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Media · Entertainment · Advertising

Media, entertainment, and advertising audiences move fast. The data that tracks them should move faster.

We unify audience, content, and campaign data into one governed source so media, entertainment, and advertising teams can measure performance, attribute spend, and act on engagement in near real time.

The engagement

A partner who understands Media, Entertainment & Advertising.

No one spends the first month explaining media, entertainment & advertising to us. The team arrives knowing the sector's systems, regulations, and reporting rhythms, then builds the data models, governance, and dashboards alongside in-house teams, against the metrics they already answer for.

  • Viewing, subscription, and engagement data unified into one source
  • Near-real-time campaign and ad attribution across channels
  • Content performance analytics that guide what to commission
  • Audience signal teams act on, not gut feel
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A Media, Entertainment & Advertising working environment, the setting this data foundation serves

What we stand up

The foundation for Media, Entertainment & Advertising

The capabilities we put in place, and how fast they reach first value.

Audience
One unified, consent-aware view
Every channel
Attribution in one place
8–16 wks
To first value in production
SnowPro
Certified engineers on delivery

Challenges we solve

What Media, Entertainment & Advertising teams are up against

The recurring problems we hear, and how we resolve them.

Audience data scattered across platforms

We unify viewing, subscription, and engagement data into one source.

Campaign attribution that arrives too late

We deliver near-real-time attribution across channels and spend.

Content decisions made on gut feel

We surface content performance analytics that guide what to commission.

What gets delivered

Deliverables

Tangible outcomes engineered to move the metrics that matter.

Audience & engagement analytics

A unified view of who is watching, reading, and subscribing.

Campaign & ad attribution

Cross-channel attribution that connects spend to outcomes.

Content performance analytics

What resonates, by title, format, and platform.

Unified media data foundation

A governed foundation across ad, subscription, and content systems.

Stack

Tools & technologies

The Snowflake-first stack we reach for in this sector.

SnowflakeOpenflowCortexStreamlit
Media, Entertainment & Advertising data and AI delivered on Snowflake

Media · Entertainment · Advertising

Built for Media, Entertainment & Advertising, on Snowflake.

ComplianceMED

Built for the regulators

Consent-aware audience data, governed for privacy across every channel. How we keep data safe →

Questions

Common questions in this sector

How do media companies unify audience data spread across platforms?

Viewing, subscription, and engagement data is unified into one governed source on Snowflake, which is what turns audience data scattered across platforms into a single view of who is watching, reading, and subscribing. Viewnear builds that governed foundation across ad, subscription, and content systems. Audience data is handled consent-aware, governed for privacy across every channel.

Can Snowflake do cross-channel campaign and ad attribution?

Cross-channel attribution runs on Snowflake once campaign, audience, and spend data share one governed source, and it is delivered near real time rather than arriving too late to act on. Viewnear unifies audience, content, and campaign data so media, entertainment, and advertising teams can measure performance, attribute spend, and act on engagement in near real time, with attribution connecting spend to outcomes across channels.

What data does a content team need to decide what to commission?

Content performance analytics shows what resonates by title, format, and platform, which is what replaces gut feel in commissioning decisions. Viewnear delivers that analytics on Snowflake from unified audience, content, and campaign data, so engagement can be acted on in near real time.

Let's stand up a lasting data & AI practice.

Tell us where the organization stands (migrating, scaling, or shipping AI) and we'll map the fastest path to use cases in production, run by in-house teams.