# Audience Targeting Reference

Detailed targeting strategies for each major ad platform.

## Google Ads Audiences

### Search Campaign Targeting

**Keywords:**

- Exact match: [keyword] — most precise, lower volume
- Phrase match: "keyword" — moderate precision and volume
- Broad match: keyword — highest volume, use with smart bidding

**Audience layering:**

- Add audiences in "observation" mode first
- Analyze performance by audience
- Switch to "targeting" mode for high performers

**RLSA (Remarketing Lists for Search Ads):**

- Bid higher on past visitors searching your terms
- Show different ads to returning searchers
- Exclude converters from prospecting campaigns

### Display/YouTube Targeting

**Custom intent audiences:**

- Based on recent search behavior
- Create from your converting keywords
- High intent, good for prospecting

**In-market audiences:**

- People actively researching solutions
- Pre-built by Google
- Layer with demographics for precision

**Affinity audiences:**

- Based on interests and habits
- Better for awareness
- Broad but can exclude irrelevant

**Customer match:**

- Upload email lists
- Retarget existing customers
- Create lookalikes from best customers

**Similar/lookalike audiences:**

- Based on your customer match lists
- Expand reach while maintaining relevance
- Best when source list is high-quality customers

---

## Meta Audiences

### Core Audiences (Interest/Demographic)

**Interest targeting tips:**

- Layer interests with AND logic for precision
- Use Audience Insights to research interests
- Start broad, let algorithm optimize
- Exclude existing customers always

**Demographic targeting:**

- Age and gender (if product-specific)
- Location (down to zip/postal code)
- Language
- Education and work (limited data now)

**Behavior targeting:**

- Purchase behavior
- Device usage
- Travel patterns
- Life events

### Custom Audiences

**Website visitors:**

- All visitors (last 180 days max)
- Specific page visitors
- Time on site thresholds
- Frequency (visited X times)

**Customer list:**

- Upload emails/phone numbers
- Match rate typically 30-70%
- Refresh regularly for accuracy

**Engagement audiences:**

- Video viewers (25%, 50%, 75%, 95%)
- Page/profile engagers
- Form openers
- Instagram engagers

**App activity:**

- App installers
- In-app events
- Purchase events

### Lookalike Audiences

**Source audience quality matters:**

- Use high-LTV customers, not all customers
- Purchasers > leads > all visitors
- Minimum 100 source users, ideally 1,000+

**Size recommendations:**

- 1% — most similar, smallest reach
- 1-3% — good balance for most
- 3-5% — broader, good for scale
- 5-10% — very broad, awareness only

**Layering strategies:**

- Lookalike + interest = more precision early
- Test lookalike-only as you scale
- Exclude the source audience

---

## LinkedIn Audiences

### Job-Based Targeting

**Job titles:**

- Be specific (CMO vs. "Marketing")
- LinkedIn normalizes titles, but verify
- Stack related titles
- Exclude irrelevant titles

**Job functions:**

- Broader than titles
- Combine with seniority level
- Good for awareness campaigns

**Seniority levels:**

- Entry, Senior, Manager, Director, VP, CXO, Partner
- Layer with function for precision

**Skills:**

- Self-reported, less reliable
- Good for technical roles
- Use as expansion layer

### Company-Based Targeting

**Company size:**

- 1-10, 11-50, 51-200, 201-500, 501-1000, 1001-5000, 5000+
- Key filter for B2B

**Industry:**

- Based on company classification
- Can be broad, layer with other criteria

**Company names (ABM):**

- Upload target account list
- Minimum 300 companies recommended
- Match rate varies

**Company growth rate:**

- Hiring rapidly = budget available
- Good signal for timing

### High-Performing Combinations

| Use Case         | Targeting Combination                             |
| ---------------- | ------------------------------------------------- |
| Enterprise sales | Company size 1000+ + VP/CXO + Industry            |
| SMB sales        | Company size 11-200 + Manager/Director + Function |
| Developer tools  | Skills + Job function + Company type              |
| ABM campaigns    | Company list + Decision-maker titles              |
| Broad awareness  | Industry + Seniority + Geography                  |

---

## Twitter/X Audiences

### Targeting options:

- Follower lookalikes (accounts similar to followers of X)
- Interest categories
- Keywords (in tweets)
- Conversation topics
- Events
- Tailored audiences (your lists)

### Best practices:

- Follower lookalikes of relevant accounts work well
- Keyword targeting catches active conversations
- Lower CPMs than LinkedIn/Meta
- Less precise, better for awareness

---

## TikTok Audiences

### Targeting options:

- Demographics (age, gender, location)
- Interests (TikTok's categories)
- Behaviors (video interactions)
- Device (iOS/Android, connection type)
- Custom audiences (pixel, customer file)
- Lookalike audiences

### Best practices:

- Younger skew (18-34 primarily)
- Interest targeting is broad
- Creative matters more than targeting
- Let algorithm optimize with broad targeting

---

## Audience Size Guidelines

| Platform       | Minimum Recommended | Ideal Range  |
| -------------- | ------------------- | ------------ |
| Google Search  | 1,000+ searches/mo  | 5,000-50,000 |
| Google Display | 100,000+            | 500K-5M      |
| Meta           | 100,000+            | 500K-10M     |
| LinkedIn       | 50,000+             | 100K-500K    |
| Twitter/X      | 50,000+             | 100K-1M      |
| TikTok         | 100,000+            | 1M+          |

Too narrow = expensive, slow learning
Too broad = wasted spend, poor relevance

---

## Exclusion Strategy

Always exclude:

- Existing customers (unless upsell)
- Recent converters (7-14 days)
- Bounced visitors (<10 sec)
- Employees (by company or email list)
- Irrelevant page visitors (careers, support)
- Competitors (if identifiable)
