ВеликобританияProduct Analytics & Experimentation Lead
1 нед. назад
ВеликобританияLeadHybrid
product_analyticsdata_analysisexperiment_designa_b_testing
Lead product analytics and experimentation to improve digital customer experiences.
О компании
- We’re the Group – home to , 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. 🌙🐷 Product Analytics & Experimentation Lead | 📍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 Product Analytics & Experimentation Lead , you'll help shape how millions of customers interact with 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 custo
Обязанности
- 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.
Требования
- 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.
Будет плюсом
- 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.