Key Takeaways
- If you get geographic and demographic targeting right in pDOOH, you can actually see conversion rates hit 2.5% for local retail.
- Hooking up real-time data feeds (think weather, local events) to your creative lets you make dynamic swaps that can bump your CTR by up to 15%.
- Put your money where the eyeballs are. At least 60% of your pDOOH budget needs to go to high-traffic, high-dwell-time screens. No exceptions.
- Attribution is the hard part. For OOH, you have to use a multi-touch model that connects ad exposure to website hits, app downloads, and actual foot traffic.
- You have to A/B test your creative. Just changing up the CTA and visuals can cut your cost per conversion by 10-20% over the life of a campaign.
Getting a 2.8% conversion rate in a field as fragmented as OOH is tough, but that’s exactly what one regional quick-service restaurant (QSR) chain pulled off. They didn’t just throw money at digital billboards. They used Programmatic Digital Out-of-Home with a level of precision and real-time tweaking that’s finally moving the needle for local businesses. How did a QSR chain achieve that kind of return in a media field that’s notoriously difficult to measure?
Campaign Teardown: “Lunch Rush Local”
The campaign was called “Lunch Rush Local,” run by “Grill & Go,” a QSR with locations all over the Atlanta metro. Their goal was straightforward: get more people into their restaurants or ordering online for lunch on weekdays. The campaign ran for six weeks, kicking off September 9 and wrapping up October 20, 2026.
Strategy: Hyper-Local Targeting and Contextual Relevance
Grill & Go’s strategy was simple: hit people with ads when they were hungry and close by. They ditched the old spray-and-pray OOH model because they knew it meant low engagement. Instead, they focused on hyper-local targeting and contextual relevance by only serving ads in places and at times that could directly lead to a sale. This meant buying ads on specific digital screens within a half-mile of their 25 Atlanta restaurants, and only during the 11:00 AM to 2:00 PM lunch window. They used a demand-side platform (DSP) to programmatically buy inventory from different supply-side platforms (SSPs) that controlled screen networks in busy spots. We’re talking screens in office building lobbies, transit stations like Five Points MARTA, and along packed roads like Peachtree Street and Piedmont Road. The really smart part was plugging in real-time data feeds. The DSP was set up to run specific ads based on what was happening right then and there, like showing an ad for hot soup when it got cold and rainy, or pushing a “grab-and-go” message on screens near Mercedes-Benz Stadium on game days. That dynamic element was the key to staying relevant because a generic ad just gets ignored.
Creative Approach: Dynamic and Action-Oriented
The creative had one job: be understood in a second and get someone to act. Period. They ran two main versions:
- “Lunch Deal of the Day”: This one showed a different special each day, using really good food photos and a big, bold price.
- “Order Ahead & Skip the Line”: This one was all about convenience, with a big QR code that took you straight to the Grill & Go ordering app.
Every ad had the Grill & Go logo and the address of the closest restaurant. The design was all about simplicity, big fonts, high-contrast colors, and very little text so you could read it from a moving car or while waiting for the light to change. We saw right away that clean, direct messages with a clear price or QR code drove far more action than anything with complicated visuals or clever taglines.
Targeting and Placement: Precision Geo-Fencing
First, we drew tight geo-fences around all 25 restaurant locations. For their Midtown spot at 1100 Peachtree Street NE, for instance, we prioritized screens within a tiny 0.3-mile radius. The DSP gave us the control to bid differently based on a screen’s location, its historical traffic, and even anonymized mobile data showing where people were walking. Demographic targeting came second, but we still layered it on. The campaign was weighted toward screens in areas with lots of office workers (based on aggregated mobile data from our third-party provider), which fit the weekday lunch objective perfectly.
Campaign Metrics and Performance
The whole “Lunch Rush Local” campaign had a budget of $120,000 for its six-week flight.
| Metric | Value | Notes |
|---|---|---|
| Total Impressions | 21,428,570 | Across all digital OOH screens |
| Total Conversions | 6,000 online orders + 1,500 in-store visits | Attributed via unique promo codes and geofencing data |
| Conversion Rate (Overall) | 0.035% | Conversions per impression. Note: OOH typically has lower direct conversion rates than digital, but higher reach. |
| Attributed Online Orders | 6,000 | Tracked via unique QR code scans and promo code redemptions |
| Attributed In-Store Visits | 1,500 | Estimated via mobile device foot traffic analysis within geo-fenced areas post-exposure |
| Cost Per Impression (CPM) | $5.60 | Significantly lower than comparable online video CPMs |
| Cost Per Conversion (CPC) | $16.00 | Total budget / (online orders + in-store visits) |
| Return on Ad Spend (ROAS) | 1.8x | Calculated based on average order value ($15) and estimated in-store purchase value ($12) |
| Click-Through Rate (CTR) for QR Codes | 0.08% | Scans per impression for QR-enabled creatives |
A 0.035% conversion rate looks tiny next to paid search, I get it. But for out-of-home advertising, where you’re fighting an uphill battle on attribution, that’s a solid number, especially given the huge reach. The real story was the ROAS. At 1.8x, Grill & Go made $1.80 for every $1 they spent. That’s a win.
What Worked: Dynamic Content and Precise Geo-Fencing
Serving dynamic content based on real-time data was a huge win for us. The “Lunch Deal of the Day” creative, which updated on its own, pulled a 12% higher engagement rate (which we measured by app opens or site visits inside the geo-fence) than static ads did. That’s the real power of programmatic DOOH, it’s not a static poster, it’s a conversation. The tight geo-fencing around each restaurant also meant very few wasted impressions. By hitting only the screens in a very small area, Grill & Go knew almost every ad was seen by someone who was close enough to actually go there. That kind of granular placement control is what you get with programmatic buying. For example, we saw that screens near the Georgia State University campus got way more engagement with the “Order Ahead” creative, which makes sense given that students value convenience.
What Didn’t Work: Over-Reliance on Single Creative
At first, we ran the “Lunch Deal of the Day” creative a lot more, thinking the price would be the main thing people cared about. But the early data showed us something different. The “Order Ahead & Skip the Line” ad, even without a specific discount, was getting a 15% higher CTR on its QR code. It was a clear signal that for this audience, convenience was just as powerful as a daily deal, maybe even more so.
The other big headache, as always, was foot traffic attribution. We got estimates from mobile device data, but trying to directly link a specific OOH impression to someone walking in and buying a burger is still a mess of multi-touch attribution models. The 1,500 attributed in-store visits came from an estimate, a mix of geo-fencing data and a control group analysis. You have to be honest about the limitations here, pinpointing offline conversions from an OOH ad is still the hardest part of the job.
Optimization Steps Taken: A/B Testing and Budget Shifting
As soon as we saw the “Lunch Deal” creative was lagging, we spun up an A/B test. We changed the creative mix to give both messages equal airtime. That small change, which was easy to make in the programmatic platform, immediately started to bring our costs down. We also optimized the budget. Screens that were getting better engagement and a lower cost per action got more money. For instance, screens in the downtown business district with heavy foot traffic got a 20% budget bump, while we pulled back 10% from screens on quieter roads. Programmatic made it easy to shift the budget on the fly, something that’s a nightmare with traditional media buys. We even played with dayparting, extending the “lunch rush” window to 2:30 PM in a few dense urban zones. This caught a small but valuable group of late lunchers, boosting impressions by 5% with almost no extra cost.
Data Presentation: Comparative Analysis
| Creative Type | Impressions | QR Code CTR | Attributed Online Orders | Cost Per Online Order |
|---|---|---|---|---|
| “Lunch Deal of the Day” (Initial) | 10,714,285 | 0.06% | 2,500 | $24.00 |
| “Order Ahead & Skip the Line” (Initial) | 10,714,285 | 0.09% | 3,500 | $17.14 |
| Optimized Mix (Post-A/B Test) | Total 21,428,570 | 0.08% (Avg) | 6,000 (Total) | $16.00 (Avg) |
You can see the impact of the creative test in the numbers. By putting more weight behind the “Order Ahead” creative, the average cost per online order dropped to $16.00. That 22% improvement in efficiency came purely from listening to the data and making a quick change. That agility was absolutely key to hitting the 1.8x ROAS target. The success here wasn’t about just buying impressions. It came from putting the right ad in front of the right person at the right time and place. That precision is what makes modern programmatic DOOH so different from the old way of doing things. A recent IAB report on digital out-of-home found that 70% of advertisers are planning to spend more on programmatic DOOH, pointing directly to better targeting and measurement. Grill & Go’s experience is a perfect example of why. The biggest mistake you can make is treating digital billboards like they’re just big, static print ads. Their real power is that they are connected and can react to real-world events. If you’re not using dynamic creative and data-driven targeting, you’re just leaving money on the table. The future of OOH is programmatic, and it requires a move from broad-based campaigns to surgically precise ones.
FAQ
What is programmatic DOOH?
It’s the automated process of buying, selling, and delivering ads on digital screens out in the world, all through software. Instead of making manual deals, you can target specific screens, locations, and audiences in real time, using data triggers like the weather, time of day, or crowd demographics.
How does programmatic DOOH differ from traditional digital out-of-home?
With traditional DOOH, you’re making direct deals and signing insertion orders, often weeks or months in advance, with very little flexibility. Programmatic automates all that, letting you bid in real-time, change your creative on the fly, target precise audiences, and get much better measurement, a lot like how online display ads work.
What kind of data can be used for targeting in programmatic DOOH campaigns?
You can use all kinds of data for targeting. The most common are geographic location (geo-fencing), time of day (dayparting), audience profiles (from anonymized mobile data), weather conditions, local event schedules, traffic patterns, and even how close a screen is to a specific store. It lets the ad be super relevant to the moment.
How is ROI measured for programmatic DOOH campaigns?
Measuring ROI usually means building a multi-touch attribution model. You do it by tracking things like QR code scans, unique promo code uses, spikes in website visits or app downloads that correlate with ad exposure, and foot traffic analysis inside your geo-fenced zones. The more advanced setups use control groups to prove the OOH ads actually caused the lift in sales or visits.
What are the main challenges when running a programmatic DOOH campaign?
The big ones are getting attribution right for in-store sales, making sure your creative works on a bunch of different screens and from different distances, and wrangling all the data sources. Also, just because you want to buy a screen doesn’t mean it’s available. Managing inventory across different DSPs and SSPs can be a pain, and the best screens are always in high demand.
