/51-audience-research-global

name: 51-audience-research-global
description: "Use when paid ad AUDIENCES must be researched and defined before launch — target profile, interest and behavior mapping per platform, audience sizing, cold, warm, and hot tiering, lookalike seeds, exclusions, and ranked targeting hypotheses to test. Trigger on 'audience research', 'who should I target', 'interest targeting', 'Meta audience for this product', 'TikTok targeting ideas', 'my targeting is too broad'. Also use when launch is imminent and the ad set targeting is still empty. Not for — persona and JTBD depth for content, see `09-customer-insight-global`; warm retargeting tiers, see `56-retargeting-plan-global`; where the budget goes, see `54-media-plan-global`; the campaign hierarchy, see `52-account-structure-global`."
metadata:
  version: 1.0.1
  category: performance
license: MIT
triggers:
  - "audience research"
  - "target audience"
  - "interest targeting"
  - "audience for campaign"
  - "who should I target"
  - "Meta audience"
  - "TikTok audience"
  - "lookalike seed"
output: "File .md — audience profile, ready-to-paste targeting settings per platform, cold/warm/hot tiers, lookalike seed brief, and a ranked list of targeting hypotheses to test"
related:
  - product-marketing-context-global
  - 09-customer-insight-global
  - 08-competitor-research-global
  - 10-reverse-kpi-global
  - 52-account-structure-global
  - 54-media-plan-global
  - 56-retargeting-plan-global

Audience Research (Global)

Wrong targeting burns budget no matter how good the copy or creative is. This is the first step of the performance chain: 51 -> `10-reverse-kpi-global` -> `54-media-plan-global` -> `53-tracking-setup-global` -> `52-account-structure-global`. If there is no customer insight yet, run `09-customer-insight-global` first.

Information gathering

Read `.agents/product-marketing-context-global.md` and any output from `09-customer-insight-global`. If information is missing, ask up to 4 questions:

1. **What product or service will run ads?** Price point and market tier (mass / mid / premium)? 2. **What existing customer data is available?** Age, gender, geography, purchase behavior, past customer list, CRM export, pixel data. 3. **Which platforms and which markets?** Meta / Google / TikTok / YouTube / LinkedIn / Pinterest — and which countries. Primary objective: lead gen / conversion / traffic / awareness? 4. **Planned budget and target CPA/CPL?** If not calculated yet, run `10-reverse-kpi-global`.

Principles

1. **Geography is the biggest cost lever, before interests.** Per `references/benchmarks-global.md`, Tier 1 markets (US, Canada, Australia, Western EU) run 6-7x the CPM of Tier 2 (SEA, LATAM). US Meta CPM sits at $15-25 vs $2-6 in Brazil/LATAM. Decide the market before debating interest stacks. 2. **Research before copy and before campaign build.** Never the reverse. 3. **Broad first, narrow only with evidence.** Modern delivery algorithms optimize well on a wide pool plus strong creative. Narrow only when segment data proves it. 4. **One clear interest theme per ad set.** Stacking many unrelated interests makes it impossible to tell which one worked. 5. **Write pain points in the customer's own words**, not marketer language. 6. **Size for spend, not for a magic number.** A cold ad set must be large enough to spend its daily budget for at least 7 days without frequency passing 2.5. A tight interest stack saturates fast in a Tier 1 market where CPM is $13-20. 7. **This is a living document.** Update it after 3-5 days of live data by comparing CPA per segment.

Workflow

1. Core audience profile

Build from real data (CRM, analytics, order history, platform audience insights) plus `09-customer-insight-global`:

| Field | Detail | |-------|--------| | Age | [primary band + secondary band] | | Gender | [actual split from data, not assumption] | | Markets | [countries/regions you can actually ship to or serve] | | Market tier | Tier 1 (US/CA/AU/W.EU) / Tier 2 (SEA/LATAM) / mixed | | Income / budget band | [must match the price point] | | Job or role | [primary segment; required for B2B] | | Primary device | Mobile / Desktop / Both | | Language | [ad language per market] |

For B2B, add company size, industry, seniority, and buying committee role.

2. Psychographics and behavior

• **Top pain points:** 3-5, phrased the way customers say them.
• **Buying motivation:** what they want to gain, what they want to avoid.
• **Purchase context:** card-first checkout, subscription comfort, review dependence, return-policy sensitivity.
• **Online behavior:** platforms used, peak hours per market timezone, content formats they engage with.

3. Targeting settings per platform

Only build blocks for platforms that will actually run. Each block should be paste-ready into the ads manager.

• **Meta Ads:** age, gender, locations (list countries explicitly, exclude where you cannot fulfill); detailed targeting with 10-15 related interests grouped into 2-3 themes for separate testing; behaviors; exclusions (past purchasers, submitted leads); a broad-vs-narrow recommendation. Note whether Advantage+ audience will be used as a control.
• **Google Ads:** in-market audiences; custom segments built from 10-15 high-intent search terms; affinity; Customer Match if a consented list exists. Search intent beats demographic targeting here.
• **TikTok Ads:** age, gender, interests, behaviors (recent video interactions), device OS, creator-adjacent targeting.
• **YouTube Ads:** custom segments from search terms, placements (specific channels/videos), topics, life events.
• **LinkedIn Ads (B2B only):** job title, function, seniority, company size, industry, member skills, matched company lists. Expect CPM $30-100+ per `references/benchmarks-global.md` — validate the economics with `10-reverse-kpi-global` before committing.
• **Pinterest Ads:** interests, keywords, actalike audiences. Strongest for home, fashion, DIY, and female 25-54.

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