand.

Air paired their refined audiences with structured campaign measurement using controlled testing and performance monitoring. This allowed the team to isolate which audience segments, placements, and messaging combinations were contributing to qualified lead generation.

The result was not only better efficiency — but healthier pipeline momentum.

Result: MQL volume increased by 34% without increasing spend.

Why it worked: Air shifted focus from raw traffic acquisition to audience impact and downstream quality metrics.

Pillar 3 · Sustain Performance Through Iteration (Learning Flywheel)

Goal: Maintain gains without creative or audience fatigue.

With a stable targeting framework in place, Air focused on steady creative refresh and iterative testing. Performance insights from Primer helped inform which segments warranted increased spend and which should be constrained or rotated out.

This prevented regression to high-cost patterns and ensured ongoing improvements were sustainable — not one-time corrections.

Practical Guidance from Air

The Outcome

Air transformed paid acquisition from a deteriorating cost center into a predictable growth engine.

Cost per lead declined by 50%, MQL volume grew by 34%, and performance stability returned across channels. Instead of guessing where budget was working, the team gained visibility into which audiences and campaigns were driving qualified demand — restoring confidence in paid as a core growth lever.

The result was not just improved efficiency, but renewed strategic clarity around where to invest for scalable pipeline creation.