Two Years as a Lead Data Analyst at Tokopedia: My Journey and Key Learnings

A. Background

I have had the incredible opportunity to serve as a Lead Data Analyst at Tokopedia, one of Southeast Asia’s leading e-commerce platforms. Today, I want to share my journey, the lessons I've learned, and some insights that could benefit aspiring data analysts.

Tokopedia is a pioneering e-commerce platform in Indonesia, revolutionizing the way people shop and sell online. My journey with Tokopedia began when I joined the company as a Lead Data Analyst for the Loyalty & Gamification team, then I was gradually assigned to other teams such as Subscription, Account, Recommendation, and Experimentation. This experience has been both challenging and rewarding, shaping me into a more skilled and insightful professional.

B. Key Learnings

B.1. Data-Driven Decision Making

One of the most significant lessons I've learned is the power of data-driven decision-making. At Tokopedia, data is at the heart of every strategic move. From optimizing algorithm precision to improving recommendation accuracy, leveraging data has driven growth and efficiency. For instance, by analyzing user historical activities and behavior data, we identified improvement in our subscribers compared to the non-subscribers, leading to a 20% increase in average order value (AOV). Another example is that we keep doing A/B testing in recommendation widgets to continuously increase our primary metrics, such as conversion rate (CVR), click-through rate (CTR), and repurchase rate (RPR).

B.2. Building and Leading a Team

Leading a team of talented data analysts has been a fulfilling experience. Building a cohesive team that collaborates effectively was initially challenging, but by fostering an environment of open communication and continuous learning, we achieved remarkable results. Regular team meetings, knowledge-sharing sessions, and constructive feedback have been key to our success. Thanks to my precious team members for working together with me.

B.3. Various Analytical Techniques

Throughout my tenure, I've had the chance to delve into various analytical techniques such as regression analysis, XGBOOST, causal inference analysis, clustering analysis, time-series forecasting, and propensity score matching. These techniques have not only expanded my skill set but also significantly enhanced our ability to forecast trends and make proactive decisions. Utilizing tools like Python (using Anaconda or Google Collabs), R (using R studio), SQL (Google BigQuery), and Tableau have been indispensable in our analytical toolkit.

B.4. Collaboration with Other Departments

Collaboration across departments is vital for a data analyst. At Tokopedia, we work closely with product development, marketing, business, and customer service teams to ensure that our insights align with the company's goals. I also learned that when working with various stakeholders, we need to prepare different approaches, because not only the goal of each department would be very different, but the people also come from various backgrounds, as data analytics professionals we need to be able to communicate the analytics things to be understandable as easy as possible to them.

B.5. Continuous Learning and Adaptation

The field of data analytics is ever-evolving, and staying up-to-date with the latest trends and technologies is essential. I've made it a point to enroll in online courses and participate as a guest lecturer on many occasions. This commitment to continuous learning has not only kept me informed but also inspired innovative approaches to our projects.

C. Challenges and How I Overcame Them

One of the biggest challenges I faced was dealing with data quality issues. Inconsistent and incomplete data can significantly hinder analysis. To address this, we implemented robust data validation and cleaning processes, which improved the accuracy of our insights. Additionally, managing time and prioritizing tasks in a fast-paced environment required effective time management skills and strategic planning.

D. Advice for Aspiring Data Analysts

For those looking to advance in the field of data analytics, my advice is to focus on both technical and soft skills. Mastering tools like SQL, Python, and R is crucial, as well as BI tools such as Tableau and Looker, but equally important is the ability to communicate insights effectively and work collaboratively with diverse teams. Never stop learning, stay curious, and be open to new challenges.

E. Conclusion

My two years as a Lead Data Analyst at Tokopedia have been a period of immense growth and learning. The experiences and insights gained have been invaluable, and I hope my journey inspires others to pursue their path in data analytics. If you have any questions or thoughts, feel free to reach out. Let’s continue the conversation and learn from each other.

F. Last but not Least

I want to say thanks and apologize to everyone working together with me at Tokopedia, especially the data analytics team Ramadhiyan Firdan , Meri Andani R. , Abdul Rachim Winata , Mahesa Oktareza , Ahmad Yusuf Albadri , Leiditya Naristi , Hanny Nur Hanifah , Ahmad Nur Aziz , Muhammad Aulia A. , Ryvan Arnandha Putra , Adiyoga Istiono Putra , product development team (PM, Engineers, EP, and many more) of Loyalty, Gamification, Subscription, Account, Recommendation, and Experimentation, and others that I can't mention one by one. See you when I see you!