
Gaurav B.
Performance Marketing Expert
SUMMARY OF EXPERIENCE
β’ 7+ years of performance marketing experience across agency environments, currently managing YouTube's in-house marketing platforms at Media Monks whilst specialising in Meta advertising with Facebook Certified Media Buyer and Planner credentials.
β’ At Merkle Sokrati (Dentsu), Gaurav led a team of 7 media buyers managing βΉ40 crore monthly spends, drove quarterly client calls linking digital strategies to business KPIs, and contributed to org-level strategy whilst training teams. He achieved remarkable results including improving Aditya Birla Capital's lead volume from 2K to 23K with 5x better CPL.
β’ During his stint at BrightChamps, he restructured Meta account setups to scale two businesses and three products by 3x whilst improving ROAS by 250%, and reduced TenderCuts' CAC from βΉ2.2K to βΉ1K with 30% higher scale.
π What we loved about them
β’ Meta platform mastery for lead generation and conversion campaigns β This is clearly his strongest suit based on multiple data points. His Facebook certifications combined with the Aditya Birla Capital achievement (2K to 23K leads with 5x better CPL) and BrightChamps results (250% ROAS improvement whilst scaling 3x) demonstrate he genuinely understands Meta's algorithm and can structure campaigns for both volume and efficiency.
β’ Explains complex technical concepts in accessible ways without condescension β Throughout the interview, whether discussing attribution models, CBO mechanics, or pixel troubleshooting, he consistently translated technical details into clear explanations that showed deep understanding rather than hiding behind jargon β exactly what's needed when communicating with clients and cross-functional teams.
β’ Refreshingly honest and self-aware about his strengths and limitations β When we pushed him on automated rules, he didn't deflect or make excuses but candidly explained his past struggles with Meta's system while acknowledging it might have improved, showing he's open to revisiting approaches.
β’ Takes genuine ownership and pride in his work beyond just clocking hours β His admission that he monitors campaigns hourly even after office hours because he "goes crazy behind numbers" and wants to see how his planning plays out reveals someone who's intrinsically motivated by results.
βΉοΈ Things to be aware of
β’ He doesn't have a notice period and is available immediately.
πβοΈ Where he may need support
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Although he lacks extensive experience with LinkedIn and Bing ads, his proficiency in Google ads suggests a high adaptability to new platforms.
π©π» Technical interview performance
Objective
βThis candidate was invited to a 60-minute follow-up interview to assess their technical capabilities in more detail. During this interview, we assessed their critical-thinking skills, technical expertise, and overall conversational skills.
Technical abilities
β’ Campaign strategy and planning [9/10]: Gaurav demonstrates exceptional strategic maturity in his campaign planning approach. His systematic use of customer data to inform every decision - from geo-targeting to budget allocation - shows he truly understands performance-driven strategy. The proportional budget splits (48% to US based on 5,000 customers, identifying Switzerland's 45 ROAS despite smaller volume) reveal sharp analytical thinking. His phased approach is particularly sophisticated - building audiences through lead generation before converting them maximises efficiency and avoids burning budget on cold traffic. The three-tier audience structure with proper exclusion hierarchies prevents waste and ensures each campaign targets genuinely new prospects.
β’ Channel expertise [9/10]: Gaurav's Meta platform mastery is outstanding, as seen with how he handled the iOS 14 crisis - where he immediately implemented CAPI, Aggregated Events Management, and pixel prioritisation - showing he can navigate serious technical complications under pressure rather than just knowing the platform superficially. His direct Meta rep relationships for early platform updates give him genuine competitive advantage that most practitioners don't have, which means he's often ahead of changes rather than scrambling to react. His nuanced understanding of CBO versus ABO trade-offs reveals sophisticated thinking about auction mechanics where he doesn't dogmatically prefer one approach but genuinely understands when each is optimal based on campaign objectives. The layering of behavioural targeting onto interest segments to filter for high-net-worth individuals demonstrates advanced sophistication beyond basic targeting, and his campaign nomenclature system shows deep thinking about structuring accounts for maximum analytical clarity.
β’ Data analysis and optimisation [9/10]: Gaurav's analytical approach is comprehensive and methodical, with his practice of cross-referencing Meta with Google Analytics using UTM parameters demonstrating proper multi-source validation rather than blind trust in single platforms. The creative testing methodology he's developed - testing 10-12 variants to identify patterns, then running formal A/B tests on winners to build a documented library - shows systematic optimisation beyond random experimentation whilst creating genuine institutional knowledge. His ability to explain attribution discrepancies between first-click and last-click models to clients without getting defensive reveals mature analytical communication, which is rare.
β’ Conversion rate optimisation [9/10]: Gaurav demonstrates strong understanding of optimisation mechanics across the full funnel, with his clear grasp of CBO versus ABO strategies showing he understands how different structures fundamentally influence learning efficiency and conversion outcomes. His point about CBO allowing the algorithm to find converting audiences during learning phases whilst ABO forces spend regardless of performance really captures the core trade-off between approaches. The way he structures exclusions by removing retargeting audiences from prospecting campaigns shows systematic thinking about conversion efficiency rather than letting campaigns compete against each other, and his behavioural layering approach with frequent international travellers specifically optimises for conversion likelihood by filtering for prospects with demonstrated purchase intent and financial capacity.
β’ Reporting and communication [9/10]: We found his reporting capabilities to be exceptionally thorough, which becomes evident through his detailed nomenclature system that enables granular analysis by platform, audience, age, gender, and placement without relying on native breakdowns that don't always capture what you actually need. His ability to explain complex attribution discrepancies without creating confusion shows mature communication skills combined with technical fluency, and the way he collaborates with technical teams by translating marketing terminology into language developers understand demonstrates true cross-functional ability.
Areas of growth
β’ Developing more detailed scaling frameworks around budget pacing curves and efficiency thresholds when increasing spend 3-4x in compressed timeframes would elevate his skills further.
β’ Building formal statistical frameworks would strengthen his foundation - specifically around determining when performance differences are statistically significant versus random variance. Incorporating incrementality testing or holdout groups would add another analytical dimension beyond last-click attribution.