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Agencies · New Business

Agency New-Business Research: Know the Prospect's Audience Landscape Before You Pitch

Every pitch deck claims audience understanding; very few can show their work. Map a prospect’s audience landscape in days using coded data from a 102M-domain database — not borrowed assumptions. The result is a pitch built on evidence the incumbent probably hasn’t shown.

Profile the prospect’s own domains and competitors’ with IAB Audience Taxonomy 1.1-aligned segments
Define the buyer in fixed vocabulary codes — demographics, interests, purchase intent
Pull open-web domains that demonstrably reach that buyer — a media POV you can defend line by line
102Mdomains with audience attributes
1,667deterministic personas
285sub-interests (INT.*)
283purchase-intent segments (PI.*)
IAB Audience Taxonomy 1.1 aligned Fixed, versioned vocabularies (v1.0) Public-content signals, no PII Banded confidence per attribute Pitch-ready in days, not weeks
The new-business problem

Pitches are won on specificity, and specificity needs data

Prospects hear the same audience generalities from every agency on the shortlist. What they rarely hear is their own audience landscape, mapped in a taxonomy they can verify.

The usual pre-pitch research

  • Persona slides recycled from the last pitch in the category, with the logo swapped.
  • Audience claims sourced from panels the prospect can’t interrogate.
  • A media POV naming the same twenty premium sites every competitor’s deck names.
  • No answer when the CMO asks “where does our buyer actually spend time online?”

Research built on coded audience data

  • The prospect’s buyer defined in enumerated segments both sides can read.
  • Prospect and competitor domains profiled with the same instrument — honest comparisons.
  • An inventory landscape from 102M domains, including the long tail no template deck surfaces.
  • Every claim traceable to a code, a label and a confidence band.
Workflow

From RFP to pitch-ready landscape in four working sessions

Each step fits inside a normal pitch window and produces an artifact that goes straight into the deck.

Session 1 — define

Translate the brief’s buyer into vocabulary codes

Turn “active urban 25–34s considering premium running shoes” into checkable terms: age_bracket: 25_34, urbanicity: urban, INT.healthy_living.fitness_and_exercise, PI.clothing_accessories.footwear. The published taxonomy is the shared reference.

Session 2 — profile

Profile the prospect and its competitors

Run the prospect’s domains and three or four competitors’ through the real-time API or the database. You now know which audience each brand’s content attracts — and where the prospect’s profile diverges from its stated buyer.

Session 3 — map

Pull the inventory landscape for the buyer

Filter the 102M-domain database for domains carrying the buyer’s segment codes. The output is the addressable open-web landscape — publishers, niches and long-tail communities ranked by attribute fit and confidence.

Session 4 — package

Build the deck artifacts

Audience-gap chart, competitor benchmark table, curated inventory shortlist, and a persona view from 1,667 deterministic personas. Everything cites codes and labels, so the deck survives due diligence.

Deliverables

What lands in the pitch deck

Three artifacts from the same data pull, all defensible in the room and in procurement afterwards.

Audience-gap analysis

The prospect’s attracted audience versus its stated target, attribute by attribute — the slide that shows you understand their problem.

Competitor benchmark

Side-by-side audience profiles on identical coded fields — no methodology argument, one instrument for everyone.

Inventory POV

A curated domain landscape reaching the buyer segment, including cookieless-heavy environments — ready to become the plan if you win.

Worked example

Pitching a running-shoe brand: what the research turns up

Buyer definition from Session 1: 25_34, urban, fitness interests, footwear and athletics-equipment intent. Three findings shown as the deck would present them.

AttributeProspect's own siteLead competitor's siteRunning-content publisher (opportunity)
Interests INT.style_fashion.street_style Street Style
INT.style_fashion.fashion_trends Fashion Trends
INT.healthy_living.fitness_and_exercise Fitness & Exercise
INT.sports.track_and_field Track & Field
INT.healthy_living.fitness_and_exercise Fitness & Exercise
INT.healthy_living.nutrition Nutrition
Purchase intent PI.clothing_accessories.footwear Footwear PI.clothing_accessories.footwear Footwear
PI.sporting_goods.athletics_equipment Athletics Equipment
PI.sporting_goods.athletics_equipment Athletics Equipment
PI.apps.health_and_fitness_apps Health & Fitness Apps
Age bracket 18_24 25_34 25_34 / 35_44
Life stage young_single Young single young_professional Young professional young_professional Young professional
Confidence high high high
What it means for the pitch Fashion audience, not the performance-runner buyer — the gap slide Competitor owns the performance audience — the urgency slide Exactly the buyer, under-contested — the opportunity slide

One research pass produced the diagnosis (audience gap), the stakes (competitor position) and the plan (opportunity inventory). Each cell traces to a coded record the prospect can audit.

Sourcing compared

Where this sits among new-business research sources

CriterionSyndicated panelsSocial listeningDomain-level audience data
Covers specific competitorsOnly large brandsYesYes — any domain, 102M covered
Maps to actionable inventoryIndirectlyNoDirectly — output is a domain list
Auditable by the prospectPanel methodology on requestRarelyYes — fixed public taxonomy, confidence bands
Fits a pitch windowDepends on subscriptionFastFast — instant download or API
Captures brand sentimentPartiallyYesNo — pair with listening tools

The sources stack: listening tells you what people say about the brand; this data tells you where the buyers are — as an inventory list the media team can act on immediately.

Keep exploring

Related use cases

FAQ

New-business research, answered

Can we really turn this around inside a pitch window?

Yes — that constraint shaped the product. The demo dashboard profiles domains interactively with no setup. The Top 1M database is an instant card purchase with immediate download, and the API needs one call per URL. The four-session workflow is typically a few working days.

Is it appropriate to profile a prospect's site without telling them?

The data describes what public web content attracts as an audience — the same judgement any planner forms by reading the site, made systematic. There is no PII, no user tracking and no access to private data. Agencies routinely present this research in the pitch itself because the method withstands scrutiny.

What exactly do we buy for a new-business team?

Most teams start with API credits (e.g. Pro at $99/month for 10,000 credits) and add a database tier for landscape pulls: Top 100k at $490 one-time, Top 1M at $1,990, vertical or country slices at $190–$490. Quarterly refreshes keep pursuits current. Details on pricing.

Does the research stay useful after the pitch is won?

That’s the quiet advantage: the inventory landscape becomes the first media plan, the competitor benchmark becomes the reporting baseline, and the buyer’s coded definition carries into persona-based planning unchanged — because everything was expressed in versioned vocabulary terms from day one.

Walk in knowing their audience better than they do

Profile your next prospect in the demo today, or license the database and make landscape mapping a standard step in every pursuit.

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