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Inderdeep Singh

Abhilasha D.

Affiliate Marketer

SUMMARY OF EXPERIENCE

β€’ Abhi has 3+ years of affiliate marketing experience at CJ Affiliate, where she manages nine enterprise programmes across retail and technology, supporting a portfolio that contributes to over $900M in annual revenue through publisher partnerships and commission strategy.


β€’ At CJ, she led the Nordstrom network onboarding end-to-end, co-built a machine learning publisher recruitment tool with the data science team, and automated outreach workflows using AI tools, reducing production time by 50%.


β€’ Before CJ, she spent 6 years at Yahoo across ad operations and B2B marketing, managing 500+ campaigns for 80+ advertisers and introducing zero-based budgeting that delivered $300K in savings across marketing programmes.

πŸ‘  What we loved about them

β€’ Builds systems and processes from the ground up: Something we found genuinely impressive about Abhi is her consistent instinct to build systems and structure wherever she lands. At Yahoo Business, she onboarded Airtable and Anaplan to fix a contract management problem that had been sitting unaddressed, then introduced zero-based budgeting that generated $500K in savings. At CJ, she noticed new hires were struggling to understand the marketing lifecycle, so she built a training program. Then she collaborated with the data science team to develop a machine learning tool for publisher recruitment. She spotted the gaps and filled them. 


β€’ Cares a lot about data integrity: When presented with the scenario of a publisher whose conversions had dropped to zero, her first question was whether the data was even being captured correctly. She worked through whether there could be a tag issue, a broken landing page, or a tracking problem before drawing any conclusions about performance. We believe this is the right first instinct in a role where inaccurate data can lead to flawed account decisions, and it gives us confidence she won't make reactive changes based on numbers she hasn't yet validated.


β€’ Deep ad-operations experience: Managing 500+ campaigns across Yahoo's DSP, Gemini, and BrightRoll means she understands how ad serving, tracking, and attribution actually work at an infrastructure level, so when something breaks in an affiliate programme, such as a tag firing incorrectly or traffic not being attributed to the right publisher, she's drawing on genuine technical experience rather than working through it from first principles. She also mentioned in the interview that her ad ops years gave her a strong grasp of how creative and ad copy directly affect campaign performance, which translates cleanly into affiliate work when she's advising on creative refreshes or diagnosing a drop in publisher-driven traffic. We feel this background also makes her a more credible voice in conversations with advertisers who come from a paid media world.

ℹ️  Things to be aware of

β€’ She has a 60 day notice period (can be negotiated to 30 days)


β€’ Her reason for changing roles is for more market exposure, more ownership, a better salary, and the chance to build things that genuinely last.

πŸ’‍♀️  Where he may need support

  • Although he lacks extensive experience with LinkedIn and Bing ads, his proficiency in Google ads suggests a high adaptability to new platforms.

πŸ‘©‍πŸ’»  Technical interview performance

Objective

​This 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€’ Programme auditing and performance diagnostics [8.5/10]: Abhilasha's audit instincts are solid and follow a logical order that comes from real practice. When she walked through her process for inheriting an existing program, she went straight to attribution setup, reversal tracking, and commission structure before touching publisher performance, which is the right sequence. She also thinks in terms of categorisation, segmenting publishers by revenue tier and funnel position, so she has a usable starting point for any activation or pruning decisions. The 120-affiliate scenario gave us a clearer view of how she operates under ambiguity. She mapped the active 15 by revenue contribution, factored in onboarding recency before deciding what to remove, and set clear thresholds (14 days for clicks, a month for revenue) before drawing conclusions. When asked about traffic being down across the board, she zoomed out first to consider macro factors using the post-COVID market shift as a reference point, then narrowed in to ad copy, landing pages, creative rotation, and A/B testing. We think her diagnostic instincts are well-calibrated for this level of experience, and she can hold the bigger picture alongside the detail without getting lost in either.


β€’ Publisher recruitment and relationship management [8/10]: Abhilasha has a practical and well-considered framework for recruitment that adjusts depending on where a program sits in its lifecycle. For a new program, she leans toward top and mid-funnel publishers to build visibility; for a scaling one, she tilts toward bottom-funnel partners like cashback, coupon, and comparison sites where purchase intent is already present. She also factors in audience demographics, geographic traffic sources, content category alignment, and whether competitors are already active on a given publisher, which gives her selection decisions a commercial logic that goes beyond pattern matching. On the outreach side, she described sending a comprehensive first email covering commission rates, available offers, seasonality calendars, logos, and creatives, with an open invitation to jump on a call. For a disengaged publisher, she tried email, then phone, then CPA reduction as a last escalation before removing them from the program. We feel her instinct to exhaust relationship channels before making structural changes is the right one, and her understanding that strong relationships can absorb short-term commission gaps reflects how affiliate partnerships actually work in practice.


β€’ Client communication and account ownership [9/10]: This is probably where Abhilasha feels most natural and most confident. She has a structured communication rhythm in place, including weekly reports on Mondays, monthly performance summaries, campaign period-over-period reviews, and QBRs where she pushes for budget conversations. The advice she carried from a former CMO, that no update is also an update, comes through in how she manages client expectations, and it's the kind of mindset that prevents small silences from turning into account friction. When handling the commission pushback scenario, she built her case using sale amount, conversion rate, average order value, and clicks to argue for situational commissioning on high-performing publishers, and she was willing to take that back to the publisher too, giving them a performance-linked path to a higher CPA rather than just delivering bad news. We believe what comes through most here is that she genuinely sees herself as a liaison between advertiser and publisher, and she keeps both sides in mind without losing sight of who she's ultimately accountable to. She's commercially grounded and comfortable having difficult conversations when the data supports her position.


β€’ Programme strategy and prioritisation [8/10]: When presented with the live scenario involving a sustainable lifestyle brand mid-migration, Abhilasha's thinking was organised and she understood the risks that come with a platform move. Her first instinct was to audit before the migration happened, and she correctly flagged content and editorial partners as the most vulnerable relationships to protect during the transition. She planned a structured communication rollout to keep publishers informed, flagged sub-network compliance as something to address early, and identified niche sustainability-aligned influencers as the right activation route for a brand with that kind of positioning. We feel her ability to read the brand's context and adapt her approach to its specific needs comes through well in this scenario. She also capped her first 30-day scope to understanding and audit rather than action, which is exactly the right call before making any structural changes to a program you've just inherited. Beyond the live scenario, her background in building a machine learning model for publisher recruitment and a Tableau dashboard for competitor offer tracking suggests she can operate above the day-to-day execution layer when given the space and tools to do so.

Areas of growth

β€’ Whilst she instinctively builds systems, she's aware that she occasionally ends up over-engineering processes in environments where speed and informality are the norm. It's a minor consideration, but one worth being aware of as she finds her feet in the role.


β€’ Some of her reporting cadence reflects an enterprise context with larger internal teams, and in a leaner agency setup she'll need to adapt to faster, less formal communication rhythms depending on the client. She also acknowledged that her natural directness can sometimes read as bluntness, which in client-facing settings is worth being conscious of, particularly in higher-stakes conversations where delivery and tone carry as much weight as the substance of the message.

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