CUSTOMER INSIGHTS ANALYST Hush is an ambitious and distinctive fashion brand, with plans to double the business over the next few years.
Founded 21 years ago, we are now established as one of the UK's leading online fashion retailers.
We employ around 130 employees across head office and retail, creating and selling a beautiful range of women's clothing and accessories characterised by effortlessness, simplicity and a laidback sense of style.
Despite the challenges to the retail industry, Hush has continued grow – and our company culture still reflects our entrepreneurial roots and relaxed aesthetic.
We love hard-working and talented people with a can-do attitude and a passion for what they do.
THE ROLE We are looking for an experienced and detail-oriented Data Analyst to join our analytics team.
This role involves unlocking insights from customer, marketing, and site performance data, and providing actionable recommendations that will drive growth and optimise the customer journey.
You will work closely with cross-functional teams and senior leadership, helping to shape strategies based on data.
A strong background in D2C eCommerce , Advanced Google Analytics , and SQL is required, with the ability to provide training and mentorship across teams to support self-serve analytics.
RESPONSIBILITIES Customer & Marketing Analytics: Perform deep dives into customer behaviour and marketing performance, focusing on segmentation, customer lifetime value, churn analysis, and conversion optimisation.
You will use these insights to inform acquisition and retention strategies and optimise channel spend.
Advanced Google Analytics & Event Tracking: Manage and analyse data from Google Analytics , setting up and optimising event tracking to measure user behaviour across the site.
Experience with event measurement (e.g., page views, clicks, conversions) is critical for optimising the digital experience.
Attribution Modelling & A/B Testing: Implement multi-touch attribution models to evaluate the effectiveness of marketing channels.
Lead A/B testing initiatives for marketing and support CRO manager, ensuring rigorous statistical analysis to derive meaningful insights that improve customer engagement and drive sales.
Data Reporting & Dashboards: Build and maintain robust reporting frameworks using BI tools such as Tableau or Power BI, creating dynamic dashboards for marketing, product, and finance teams.
You will ensure stakeholders have access to real-time data for informed decision-making and performance tracking.
SQL & Data Management: Use advanced SQL to extract, clean, and manipulate large datasets from various sources.
Your SQL expertise, including the use of window functions, will support ad-hoc analysis, reporting, and ongoing optimisation projects.
Cross-Functional Collaboration: Work closely with marketing, product, e-commerce and finance teams to ensure that data-driven insights align with business goals.
You will collaborate on key initiatives, such as customer journey mapping, product performance analysis, and budget optimisation.
Training, Upskilling, and Mentorship: Provide basic training and guidance to help cross-functional teams (e.g., marketing and product) use analytics tools to self-serve data for their needs.
Upskill and mentor junior team members and stakeholders to foster a culture of data-driven decision-making across the business.
Data Storytelling & Senior Leadership Presentations: Synthesise complex data into clear and actionable insights that can be presented to senior leadership.
Develop and present compelling narratives around customer behaviour, marketing effectiveness, and business performance to guide strategy.
Continuous Improvement & Innovation: Stay up-to-date with the latest trends in eCommerce and Marketing analytics and propose innovative approaches to data analysis, ensuring the company remains competitive in the premium fashion space.
THE PERSON D2C eCommerce Analytics: Proven experience in analysing and optimising D2C eCommerce performance.
You must have a strong understanding of customer journey metrics and the unique challenges of selling directly to consumers online.
Advanced Google Analytics: Deep knowledge of Google Analytics, including event tracking and custom reporting, to monitor and measure user interactions on the website and improve the overall digital experience.
Advanced SQL Skills: Expertise in SQL, including the ability to write complex queries using window functions, joins, and subqueries.
You must be comfortable working with large datasets from relational databases, ensuring data accuracy and efficiency.
BI Tools: Proficiency in BI tools such as Tableau, Power BI, Looker or similar to create dashboards and visualisations for various teams, ensuring that data is accessible and actionable.
Attribution & A/B Testing: Strong understanding of attribution modelling and statistical principles behind A/B testing.
Experience designing, executing, and analysing experiments to optimise conversion rates, marketing spend, and user experience.
Cross-functional Collaboration & Training: Experience working across teams to align data insights with business goals.
Proven ability to provide training, mentorship, and upskilling for non-technical teams to foster self-service analytics.
Data Storytelling & Communication: Strong verbal and written communication skills, with the ability to translate complex data into clear, actionable insights for senior leadership and stakeholders.
Strong ability to work collaboratively across teams, balancing the needs of marketing, product, and finance.
Excellent problem-solving skills, with the ability to turn business challenges into analytical opportunities.
High attention to detail and organisational skills to manage multiple projects simultaneously and ensure accuracy.
Passion for data and a proactive approach to staying updated with the latest trends and tools in eCommerce analytics.
Fashion Industry Knowledge (desired but not essential): Previous experience in the fashion industry is a bonus, but a passion for premium fashion and understanding consumer behaviour is essential.
Additional Skills (desired but not essential): Experience with Python or R for advanced data analysis is a plus, as is knowledge of advanced statistical techniques to improve predictive modelling capabilities.
We are committed to fostering diversity, equity and inclusion in everything we do.