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- Tasks: Analyse user behaviour and trends to enhance our ticket marketplace experience.
- Company: Twickets is the UK's top ticket marketplace, promoting fair resale for events.
- Benefits: Enjoy remote work flexibility and a competitive salary of up to £50,000.
- Why this job: Join a dynamic team driving data-driven decisions in a fast-growing company with big-name partners.
- Qualifications: Bachelor’s degree in Data Science or related field; 2+ years in web analytics required.
- Other info: Experience with AI tools and e-commerce environments is a plus.
The predicted salary is between 36000 - 60000 £ per year.
About Twickets: Twickets is the UK's leading ticket marketplace. We work with music artists, comedians, festivals, venues, theatres and sporting organisations to bring fair ticket resale to their events, by capping prices at the original face value. Partners include Oasis, Foo Fighters, Kylie and Coldplay. In the past 12 months alone 8m unique visitors have used our platform, with revenue growing at over 30% year on year.
Job Summary: We are looking for a Web Data Analyst to join our growing team and drive data-driven decision-making for our online marketplace. This role involves analysing and interpreting key user behaviours and trends on our platform, identifying actionable insights to improve user experience and satisfaction, optimising site performance and user flow to increase conversions and engagement, and segmenting our audience for more personalised and effective marketing campaigns. You’ll also develop dashboards and reports for ongoing monitoring and decision-making, as well as supporting partners.
The ideal candidate will have experience in creating and implementing data strategies, reviewing current data setups to ensure robust data collection, proposing scalable solutions, and building tools to support both data strategy and advanced analytics. Experience leveraging AI or machine learning tools for predictive analysis, personalisation, or automation is a strong plus.
Key Responsibilities:
- Business Intelligence Dashboards
- Build and maintain user-friendly dashboards to visualise key metrics and trends
- Enable real-time tracking of KPIs such as ticket sales, average transaction value, repeat user rate, buyer seller conversions, and marketing campaign performance
- Develop partner-friendly dashboards to visualise partnership success
- Identify unusual activity patterns that may indicate fraudulent transactions or policy violations
- Incorporate AI-driven insights or anomaly detection methods to improve fraud monitoring and trend forecasting
- Data Analysis
- Utilise statistical and AI-enhanced models to analyse user behaviour and forecast engagement trends
- User Behaviour Analysis: Track and analyse user interactions on the marketplace, including buyer and seller activity, cart abandonment, and checkout flow
- Conversion Optimisation: Identify drop-off points in the user journey and provide data-backed recommendations to improve conversion rates
- Traffic & Engagement Monitoring: Analyse website traffic sources (organic, paid, referral, direct), monitor bounce rates, and assess the effectiveness of marketing campaigns
- Customer Segmentation
- Use data to segment users by behaviour, demographics, geography, and preferences
- Customer Lifetime Value (LTV) Analysis: Segment users based on engagement, spending habits, and retention to predict LTV and identify high-value customers
- Explore predictive modeling or AI-powered clustering techniques to deepen segmentation accuracy
- A/B Testing & Experimentation
- Design and analyse A/B tests to optimise homepage layouts, product pages, search filters, and checkout processes
- Leverage AI or automation tools to streamline experiment design and result analysis
- Marketing Insights and Targeting
- Use insights to design data-driven marketing campaigns
- Recommend strategies for email campaigns, retargeting, etc.
- Work with AI-enabled marketing platforms to personalise user outreach and automate campaign targeting
- Data Quality & Tracking
- Ensure accurate implementation of tracking tools (Google Analytics, Google Tag Manager, Cookie Bot) and troubleshoot any data inconsistencies
- Manage and maintain incoming data feeds
- Support integration of AI or ML models into tracking and reporting infrastructure when applicable
Required Skills & Qualifications:
- Bachelor’s degree in Data Science, Business Analytics, or a related field
- 2+ years of experience in web analytics, preferably within an e-commerce or online marketplace environment
- Strong proficiency in Google Analytics (GA4), or similar web tracking tools
- Hands-on experience with SQL for data extraction and analysis
- Familiarity with BI data visualisation tools (Tableau, Looker, or similar)
- Experience with A/B testing tools (Optimizely, VWO, or similar)
- Understanding of SEO, paid marketing analytics, and user acquisition strategies
- Strong analytical and problem-solving skills with the ability to turn data into actionable insights
- Excellent communication skills to present findings to both technical and non-technical stakeholders
Preferred Qualifications:
- Experience working with an online marketplace, e-commerce, or SaaS business
- Familiarity with CRM and customer behaviour tracking tools (Brevo, Hubspot, or similar)
- Basic knowledge of Python or R for data analysis
- Understanding of UX principles and CRO (Conversion Rate Optimisation) best practices
- Experience with BigQuery or other cloud-based data warehouses
- Experience with AI/ML platforms or tools (e.g., Google Vertex AI, Amazon SageMaker, or low-code AI tools) for predictive modeling, personalisation, or automation use cases
Job Type: Full-time / Fully Remote
Salary: Up to £50,000 ATE
Contact Detail:
Twickets Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, such as Google Analytics (GA4) and SQL. Having hands-on experience with these tools will not only boost your confidence but also demonstrate your readiness to hit the ground running.
✨Tip Number 2
Showcase your analytical skills by preparing examples of how you've used data to drive decisions in previous roles. Be ready to discuss specific projects where you identified trends or insights that led to measurable improvements.
✨Tip Number 3
Network with professionals in the e-commerce and online marketplace sectors. Engaging with industry peers can provide valuable insights and potentially lead to referrals, which can significantly enhance your chances of landing the job.
✨Tip Number 4
Prepare to discuss your experience with A/B testing and how it has impacted user engagement in your past roles. Being able to articulate your approach to experimentation will show your potential employer that you understand the importance of data-driven decision-making.
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data analysis, web analytics, and any specific tools mentioned in the job description, such as Google Analytics or SQL. Use keywords from the job listing to ensure your application stands out.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data analysis and how it can drive decision-making in an online marketplace. Mention specific projects or experiences that demonstrate your ability to analyse user behaviour and optimise conversions.
Showcase Your Skills: Include examples of your experience with A/B testing, dashboard creation, and customer segmentation. If you have worked with AI or machine learning tools, be sure to highlight this as it is a strong plus for the role.
Prepare for Technical Questions: Anticipate technical questions related to data analysis and web tracking tools during the interview process. Brush up on your knowledge of statistical models, data visualisation, and any relevant programming languages like Python or R.
How to prepare for a job interview at Twickets
✨Showcase Your Analytical Skills
Be prepared to discuss your experience with data analysis and how you've used it to drive decision-making in previous roles. Highlight specific projects where you implemented data strategies or created dashboards that led to actionable insights.
✨Familiarise Yourself with Relevant Tools
Make sure you know the ins and outs of tools like Google Analytics, SQL, and any BI visualisation tools mentioned in the job description. Be ready to explain how you've used these tools to analyse data and improve user experiences.
✨Prepare for Technical Questions
Expect questions that test your knowledge of A/B testing, customer segmentation, and predictive modelling. Brush up on these concepts and be ready to provide examples of how you've applied them in real-world scenarios.
✨Communicate Clearly
Since you'll need to present findings to both technical and non-technical stakeholders, practice explaining complex data insights in simple terms. This will demonstrate your ability to bridge the gap between data and actionable business strategies.
