Technical abilities

• Campaign strategy and planning [7.5/10]: Himanshi demonstrates solid strategic thinking when structuring campaigns aligned with business objectives. Her rationale for allocating 60% to Shopping campaigns based on control and visual appeal shows practical judgement, as does separating branded and non-branded search campaigns. Building on this foundation, her approach of starting with Maximize Clicks before moving to Target ROAS indicates she understands campaign maturity and data requirements. She's particularly strong at drafting detailed strategies that account for product scope and categories, which is evident in how she broke down Shopping campaigns by priority levels and product groups. We appreciated that she understands different campaign purposes - Shopping for high-intent visual browsing, Search for direct intent, Display for remarketing. This understanding extends to her point about balancing CAC at a blended level using lower-cost remarketing, which shows she thinks about portfolio effects rather than isolated performance. She also recognises when strategy needs seasonal adaptation for business priorities like Black Friday, demonstrating flexibility in her planning approach.

• Channel expertise [8/10]: Himanshi shows strong Google Ads platform knowledge with genuine depth in functionality. She's well-versed with the dashboard and comfortable navigating campaign types from Shopping to Search to Display. Her explanations of Shopping campaign controls through visual elements and priority settings demonstrate operational experience, which is further evidenced by her understanding of remarketing mechanics like excluding active users, targeting cart abandoners, and creating audience segments in GA4 for sophisticated targeting. This hands-on experience comes through clearly in how she discusses setting up campaigns, managing ad groups, applying negative keywords, and adjusting bids. Moreover, her comfort with bidding strategies and knowing when to transition between them indicates practical platform knowledge rather than theory. All of this points to someone who's clearly managed campaigns at scale and understands the day-to-day mechanics of the platform.

• Data analysis and optimisation [7/10]: Himanshi efficiently approaches data collection, consistently referencing full funnel metrics from impressions through conversions. She reads relevant numbers well and focuses on metrics that matter - ROAS, CAC, and LTV. Complementing this focus, her approach of making granular changes and waiting 7-14 days shows she understands algorithm learning periods. She also demonstrates analytical thinking by recognising that drop-offs stem from external factors like competition or internal issues like app problems. Her example of testing brand match keyword removal further shows comfort running experiments and monitoring impact systematically. This carries through to how she clearly tracks funnel performance and investigates when metrics deteriorate to identify what's driving changes.

• Conversion rate optimisation [7/10]: Himanshi has a strong understanding of navigating ad sets, campaigns, and bidding strategies to optimise winning combinations. She clearly identifies what's working and shifts budget toward better performers. Taking this further, her discussion of creating different messaging for women buying gifts versus men buying for themselves shows she thinks about user psychology. She also understands creative testing parameters and uses competitor performance as an evaluation metric, which means she's thinking about relative performance not just absolute numbers. This mindset carries through to her remarketing approach with tailored messaging for different segments, demonstrating CRO thinking - cart abandoners need different nudges than registered non-purchasers. She talks about identifying funnel drop-offs and investigating root causes, and her point about leveraging the NFL endorsement strategically for different use cases shows she optimises creative based on customer motivation rather than taking a one-size-fits-all approach.

• Reporting and communication [7.5/10]: Himanshi communicates clearly and creates summarised reports highlighting key metrics stakeholders care about. She understands different audiences need different detail levels - presenting ROAS, CAC, and LTV to leadership whilst drilling into funnel details when problems arise. This flexibility extends to her experience with daily sync-ups and weekly reviews, showing comfort with regular reporting cadences. She also has good grasp of GA4 dashboard and familiarity with various client-specific tools, suggesting she adapts to different systems well. What's particularly positive, and perhaps most encouraging, is her genuine keenness to learn new tech enablements. Throughout the interview, she was transparent about assumptions and data gaps, indicating honest communication rather than overselling. She also explained her reasoning in ways that were easy to follow and asked clarifying questions when needed, which are valuable traits for client-facing work.

Areas of growth