First-party data (1PD) in CTV refers to an advertiser's own customer data — CRM records, app user IDs, purchase history, subscription data — used to target CTV audiences. In web advertising, first-party data activation is well-established via pixel-based audiences. In India CTV, first-party data activation faces a specific set of technical constraints: no cookies, device ID-based matching with low match rates, and walled garden limitations on the largest publisher. Understanding what is actually achievable with first-party data in India CTV prevents over-promises and helps build appropriately scoped plans.
What first-party data looks like in India CTV
An advertiser's first-party data typically exists as: hashed email addresses, hashed mobile phone numbers (widely available in India due to mobile-first account creation), app user IDs (for brands with mobile apps), or CRM segments (existing customers, lapsed users, high-LTV customers, churned subscribers).
To activate this data on India CTV, the advertiser uploads the hashed list to a DSP (DV360 or TTD). The DSP attempts to match each hashed identifier to a device ID in its identity graph. The matched device IDs become the targetable CTV audience.
Match rates for India CTV first-party data
Match rates are the fraction of uploaded records that successfully resolve to a CTV device ID. In India:
| Data type uploaded | Typical India match rate | Notes |
|---|---|---|
| Hashed mobile number | 20–35% | Best match type for India; mobile numbers widely linked to Google/telecom identity |
| Hashed email | 15–25% | Lower in India where mobile-first accounts don't always have emails |
| App user ID | 10–20% | Requires DSP-app partnership for cross-device resolution |
A brand uploading 10 million hashed mobile numbers will match approximately 2–3.5 million CTV device IDs. This is the actual addressable first-party audience for CTV — not 10 million.
Use cases for first-party data in India CTV
Customer suppression: Excluding existing customers from acquisition campaigns. Match rate limitations are less important here — suppressing 30% of existing customers from CTV is still valuable even if 70% are not matched.
Lapsed user re-engagement: CTV as a brand reminder for users who have stopped using an app or have not purchased in 6+ months. Premium placement, higher CPM, but high-value audience.
Upsell and cross-sell: Targeting existing customers with an upgrade offer (e.g., prepaid to postpaid, basic to premium subscription). Works best for brands where CTV's household reach reinforces a decision already in progress.
Lookalike expansion: DSPs can model "lookalike" audiences of devices that share behavioural profiles with the uploaded first-party seed. This expands reach while maintaining some profile similarity. Lookalike match quality in India is lower than in more data-rich markets.
JioHotstar and first-party data
First-party data activation on JioHotstar's direct inventory works differently. JioHotstar operates a clean room arrangement where advertisers can share encrypted first-party data — Jio phone numbers or JioHotstar account IDs — which are matched against JioHotstar's own subscriber data. The matched audience is activated within JioHotstar's system. The advertiser does not receive the matched device IDs — the matching happens inside JioHotstar's environment. This is more accurate than DSP-based matching but requires direct engagement with JioHotstar's advertising team and higher minimum campaign commitments.
Privacy and consent considerations
India's Digital Personal Data Protection Act (DPDPA) 2023 requires explicit consent for using personal data in advertising. Advertisers activating first-party CRM data for CTV targeting must ensure their privacy policy covers CTV advertising use cases and that consent was collected for marketing purposes. Hashing data before upload does not remove the consent obligation — it only protects the raw data from exposure in transit.