Overview
Miter's paid media program was generating form fills but optimizing blindly, without downstream conversion signals, the budget was flowing toward volume over quality. Over 90 days, Omni Lab rebuilt the measurement foundation, restructured campaign architecture, and scaled spend into proven segments. The result: SAL volume roughly doubled, and SQLs reached consistent all-time monthly highs.
The Challenge
Miter operates in a specialized vertical where buyers, construction, and field service companies evaluating payroll and workforce tools, carry high intent but require careful qualification. The paid media program had real traction, but the infrastructure to act on it was missing.
Without MQL, SQL, and SAL-level conversion signals flowing back into the ad platforms, the campaigns had no way to distinguish a qualified opportunity from a form fill. Bidding strategies were calibrated to volume, not value. Budget allocation followed assumptions rather than evidence. The program was generating activity. It wasn't reliably generating pipeline.
The Approach
Building the measurement foundation before scaling. The first priority was wiring offline conversion values into Google Ads and Bing, mapping MQL, SQL, and SAL events back to individual campaigns. This single infrastructure change transformed what was possible downstream. For the first time, campaigns could be evaluated and optimized against the metrics that actually determined revenue, not just platform-reported conversions.
Evolving bidding strategy as data matured. Rather than defaulting to sophisticated bidding from the start, the team deliberately staged the transition. Campaigns began on Manual CPC to gather clean data, moved to Maximize Conversions as volume grew, and graduated to Target ROAS and Maximize Conversion Value once enough downstream signal existed to optimize reliably. This sequenced approach, conservative early, aggressive once evidence supported it, is what allowed one construction payroll campaign to grow conversions by more than 1,000% in a single month after a period of measured data collection.
Allocating budget to efficiency, not assumption. Google spend scaled by roughly 75% over the period, but the increase wasn't uniform. Budget followed a clear threshold: campaigns demonstrating cost-per-SAL within the target received more. Campaigns that couldn't demonstrate efficiency were held flat or restructured. Bing, initially underfunded relative to its performance, was identified as an underexploited channel and scaled accordingly after the data made the case.
Separating match types to protect high-intent traffic. High-intent exact-match keywords were competing for budget with broader phrase-match terms in the same campaigns and losing. Splitting them into dedicated campaigns with separate bidding strategies gave each segment the investment and optimization logic appropriate to its role in the funnel. This structural fix improved both volume and quality across the non-brand program.
Tightening audience quality rather than chasing reach. On LinkedIn, underperforming industry segments were removed from targeting to concentrate impression share on Miter's core ICP. Retargeting windows were tightened from 180 days to 90 days to improve audience recency and relevance. On the search side, high-spend keywords that did not contribute to the downstream pipeline were paused, and impression share was redirected to proven converters. Device-level data revealed that mobile traffic was generating clicks without converting downstream. Mobile targeting was disabled on exact-match non-brand campaigns to improve SAL and SQL quality.
The Results
SAL volume roughly doubled over the engagement period compared to the prior three months, with March reaching the highest single-month total in the program's history. SQLs held at near-record levels for three consecutive months, February, March, and April, reflecting consistent pipeline quality rather than a one-time spike.
The Bing program, often treated as a secondary channel, demonstrated cost-per-conversion competitive with Google's at scale and was scaled up rather than held flat. LinkedIn retargeting audiences converted at a 3% rate, performing as a warm-pipeline reinforcement layer rather than a direct-response channel.
Across the board, the pattern was the same: structural fixes compounding into efficiency gains, and efficiency gains compounding into scale.
"Patience compounds results. March underperformance led to April's improvement as we gathered data."
Strategic Takeaway
Miter's results reflect what happens when infrastructure, strategy, and execution are aligned. No single tactic drove the outcome, it was the cumulative effect of accurate measurement, disciplined budget allocation, and bidding strategies calibrated to account maturity. The program is now optimized against real pipeline metrics, with the architecture in place to sustain and build on these results as conversion volume continues to grow.
