Breaking LinkedIn Dependence: How Crossover Diversified Talent Acquisition with Google & X Ads
Crossover is the world’s largest database of skilled remote talent, connecting professionals with high-paying roles that rival Silicon Valley compensation. The company specializes in sourcing and assessing software engineers, particularly AI-powered engineers, through a rigorous recruitment funnel that includes cognitive, skills-based, and real-world evaluations. This unique process allows them to identify top-tier talent for global employers while ensuring both quality and performance.
Despite their strong positioning, Crossover faced critical challenges with their acquisition strategy. At the time of engagement, 99% of their applicant pipeline came exclusively from LinkedIn Job Ads, largely due to the platform’s streamlined “Easy Apply” feature. While this provided scale, the dependence on LinkedIn created two major risks: rising CPCs were making campaigns increasingly unsustainable, and over-reliance on one platform limited scalability and exposed the company to volatile costs.
Additionally, unlike LinkedIn, other channels, such as Google and X required candidates to complete applications directly on Crossover’s website. This additional friction risked reduced conversion rates, making campaign design and user experience optimization critical. At the same time, Crossover was competing against established global recruitment firms such as Turing, Toptal, and BairesDev, all of whom were aggressively investing in PPC channels.
From 99% LinkedIn Reliance to Multi-Channel Recruitment: Crossover’s PPC Transformation
Crossover’s challenge was therefore twofold: reduce dependency on LinkedIn by diversifying into new ad platforms, while maintaining lead quality and achieving cost-effective conversions across global regions. They also needed to navigate geographic complexities, avoiding high-fraud areas such as Nigeria, carefully managing high-cost Western markets, and maximizing performance in the APAC, LATAM, and Eastern European regions.
The Goals
Approach
- Conducted in-depth audits of existing campaigns, identifying inefficiencies such as broad match dependencies, generic ads, and poor geographic segmentation.
- On Google Ads, introduced advanced keyword research focused on trending AI engineer terms, long-tail job-specific queries, and geo-targeted keywords.
- Implemented Dynamic Search Ads (DSA) with structured job feeds, ensuring ads dynamically matched relevant engineering roles.
- Built RLSA campaigns to retarget job seekers who visited Crossover’s career pages, paired with Google Lead Forms to simplify application capture.
- Integrated campaigns with Crossover’s CRM via Google Ads API, enabling near real-time access to application data.
- On X Ads, shifted from sales-focused campaigns to a phased funnel strategy, starting with awareness and consideration before progressing to conversions.
- Organized campaigns region-wise, with refined targeting of the 25–34 demographic that demonstrated highest responsiveness.
- Leveraged lookalike audiences based on qualified applicants, using carousel and video creatives for awareness, and static ads for conversions.
- Tested emerging X Hiring Beta features for direct job listings and in-app applications, while running ongoing creative A/B testing across both platforms.
The Results
- Google Ads delivered 92 total conversions across multiple engineering specialties.
- X Ads generated eight qualified applications at an average CPL of $49.60, proving viability as a supplemental channel.
- Geographic insights confirmed India, APAC, and Eastern Europe as the strongest performers, with cost-effective acquisition metrics.
- Successfully reduced dependency on LinkedIn from 99% single-channel reliance, establishing a multi-platform acquisition strategy.
- Achieved a $4.00 average cost per application on X Ads, competitive for initial exploration into new talent pools.
- Campaign structure now supports scalable, diversified hiring pipelines across multiple markets, with lower risk and improved long-term ROI.