OrchestriAI
MarketingWorkflow AutomationMarketing agency running outbound for B2B clients

Cold Email Personalization Using Live Meta Ads Data

Automated lead enrichment that pulls real-time Meta Ads Library data and generates personalized cold email openers based on each prospect's active ad campaigns.

Verified client engagementBy Shariq Riaz ·

Engagement map

From operating problem to measured outcome

2 weeks build + ongoing refinement delivery · 5 tools in the implementation stack

  1. 01
    01Marketing agency running outbound for B2B clients

    Challenge

    The client was running cold outbound at scale, Apollo for sourcing, Airtable as the data hub, PlusVibe for sending.

  2. 02
    02n8n + Meta Ads Library API

    What we built

    We built an n8n workflow that sits between lead qualification and campaign enrollment.

  3. 03
    032 weeks build + ongoing refinement

    Result

    The manual research step was eliminated entirely.

Recorded outcomes

Manual research per lead
EliminatedEngagement result
Enrichment coverage
100% of qualified leadsEngagement result
Creative classification
Static, video, UGC detectionEngagement result

Delivery timeline: 2 weeks build + ongoing refinement. Metrics are shown in the same context as the published engagement.

Source providedVerified client engagement

Problem, implementation, outcome

01

Challenge

The client was running cold outbound at scale, Apollo for sourcing, Airtable as the data hub, PlusVibe for sending. The emails were generic. Every prospect got the same opener regardless of whether they were spending $50k/month on Meta ads or running nothing at all. The personalization layer was manual: someone would check the Meta Ads Library, note what kind of creatives a brand was running, and write a one-liner. That doesn't scale past a few dozen leads a day.

02

What we built

We built an n8n workflow that sits between lead qualification and campaign enrollment. For each qualified lead, it cleans the company name (strips legal suffixes, generic industry words), queries the Meta Ads Library for active campaigns, counts ads by creative type (static, video, UGC), and generates a short personalization line, something like how many active campaigns they're running and whether they lean toward video or static. Leads with active ads get routed into one PlusVibe campaign with the enrichment data attached. Leads with zero ads get routed separately so they don't receive broken or irrelevant personalization. The whole pipeline runs hands-off once a lead hits the qualification threshold.

03

Result

The manual research step was eliminated entirely. Every outbound email now references the prospect's actual advertising activity, real data, not templates. The enrichment runs automatically for every qualified lead, and the campaign routing ensures no prospect gets a personalization line that doesn't match reality. Post-delivery, we ran several rounds of refinement on creative classification accuracy and campaign upload logic to tighten the output quality.

Implementation stack

n8n
Meta Ads Library API
PlusVibe
Apollo
Airtable
Delivery timeline: 2 weeks build + ongoing refinement

Related case studies

Results like these start with a free call.

If the same approach fits your situation, I'll tell you how. If it doesn't, I'll tell you that too.

Book a Free Call