Why CTV in India can no longer be planned as one market
Connected TV in India has stopped being a small, urban, premium habit. Smart TVs are cheap now. Fibre broadband has reached deep into small towns. The living room screen has quietly turned into a digital one, and YouTube sits at the centre of it, pre-loaded on almost every Smart TV sold in the country. If you’re still weighing whether CTV deserves a line item in your media plan at all, our earlier piece on why CTV belongs in your advertising plan is a good starting point before diving into the state-level numbers below.
Kantar’s Media Compass report puts monthly CTV viewers in India at 166 million as of Q1 2026, up 23% year on year. That is fast growth by any standard, and it is the number most industry conversations about CTV lead with. But a single national figure hides more than it reveals. It tells a brand that CTV is growing. It tells them nothing about where to put a rupee.
We wanted to know what CTV in India looks like once you stop treating it as one market and start treating it as twenty-plus separate ones. So we pulled reach data from YouTube’s Reach Planner, ran it for a brand-awareness campaign at maximum budget over a 28-day window, and broke it down state by state, and by urban and rural geography within each state. This report is the result. It is meant to work as a full planning reference, not a single headline finding, which is why it covers scale, penetration, cost efficiency, frequency, and the urban-rural split, in that order, before landing on our sharpest and most counter-intuitive observation at the end.
Key findings at a glance
- Uttar Pradesh and Maharashtra are India’s two largest YouTube CTV markets, together reaching more than 50 million connected viewers.
- Most leading states plateau at roughly 17.5-18.1% penetration, a shared structural ceiling, even under a maximum, uncapped campaign budget.
- Uttar Pradesh, Bihar, West Bengal, Odisha, Jharkhand, and Assam sit well below that ceiling, at 6-13% penetration, despite large populations, marking them as the biggest untapped CTV opportunities in India.
- Cost per reached user ranges from ₹0.09 (urban Himachal Pradesh) to ₹1.75 (rural Jharkhand and Chhattisgarh), a roughly twentyfold spread across the country.
- Rural CTV penetration beats urban penetration in several of India’s more digitally advanced states, including Gujarat, Telangana, Kerala, Punjab, and Haryana, reversing the usual urban-first assumption.
- High cost paired with high frequency (35.5x in rural Jharkhand, 34.6x in rural Chhattisgarh) signals a reach ceiling, not strong engagement.
🎥 Prefer to watch this in a minute? Here’s a quick video walkthrough of the headline findings from this report:
Why this report exists
Most public research on Indian CTV stops at national numbers: audience size, growth rate, device shipments. That is useful for understanding the category as a whole, but it does not help a media planner decide where to allocate a budget this quarter.
CTV buying decisions get made state by state, sometimes city by city. A brand needs to know whether Telangana behaves like Karnataka. Whether Bihar’s audience looks anything like Maharashtra’s. Whether the cheapest reach in the country sits in a metro or in a hill state most planners never think about. Whether a state with a huge population is actually a huge opportunity, or whether its scale is misleading. Nobody publishing in India right now has an easy way to answer these questions with real numbers. This report tries to close that gap using planning-tool output rather than survey estimates or shipment data.
Three specific gaps stand out in existing coverage. First, almost nothing published breaks CTV down by urban and rural geography within a state, so a genuinely large and, in several states, deeper rural audience stays invisible in the national narrative. Second, cost and frequency benchmarks are rarely discussed at the state level at all, which means planners have no reference point for where a rupee goes furthest or where a campaign is likely to hit a reach ceiling. Third, there is no easy way to tell whether a state’s population size actually converts into CTV opportunity, or whether its scale is a demographic mirage sitting on top of low penetration, as this report shows is the case for Uttar Pradesh. This report is built specifically to answer those three questions with numbers, not impressions. For the category-level shifts happening alongside this state-level picture, AI-driven planning, regional targeting, hybrid monetization, our Top CTV Advertising Trends to Watch in 2026 covers where the wider CTV ecosystem is headed.
Why YouTube is a fair proxy for Indian CTV
No single platform can represent all of India’s connected TV viewing, and this report should not be read as a census of every CTV app in the country. But YouTube comes closer than anything else that publishes usable, comparable planning data across states.
YouTube is India’s largest video platform by a wide margin, with a monthly user base in the 450 to 500 million range, the biggest audience it has in any country in the world. On the CTV screen specifically, Google has reported that YouTube’s connected TV audience in India crossed 75 million, and it is one of the primary destinations feeding the 166 million monthly CTV viewers Kantar counted. Unlike subscription platforms that are walled off by paywalls, tiered pricing, or narrow content libraries, YouTube is used across income levels, languages, states, and age groups. It behaves like a utility rather than a niche habit.
That is the basis for treating YouTube CTV reach as a working proxy for the broader shape of CTV adoption in India. It is not a perfect stand-in, and we flag where that matters throughout this report, but it is one of the very few platforms offering a public, planning-grade interface that can be compared consistently across every major state, split by urban and rural geography, under one fixed set of campaign settings. That consistency is the entire value of this exercise. It turns a scattered, anecdotal picture of Indian CTV into a single, comparable dataset. YouTube is one of several CTV platforms available through The Media Ant’s CTV advertising marketplace, alongside JioHotstar, Samsung CTV, Zee5, and others, for brands looking to act on the patterns in this report.
Methodology
The numbers in this report come from YouTube’s Reach Planner tool, pulled under one consistent set of settings for every state.
| Parameter | Value |
|---|---|
| Campaign objective | Brand awareness |
| Campaign window | August 1 to 28, 2026 |
| Budget | Maximum available, to surface ceiling reach |
| Geography | State level, split into Total, Urban, and Rural |
| Metrics captured | Population, Estimated Reach, Reach Penetration, CPM, Cost per Reached User, Average Frequency |
Population figures are the census numbers built into Reach Planner itself, not a separate third-party source. Reach penetration is estimated reach divided by population for that geography. Cost per reached user is budget spent divided by unique people reached. Using one fixed set of campaign parameters across every state is what makes the comparisons in this report directionally sound. Any difference we observe between states is a difference in underlying reach opportunity, not a difference in how the campaign was configured.
One clarification that matters for how these numbers should be read: “Estimated Reach” here is a count of people, not a count of connected TV sets or devices. YouTube’s Reach Planner uses a “Unique Reach” metric that accounts for co-viewing, estimating that a single CTV screen is often watched by more than one person at a time, using signals like device type, viewing behaviour, genre, time of day, and panel-based data. So a household of four watching the same screen can be counted as up to four unique viewers reached, not one. This is a meaningful difference from simply counting connected TVs or households, and it’s worth keeping in mind when comparing these reach figures against device-shipment or household-penetration numbers from other sources, since they are not measuring the same unit. (Source: YouTube expands CTV reach metric to account for co-viewing, Indian Television Dot Com.)
This has a direct implication for the scale rankings in this report. Average household size in India varies noticeably by state, larger in states like Uttar Pradesh and Bihar, smaller in states like Kerala and Tamil Nadu, and a co-viewing-adjusted reach metric will mechanically credit more unique viewers per screen in states where households run larger, independent of how many CTV devices are actually in use. That means some part of Uttar Pradesh’s outsized absolute reach, and some part of the gap between large-household and small-household states more generally, could reflect household size rather than device penetration alone. We cannot separate these two effects from Reach Planner’s output, since it doesn’t disclose device counts or average co-viewing multipliers by state, so this report’s scale and reach figures should be read as “unique people reached” exactly as labelled, not silently treated as “number of CTV devices” or “number of CTV households,” even directionally.
One detail worth stating plainly, because it trips up a first read of this data: Total, Urban, and Rural numbers for a state were each pulled as independent planning scenarios, not as one campaign split three ways. Urban and rural reach for a state will therefore not always add up neatly to the state total, and in some cases a rural figure alone can look close to, or even exceed, part of what the state total implies. Our working explanation is that Reach Planner re-optimises delivery independently for whichever geography is selected, rather than subdividing one fixed campaign across sub-geographies. Google has not published the exact mechanics behind this behaviour, so treat that explanation as our best working hypothesis rather than a confirmed fact. The practical takeaway is simple: use Total, Urban, and Rural each as its own planning scenario, and do not attempt to reconcile them arithmetically.
What this data is, and what it is not
A few honest limits, stated upfront so the numbers get used carefully rather than over-read.
- One platform, not all of CTV. YouTube is the largest single CTV destination in India, but Smart TV home screens, other streaming apps, and FAST channels all carry viewers this dataset does not touch. It also excludes closed subscription apps such as Netflix or Disney+ Hotstar, and any viewing that happens through set-top boxes rather than Smart TV operating systems.
- Reach counts people, not connected TV sets. As noted in the methodology above, these figures reflect Reach Planner’s co-viewing-adjusted “Unique Reach” estimate, not a device or household count. Do not read the reach numbers in this report as a proxy for the number of CTV sets or CTV households in a state; they measure something related but distinct.
- Modelled, not delivered. These are Reach Planner estimates, generated by Google’s own forecasting engine, not results from a campaign that actually ran. Real-world delivery depends on creative quality, seasonality, competitive auction pressure on the day, and inventory availability, and can vary from the modelled forecast.
- A maximum-budget scenario. Because the budget was deliberately set to the ceiling in every market, the bidding engine was free to overpay for scarce inventory wherever it existed. These cost figures represent the upper edge of what CTV costs in each state under aggressive, uncapped buying, not a typical, disciplined, flighted media rate. A brand running a constrained-budget campaign should expect materially lower CPMs than what is shown here, particularly in the highest-cost markets.
- Rural and urban are census labels, not lived reality. A “rural” pocket sitting next to a booming metro can look and behave nothing like a rural pocket four hours from the nearest city. The two-way split used throughout this report is a useful planning lens, but it flattens genuine variation inside each bucket, a point we return to in detail later in this report.
- A snapshot, not a constant. Given Kantar’s own 23% year-on-year CTV growth figure, a repeat of this exercise twelve months from now would very likely show meaningfully different penetration levels, especially in the states that currently lag. Treat this as a benchmark for August 2026 campaign planning, due for a refresh as the category keeps moving.
- Independent scenarios, not additive segments. As noted in the methodology above, Total, Urban, and Rural figures for any given state should not be summed or reconciled against each other. Each is its own answer to the question: under these campaign settings, what does reach look like for this specific geography?
- Read this as a directional benchmark, not a quote. Every number in this report is tied to one specific campaign window, one objective, and one uncapped budget setting. Change any of those three inputs, run a shorter flight, target a performance objective instead of awareness, or cap the budget, and the reach, penetration, CPM, and cost figures will move, in some states significantly. The value of this report is in the patterns it surfaces (where scale sits, which states have hit a ceiling, where rural outperforms urban, and why) not in treating any single figure as fixed. Anyone planning an actual campaign should pull their own numbers directly from YouTube’s Reach Planner for their specific dates, objective, and budget, and use this report as the map for where to look closely.
- Existing inventory already booked in a market is an unknown variable. Reach Planner does not disclose whether its cost and scarcity estimates account for CTV inventory other advertisers have already committed to in a given state at the time of the query. If competing brands had already booked up meaningful inventory in, say, rural Jharkhand or rural Haryana, that alone could push cost per reached user higher, independent of genuine household scarcity. We cannot separate “genuinely scarce households” from “inventory already spoken for” using the tool’s output alone, so the cost figures in this report should be read as what the market looked like at the time of extraction, not a fixed structural ceiling.
- The campaign window overlaps India’s festive season build-up. August sits just ahead of a run of major festive periods, Onam, Ganesh Chaturthi, and the lead-up to Navratri and Diwali, when advertiser demand for video and CTV inventory typically rises across the country. Some of the elevated CPMs and cost per reached user figures in this report, particularly in the highest-cost states, may partly reflect this seasonal demand rather than pure household scarcity. A campaign pulled in a quieter month could show meaningfully lower costs in the same states.
- Population figures are Reach Planner’s own estimates, not a live census. The population numbers used to calculate penetration in this report are the figures built into Reach Planner at the time of extraction. They carry the same administrative lag as the rural and urban classifications discussed later in this report, and they have not been independently verified against the latest government population data. Penetration percentages should be read with that in mind, as a function of Reach Planner’s internal population base rather than an independently audited one.
The shape of India’s CTV market: scale leaders
The first and most basic planning question is simple: which states offer the largest reachable CTV audience in absolute terms? Ranked purely by estimated reach, the picture is dominated by a handful of India’s most populous states.
- Uttar Pradesh — 26.70M
- Maharashtra — 24.20M
- Tamil Nadu — 15.40M
- Karnataka — 13.20M
- Gujarat — 12.30M
- Madhya Pradesh — 11.00M
- West Bengal — 11.60M
- Andhra Pradesh — 10.10M
- Rajasthan — 9.81M
- Bihar — 8.35M
Uttar Pradesh and Maharashtra sit well clear of everyone else, together accounting for more than 50 million reachable connected viewers, close to a third of Kantar’s entire national CTV audience figure inside just two states. For any brand planning a large-scale national awareness campaign, these two states are close to non-negotiable anchors. They are where the sheer weight of population converts into the largest absolute pools of reachable people, regardless of how deep or shallow that reach is as a share of each state’s population.
But scale alone tells an incomplete story, because Uttar Pradesh and Maharashtra get to their numbers in very different ways.
Maharashtra is a balanced asset. Its reach splits fairly evenly, 10.90M urban and 15.90M rural, for a state with a genuinely mixed urban-rural population base. This is what a mature, broad-based CTV market looks like: no single geography is carrying the state, and both urban and rural buying behave in a way that is broadly consistent with the state’s underlying demographic split.
Uttar Pradesh’s reach is a rural story almost entirely. Of its 26.70M total reach, 19.50M comes from rural UP. The state’s overall penetration sits at a modest 10.8%, well below most of the leading pack. UP is not a mature CTV market in the way Maharashtra is. It is a massive, still largely untapped one, carrying its scale from sheer population size rather than deep, widespread adoption. We return to what that means for planners later in this report.
Beyond the top two, the next tier, Tamil Nadu, Karnataka, and Gujarat, delivers meaningful but noticeably smaller absolute pools, in the 12 to 15 million range. These states matter for national campaigns, but they are not going to move a country-wide reach number the way UP and Maharashtra do. They matter more, as the next section shows, for how efficiently and how deeply they can be worked.
The two-speed penetration market
Most of India’s leading CTV states plateau at roughly the same penetration ceiling, 17.5% to 18.1%, regardless of how large or small their population is. Scale answers “how many people,” but penetration answers a sharper question: “how much of this state’s population can this campaign actually reach.” That distinction matters enormously for planning, because a state can be one of India’s largest CTV markets by volume and still rank only mid-table, or worse, on penetration.
Total reach penetration clusters tightly for most of India’s leading states, all sitting within roughly half a percentage point of each other, in the 17.5% to 18.1% band: Maharashtra, Andhra Pradesh, Karnataka, Himachal Pradesh, Tamil Nadu, Telangana, Punjab, Haryana, and Uttarakhand. That tight clustering looks like a genuine ceiling. Even with an uncapped, maximum-budget campaign designed specifically to push reach as far as possible, these states all plateau in almost exactly the same place. That is a strong signal that roughly 18% of population is close to the current structural limit of what YouTube CTV, as currently deployed and measured, can deliver in India’s more digitally advanced states.
A second, distinctly separate group sits well below that line, in some cases at close to a third of the leading states’ level:
- Uttar Pradesh — 10.8%
- West Bengal — 10.8%
- Rajasthan — 11.4%
- Madhya Pradesh — 12.2%
- Chhattisgarh — 13.1%
- Jharkhand — 9.5%
- Odisha — 8.3%
- Assam — 7.6%
- Bihar — 6.2%
These are not small or marginal states. Several of them, Uttar Pradesh, West Bengal, Rajasthan, Bihar, are among India’s largest by population. That combination, large population and low penetration, is precisely what makes this second group so significant for planning. The gap between the leading cluster’s roughly 18% ceiling and this lagging group’s 6 to 13% band represents a genuinely enormous pool of people that current CTV campaigns are reaching poorly, if at all. Bihar’s population of 134 million and its 6.2% penetration together mean well over 125 million people in that single state sit largely outside the reach of a maximised YouTube CTV brand campaign today.
This two-speed pattern is arguably the single most useful planning fact in this entire dataset: India’s CTV market is not evenly maturing across the country. It is maturing in a fairly tight cluster of states that have already reached a shared structural ceiling, while a second, larger cluster of states remains substantially underdeveloped by comparison. A national campaign strategy that treats every state the same will systematically under-invest in the states with room to grow and over-invest, relative to marginal return, in states that are already close to saturated.
Cost to reach: where a rupee goes furthest
Cost per reached user on YouTube CTV in India ranges from ₹0.09 to ₹1.75, a roughly twentyfold spread across the country under identical campaign settings, which makes it one of the most useful, and most volatile, metrics in this dataset for budget allocation.
The cheapest incremental reach in the country sits in small, well-connected urban markets, concentrated in the hill states and the wider NCR belt:
- Himachal Pradesh, urban — ₹0.09
- Haryana, urban — ₹0.10
- Uttarakhand, urban — ₹0.11
- Telangana, urban — ₹0.14
- Punjab, urban — ₹0.21
At the opposite end, the most expensive reach in the country clusters just as tightly, mostly in rural pockets of eastern India, with one notable urban outlier:
- Jharkhand, rural — ₹1.75
- Chhattisgarh, rural — ₹1.75
- Bihar, urban — ₹1.64
- Telangana, rural — ₹1.64
- Gujarat, rural — ₹1.46
Bihar urban is the one anomaly in that list, and it is worth calling out rather than folding in quietly. A small urban population (15.2M) paired with the highest frequency figure in the entire dataset, 36.86x, suggests the same reach-ceiling pattern discussed later in this report is showing up in an urban market here, not just a rural one.
The gap here is close to twentyfold between the cheapest and most expensive markets in the dataset, inside the same country, the same platform, and the same campaign settings. That is a far wider spread than the penetration numbers show, and it means cost efficiency deserves its own, separate place in any planning framework, rather than being treated as a secondary detail once reach and penetration have been decided.
It is also worth noting that cheap and deep do not always travel together. Himachal Pradesh urban is both extremely cheap and sits inside a state with strong overall penetration, an easy win. But some of the cheapest markets are small in absolute terms, Himachal Pradesh’s entire urban population is only 816K people, so cheap cost per reached user there buys efficiency, not scale. Planners chasing volume and planners chasing efficiency are, in several cases, going to be looking at different states entirely.
What’s actually driving the cost spread: price, or frequency?
It would be easy to read a twentyfold spread in cost per reached user as a story about advertisers bidding up scarce inventory. The data points to a more specific, and more checkable, explanation: it’s mostly a frequency problem, not a price problem.
Look at what each underlying metric actually does across the dataset. CPM, the price paid per impression, barely moves: from ₹43.54 (Punjab total) to ₹101.92 (West Bengal total), roughly a 2.3x spread nationwide. Average frequency moves far more: from 2.85 (Himachal Pradesh urban) to 36.86 (Bihar urban), close to a 13x spread. Cost per reached user, which is arithmetically close to CPM multiplied by frequency, tracks that 13x frequency spread far more closely than it tracks the 2.3x CPM spread.
State by state, the same pattern holds. In Haryana, urban CPM is ₹49.02 and rural CPM is ₹70.26, only about 1.4x apart. But urban frequency is 3.11 against rural frequency of 27.11, nearly 9x apart, and cost per reached user swings by a similar margin. Gujarat is a useful check on this because its urban segment, despite being “urban,” has unusually low penetration (9.7%): frequency there climbs to 30.95 and cost per reached user lands at ₹1.40, close to rural Gujarat’s ₹1.46, even though the two segments have very different CPMs.
The likely mechanism: in any pocket where the addressable pool of unique viewers is small, whether that’s a genuinely sparse rural area or a thin urban segment like Gujarat’s, the platform has to serve each person considerably more times before it can count them as reached. That drives up cost per reached user through repetition, not through a higher per-impression price. It is a smaller-audience, lower-viewership-per-person efficiency problem more than a bidding war.
We want to be direct about what we can and can’t claim here. This pattern is visible and consistent in the numbers Reach Planner reports, and it is a more defensible read than assuming pure inventory scarcity, since CPM itself barely moves while frequency and cost move together. What we cannot do, because this isn’t our tool and Google hasn’t published the underlying auction mechanics, is confirm the reason the frequency requirement is so much higher in these pockets, whether that’s genuinely fewer people watching, shorter viewing sessions, less time spent on the platform, or something else in how the algorithm paces delivery. Treat this as the best explanation the data itself supports, not a confirmed mechanism.
Frequency and the reach-ceiling problem
Average frequency, how many times the same unique viewer is served an ad over the 28-day window, is the metric most likely to be misread if looked at on its own. A naive read might treat high frequency as a sign of strong engagement or a captive audience. The data here suggests the opposite is usually true.
The states with the highest cost per reached user also carry, almost without exception, the highest average frequency in the dataset: 35.5x in rural Jharkhand and 34.6x in rural Chhattisgarh, well above the typical 15x to 25x range seen through most of the rest of the country. Bihar urban, at 36.86x, is the single highest frequency figure in the entire dataset, despite Bihar urban being a comparatively small, contained market.
Read alongside cost, this combination is a specific and identifiable pattern: rising cost, paired with rising frequency, in a market where absolute reach and penetration both stay comparatively low. That is not a sign of an engaged audience being served efficiently. As shown in the cost section above, it is closer to a smaller, harder-to-expand pool of households being served repeatedly because far fewer unique viewers are available to reach in that pocket, not because the platform is charging more per impression. For a planner, this combination should be read as a structural reach ceiling, not a performance win, and it is a useful diagnostic to apply to any state before committing a large budget there in the hope of finding more volume: if cost and frequency are both already elevated, more budget is likely to buy more repetition, not more unique reach.
The Eastern India gap
Layer the penetration numbers and the frequency numbers together, and a distinct geographic cluster falls out of the data on its own: eastern India.
Five states sit together at the bottom of rural penetration, and all five sit in the eastern half of the country: Bihar, Odisha, Jharkhand, Assam, and Chhattisgarh. Rural penetration in this group runs well under 10% in most cases, with Assam rural at just 4.5%, the single lowest figure anywhere in this dataset. Five states clustering in the same underperforming band, rather than one isolated outlier, is a stronger and more structural signal than any one state’s number taken alone. This looks less like a series of unrelated local dips and more like a genuine regional pattern in how CTV infrastructure and adoption have spread across the country so far.
This isn’t purely a pattern internal to YouTube’s own numbers, either. Nielsen’s India Internet Report 2025 found smart TV penetration by region at 25% in South India, 16% in West India, 10% in North India, and just 5% in East India, less than a third of the West’s figure and the lowest of any region in the country. That’s an independent, device-level data point pointing in the same direction as our reach data: eastern India isn’t just under-reached on YouTube CTV specifically, it appears to have the least smart TV hardware in Indian homes to begin with, which is consistent with, and helps explain, the low penetration this report finds across Bihar, Odisha, Jharkhand, Assam, and Chhattisgarh. (Source: South India leads smart TV adoption at 25% as India crosses 915 million internet users, Storyboard18, reporting on Nielsen’s India Internet Report 2025.) This is a regional figure, not a state-level one, so it corroborates the pattern rather than confirming each state’s exact number, but it’s a useful outside check given that the rest of this report relies on a single platform’s data.
The frequency data reinforces the same point from a different angle. In rural Jharkhand, the average viewer is being reached 35.5 times over the 28-day campaign. That is not deep engagement with a captive audience. It is the algorithm running out of new households to find in a genuinely constrained inventory pool, and serving the same limited set of viewers on repeat instead.
For brands, this eastern cluster is worth treating as a distinct planning category of its own, separate from both the high-penetration leading states and from a scale anchor like Uttar Pradesh. It is a region where current CTV infrastructure and adoption both still have real room to grow, where campaigns today are likely to hit a reach ceiling quickly if run at scale, and where the underlying cause, as the closing section of this report shows, is closely tied to how income is distributed between urban and rural households within each of these states.
The Uttar Pradesh opportunity
Uttar Pradesh deserves its own section because its numbers do not fit cleanly into either the “scale leader” bucket or the “lagging market” bucket. It is, in a real sense, both at once.
UP is the country’s largest state by population, at 248 million people, and its largest by absolute CTV reach, at 26.70M. On volume alone, no state in India comes close. But its penetration rate of 10.8% sits well below the leading cluster’s roughly 18% band, and that shortfall is driven almost entirely by rural UP, which manages just 10.1% penetration despite carrying the largest single rural population of any state in the dataset, at 193 million people.
That specific combination, enormous scale paired with meaningfully low penetration, makes Uttar Pradesh the single largest pool of not-yet-reached CTV viewers anywhere in India. Multiply UP’s 193 million rural population by the gap between its current 10.1% rural penetration and the roughly 18% ceiling that leading states have already reached, and the scale of the untapped opportunity becomes clear: tens of millions of people in rural UP alone who behave, structurally, like the audience leading states have already captured, but who current CTV delivery has not yet reached. Worth noting, per the methodology above, that this reach figure is co-viewing-adjusted, and UP’s average household size runs larger than in many of the leading states, so part of its absolute scale reflects more people per screen rather than more screens outright. That doesn’t change the underlying opportunity, UP’s low penetration relative to the leading cluster is a separate, household-size-independent signal, but it does mean the 26.70M figure shouldn’t be read as a device or household count.
As rural connectivity infrastructure continues to expand across the state, this is arguably the single market with the most long-term upside for CTV advertising agencies in India over the next few years. It also deserves a fundamentally different kind of campaign thinking than a state like Kerala or Telangana, where the ceiling is already close and further budget mostly buys frequency rather than fresh reach. In UP, by contrast, there is a large, genuinely unreached audience still waiting to be found, which argues for sustained, patient investment aimed at reach growth rather than a short flight optimised purely for immediate efficiency.
Reading the data against different campaign objectives
Pulling scale, penetration, cost, and frequency together, four distinct patterns emerge from this dataset, each answering a different planning question. Which one matters most depends entirely on the brief, an objective built around volume calls for a different state than one built around efficiency, and most large national campaigns will need to weigh more than one of these at once rather than optimising for a single pattern across the whole country. These are read-outs of what the data shows, not a fixed sequence of moves to run regardless of brief.
If the objective is country-wide volume: Uttar Pradesh and Maharashtra are where the absolute numbers are largest. Together they deliver more than 50 million reachable connected viewers, close to a third of India’s entire estimated CTV audience, inside just two states. A brief that prioritises raw reach and impression volume above all else will find that scale concentrated here, though it’s worth weighing against penetration data above, since UP in particular reaches that scale through low penetration across a huge population rather than deep saturation.
If the objective is cost efficiency: Himachal Pradesh, Haryana, and Uttarakhand urban show the lowest cost per reached user in the country, from ₹0.09 to ₹0.11. A brief working against a fixed budget and optimising for unique households reached per rupee would look here first, keeping in mind these are also comparatively small markets in absolute terms, so efficiency here trades off against total volume.
If the objective is long-term category building in an underdeveloped market: rural Uttar Pradesh stands out as the largest pool of unreached CTV viewers in the dataset, and one likely to keep growing as rural infrastructure expands. This pattern fits a sustained, multi-flight investment horizon better than a single short campaign, since the upside here is about capturing growth over time rather than efficient reach today.
If the objective is sustained presence in an already-mainstream category: states in the leading penetration cluster, Telangana, Kerala, Maharashtra, Punjab, and Haryana among them, show CTV behaving like an established channel rather than an emerging one. The data suggests further budget in these states is more likely to add frequency against an already-reached audience than meaningfully expand unique reach, which is worth factoring into how success gets measured there.
The throughline across all four reads is the same: these patterns point in different directions, sometimes toward different states entirely, which is why a single national plan built on country-wide averages will tend to over-serve some states and under-serve others relative to what any specific brief is actually trying to achieve. The right mix depends on the brief in front of you; this data is meant to make that trade-off visible, not to prescribe one answer for every campaign. If you want to translate any of these reads into an actual media plan, The Media Ant’s CTV advertising planning tool lets you select cities or states, set an objective, maximise reach or minimise cost, and get a data-backed plan built around it.
The urban-rural divide: a closer look
Everything covered so far treats each state as a single unit. But inside almost every state in this dataset, there is a second, sharper story sitting underneath the state-level numbers: how reach splits between urban and rural geography. This is worth its own detailed look, because the pattern it reveals runs against one of the most deeply held assumptions in Indian media planning.
The core finding
The standard assumption in Indian advertising is that CTV is a premium, urban-first medium. This dataset shows that assumption breaking down in close to half of India’s largest states. In several of them, rural CTV penetration is not just present, it is higher than urban penetration, sometimes by a wide margin.
| Gujarat | 9.7% | 27.0% | +17.3 |
| Telangana | 18.0% | 32.2% | +14.2 |
| Kerala | 18.0% | 28.9% | +10.9 |
| Punjab | 18.1% | 28.9% | +10.8 |
| Haryana | 18.0% | 26.2% | +8.2 |
In Gujarat, urban penetration is a single-digit 9.7%, while rural runs to 27.0%, close to a three-fold gap in exactly the opposite direction from what most planning frameworks would predict going in. Telangana rural, at 32.2%, is the single highest penetration figure anywhere in this entire dataset, urban or rural, in any state.
The cost data tells the same story from a different angle, and this is where the pattern becomes impossible to ignore. In Haryana, an urban CTV user costs an efficient ₹3.11 to reach. A rural user in that exact same state costs ₹27.11, nearly nine times more, inside the same state boundary, under the same campaign, on the same platform.
Three explanations, and the one that actually holds
We tested three possible drivers before landing on the one that explains the pattern consistently.
Urbanisation rate does not explain it. Karnataka is fairly urbanised, with roughly 38.7% of its population classified urban, yet its urban penetration still comfortably beats rural, 17.8% versus 11.6%. Himachal Pradesh sits at the opposite extreme, one of the least urbanised states in the country at around 10.1% urban, yet its rural penetration beats urban, 20.1% versus 18.0%. If urbanisation rate were the driver, both states should behave in the same direction relative to each other. They do not. It is not a clean predictor.
Overall state affluence does not fully explain it either. Telangana and Karnataka are two of India’s highest per-capita-income states by recent MoSPI figures, yet they pull in opposite directions on this exact metric. Telangana rural crushes urban, 32.2% versus 18.0%. Karnataka urban beats rural, 17.8% versus 11.6%. A state’s overall wealth level alone does not decide which way its urban-rural CTV split falls.
What actually explains it: how evenly income is spread between rural and urban households within a state, not how wealthy the state is overall. A PLFS-based study of household consumption expenditure calculated the ratio between average urban and average rural household spending for each state. Kerala has the most equal ratio in the country, at 1.23, meaning urban and rural households there spend almost the same amount on average. Jharkhand, Odisha, and Chhattisgarh sit at the opposite end, with ratios of 2.69, 2.81, and 3.01 respectively, all well above the national average of 2.17. In those three states, urban households spend far more than rural households on average.
Match that spending-ratio data against the CTV penetration numbers, and the pattern holds up cleanly across the dataset. Kerala, with its near-equal spending ratio, shows rural CTV penetration beating urban. Jharkhand, Odisha, and Chhattisgarh, with their wide spending ratios, all show urban comfortably beating rural, with Odisha producing one of the widest urban-over-rural gaps anywhere in the dataset. The underlying mechanism appears straightforward: where a state’s rural households have closed the spending gap with urban households, they have also closed the CTV reach gap. Where that spending gap stays wide, CTV stays a clearly urban-skewed medium.
Two exceptions worth naming rather than smoothing over
Karnataka ranks second nationally on per-capita income, yet its CTV pattern behaves like a far less equal, lower-income state, with urban comfortably ahead of rural. The likely explanation is geographic concentration rather than genuine statewide equality: Karnataka’s income is unusually concentrated in Bengaluru specifically. The state-level income figure conceals a large gap between Bengaluru and the rest of Karnataka, in a way that more evenly distributed state economies, Telangana’s for instance, simply do not share. Karnataka is, in effect, one very rich city and a much less affluent rest-of-state being averaged together into a single statewide figure that flatters the non-Bengaluru parts of the state.
Punjab is a smaller, differently shaped exception. Punjab’s overall economic growth has lagged the national average for several decades, yet its rural CTV penetration comfortably beats urban, 28.9% versus 18.1%. That is consistent with Punjab’s agrarian economy putting real, direct income into rural households even in years when the state’s aggregate growth story, driven more by broader structural factors, has been comparatively weak. Rural prosperity and statewide growth are not the same thing, and Punjab is the clearest single example of that distinction inside this dataset.
The administrative recalculation trap
There is a structural reason this inversion is even possible in the first place, and it comes down to how India draws the line between rural and urban in official records.
Census boundaries lag behind real estate development on the ground, often by years. In fast-growing corridors around cities like Bengaluru, Hyderabad, and Ahmedabad, industrial and IT-sector expansion has pushed housing development well past old municipal limits. Gated communities and high-density apartment complexes have gone up in areas that remain, on paper, governed by rural local bodies, simply because the administrative map has not caught up to the physical one. A community like Doddanagamangala in Karnataka is a clear example: administratively rural, but filled with high-earning professionals living in modern multi-storey towers, with near 100% fibre broadband penetration and a 4K Smart TV in most living rooms. YouTube’s Reach Planner correctly picks up that household’s genuinely urban-style digital activity, but files it under the label the census assigns it: rural.
That specific mismatch, combined with the genuine rural affluence documented above in states like Haryana, Punjab, and Telangana, may be part of what’s pushing rural CPMs up in these specific states, alongside genuine competitive demand from other advertisers. But as the cost section earlier in this report shows, CPM itself moves comparatively little across the country. Most of the cost gap between urban and rural comes from frequency, not price, which points to a smaller addressable pool of unique viewers needing to be served repeatedly, rather than a straightforward bidding war over scarce inventory. Bidding pressure from other brands chasing the same peri-urban and prosperous rural households is a plausible contributing factor, but it is not something we can confirm from Reach Planner’s output alone, so we’d rather flag it as one possible piece of the picture than present it as the settled explanation.
What this means for planning, specifically
The practical implication is direct: rural CTV in states like Telangana, Gujarat, Punjab, Kerala, and Haryana is not a fallback or a secondary audience to be picked up once the urban budget is spent. In these specific states, it is where the deeper, and in some cases the larger, opportunity actually sits. A campaign planned with a default urban-first heuristic in these markets risks systematically under-investing in the audience segment that this data shows is actually driving CTV adoption forward.
At the same time, this pattern is not universal, and treating “rural beats urban” as a blanket rule for India would be exactly the kind of national-average thinking this report set out to argue against. In Karnataka, and across most of eastern India, urban still leads rural clearly, for the specific, identifiable reasons laid out above. The right planning approach is state-specific in both directions: know which states have flipped, know why, and plan accordingly, rather than applying either an urban-first or a rural-first assumption uniformly across the whole country.
🎥 Want the full walkthrough, including how we arrived at each explanation and what we ruled out along the way? Watch our detailed video breakdown of this report:
The full state-level dataset
All figures below are from YouTube Reach Planner, for a brand-awareness campaign, August 1-28 2026, maximum budget.
| State | Geography | Population | Est. Reach | Penetration | CPM (₹) | Cost/Reached User (₹) | Frequency |
|---|---|---|---|---|---|---|---|
| Uttar Pradesh | Total | 248.0M | 26.70M | 10.8% | 82.59 | 1.05 | 19.51 |
| Uttar Pradesh | Urban | 55.1M | 9.89M | 17.9% | 68.70 | 0.68 | 15.01 |
| Uttar Pradesh | Rural | 193.0M | 19.50M | 10.1% | 84.64 | 1.03 | 18.88 |
| Maharashtra | Total | 134.0M | 24.20M | 18.1% | 64.36 | 0.98 | 22.90 |
| Maharashtra | Urban | 60.5M | 10.90M | 18.0% | 56.00 | 0.38 | 10.53 |
| Maharashtra | Rural | 73.3M | 15.90M | 21.7% | 86.84 | 1.21 | 20.52 |
| Tamil Nadu | Total | 86.0M | 15.40M | 17.9% | 68.46 | 0.93 | 20.23 |
| Tamil Nadu | Urban | 41.6M | 7.47M | 18.0% | 52.84 | 0.40 | 11.21 |
| Tamil Nadu | Rural | 44.4M | 9.54M | 21.5% | 94.95 | 1.59 | 24.34 |
| Karnataka | Total | 73.4M | 13.20M | 18.0% | 73.25 | 1.09 | 22.50 |
| Karnataka | Urban | 28.4M | 5.05M | 17.8% | 55.71 | 0.28 | 7.56 |
| Karnataka | Rural | 45.1M | 5.24M | 11.6% | 85.01 | 1.33 | 23.68 |
| Gujarat | Total | 73.7M | 12.30M | 16.7% | 89.69 | 1.44 | 24.35 |
| Gujarat | Urban | 31.4M | 3.06M | 9.7% | 67.22 | 1.40 | 30.95 |
| Gujarat | Rural | 42.3M | 11.40M | 27.0% | 90.59 | 1.46 | 24.30 |
| West Bengal | Total | 107.0M | 11.60M | 10.8% | 101.92 | 1.60 | 22.88 |
| West Bengal | Urban | 34.2M | 6.11M | 17.9% | 77.46 | 0.92 | 17.67 |
| West Bengal | Rural | 72.4M | 7.10M | 9.8% | 89.78 | 1.40 | 22.89 |
| Madhya Pradesh | Total | 89.9M | 11.00M | 12.2% | 85.53 | 1.16 | 20.75 |
| Madhya Pradesh | Urban | 24.8M | 3.61M | 14.6% | 66.84 | 1.20 | 26.95 |
| Madhya Pradesh | Rural | 65.1M | 9.89M | 15.2% | 85.39 | 1.20 | 21.58 |
| Andhra Pradesh | Total | 56.1M | 10.10M | 18.0% | 59.59 | 0.73 | 19.04 |
| Andhra Pradesh | Urban | 18.7M | 3.38M | 18.1% | 45.11 | 0.34 | 11.26 |
| Andhra Pradesh | Rural | 37.4M | 8.96M | 24.0% | 93.73 | 1.51 | 24.83 |
| Rajasthan | Total | 85.8M | 9.81M | 11.4% | 83.91 | 1.19 | 20.92 |
| Rajasthan | Urban | 21.3M | 3.53M | 16.6% | 71.84 | 0.97 | 20.65 |
| Rajasthan | Rural | 64.5M | 8.81M | 13.7% | 83.70 | 1.20 | 21.04 |
| Bihar | Total | 134.0M | 8.35M | 6.2% | 78.90 | 1.17 | 22.58 |
| Bihar | Urban | 15.2M | 2.45M | 16.1% | 66.04 | 1.64 | 36.86 |
| Bihar | Rural | 119.0M | 7.96M | 6.7% | 77.92 | 1.12 | 22.29 |
| Telangana | Total | 41.7M | 7.45M | 17.9% | 47.68 | 0.39 | 12.77 |
| Telangana | Urban | 20.2M | 3.64M | 18.0% | 47.73 | 0.14 | 4.46 |
| Telangana | Rural | 21.5M | 6.93M | 32.2% | 76.28 | 1.64 | 32.30 |
| Kerala | Total | 35.5M | 6.23M | 17.5% | 61.02 | 0.92 | 22.75 |
| Kerala | Urban | 13.7M | 2.46M | 18.0% | 47.36 | 0.41 | 12.98 |
| Kerala | Rural | 21.8M | 6.31M | 28.9% | 84.84 | 1.14 | 20.07 |
| Punjab | Total | 33.1M | 5.93M | 17.9% | 43.54 | 0.36 | 12.18 |
| Punjab | Urban | 12.4M | 2.24M | 18.1% | 43.82 | 0.21 | 7.16 |
| Punjab | Rural | 20.7M | 5.98M | 28.9% | 46.95 | 0.62 | 19.75 |
| Haryana | Total | 31.5M | 5.64M | 17.9% | 47.10 | 0.23 | 7.32 |
| Haryana | Urban | 11.0M | 1.98M | 18.0% | 49.02 | 0.10 | 3.11 |
| Haryana | Rural | 20.5M | 5.37M | 26.2% | 70.26 | 1.29 | 27.11 |
| Jharkhand | Total | 42.0M | 4.00M | 9.5% | 73.01 | 1.66 | 33.13 |
| Jharkhand | Urban | 10.1M | 1.47M | 14.6% | 66.72 | 1.45 | 32.73 |
| Jharkhand | Rural | 31.9M | 3.41M | 10.7% | 73.25 | 1.75 | 35.52 |
| Chhattisgarh | Total | 31.6M | 4.14M | 13.1% | 74.88 | 1.69 | 33.62 |
| Chhattisgarh | Urban | 7.33M | 1.33M | 18.1% | 62.01 | 1.30 | 31.45 |
| Chhattisgarh | Rural | 24.2M | 3.53M | 14.6% | 74.85 | 1.75 | 34.55 |
| Odisha | Total | 49.5M | 4.11M | 8.3% | 78.74 | 1.15 | 21.87 |
| Odisha | Urban | 8.27M | 1.48M | 17.9% | 50.13 | 0.32 | 9.39 |
| Odisha | Rural | 41.3M | 2.82M | 6.8% | 76.82 | 1.34 | 25.52 |
| Assam | Total | 37.4M | 2.84M | 7.6% | 81.45 | 1.50 | 28.64 |
| Assam | Urban | 5.27M | 0.95M | 18.0% | 51.47 | 0.23 | 7.01 |
| Assam | Rural | 32.2M | 1.44M | 4.5% | 77.09 | 1.48 | 28.96 |
| Uttarakhand | Total | 12.6M | 2.26M | 17.9% | 47.28 | 0.24 | 7.36 |
| Uttarakhand | Urban | 3.80M | 0.683M | 18.0% | 46.55 | 0.11 | 3.57 |
| Uttarakhand | Rural | 8.79M | 1.65M | 18.8% | 63.18 | 0.33 | 8.06 |
| Himachal Pradesh | Total | 8.09M | 1.46M | 18.0% | 57.01 | 0.44 | 11.31 |
| Himachal Pradesh | Urban | 816K | 147K | 18.0% | 44.83 | 0.09 | 2.85 |
| Himachal Pradesh | Rural | 7.28M | 1.46M | 20.1% | 58.53 | 0.66 | 17.09 |
Note: Total, Urban, and Rural figures for each state are independent Reach Planner scenarios and should not be added together.
Frequently asked questions
What is Connected TV (CTV) advertising?
CTV advertising means running ads on video content watched on a television screen through the internet, rather than through a cable or satellite box. It includes YouTube on a Smart TV, streaming apps, and any app running on a television’s own operating system.
Why does this report use YouTube instead of all CTV platforms combined?
No public planning tool covers every CTV app in India at once. YouTube is the largest single video platform in the country, with a monthly user base of 450 to 500 million, and it is pre-loaded on most Smart TVs sold here. That makes it one of the few platforms with both the scale and the public planning data to support a state-by-state comparison, even though it does not capture viewing on closed apps like Netflix or Disney+ Hotstar.
Which Indian states have the largest YouTube CTV reach?
By absolute estimated reach, Uttar Pradesh (26.70M) and Maharashtra (24.20M) lead the country by a wide margin, followed by Tamil Nadu (15.40M), Karnataka (13.20M), and Gujarat (12.30M).
Which states have the highest CTV penetration?
Telangana rural leads the entire dataset at 32.2% penetration. Most of the leading states, including Maharashtra, Andhra Pradesh, Karnataka, Himachal Pradesh, Tamil Nadu, Punjab, Haryana, and Uttarakhand, cluster tightly around 17.5-18.1% total penetration, suggesting a shared structural ceiling.
What does it cost to reach a CTV viewer on YouTube in India?
Cost per reached user ranges from as low as ₹0.09 in urban Himachal Pradesh to as high as ₹1.75 in rural Jharkhand and rural Chhattisgarh, under a maximum-budget brand awareness campaign. Cost is consistently lower in dense urban markets and higher in smaller, scarcer rural and peri-urban pockets.
Which Indian states have the biggest untapped CTV opportunity?
Uttar Pradesh stands out. It has the largest population and the largest absolute CTV reach in the country, but its penetration rate of 10.8% is well below the leading states, meaning a large share of its population is still unreached. Bihar, Odisha, Jharkhand, Assam, and Chhattisgarh, all in eastern India, also show low penetration and represent a similar long-term opportunity.
What is the “reach ceiling” and how do you spot it in CTV data?
A reach ceiling shows up as rising cost per reached user paired with rising average frequency, in a market where absolute reach and penetration both stay low. It means the addressable pool of unique viewers is small, so far more impressions per person are needed to register them as reached, rather than the platform genuinely expanding its audience. Rural Jharkhand (35.5x frequency) and rural Chhattisgarh (34.6x) are the clearest examples in this dataset.
Is rural CTV reach in India really higher than urban reach?
In several states, yes. Gujarat, Telangana, Kerala, Punjab, and Haryana all show rural penetration well ahead of urban penetration, with Gujarat showing the widest gap (9.7% urban versus 27.0% rural). This runs against the common assumption that CTV is an urban-first medium, though it is not a universal pattern across every state.
Why is rural CTV penetration higher than urban in some states?
The clearest explanation in this data is how evenly income is spread between rural and urban households in a state, not urbanisation rate or overall wealth. States with a smaller urban-rural spending gap, like Kerala, show rural reach catching up to or beating urban reach. States with a wide spending gap, like Jharkhand, Odisha, and Chhattisgarh, show urban reach staying well ahead.
What is the “administrative recalculation trap” in CTV planning?
It refers to census boundaries not keeping pace with real estate growth. Fast-growing residential belts around cities like Bengaluru, Hyderabad, and Ahmedabad are still officially classified as rural even though they have modern housing, fibre broadband, and Smart TVs. Planning tools then report genuinely urban-behaving households under a rural label, which helps explain why rural CPMs can spike sharply in specific states.
Does “reach” in this report mean the number of connected TVs?
No. Reach here counts people, not devices. YouTube’s Reach Planner uses a “Unique Reach” metric that accounts for co-viewing, estimating multiple viewers per screen using device type, viewing behaviour, genre, time of day, and panel data, so a household watching together on one Smart TV can count as several unique people reached, not one device impression.
What time period and settings does this CTV data cover?
All figures come from YouTube Reach Planner for a brand-awareness campaign running August 1-28, 2026, with the budget set to maximum to surface ceiling reach. Figures represent independent Total, Urban, and Rural planning scenarios and should be read as planning estimates rather than actual delivered campaign results.
Will these exact numbers apply to my campaign?
Not precisely. Reach, penetration, CPM, and cost per reached user in Reach Planner all shift with the campaign period, the objective, and the budget setting. The figures in this report are meant to show the pattern across states, not to substitute for your own numbers. Anyone planning a real campaign should pull figures directly from YouTube’s Reach Planner for their own dates, objective, and budget.
Data source: YouTube Reach Planner, campaign parameters as stated in Methodology above. Consumption expenditure ratios referenced from PLFS 2018-19 unit-level analysis. Per-capita income figures referenced from MoSPI state income data. National CTV market figures referenced from Kantar’s Media Compass report, Q1 2026.
This report is published by The Media Ant and will be updated as YouTube Reach Planner data changes.
