Media & Marketing Audience Intelligence Multicultural

Audience intelligence automation, built for a multicultural media agency.

An independent media and marketing strategy agency, focused on multicultural audiences, built an AI platform that turns a media brief into a channel-ready plan, compressing days of manual research into minutes.

Up to 5xMore research volume, per planner
>90%Of briefs completed without increasing headcount
9K+Data points tracked, per audience
01 · Client

A media agency built around multicultural audiences.

The agency provides media planning and audience intelligence for brands reaching multicultural and nuanced audiences. Its own research and data platform powers every campaign, from audience discovery through to channel activation.

RegionUSA · London · Spain
SectorMedia & marketing strategy
Founded2004
Media reach1,000+ diverse-owned publishers, worldwide
SpecializationMulticultural & nuanced audience research
Function in scopeAudience intelligence & media planning
02 · The problem

Where the research time actually went.

Every campaign needed a fresh, accurate picture of its audience, and every time, an analyst had to start that research all over again.

01

Manual, analyst-dependent research

An analyst pulls syndicated crosstabs, reads hundreds of rows, cross-references sentiment, and hand-builds a media list. It’s slow, and it varies from one analyst to the next.

02

Off-the-shelf tools don’t close the gap

Raw panel data is rich but unread. One-size-fits-all targeting ignores cultural over-indexing and treats multicultural audiences as a general-market afterthought.

03

A snapshot from a single point of view

Syndicated panel data is authoritative but lags (often 12 to 18 months), so a plan built on it can be a plan built on last year’s audience.

04

The obvious traits, not the real insight

The highest-indexing traits in any dataset are usually the ones a planner already knew. What’s worth paying for is what nobody would have guessed.

03 · Why not native

What a real fix had to get right.

One research panel was never going to close this gap, no matter how skilled the analyst. Four things had to hold at once.

01

Cross-check every source, not just one

Merge multiple independent research sources into a single, weighted view, rather than trusting one panel’s point of view.

02

Catch what’s genuinely unexpected

Score findings for real, surprising relevance, not just the traits that were already obvious.

03

Track how an audience changes, not just where it stands

Carry a multi-year behavioral history, so a profile reflects what’s changed, not a single moment in time.

04

Say so when the evidence is thin

Score every answer for confidence, and flag clearly wherever the data doesn’t fully support it.

04 · What Lyzr built

A signal layer, not another point tool.

Lyzr built an Intelligence Agent, a chain of specialized agents, that reads a brief, cross-checks the evidence across sources, and returns an audience profile with a recommended channel mix and a curated inventory package.

Multicultural over-index detection
Isolates what makes an audience distinctive against the general population, and drops average behavior entirely.
Multi-source cross-checking
Merges multiple independent research sources into one weighted evidence set.
Confidence-scored, source-traceable answers
Every trait, channel and inventory line carries a confidence score and a named source.
Channel-mix & curated inventory
Scored signal becomes a recommended channel split and a vetted, activatable inventory package.
05 · Architecture

How a brief moves through the system.

A request moves through three stages, each backed by its own layer of caching so a brief never waits on a live data pull twice.

System architecture
The API layer never inlines a live pull, Core logic decides what a signal means, and the Intelligence Layer only enriches a decision the code already made.
Client

User Interface

Profile views, pivot approvals

API service

API Layer

Auth, routing, degrade-safe

Core

Core Application Logic

5 specialized engines, orchestrated

The engines, in order

Profile analysis engine

Audience sweep engine

Insight engine

Context monitoring engine

Activation builder

Intelligence layer
Lyzr Studio agents
Resolution
Classification
Narrative
Activation

Enriches a decision Core has already made.

Data & storage

Data & Storage

MongoDB
Caches
06 · Controls & governance

Checked before it reaches a planner.

The system never lets a guess pass as fact.

Over-index filtering
Only behaviors that exceed the population baseline carry forward; average behavior is dropped entirely.
Confidence scoring
Every trait, channel and inventory line carries a confidence score and a traceable source.
Never invented
If the evidence is thin, the system says so and lowers its confidence; it never presents a guess as a fact.
Anti-stereotype & publisher integrity
Cultural context is preserved, never caricature; curated inventory is vetted against a diversity-ownership registry.
Human review
A planner checks the summary, channel mix and package against the evidence before anything ships.
07 · Re-imagined workflow

From days of manual research to one guided brief.

Before: an analyst pulls syndicated crosstabs, reads hundreds of rows, and hand-builds a media list, a process that varies analyst to analyst. After: a planner works through a guided intake, and the engine returns a cross-checked, confidence-scored plan.

08 · Results

What the engine is built to compress.

Same evaluation, transformed: from manual research to one governed run.

MeasureBeforeAfter
Research baseOne syndicated panel, read manuallyFour sources merged under one weighting model
How current the read isA point-in-time snapshotFive years of movement, ranked by what changed
What gets foundThe most obvious, highest-indexing traitsFindings checked against the audience’s own demographics
Inventory recommendationsA generic list, loosely tied to behaviorPublisher-vetted, matched to real behavioral signal
How defensible it is“Trust the analyst”Every line carries a confidence score and a named source
Speed per briefDays, varying by analystMinutes, consistent across the team
One clickFrom a completed brief to a channel-ready plan
Up to 5xMore research volume, per planner
9K+Data points tracked, per audience
09 · What’s next

From media planning to a second product, bridged together.

The same governed AI layer already powers a second product for building audience personas, connected to the media planning engine through a fully deterministic bridge, so a persona can define a media audience, and media findings can enrich a persona, without either side losing traceability.

Same evidence-first core, ready to extend

Got a use case in mind?

Platform, engineers and governance all in. We will map your workflow against the same four tests this one had to pass.