Head of Product Analytics

ABOUT THE ROLE:

As a Head of Product Analytics you’ll work closely with Tide’s product teams to use data to drive product adoption. You’ll work within the product analytics team to use data to inform our collective understanding of users, their problems and thus inform product strategy.

This role will suit an individual that can operate with a high degree of independence and has hands-on experience of proactively working with the product community. You are an expert and constructive critique of digital products with strong views on data-driven techniques to improve adoption and engagement of various products & features. You will be working as a part of the product squad with a functional reporting into the Head of Product.

Some of the things you’ll be doing:

• Product Discovery - hypothesis driven deep dives (existing product usage data) to identify user problems, quantify size of the problem and highlight solution(s).
• Solution confidence - product experiments are a means to an end. They help us produce data to build confidence on the product & features we plan to invest in. You would be the product experimentation expert and would observe data, propose, design and analyse product experiments.
• Product and feature performance review - new features solve user user problems and drive product usage and thus adoption. You would work with product teams to identify & analyse various impact hypotheses behind new products and features and define measurable KPIs.
• User research - solving user problems helps us achieve commercial goals. You would identify opportunities, perform data deep dives (exploratory and hypothesis driven) to improve our collective understanding of user problems and assist working groups to focus on and prioritise high impact user problems.
• Goals to KPI translations - you would work with product managers to break overall revenue goals into business KPIs, identify impact hypotheses and convert into measurable product KPIs. You would work with analytics engineers to enable KPI reporting through visually speaking dashboards.
• Engagement to LTV correlations - engagement driven products and features have an indirect, unestablished impact on member longevity (commercially speaking LTV). We use data to establish this correlation and quantify the indirect impact. You would be required to perform custom analysis, using statistical methods to validate these correlations and assist product teams to prioritise investment on scaling product and features that have an indirect impact on engagement, longevity and thus LTV.
• Experimentation & product growth - you will operate with a high degree of user behaviour awareness (backed by consistent event data observation) and assist product managers by designing experiments to drive product adoption. You would use custom data analysis and statistical methods to analyse experiment results.
• Self Serve Product Analytics - partner with data, engineering, data prod