LinkedIn Lookalike Audiences Discontinued: What to Use Instead

TL;DR: LinkedIn discontinued Lookalike Audiences in February 2023 (replaced "Lookalike" with "Audience Expansion" feature). No direct lookalike replacement exists. Best alternatives: Use Matched Audiences + Audience Expansion, leverage Website Demographics for insights, expand targeting manually with similar attributes, or use third-party enrichment tools. Focus on first-party data strategies.

What Happened to LinkedIn Lookalike Audiences?

Timeline of Discontinuation

February 2023: LinkedIn removed Lookalike Audiences feature Reason cited: "Optimizing our product offerings" Replacement offered: Audience Expansion (not equivalent) Existing lookalikes: Stopped updating, became static audiences Key differences:

• Old Lookalike: Created separate audience of similar people

• New Expansion: Broadens existing targeting automatically (less control)

Why LinkedIn Removed Lookalikes

Official reason: Product optimization Speculated reasons:

• Low adoption (many advertisers didn't use feature)

• Privacy regulations (EU GDPR, CCPA restrictions)

• Algorithm complexity (hard to maintain accuracy)

• Performance issues (lookalikes often underperformed manual targeting on LinkedIn)

Unlike Facebook/Meta: LinkedIn lookalikes never worked as well due to smaller professional network data set.

LinkedIn's "Audience Expansion" (Not a True Replacement)

What Audience Expansion Is

LinkedIn's current alternative to lookalikes:

How it works:

• You set specific targeting (job titles, companies, etc.)

• Toggle "Enable Audience Expansion" ON

• LinkedIn automatically includes similar members beyond your targeting

• You don't control who's added

Example:

• Your targeting: Marketing Managers at software companies

• With expansion: LinkedIn adds Marketing Directors, Growth Managers, similar roles at tech companies

• No transparency into exactly who's added

Audience Expansion vs Lookalike Audiences

Bottom line: Audience Expansion is reach tool, not precision lookalike tool.

How to Use Audience Expansion

1. Campaign setup > Targeting section

2. Set your core targeting criteria

3. Scroll to Audience Expansion

4. Toggle Enable Audience Expansion ON

5. LinkedIn shows expanded audience estimate

When to use:

• Brand awareness campaigns (reach over precision)

• Large budgets (can afford to test expanded audience)

• Proven offers (high conversion rate even with broader audience)

When NOT to use:

• Highly specific ICP (tight targeting required)

• Limited budget (can't waste spend on low-fit prospects)

• Bottom-funnel campaigns (need qualified leads only)

Alternative Strategies to Replace Lookalikes

Strategy 1: Matched Audiences + Manual Expansion

What it is:

Use Matched Audiences (contact upload) as seed, then manually target similar attributes.

How to do it: Step 1: Upload customer list

1. Campaign Manager > Account Assets > Matched Audiences

2. Upload CSV of customer emails

3. LinkedIn matches 40-60% to member profiles

Step 2: Analyze matched audience

1. Download matched audience insights (if available)

2. Note common attributes:

- Job titles (75% are Directors)

- Industries (60% are Software)

- Company sizes (50% are 201-500 employees)

- Seniority (80% are Manager+)

Step 3: Create new campaign targeting those attributes

1. New campaign > Targeting

2. Job titles: Director, VP, Manager (based on Step 2)

3. Industry: Software, Technology

4. Company size: 201-500, 501-1000

5. Seniority: Manager+

Result: You've manually created a "lookalike" by identifying customer patterns and targeting similar prospects. Pros:

• Full control over attributes

• Transparent targeting

• Can A/B test attribute combinations

Cons:

• Time-consuming

• Requires analysis skills

• Less automated than true lookalike

Strategy 2: Website Demographics Insights

What it is:

Use LinkedIn Website Demographics to discover who visits your site, then target similar profiles.

How to do it: Step 1: Install Insight Tag and collect data

• Minimum 300 LinkedIn member visits

• 30+ days of data recommended

Step 2: Analyze Website Demographics

Campaign Manager > Analyze > Website Demographics

Metrics to review:

• Job Functions (e.g., 35% Marketing, 20% IT)

• Seniority Levels (e.g., 40% Manager, 25% Director)

• Industries (e.g., 30% Software, 20% Financial Services)

• Company Sizes (e.g., 45% are 201-500 employees)

Step 3: Build campaign targeting those demographics

• Target top 3 job functions

• Target top 2 seniority levels

• Target top 3 industries

Result: You're targeting people similar to those already interested in your content. Pros:

• Based on real visitor data

• Identifies warm audience segments

• Free (no additional tools needed)

Cons:

• Requires Insight Tag installed

• Need sufficient traffic (300+ visits)

• Correlation doesn't equal causation (visitors ≠ buyers)

Strategy 3: Layer Multiple Targeting Criteria

What it is:

Instead of lookalikes, use hyper-specific multi-criteria targeting.

How to do it: Example ICP: B2B SaaS selling to marketing teams at mid-market companies Layer 1: Job Function

• Marketing

Layer 2: Seniority

• Manager

• Director

Layer 3: Company Size

• 201-500 employees

• 501-1000 employees

Layer 4: Industry

• Computer Software

• Marketing & Advertising

Layer 5: Groups

• Members of "B2B Marketing" groups

• Members of "Growth Marketing" groups

Layer 6: Skills

• Digital Marketing

• Marketing Automation

Result: Highly targeted audience that resembles ideal customers without needing lookalike algorithm. Pros:

• Precision targeting

• Control over every criterion

• Can incrementally expand by loosening one criterion at a time

Cons:

• May result in small audience (<10,000)

• Time-consuming to set up

• Requires deep understanding of ICP

Strategy 4: Retargeting + Cold Audience Combo

What it is:

Combine retargeting warm audience with cold but similar attributes.

How to do it: Campaign A: Retargeting

• Target: Website visitors (last 90 days)

• Budget: 40% of total

• Goal: Convert warm leads

Campaign B: Cold Lookalike Proxy

• Target: Same job titles/industries as retargeting audience

• Budget: 60% of total

• Goal: Find new similar prospects

Insight: Check which job titles/companies from Campaign B convert best, then refine targeting further. Result: Testing approach to discover best-fit cold audience. Pros:

• Data-driven (refine based on actual conversions)

• Balances warm and cold outreach

• Scalable as you learn what works

Cons:

• Requires retargeting pool first

• Takes time to gather conversion data

• More complex to manage (2 campaigns)

Strategy 5: Third-Party Enrichment Tools

What it is:

Use data enrichment platforms to find similar companies/contacts.

Tools:

• ZoomInfo: Upload customer list, get "lookalike companies"

• Clearbit: Enriches leads with firmographic data

• 6sense: Predictive audiences based on intent data

• Bombora: Company-level intent data

How to do it: Step 1: Upload customer list to enrichment tool Step 2: Tool identifies similar companies/contacts Step 3: Export enriched list Step 4: Upload to LinkedIn as Matched Audience Example workflow:

1. Upload 500 customers to ZoomInfo

2. ZoomInfo returns 5,000 similar companies

3. Export company names

4. Upload to LinkedIn as Company List audience

5. Target employees at those companies

Pros:

• Closest to true lookalike functionality

• Leverages external data sources

• More sophisticated matching algorithms

Cons:

• Costs money ($5,000-50,000/year for enrichment tools)

• Requires additional tool integration

• Data privacy considerations

Comparison: Lookalike Alternatives

What Meta/Facebook Advertisers Should Know

If you're used to Facebook Lookalike Audiences: Key differences on LinkedIn:

• LinkedIn's professional data set is smaller

• B2B targeting requires different approach (job-based, not interest-based)

• LinkedIn lookalikes never performed as well as Facebook's

• Manual targeting often outperforms automated on LinkedIn

Strategy shift:

• On Facebook: Rely on lookalikes for scale

• On LinkedIn: Use precise manual targeting + gradual expansion

Why LinkedIn is different:

• 1 billion members (vs Facebook's 3 billion)

• Professional network (narrower use case)

• B2B focus (smaller addressable market per advertiser)

• Better native targeting options (job title, company, seniority)

Future of LinkedIn Audience Targeting

LinkedIn's direction:

• Focus on AI-powered Audience Expansion (not manual lookalikes)

• Privacy-first targeting (less third-party data)

• First-party data emphasis (Matched Audiences, retargeting)

• Predictive audiences (LinkedIn determines best audience automatically)

Recommendation: Don't wait for lookalikes to return. Adopt first-party data strategies now.

FAQs

Will LinkedIn bring back Lookalike Audiences?

Unlikely. It's been discontinued since February 2023 with no indication of return. LinkedIn is investing in Audience Expansion instead.

Can I still access old Lookalike Audiences I created?

No. Existing lookalike audiences stopped updating and were eventually deprecated. They no longer appear in Matched Audiences.

Does Audience Expansion work as well as Lookalikes?

No. Audience Expansion is less precise. You can't control match percentage or see expanded audience attributes. It's a reach tool, not a targeting precision tool.

What's the best replacement for LinkedIn Lookalikes?

For most advertisers: Matched Audiences + Manual Expansion (Strategy 1) For enterprises: Third-party enrichment tools (Strategy 5) For brand awareness: Audience Expansion toggle

Can I use LinkedIn's algorithm to find similar people?

Yes, indirectly. Use Audience Expansion toggle. LinkedIn's algorithm adds similar members automatically, but you can't control who's added.

How do I target similar companies without lookalikes?

Option 1: Upload customer company list as Matched Audience, target employees Option 2: Use Website Demographics to identify visiting companies, target similar company profiles Option 3: Use third-party tools (ZoomInfo, 6sense) to identify similar companies

Best Practices for Post-Lookalike LinkedIn Targeting

1. Embrace manual targeting precision

LinkedIn's native filters (job title, company, seniority) are powerful. Use them.

2. Start narrow, expand gradually

Begin with tight ICP targeting, then loosen one criterion at a time based on performance.

3. Test Audience Expansion cautiously

Enable on 1-2 campaigns first. Monitor cost per conversion. Disable if quality drops.

4. Prioritize first-party data

• Build email lists → Upload as Matched Audiences

• Install Insight Tag → Use Website Demographics

• Retarget engaged users

5. Use attribution data to refine

Check which job titles/companies convert → Target more of those attributes.

6. Don't over-rely on automation

LinkedIn's automated targeting (Audience Expansion, Predictive) is less mature than Facebook's. Manual targeting often wins.

7. Leverage Website Demographics monthly

Review report every 30 days. Adjust targeting based on who's actually visiting.

8. Test multiple strategies

Run parallel campaigns:

• Campaign A: Matched Audiences only

• Campaign B: Manual demographic targeting

• Campaign C: Audience Expansion enabled

Compare performance, scale winner.

Glossary

Verification Checklist

When building lookalike alternative strategy:

• [ ] Insight Tag installed for Website Demographics (if using Strategy 2)

• [ ] Customer email list prepared for Matched Audience upload (if using Strategy 1)

• [ ] ICP documented (job titles, seniority, industries, company sizes)

• [ ] Multiple campaigns set up to test different strategies

• [ ] Audience Expansion toggle tested on at least 1 campaign

• [ ] Conversion tracking configured to measure which strategy works best

• [ ] Budget allocated across test campaigns (not all in one approach)

• [ ] Quarterly review scheduled to refine targeting based on performance

• [ ] Third-party tools evaluated if budget allows (for Strategy 5)

• [ ] Attribution reports reviewed to identify best-converting segments

Next Steps

Immediate actions:

1. Stop waiting for lookalikes to return - They won't

2. Choose 1-2 alternative strategies from above

3. Implement this week - Start with Matched Audiences + Manual Expansion

4. Run for 30 days - Gather performance data

5. Optimize based on results - Double down on what works

Long-term strategy:

• Build first-party data assets (email lists, website traffic)

• Invest in conversion tracking to identify best audiences

• Test Audience Expansion quarterly (LinkedIn improves algorithm over time)

• Consider third-party enrichment tools if budget allows

Success metric:

Compare cost per conversion before/after transitioning from lookalikes (or from other platforms). Aim to match or beat previous performance within 90 days.