Lead Product Analyst

Job description

We’re the Moonpig Group – home to Moonpig, Greetz, Red Letter Days and Buyagift – and we’re on a mission to make people feel loved, celebrated and remembered. Whether it’s a card that gets them laughing out loud or a gift that makes their day, we help people stay close, no matter the miles. We’re proud to be leading the online gifting revolution, with brilliant products, clever tech and a whole lot of heart. Our platform makes it easy to create moments that matter – packed with personal touches and delivered with care. We’re not just about selling cards or gifts – we’re here to spread joy, spark smiles and make every celebration feel extra special. And with values that guide how we work and support one another, we’ve built a place where people (and ideas) can truly thrive. If you’re looking to make an impact, bring your spark and be part of something meaningful – we’d love to have you on the team. 🌙🐷 ### **Lead Product Analyst** | 📍London – Hybrid (1–2 days per week) | 💰Competitive Salary + Benefits ### About the Role Are you passionate about turning customer behaviour into better digital experiences? As our **Lead Product Analyst**, you'll help shape how millions of customers interact with Moonpig by uncovering insights that drive smarter product decisions. This is a senior individual contributor role where you'll partner closely with Product, Data and Engineering teams to understand customer behaviour, identify opportunities to improve the customer journey, and help teams measure the impact of the changes they make. You'll play a key role in building confidence in our product metrics, improving experimentation practices, and enabling teams to make evidence-based decisions. If you enjoy solving complex problems, translating data into clear recommendations and helping others learn from customer behaviour, we'd love to hear from you. ### Key Responsibilities: - Partner with Product teams to understand customer journeys, product questions and opportunities to improve the customer experience. - Conduct exploratory behavioural analysis using techniques including funnel, journey, cohort, segmentation and retention analysis. - Translate analytical findings into clear, practical recommendations that help teams prioritise what to improve next. - Define, maintain and govern product and behavioural metrics to ensure consistent, reliable measurement across teams. - Validate product tracking and data quality, working closely with Data and Engineering colleagues to resolve issues. - Provide guidance on experimentation best practice, including hypotheses, success metrics, test validity and interpretation of results. - Develop repeatable frameworks, documentation and resources that enable consistent measurement and learning across Product teams. - Build confidence across teams in using behavioural data to inform product decisions. - Collaborate with cross-functional partners to champion strong analytical thinking and customer-focused decision making. ### About You: - Significant experience in Product Analytics, Customer Analytics or a similar role within a digital product or e-commerce environment. - Strong hands-on SQL skills with the ability to investigate data, challenge assumptions and communicate findings clearly. - Experience exploring customer behaviour through funnel, journey, cohort, segmentation or retention analysis. - Proven ability to define, maintain and govern product metrics to improve the quality and consistency of measurement. - Experience supporting experimentation through structured testing, robust measurement and thoughtful interpretation of results. - Excellent communication skills with the ability to explain complex analysis in a clear and practical way. - Strong collaboration skills and experience partnering with Product and cross-functional teams. - Experience creating analytical frameworks, documentation or resources that help teams measure products consistently. - Comfortable working through ambiguity while remaining focused on customer behaviour and product outcomes. ### Nice to Have: - Working knowledge of Python. - Experience with product analytics platforms such as Mixpanel, Amplitude or similar. - Familiarity with Snowflake, Tableau or comparable data platforms. - Experience using causal inference techniques such as regression, matching, difference-in-differences or uplift modelling. - Experience evaluating recommendation, personalisation or AI-enabled product features. - Experience sharing analytical knowledge through coaching, documentation or communities of practice.