Pallavi Modi is a product leader specialising in growth, retention, and platform enablement across large scale consumer ecommerce. She is currently Director of Product for Acquisition and Retention, AI and Tech Platforms at zooplus in Munich, where she leads a 160+ cross functional organisation spanning core web and mobile experiences and enterprise tooling. Her work focuses on scaling AI driven personalisation, propensity modelling and next best action decisioning, activating customer audiences through CDP powered segmentation and journey automation, and shifting teams towards modular, reusable component ownership. She also drives platform standardisation, integration quality, and cost efficient scaling for tens of millions of active customers.
Previously, Pallavi was Associate Director of Product at HelloFresh, leading loyalty and habit building initiatives and launching the Customer Wallet that laid the foundation for HelloFresh Rewards. Before that she held senior product roles at Flix, including Domain Product Owner (Group Product Manager), building marketplace products, partner self service capabilities, and experimentation programmes.
Upcoming Talks
28 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.
