43% of Restaurant Offer Tests Reached at Least 2x ROAS. So Run Three, Not One.
In Feast data, 21 of 49 eligible restaurant offer tests reached at least 2x tracked gross ROAS. See why one test is a poor verdict.
In a Feast analysis dated July 12, 2026, 21 of 49 eligible restaurant offer campaigns reached at least 2x Feast-tracked gross ROAS. In other words, 43% recorded at least two dollars in attributed gross revenue for every dollar of mapped Facebook ad spend.
This is not an industry benchmark, a profit claim, or a promise that your next offer will work. It is evidence that one campaign is a weak basis for deciding whether restaurant advertising works at all.
The practical response is to run three separate offer tests, one after another. Three is not magic and it does not guarantee a winner. It simply gives you more than one chance to learn whether the problem was the offer, the ad, the path to the restaurant, or the economics.
What the 43% actually measures
The analysis included Feast restaurant campaigns with at least $100 in mapped paid-social spend and POS-linked order records. The $100 was an inclusion rule, not a recommended test budget. Internal test organizations were excluded, and 25 duplicate campaign records from shared ad accounts were removed before the campaigns were counted.
| Part of the analysis | What was counted |
|---|---|
| Campaigns | 49 eligible restaurant offer campaigns |
| Result | 21 reached at least 2x Feast-tracked gross ROAS |
| Revenue | Gross, non-voided order total attributed to the Feast campaign |
| Spend | Mapped Facebook ad spend for that campaign |
The analysis does not show full-cost profit or prove that the ads caused every attributed sale. Restaurants without the required POS-linked data were outside the group, so the 43% should not be presented as what restaurants everywhere normally achieve.
One failed offer does not tell you why it failed
In the same historical group, 49% of eligible campaigns finished below 1x Feast-tracked gross ROAS and 20% recorded no attributed orders. A miss was common in this particular dataset.
That does not make a loss acceptable. It shows why the first result needs a diagnosis rather than a verdict.
If people barely respond, the offer, ad, audience, or landing page may be weak. If people claim or reserve but do not arrive, the problem may be timing, reminders, availability, or the restaurant experience. If guests arrive but the sales cannot be connected, the tracking or POS handoff may be broken. If sales are connected but the campaign still loses money after food, discounts, labor, and fees, the offer economics are the problem.
“Although we do social media and digital marketing, we can't figure out why it's not working.”Restaurant owner
One test can reveal a problem. It usually cannot show whether a different offer would solve it.
Three tests are useful only when each one answers a different question
Run the tests sequentially and keep the restaurant problem steady. If Tuesday dinner needs more first-time guests, do not change the daypart, audience, message, offer, and booking path all at once. Change the part the first result gave you a reason to question.
A clean three-test sequence looks like this:
- Run one offer with its own dates, spend, and trackable response.
- Follow responses through completed visits and settled checks.
- Change one meaningful part based on where people dropped out or where the math failed.
- Repeat until you have three readable results or a clear reason to stop earlier.
Campaigns are not independent coin flips. The same restaurant, season, service problem, audience, and tracking gaps can affect all three, so do not turn the 43% historical rate into a probability that one of your three must win.
Cafe Alyce missed twice before the third offer worked
Cafe Alyce makes the range concrete. The restaurant recorded two offers below the 2x line before a third crossed it.
| Test | Offer and recorded result | Tracked gross ROAS |
|---|---|---|
| 1 | $500 spend and $800 tracked revenue | 1.6x |
| 2 | Half off an appetizer with dinner; $295 spend and about $100 tracked revenue | About 0.34x |
| 3 | A $50 ribeye offered for $30; $674 spend and $5,000 tracked revenue | About 7.4x |
The third campaign later recorded $27,000 in tracked revenue, but the source does not provide a new spend figure for that later total, so it cannot be turned into a later ROAS. The case also does not prove that ribeye is a universal winning offer or that the third campaign caused every sale.
The useful lesson is the sequence. After two misses, the restaurant tried another offer and learned from a third result instead of deciding after the first campaign that Facebook ads did not work.
The sequence is most useful as restaurant-specific evidence that several distinct offers can produce very different results, not as a promise that the same three offers will work elsewhere.
Your restaurant's break-even number matters more than 2x
The 43% study used gross attributed revenue divided by ad spend because that was the consistent historical measure available. Your restaurant still has to account for the variable food and beverage cost, recorded discounts, reward fulfillment, payment processing, campaign production, software fees, agency fees, and incremental paid labor when each applies. Count every cost once.
A campaign can clear 2x gross ROAS and still disappoint after those costs. Another campaign can fall below an arbitrary internet benchmark and still make sense if its margins and repeat business support it.
Before each test, write down the largest total campaign cost your expected first checks can support. Afterward, keep four answers separate: attributed gross revenue, any observed movement in overall covers or sales, the contribution left after variable and campaign costs, and profit after the rest of the business expenses. The restaurant marketing ROI guide explains those layers in more detail.
Run three offers because one result is not enough to learn from
The 43% does not say that three campaigns guarantee success. It says restaurant offer outcomes vary widely, even inside one historical dataset, and one result leaves too many explanations open.
Use the first campaign to find the first obvious weakness. Use the second to change that weakness without rebuilding everything. Use the third to confirm whether the change improved completed visits and the money left after costs. If the economics cannot work, stop. If the records cannot show what happened, fix the measurement before spending more.
For more offer structures, start with restaurant promotions that protect the margin. If ads are already running and you need to interpret the evidence, use the restaurant-ad decision guide.
Feast connects campaign responses with supported POS sales so restaurants can see attributed gross revenue without confusing it with profit or causal lift.