DAY 1, 7 JUNE
17:15 - 18:00
ABOUT THE SPEAKER
Anton Naumenko is a hands-on Director of Engineering at thredUP leading R&D office in Kyiv, Ukraine with about 30 engineers. thredUP is the world's largest apparel resale marketplace. Anton has about 20 years of software products engineering experience. Prior to thredUP Anton has been a co-founder and CTO of Syndcode, digital products development agency, and Systems Architect at Nova Poshta. Last 4 years he has been involved in dozens of online and mobile peer-to-peer, mutlisided, managed marketplaces startups. He holds Ph.D. degree on Semantic Web from University of Jyvaskyla, Finland, and he breathes by technologies.
Speech: Data Driven Product Management at the Largest Online Apparel Resale Marketplace
thredUP is largest online apparel resale marketplace with millions of customers how are suppliers and buyers. Our major product is e-commerce marketplace website, however we also offer goody boxes, receiving secondhand clothing right to your door and selecting what you like and don't like without shipping fees or commitment to keep the clothes, brick and mortar retail stores, partner stores, listings on partner e-commerce websites, e.g. eBay. For all the products including physical retail stores we adopt data driven product development practices.
Data is first class citizen at thredUP to enable rapid cycling in Build-Learn-Scale iterations. Time to iterate defines the speed of innovation even with low success hit rate. We do embrace failure if learn along the way. Transparency in general is one of 6 core culture values. In data realm this results in open governance and democratization of data across entire organization.
Opening access to data is needed but not sufficient for fast speed data driven product development. Second secret sauce is the full-cycle product engineering mindset of small cross-functional teams. The talk covers the specifics and side effects of that.
Organization has open data, and the right structure and mindset of engineering teams, what next? The right experimentation environment including infrastructure and toolset should be in place. Augment this with the right KPIs and metrics to measure business impact, i.e. linking results of product experiments to company’s PnL and your are have true data driven product development.
We will share 2 case studies to exemplify the concepts we are discussing, The first case study is about cross converting suppliers and buyers at thredUP. The second case study is how we are approaching goal to increase seasonal assortment of the inventory.