51-audience-research-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.

### 4. Cold / warm / hot tiers

| Tier | Definition | Signal | Source |
|------|-----------|--------|--------|
| Hot | Landing page visit, add to cart, checkout started, form opened, open sales conversation | Pixel/CAPI events, CRM | Meta, Google, TikTok, CRM |
| Warm | Video watched >50%, page or post engagement, link click, follow, email opened | Engagement custom audiences, ESP segments | Meta, TikTok, email platform |
| Cold | Does not know the brand | Interest, behavior, broad, lookalike, search intent | All platforms |

Rule: cold and warm/hot must live in separate campaigns with different messages (see `56-retargeting-plan-global`). Always exclude warm and hot from cold campaigns so the data stays clean.

### 5. Lookalike and seed audiences

| Seed | Minimum seed size | Lookalike % | Platform | Purpose |
|------|------------------:|-------------|----------|---------|
| Past purchasers | >= 100 | 1-3% | Meta | Find people like the best customers |
| Qualified leads | >= 500 | 1-5% | Meta | Scale lead generation |
| Video viewers 75% | >= 1000 | Broad | TikTok | Scale awareness |
| Email / CRM list | >= 300 | 1-5% | Meta, Google Customer Match | Extend from first-party data |

Seed quality beats seed size: purchasers outperform leads, leads outperform viewers. Do not build a lookalike from a seed below the minimum. Any uploaded customer list must have marketing consent on record — see the consent section in `53-tracking-setup-global`.