Programmatic, data, AI and measurement: how outdoor advertising in India is changing

For most of its history, outdoor advertising in India was planned on experience and sold on trust. A media owner said a junction was busy, the brand saw a photograph of the hoarding, and that was the report. That is changing. Mobility data, digital screens, programmatic platforms and shared measurement tools are giving planners numbers that look more like those in digital media. The change is real, but it is uneven, and it helps to know which parts are mature and which are still early.

The backdrop: a growing medium that has to prove itself

Outdoor is the one traditional medium in India still growing. The Pitch Madison Advertising Report 2026 puts OOH spend at ₹4,835 crore in 2025, up 4% on 2024, and forecasts ₹5,077 crore in 2026 (exchange4media; Roastbrief). FICCI-EY, which uses a different method, reports 13% growth for organised OOH in 2025 (Indian Printer & Publisher).

Yet outdoor’s share stays small, at about 3% of total ad spend in the PMAR data, while digital takes about 60%. PMAR’s authors argue that in 2026 OOH should be planned as part of an “integrated attention system”, alongside large screens and digital video, rather than judged only on reach and frequency (exchange4media). In practice, a bigger share of budget depends on OOH answering the same questions digital answers: who saw it, how often, and what happened next.

1. Data-led planning

The biggest change is in planning, before any money is spent. Instead of choosing sites by reputation, planners can now use anonymised mobile location data to see how people move around a city: where office commuters cluster, which roads shoppers use on weekends, and which neighbourhoods a target audience lives in.

The best-known Indian example is RoadStar, built by Mumbai-based Relu AI and backed by the Indian Outdoor Advertising Association (IOAA) as a common measurement system. According to reporting on the platform, it draws on an anonymous panel of more than 35 million mobile users, combined with Census data and maps of points of interest. It reports unique reach, impressions, frequency and cost per thousand across tens of thousands of media sites (Pitchonnet; exchange4media).

The important caveat is that a currency only works when everyone accepts it. Agencies have raised concerns about privacy, data robustness and planning features during pilots (exchange4media). As of 2026, reporting indicates that adoption by some major agency networks was still pending (exchange4media). India has measurement tools for OOH, but not yet a single agreed currency like TV’s.

2. Programmatic buying

Programmatic DOOH lets a buyer purchase digital outdoor screens through software, usually by impression, with rules about when and where the advertisement runs. A brand might run only during commuting hours, only near its stores, or only when it rains.

In India this is still early. Estimates put programmatic at somewhere between 1–2% of DOOH (Adgully) and about 10% of DOOH, with a market of about ₹100 crore (Media4Growth). Globally, programmatic is closer to a third of DOOH, according to the same Media4Growth report. The main constraint in India is supply. The numbers can only grow as more media owners connect their screens to programmatic platforms.

There are working examples. Moving Walls reports a programmatic DOOH campaign for Zoho Workplace in India in December 2024 that delivered 92.7 million impressions and 3.16 million unique reach, using audience and location data to choose times and screens (Moving Walls case study). Figures like these come from the vendor’s own reporting, so read them as an example of what the method produces, not an independent benchmark.

3. AI: useful, but mostly behind the scenes

“AI in outdoor advertising” is often oversold. In India today, its useful applications are fairly practical:

• Site recommendation. Machine-learning models rank locations by how often a target audience passes them. RoadStar, for example, describes ML-based media recommendations.
• Audience estimation. Models turn raw mobility or traffic data into reach and frequency estimates.
• Camera-based counting. Some screen owners use computer vision to count people or vehicles near a screen and log anonymous counts. This raises privacy questions that buyers should ask about.
• Creative versions. Generative tools make it faster to produce many sizes and local-language versions of a creative, which matters because Indian OOH spans dozens of formats and languages.

Treat AI claims the way you would treat any audience number: ask what data went in, how the model was checked, and what the error range is.

4. Measurement after the campaign

Proof that an advertisement ran is now table stakes. For static sites that means dated, geo-tagged installation and monitoring photos. For digital screens it means proof-of-play logs. The bigger shift is towards measuring outcomes:

• Brand lift studies that compare awareness in campaign areas with control areas.
• Footfall attribution, which uses mobile data to compare store visits by people exposed to the media with those who were not.
• Search and web lift, which tracks branded search or site visits from campaign cities during the flight.
• Direct response, through QR codes, short URLs, WhatsApp click-to-chat and coupon codes that are unique to the medium.

None of these is perfect. A sensible plan uses one or two that fit the objective, agreed before the campaign starts, rather than an impressive-looking dashboard assembled afterwards.

What has not changed

The technology does not replace the basics. A hoarding still has to be visible from the road, readable in three seconds and placed where the audience actually goes. A metro wrap still has to be installed well and maintained. A screen still has to be switched on. Most Indian OOH, including the larger part of hoardings, car branding and transit media, is still static, and its quality depends on site selection, execution and monitoring. Data makes those decisions sharper. It does not make them for you.

What this means for brands planning OOH in 2026

1. Ask for audience data at the planning stage, not just at the reporting stage, and ask how it was produced.
2. Use digital screens where timing matters, and test programmatic in small amounts where supply exists.
3. Agree on one outcome metric before launch (search lift, store visits, QR scans or leads) and build the plan to influence it.
4. Keep proof of display non-negotiable for every format, static or digital.
5. Connect OOH to your digital plan, for example by retargeting people who were near your sites or matching creative across channels.

Key takeaways

• Indian OOH is growing, but to win a larger share of budget it has to be measured like other media.
• Mobility data and platforms like RoadStar are changing planning, though a single industry currency is not yet settled.
• Programmatic DOOH is small in India and limited by supply, but it is growing.
• AI helps mostly with planning, counting and creative production. Question the claims.
• Good execution still matters as much as good data.

If you would like a data-led plan for outdoor, transit or DOOH, talk to us.