Mixed-methods research across two countries, 119 participants
Gen Z has grown up with more advertising than any previous generation and with more tools for avoiding it. For a major social media platform trying to make its ad product feel less like an intrusion and more like a natural part of the experience, the question wasn’t just what Gen Z disliked about ads. It was what would actually make them better. What does a more ideal online ad experience look like to the cohort most allergic to traditional marketing?
The research needed to work across two very different markets (the US and India) where platform behavior, cultural attitudes toward advertising, and economic contexts diverge in meaningful ways. A single-market study would have missed that complexity entirely.
The research program was designed as a three-phase mixed-methods study, with each method building on the last. I led the research alongside one other researcher, with a design lead managing the overall program.
A mini diary study (n=21) opened the program; participants documented their ad experiences in context, over time, capturing what made an encounter feel positive or negative in the moment rather than in retrospect. This gave us naturalistic data that retrospective interviews alone would have missed: the small friction points, the moments of unexpected relevance, the reflexive swipe-past behaviors.
In-depth interviews (n=12) went deeper, exploring how participants experienced ads across multiple platforms and what they imagined a genuinely better experience might look like. These sessions moved beyond behavior into aspiration — valuable territory for a platform trying to improve rather than just optimize what it already had.
A quantitative survey (n=98, split US/India) then tested whether the themes emerging from the qualitative work held at scale, building confidence where patterns were consistent and surfacing divergence where US and Indian respondents differed meaningfully. Nine ad experience attributes were evaluated: relevance, trustworthiness, brevity, discoverability, native integration, content relationship, emotional versus informational emphasis, action ease, and social connectivity.
The gap between what Gen Z said they wanted from ads and what they said they were actually getting was wide, and it was consistent across both markets. Brevity and trust mattered most. Connection to friends mattered least. — Research finding
Data visualization was a meaningful part of the output, where I used rawgraphs.io to produce sentiment maps of how participants described the platform’s ads, segmented by market. The visual contrast between US and India responses was immediate and legible in a way that tables of percentages weren’t.
Importance ratings across 9 ad attributes, combined and by market
Sentiment bubble map built in rawgraphs.io: positive vs. negative descriptors
The research delivered a clear, evidence-grounded picture of the ideal Gen Z ad experience and the significant gap between that ideal and what the platform was currently delivering. Key findings showed that brevity and trust were the top-ranked attributes globally, while social connectivity ranked lowest. Relevance landed in the middle, suggesting that targeting alone is not sufficient — a short, trustworthy ad outperforms a targeted but long or opaque one.
The US/India split revealed meaningful divergence: Indian participants rated nearly every attribute as more important than US participants, suggesting higher baseline expectations and greater openness to ads that earn engagement. This cross-cultural nuance directly informed platform strategy for two distinct markets rather than a single averaged recommendation.
Participants across three methods — diary study, in-depth interviews, and survey — providing a layered, triangulated picture of Gen Z’s ad experience.
Distinct market profiles (the US and India) with clear, actionable differences in how participants experienced and prioritized ad attributes.
Trust and brevity ranked as the highest-priority attributes globally, ahead of relevance, native integration, and discoverability.
Sentiment maps built in rawgraphs.io made the emotional texture of participant responses immediately legible, highlighting positive versus negative descriptors, by market.