Case Studies
Pro Football Search Ads: 0.05 to 20.98 Peak ROAS in 27 Days
Google Ads sells football tickets when the budget follows intent. For a pro football client, we moved spend from Display to high-intent Google Search, targeted a radius around the stadium, built a full keyword set with negatives, and scaled only as returns held. ROAS went from 0.05 to a 20.98 peak in 27 days, and 14.06 over the full run.
What was going wrong before we changed anything?
The campaign started on Google Display. It looked busy: after 16 days it had 850K impressions. But it returned a ROAS of just 0.11x, and by the end of the Display phase ROAS had fallen to 0.05.
Display did its job, which is reach. The problem was that reach isn't the same as ticket buyers. Most people who saw those ads weren't shopping for tickets that day. No bid strategy or creative refresh could turn that audience into buyers fast enough. Automation can't fix the wrong channel.
What did we change in the first 27 days?
Everything below comes from the case study. We didn't add steps to make it look neater.
1. We moved the budget to high-intent Search
We shifted the budget from Display to high-intent Google Search. A fan typing the team's name plus "tickets" has already decided what they want. Search puts the ad in front of them at that moment.
2. We started with a tight radius, then widened it on proof
We began with a 125-mile radius around the stadium. Once demand was proven, we widened it to 200 miles plus the surrounding states. Starting tight kept early spend on the fans most likely to buy. Widening later added reach only after the returns justified it.
3. We built a full keyword architecture with negatives
We built 89 keywords across broad, phrase and exact match, backed by negative keywords. Fans search for the same tickets in many ways, so coverage matters. Negatives keep spend away from searches that look relevant but don't convert.
4. We scaled the daily budget only as returns held
The daily budget grew step by step, and only when the previous level had proven profitable. We never raised spend on hope.
5. We wrote copy with AI help and optimized it every week
We wrote and iterated the ad copy with ChatGPT, then reviewed and optimized it every week based on what was converting.
How fast did the results come in?
Checkpoint | Search ROAS |
|---|---|
Display phase (end) | 0.05 |
Early check | 4.73x |
Mid-September | 13.65x |
Peak (27 days in) | 20.98x |
Early October | 19.33x |
Full run (about 12 weeks) | 14.06 |
From 0.05 to the 20.98 peak is a 419x improvement. Over the full run of about 12 weeks, Search delivered 14.06 ROAS.
Both numbers matter. The 20.98 peak shows how quickly the right channel can turn a campaign around. The 14.06 full-run figure shows the result held for about 12 weeks, not just on one good day.
Does this work for college football and bowl games?
The same method fits college football, and bowl pushes in particular. A bowl game has a fixed date, a short selling window and fans who search by name: the team, the bowl, and "tickets". That's high intent you can bid on.
We'd apply the same steps:
Lead with Search for the people already looking for tickets.
Start with a radius you can prove, then widen it toward travelling fans once returns hold.
Build keywords around how fans actually search, with negatives from day one.
Scale on proof as the game gets closer.
Refresh copy weekly while the window is open.
We haven't run a bowl campaign as a case study yet, so we aren't quoting bowl results. The method is what carries over.
Where do Display and other channels fit?
Display and other awareness channels still have a role, such as building demand ahead of a season or for fans who don't know the schedule yet. They work best when sized around Search, not in place of it. We plan the channel mix around the goal, whether that's Google, Meta, ChatGPT Ads or another channel where fans spend time.
How can you apply this before your next home stand?
Start with three checks:
Where is the budget going? Split spend by channel and compare each against conversion value, not impressions.
Is tracking measuring ticket value? Honest ROAS depends on conversion values being right.
Are you scaling on proof? Raise budgets only when returns hold at the current level.
We review performance regularly against a verified baseline. Read the full case study, see our sports work, and how we use Google AI Max.
Next home stand or bowl push coming up? We'll start with a Search audit of your current ticketing campaigns. Book a call
Related: hockey season and group ticket ads · dynamic radius targeting
Frequently asked questions
Why switch football ticket ads from Display to Search? Display built reach but didn't sell tickets, ending its phase at 0.05 ROAS. Search reaches fans who are already looking for tickets. For a pro football client, Search reached a 20.98 peak ROAS in 27 days.
How fast can Google Search improve football ticket ROAS? For a pro football client, Search reached 4.73x at the first check and peaked at 20.98x 27 days in. Over the full run of about 12 weeks it delivered 14.06 ROAS.
Does this approach work for bowl games? The method carries over: lead with Search, start with a radius you can prove, build keywords with negatives, scale on proof and refresh copy weekly. We don't have a bowl case study yet, so we don't quote bowl results.
Was the budget increased all at once? No. The daily budget grew step by step, and only as ROAS held.