Zero party data

How Zero-Party Data from Genuin’s SDK Powers Brand Communities and Generate Media Revenue - All Without Creeping Out Consumers

The digital media landscape is increasingly defined by data privacy and personalized experiences. It’s critical that brands find a way to understand their audiences and monetize their platforms without compromising user trust. One approach that’s gaining traction is the use of zero-party data: information that customers intentionally and proactively share with a brand. When combined with Genuin’s SDK integrations, zero-party data can power the community ecosystems and unlock media revenue streams - without leaving consumers feeling “creeped out” by invasive tracking or data misuse.

​

What is Zero-Party Data?

Zero-party data refers to information that a customer actively and willingly shares with a brand. Unlike first-party data (which is collected through interactions with a customer on websites, apps, or purchases), zero-party data is explicitly provided by the customer, often in the form of preferences, interests, intentions, and feedback.

This type of data is considered highly valuable because it reflects direct insights into a customer’s mindset, helping brands understand their audience in a more personalized and transparent way.

Zero-party data differs from traditional data-collection methods in that it places the user firmly in control. Instead of relying on inferred attributes or purchasing behavioral segments from third parties, zero-party data leverages the explicit and implicit permissions that users grant directly to the brand’s ecosystem. These include:

​

A. Implicit User Permissions & Signals:

1. Device Information: iDFA (device_id), SHA, UUID, IP Address

2. Client Data: Single Sign-On (SSO), login credentials

3. User-Generated Profile & Interests: Voluntary user profile details (birthdate, social account handles), topics of interest selections to personalize user’s feed.

4. Community Engagement: Which communities or groups users join, which videos, groups, profiles, and pages they view or share, content they “Spark” (aka like), and the searches they perform

5. Content Interactions: Posting videos with linkouts, clicking on linkouts, and reposting videos with added thoughts

​

B. Explicit User Permissions:

Where the brand requests and obtains direct permission from users for sensitive data:

1. Camera Access

2. Microphone Access

3. Location Data

4. Contact Information

5. Photo Gallery

6. Speech Recognition

​

C. Brand Context Inputs:

1. The brand defines assets, categories and topics, personas, and guidelines

2. The brand creates communities, groups, posts

3. Placements of community embeds also help shape the contextual framework in which content and ads appear

​

Connecting Through Genuin’s SDK

Genuin’s SDK integrates seamlessly across multiple platforms:

1. iOS

2. Android

3. React

4. Web

5. Flutter

allowing brands to build and maintain connected experiences across devices. By collecting and analyzing zero-party data within these applications, brands can gain an understanding of user interests, engagement patterns, and community dynamics.

​

Personalization Without Overstepping

One question often raised: If the brand doesn’t share additional data with Genuin, how can Genuin enable relevant targeting? The answer lies in the way Genuin processes existing zero-party data and contextual signals:

​

A. Advertisers gets access to be in communities

Sponsored communities, groups and posts. Genuin collects engagement data on content interactions - what users view, spark, or participate in. This helps identify the context of what they are engaging with. For example, if a community and/or group page revolves around a certain topic, advertisers can display ads that are contextually relevant without requiring individual-level personal data.

​

B. Advertises can show contextually relevant programmatic ads

AdExchange gets context of the ad space from the IAB defined macros such that the programmatic advertising gets personalised to the end consumers. Custom macros list (supported by IAB) is as follows. All these are configurable by demand partners and advertisers.

iAB	Description	Values	Value type
Content Album	Album to which the content belongs	group_name	string
Content Keywords	Comma separated list of keywords describing the content	search_query	string
Content Production quality	Product quality based on IAB standards	0 - Unknown; 1 - Professionally Produced; 3 - User Generated (UGC)	integer
Content Episode	Episode number	video_name	integer
Content Livestream	0 = not live, 1 = content is live	video_stream_type	integer
Content Context	Type of content	1 - Video (i.e., video file or stream such as Internet TV broadcasts)	integer
Content URL	Url of content	video_url	string
Content Kwarray	Array of keywords	video_keywords	string array
Content Media Rating	Media rating per IQG guidelines	1 - All Audiences; 2 - Everyone Over Age 12; 3 - Mature Audiences	integer
Content Artist	Artist credited with the content	user_name	string
Content Producer Domain	Highest level domain of the content producer	White label domain e.g (iheartmedia.begenuin.com)	string
Content Genre	Genre that best describes the content	video_description	string
Content Series	Content series	group_name	string
Content Title	Content Title	video_title	string
Content Producer Category	Array of IAB content categories that describe the content producer	community_category	string
Content Language	Content language using ISO-639-1-alpha-2.	video_lng	string
Content Producer Name	Content producer or originator name	community_name	string
Content Season	Content season	group_name	string
Content Lang	Content language using IETF BCP 47.	video_lng	string
Content Embeddable	Indicator of whether the content is embeddable	1 - For embed; 0 - white label or SDK	integer
Content Channel Name	Channel the content is on	brand_name	string
Content Length	Length of content in seconds	video_length	integer

​

C. User Experience Personalization:

Feed personalization is driven by three key factors:

1. Recency of Content: Fresh, up-to-date material surfaces first.

2. User Interest: Content aligns with what users have explicitly or implicitly indicated they care about.

3. Popularity: Content that garners higher engagement from the community naturally rises, reflecting collective interests rather than personal data trails.

​

How Advertisers Benefit Without Intrusion?

A key point is that Genuin itself does not perform the ad targeting. Instead, it enables advertisers through AdExchanges with macros - metadata or contextual signals that can be leveraged by downstream Demand-Side Platforms (DSPs) and Supply-Side Platforms (SSPs). This approach allows:

• Type 1 Access: Advertisers gain access in relevant brand communities and groups focused on topics, keywords, or contexts that match the advertiser’s desired audience segments.
• Type 2 Access: Advertisers can utilize macros defined by IAB through AdExchanges to programmatically run ads targeting context or topically engaged communities, ensuring relevance without relying on invasive personal identifiers.

​

No Need for Additional User Data Sharing

Critically, the brand does not need to share any historical or fresh user-level data with Genuin or advertisers beyond what’s already captured in the zero-party data ecosystem. Instead, Genuin continuously provides raw engagement data back to the brand. This ensures a two-way, privacy-respecting relationship where the brand maintains control and ownership over user data, while still empowering advertisers to deliver meaningful, context-rich messaging.

​

Building a Privacy-Safe Revenue Model

By focusing on zero-party data and context rather than intrusive tracking, brands can foster vibrant communities, encourage engagement, and drive media revenue streams. At the same time, users can feel confident that their data is respected, their privacy is maintained, and that they are part of a genuine value exchange.

In short, zero-party data powered by Genuin’s SDK framework offers brands a path to build trustworthy communities - ones that thrive on authenticity, user empowerment, and contextual relevance, rather than shadowy data practices that erode consumer confidence.