Intel: Global Multi-Channel B2B Campaign

Overview

As Senior Paid Media Manager at Iron Horse, I led the end-to-end strategy and execution of Intel's global, multi-channel paid media campaigns across four enterprise verticals: Cloud, AI, Cybersecurity, and Gaming. With $1.5M+ in quarterly ad spend and a portfolio of 200+ ad units, the mandate was clear — drive qualified pipeline at scale for one of the world's most recognizable B2B brands.

Over nearly two years, I transformed Intel's paid media from a high-spend, low-efficiency operation into a precision performance engine. Then, in Q2 2024, the real test came: a 40% budget cut with zero reduction in performance goals. We didn't just survive it — we set new records.

The Challenges

CPL of $300 creating unsustainable cost-per-MQL across enterprise verticals
Fragmented attribution across 200+ ad units making optimization decisions slow and imprecise
Messaging misalignment across Cloud, AI, Cybersecurity, and Gaming audience segments
Junior team needing upskilling to scale repeatable performance playbooks across the agency
Q2 2024: 40% budget reduction with unchanged targets — sustain 15% increase in qualified leads, CPMQL below $250

Phase 1: Building the Performance Foundation

Persona-Driven Messaging Architecture

Mapped distinct messaging frameworks for each vertical — IT leaders and cloud architects (Cloud), data scientists and ML engineers (AI), CISOs and security architects (Cybersecurity), and gaming enthusiasts and PC builders (Gaming)
Built a full-funnel creative matrix aligning ad formats, copy angles, and CTAs to awareness, consideration, and conversion stages
Deployed advanced audience segmentation using Demandbase and LinkedIn Matched Audiences to reach in-market buyers with precision

Attribution & Tracking Infrastructure

Implemented granular UTM tracking across all 200+ ad units — creating a single source of truth for performance data
Built custom reporting dashboards in Looker Studio and Tableau connecting Supermetrics pipelines to real-time campaign data
Reduced ad waste by 60% by identifying and eliminating underperforming audience segments through conversion path analysis

Predictive Bidding & Budget Optimization

Implemented predictive bidding models prioritizing high-intent signals — job title, company size, intent topic, and recency of engagement
Established dynamic budget pacing rules to automatically shift spend toward top-performing dayparts, geos, and audience segments
Ran continuous A/B testing across copy, creative format, and landing page variants — scaling winners within 48 hours of statistical significance

Phase 1 Results

-70% CPL reduction — from $300 to $90

+60% MoM increase in MQLs across all verticals

+82% CTR improvement through persona-aligned creative

+46% Site traffic lift driven by intent-targeted campaigns

+12% Pipeline revenue increase through ABM and funnel-aligned strategy

-60% Ad waste eliminated through granular UTM attribution across 200+ ad units

Phase 2: The Budget Constraint Challenge

In Q2 2024, Intel implemented a 40% budget cut across paid media. Performance targets remained unchanged: sustain a 15% increase in qualified lead volume and maintain CPMQL below $250. Most campaigns would retreat. We reengineered.

High-Intent Targeting to Eliminate Waste

Ruthlessly reallocated budget away from broad awareness and toward bottom-of-funnel, high-intent segments only
Layered first-party audience data with intent signals from Demandbase to identify accounts actively researching Intel's core categories
Used negative audience exclusions aggressively — removing any segment with historically low conversion rates

Content Upcycling for Creative Efficiency

Instead of producing new creative with reduced budget, systematically refreshed top-performing assets from previous quarters
Recut long-form video into high-performing short clips, repurposed whitepaper content into LinkedIn carousel formats, and adapted webinar content for retargeting sequences
Maintained brand voice and message consistency while dramatically reducing creative production costs

Value-Based Bidding & First-Party Data Activation

Shifted to value-based bidding strategies that weighted lead quality over lead volume — ensuring every dollar chased the highest-value conversions
Activated first-party CRM audience segments in paid channels to retarget existing pipeline and accelerate late-stage opportunities
Implemented daily budget pacing automation to ensure zero dollar was wasted on underperforming placements

Phase 2 Results — Doing More With Less

+80% Qualified lead volume growth QoQ — on 40% less budget

-60% Paid social CPMQL reduction — well below the $250 target

Targets Exceeded Goal was +15% qualified leads at <$250 CPMQL. Delivered +80% leads at 60% lower CPMQL — with 40% less to spend.

Broader Impact

+80% YoY MQL growth across Iron Horse's full enterprise portfolio — driven by playbooks developed on Intel

3+ Junior strategists mentored and trained on repeatable performance frameworks

Role & Context

Role: Senior Paid Media Manager at Iron Horse · Period: Sep 2022 – Jul 2024 · Verticals: Cloud, AI, Cybersecurity, Gaming · Budget: $1.5M+ quarterly

Channels: LinkedIn Ads, Meta Ads, Google Ads, Programmatic (DV360) · Tools: Demandbase, Tableau, Looker Studio, GA4, Google Tag Manager, Supermetrics, SQL

Key Takeaways

Granular attribution infrastructure is the foundation — without accurate data, optimization is guesswork
Persona-aligned messaging dramatically outperforms generic B2B creative at every funnel stage
Budget constraints force strategic clarity — removing low-ROI spend often reveals that less really is more
Value-based bidding tied to lead quality, not just volume, fundamentally changes what the algorithm optimizes toward
Content upcycling can match or exceed new creative performance at a fraction of the production cost
Mentoring and playbook documentation multiplies the impact of individual performance gains across an entire organization