Identity resolution is the process of linking a CTV impression to a known person or household — connecting a device ID to a user profile, a household to a purchase history, or a viewer to a mobile device so the same person can be reached across screens. In India, identity resolution for CTV is real but incomplete. Here is the current state.
Why identity resolution matters for CTV
Without identity resolution, CTV is a broadcast medium with no targeting precision beyond content context and broad geo. Identity resolution enables:
- Audience targeting beyond contextual — reaching specific demographic or behavioural segments across platforms
- Frequency management — capping exposures to the same person across multiple platforms and devices
- Cross-screen sequencing — showing a person a video ad on CTV, then a follow-up on mobile
- Attribution — connecting a CTV exposure to a downstream conversion (store visit, app install, purchase)
- Suppression — excluding existing customers from acquisition campaigns
How India CTV platforms build identity
India's major CTV platforms use several identity signals:
Logged-in user IDs
JioHotstar, SonyLIV, Zee5, Amazon Prime Video, and Netflix all require account login to stream. The logged-in user ID is the primary identity anchor. Because these are subscription platforms, they have name, email, phone number, and payment data — rich first-party identity. When a user logs in on their Smart TV, the platform knows who is watching (at account level — not necessarily which household member).
Phone number as identity backbone
India is unique globally in that phone number is the universal login credential. Every major streaming platform uses mobile OTP for registration and login. This means the identity graph is anchored to phone numbers — which are already linked to Jio, Airtel, or BSNL telco profiles, UPI payment history, and in many cases Aadhaar KYC. The phone-number-as-identity-hub makes India's logged-in CTV identity data richer than in markets that rely on email addresses.
Device identifiers
Smart TVs use device-level identifiers: Samsung TIFA (Tracking ID for Advertising), LG's equivalent, and Fire TV's advertising ID. These are resettable and opt-out-able but are the primary signal for programmatic CTV buying in India when logged-in identity is not passed to the DSP.
IP address
Household IP address is used for frequency capping, geo-targeting (city/state level), and household-level attribution. IP matching is not precise — dynamic IPs, VPNs, and shared broadband in apartment buildings can muddle household boundaries — but it is the most widely available signal in India's open programmatic CTV market.
ACR data (limited in India)
Automatic Content Recognition — the technology that uses a TV's camera or microphone to detect what is on screen and infer the viewer — is used by Samsung and LG to build viewing history data (Samsung Viewership Data, LG Ad Solutions). ACR is available in India but privacy regulations and consumer awareness have slowed its broad adoption. It is available as a targeting and attribution signal through Samsung Ads and select DSPs.
The walled garden problem
India's CTV identity landscape is fragmented by walled gardens. JioHotstar's identity graph does not connect to SonyLIV's. Samsung Ads' device graph does not connect to Zee5's subscriber data (except through integrations negotiated directly). A cross-platform CTV identity graph — where you can cap frequency and deduplicate reach across JioHotstar + SonyLIV + YouTube CTV — does not exist natively.
The workarounds planners use today:
- IP-based household identity shared across platforms (imprecise but the most available)
- Phone-number-based ID graphs built by data clean rooms or identity vendors (LiveRamp, Jivox, or India-specific DMP players)
- Custom identity partnerships negotiated directly with platforms (available to large advertisers with data agreements)
Cross-device identity: CTV to mobile
Linking a CTV exposure to the same person's mobile device is the most valuable identity resolution use case for Indian advertisers. It enables:
- Retargeting a CTV viewer with a mobile display or video ad
- Sequenced storytelling: awareness on CTV, consideration on mobile
- Attribution: CTV exposure → mobile conversion
How this is done in India today:
- Platform-native: JioHotstar, YouTube, and Amazon can link the same account's CTV and mobile viewing within their platform. Cross-screen frequency capping and sequencing is possible within platform for advertisers buying through the platform's own tools.
- Programmatic cross-device: DSPs like DV360, The Trade Desk, and Viant use probabilistic and deterministic cross-device graphs. India coverage varies — deterministic (phone-number and email-based) coverage is better than in Western markets due to the mobile-first registration pattern.
- Telco identity: Jio's Saarthi DMP offers identity resolution that leverages Reliance's telco, JioMart, and JioHotstar ecosystem — a uniquely powerful identity graph for Jio-affiliated campaigns.
Privacy constraints
India's Digital Personal Data Protection Act (DPDPA) 2023 imposes consent requirements for personal data processing. CTV identity resolution that links browsing, purchase, or location data to viewing profiles requires explicit consent under DPDPA. Platforms building identity graphs are required to have user consent for data linkage beyond what users agreed to at subscription signup. This is an evolving area — enforcement timelines and specific compliance requirements for ad tech were still being finalised in 2026.
Planners should verify with platform partners that identity data used for targeting is DPDPA-compliant, particularly for data clean room integrations and third-party DMP segments.
Practical state of CTV identity in India (2026)
- Within-platform targeting: Strong. Logged-in identity on JioHotstar, SonyLIV, YouTube, Prime enables precise demo and interest targeting within each platform.
- Cross-platform deduplication: Weak. IP-based household matching is the best available tool but has known imprecision.
- Cross-screen (CTV to mobile): Moderate. Within-platform works well. Cross-platform requires identity partnerships or probabilistic graphs.
- Attribution to offline: Early. Data clean rooms and location data partnerships are being piloted but not standard practice.