Balancing Google Ads Traffic and Profitability with John Moran

Summary

John Moran describes a Google Ads lead-generation account caught between two outcomes: manual CPC could increase spend but delivered weak returns, while tROAS produced better returns but would not scale to the desired budget. The team’s response was to use two campaigns for different jobs: manual bidding to reach more prospects and an automated tROAS campaign to pursue profitable conversions, with offline conversion data feeding back into Google Ads.

Strategy and operating playbook

• Separate scale from profitability. The team had struggled to make either manual CPC or tROAS scale profitably on its own. Manual bidding could drive more traffic, but returns were close to or below break-even; tROAS was more efficient but constrained spend.
• Use a two-campaign structure:
  • A manual CPC campaign is intended to win more first clicks and expand reach without relying on Google’s automated bidding limits. It serves as the scale and traffic layer.
  • A tROAS campaign optimizes toward the actual value of qualified, paid leads. The team set its target at 96; the transcript does not clarify the unit or formatting.
  • The campaigns count the same underlying offline conversion differently, using primary and secondary conversion actions and a custom “actual ROAS” column for analysis.
• Optimize to business outcomes, not shallow lead events. The account excludes actions such as add-to-cart or checkout from the relevant value measurement and focuses on the offline conversion that represents a qualified, accepted lead.
• Feed offline outcomes back to Google Ads. Leads are generated through a multi-step qualification form, sold to universities, and counted as conversions after they meet criteria and are accepted. Conversion data is uploaded automatically through an API, with enhanced conversion matching using GCLID, GBRAID, and WBRAID.
• Iterate cautiously. Moran emphasizes testing before increasing budgets: make changes, observe results, and avoid scaling aggressively until performance holds. The discussion describes roughly five-day periods for evaluating whether a change is working.

Lead-generation example

The business generates prospective university applicants. A 10-step form gathers information such as age, education history, qualifications, and industry fit. The lead is sold to schools; once a school pays and the application is accepted, the outcome is imported to Google Ads as an offline conversion. This makes the conversion more meaningful than a basic form submission, but also means the feedback loop is delayed.

Key metrics and timelines cited

Measure Result or context Manual campaign spend The team discussed spending up to $2,000/day, with examples around $22 spend for $21 in value and $2,000 spend for about $1,500 in value. tROAS performance Examples included $3 spend for $6 in value, $350 for $476, and $169 for $655. Despite stronger returns in some examples, the campaign could not exceed about $495/day against a desired $1,500/day. Recent scale limitation Moran says the account had been unable to get past roughly $500/day for two months in the constrained setup. New setup’s early results The discussion mentions examples of approximately $500 cost / $778 value and $1,300 / $3,100. Some recent conversion data was still pending, so these results were preliminary. Conversion reporting delay Offline conversions typically take about 24 hours to appear, with data arriving around 4 p.m. PT / 7 p.m. ET in the example. New tROAS setting The tROAS campaign was set to 96. Moran said the available recent data was already above target and that fully updated data might show more than double the target. Treat this as an early account observation, not a confirmed sustained result. CPC bids The transcript appears to cite bids of 4.84 and 3.26 for the manual and automated campaigns, respectively; the currency and decimal formatting are unclear.

Takeaways for marketers

• Track qualified revenue or accepted leads—not just form fills—when the business has a longer sales or acceptance process.
• Expect a trade-off between automated bidding’s efficiency and its ability to spend at scale; monitor both conversion value and cost.
• Use offline conversion imports to connect ad optimization to downstream sales outcomes, while accounting for reporting delays.
• Consider assigning distinct roles to campaigns: one to create reach and first-touch traffic, another to optimize against stronger conversion signals.
• Treat early results cautiously when offline data is incomplete, and confirm performance before materially increasing spend.

Presenters and sources: John Moran; an unnamed co-host/interviewer in the Tier 11 video.