Loyalytics is a fast-growing Analytics consulting and product organization based out of Bangalore. We work with large retail clients across the globe helping them monetize their data assets through our consulting assignments and product accelerators. We are a young dynamic team of 100+ analytics practitioners working on some of the most cutting-edge tools and technologies.Who we are:
About The Job
- Technical team: A team full of data scientists, data engineers and business analysts who work with 1M+ data points every day.
- Market Size: Massive multi-billion $ global market opportunity.
- Leadership: Combined experience of 40+ years of experience in the industry.
- Customers: Word-of-mouth and referral driven marketing to acquire customers like big retail brands in GCC regions like Lulu, GMG, among others (Strong product-market fit).
- What makes us stand apart: 8 years old bootstrapped and 100+ people company that is still hiring.
We are seeking a highly skilled and detail-oriented Data Analyst specialized in Loyalty Programs to join our team. The ideal candidate will have a strong background in data analysis, statistics, and programming, with a focus on loyalty program analytics. The Data Analyst will be responsible for collecting, analysing, and interpreting data from our loyalty programs to drive actionable insights and enhance customer engagement and loyalty. This role requires a deep understanding of customer behaviour, data analysis techniques, and the ability to translate complex data into meaningful business recommendations.Responsibilities
- Collect, clean, and analyze data related to our loyalty program, including customer behavior, redemption rates, and engagement metrics.
- Identify trends, patterns, and insights from the loyalty program data to inform strategic decision-making.
- Evaluate the performance of our loyalty program by assessing its impact on customer retention, lifetime value, and overall business growth.
- Develop and maintain key performance indicators (KPIs) to monitor the programs success.
- Segment our customer base to identify different groups with unique behaviors and preferences, allowing for targeted loyalty program enhancements.
- Plan and execute A/B tests to measure the impact of changes or new features in the loyalty program and provide recommendations based on test results.
Reporting and Visualization:
- Create regular reports and dashboards to communicate insights to cross-functional teams and senior management.
- Present findings in a clear and understandable manner, with a focus on actionable recommendations.
- Collaborate with IT teams to ensure data integration and data quality, and assist in the development of data pipelines.
- Stay current with industry trends and best practices in loyalty program analytics, suggesting improvements and innovations.
Your first 30-60-90 days plan:
- Deeply understand the data, processes, client ecosystems, existing solutions and organizational structure
- Understand the high level OKRs for yourself
- You’ll be tasked with a key deliverable to be achieved in 6/12 months
- You’ll establishing ways of working with your team and clients
- You’ll develop weekly milestones and a roadmap to help you achieve your goals
- Bachelors degree in Data Science, Statistics, Computer Science, or a related field. A Masters degree is a plus.
- 5+ years of proven experience as a Data Analyst, preferably in the context of loyalty programs or customer analytics.
- Proficiency in data analysis tools and programming languages such as Python, R, SQL, and data visualization tools like Tableau or Power BI.
- Knowledge in databricks or any cloud platform (GCP, Azure, AWS).
- Strong problem-solving skills and the ability to translate data into actionable insights.
- Excellent communication and presentation skills to convey complex findings to non-technical stakeholders.
- Be a part of the dynamic and fun team, making an impact in the retail tech industry with clients like Lulu, Aster, GMG etc.
- Flexible Work Hours.
- Wellness & Family Benefits.
- Access to various learning platforms.