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‘The future designer is the one who frames better’ – in conversation with Vidisha Hegde, Spotify >
by Madanmohan Rao [November 02, 2025]
In this series of interviews, innovation platform MXR.world (‘mixers across the world’) showcases design leaders speaking at the upcoming DesignUp 2025 conference in Bengaluru (https://25.designup.io). In our earlier interviews, we featured design strategist Arvind Lodaya, NetBramha founder Aashish Solanki, Karya designer Khushboo Agarwal, and arts-science curator Madhushree Kamak.
In this interview, we feature Vidisha Hegde, Spotify’s Head of Insights – Data Science & User Research, across India, the Middle East, and Africa. With over 16 years across strategy, data science, and user research, her role is to bring clarity to complex problem spaces. Shehas held earlier roles at KPMG, Quicksand Design, and Swiggy.
Positioned at the intersection of design, technology, and business innovation, the ninth edition of DesignUp celebrates the strategic and human impact of design in shaping products, services, and organisations. It explores how design culture and ecosystems drive innovation, inclusion, and transformation across industries.
At Spotify, Vidisha helps cross-functional teams align on what really matters—turning ambiguity into sharp, insight-driven decisions. She joins us in this exclusive interview on trends in data-driven design, attaining clarity for decision making, examples of how Spotify’s data strategy, and advice for aspiring design entrepreneurs.
Madan: What are the top three emerging trends you see in data-driven design today?
Vidisha: One trend I read about and would like to see more of is conversational data, where insights talk back in real time. Whether through AI copilots or insight systems embedded in design workflows, data is starting to behave less like a report and more like a partner in the room.
A second is where I feel the next wave of design is not just about users or systems, but the spaces between them the invisible micro-moments when people switch context, emotion, or intent. Data is helping us map these states, eg. how music moves with mood, or how payment behaviour changes with signal strength. It is not static UX; it is fluid experience design.
Lastly, data storytelling will increasingly become a design skill. The more data we have, the more important it becomes to interpret it with human sensitivity. The future belongs to teams who can integrate behavioural science, ethnography, and analytics to understand why behind the number - and also have the visual clarity to make it actionable
Madan: In a world of data overload and break-neck speed, how does one develop clarity for decision-making?
Vidisha: Clarity doesn’t come from more information, it comes from framing better questions, synthesisng – not summarising – and spending more time on the design of your decision.
I find the most effective teams don’t chase every data point; they pause to align on what problem truly matters. They structure ambiguity through frameworks, create shared language between disciplines, and translate complexity into simple, human truths.
This is in fact the theme of my workshop on Monday, on the topic of Framing What Matters: A Blueprint for Insight‑Led Problem Solving. In fast-moving contexts, clarity is less about knowing everything and more about knowing what to ignore.
Madan: How do you handle the issues that arise when data-driven evidence contradicts an expert’s opinion?
Vidisha: When data and expertise disagree, I see that contradiction as a signal not conflict and that we are looking at the problem from different altitudes. The key is to make the disagreement visible and frame it as a hypothesis gap.
Then test whether the data is incomplete, or is the expert relying on existing biases? Bring both back to the same table, revisit the question, and reframe. The truth often lies in the intersection.
The goal isn’t to pick sides, but to use both to refine our understanding to evolve from 'who’s right' to 'what’s right.'
Madan: What are three outstanding examples of how Spotify has leveraged data for a better music experience?
Vidisha: Discover Weekly – this is a weekly personalised playlist with about 30 new songs based on a user's listening habits and saved tracks. Always changing and always you!
Spotify Wrapped – a huge annual cultural moment for Spotify where everyone's data turns into collective celebration of their music listening.
Algotorial playlists and mixes – where editorial human curation meets algorithms.
Madan: What are your three tips or words of advice for aspiring 'design entrepreneurs' today?
Vidisha: I will focus on one, and that is build clarity as your currency. Whether you’re pitching investors, designing for a million users, or leading a team, clarity is the rarest and most valuable thing you can offer. Focus on making your idea and thoughts sharper, well-framed and well-told.
And if there is one thing I have learned across insights, strategy, and design is that clarity is a collective act. No single person 'has' the answer. But when data, design, and decision-makers come together around a shared frame of what truly matters, the path becomes far more clear.
Madan: How do you view GenAI – as a serious challenge for designers, or an indispensable tool? How does one upskill oneself in this context?
Vidisha: AI won’t replace designers but it will replace those who design without reflection. The real edge now is in asking sharper questions, curating meaning, and keeping the human layer intact.
As for upskilling, I think the biggest skill is still curiosity. Learn how these models see the world, what data they’re trained on, and what biases they inherit. The future designer is the one who frames better.
Madan: Any other parting comments or remarks you would like to make?
Vidisha: We live in a time where anyone can build something, but not everyone builds something that matters. The difference is in how we frame problems, listen deeply, and stay curious long after the first draft.
So my only advice: keep listening, keep reframing, keep creating. The world needs more thoughtful makers!
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