Pallavi Modi is a product leader focused on building customer-centric growth engines at scale. As Director of Product at zooplus in Munich, she leads Acquisition & Retention, AI, and Tech Platforms across a 160+ cross-functional organisation spanning product, engineering, data, and platform capabilities.
Her work centres on connecting customer needs with scalable execution — from AI-driven personalisation and journey orchestration to modular platform capabilities that help teams deliver better experiences, faster. She is particularly passionate about helping organisations move beyond technology-first thinking and align teams, ways of working, and decision-making around real customer outcomes.
Before joining zooplus, Pallavi held product leadership roles at HelloFresh and Flix, where she led initiatives across loyalty, marketplaces, experimentation, and self-service platforms.
Upcoming Talks
29 May 2026
Sam Bradley brings a trust-first playbook shaped by years of work across Expedia, Stitch Fix and PayPal, where the cost of “getting it wrong” shows up as hesitation, drop off and long-term brand damage. His view: trust needs restraint. Minimise data use, add hard guardrails, and treat “creepy” as a measurable risk.
Pallavi Modi (zooplus) takes the opposing stance: trust needs context. Personalisation does not fail because it is “too much data”, it fails because it is the wrong data at the wrong moment. When teams confuse personalisation with segmentation, they start guessing intent (discounts, nudges, offers) instead of understanding context, journey stage and real-time signals. The result is not just lower conversion, it feels like “you don’t know me”.
Together, they debate where personalisation genuinely helps people and where it quietly becomes manipulation, especially when money and identity are involved.
Outcomes
- Put trust metrics alongside conversion so you can spot erosion before it hits revenue.
- Separate segmentation from true context-driven personalisation, and diagnose when “relevance” becomes assumption.
- Set clear guardrails for AI recommendations, offers, and targeting in high-trust, money-adjacent journeys.
- Align product, growth, legal, marketing and research on who owns personalisation, and what “too far” actually means.
