Business Intelligence Analyst

As a Business Intelligence Analyst at Poki, your primary responsibilities will include analyzing data to identify opportunities for player growth, enhancing marketing efficiency, and improving the monetization strategies of our games. You will be tasked with evaluating player behavior, working closely with developers to prioritize game releases, and finding ways to improve the overall experience for both players and game creators.

To qualify for the Business Intelligence Analyst role at Poki, candidates should have at least 4 years of analytical experience, a strong understanding of a multi-sided platform, and proficiency in data structuring with SQL, ideally with tools like BigQuery or Snowflake. Experience in data visualization using platforms such as Lookerstudio or Tableau is also essential. Curiosity and a business-savvy mindset are crucial traits we look for.

A Business Intelligence Analyst at Poki plays a crucial role in refining the gaming experience for our vast player community. By analyzing player data and trends, you can help improve how players discover games, ensure that developer needs are met, and optimize advertising placements to enhance user enjoyment. Your insights will feed directly into strategies that keep our 90 million monthly players engaged and satisfied.

In your role as a Business Intelligence Analyst at Poki, you will utilize various tools and technologies, primarily focusing on SQL for data structuring, and visualization tools like Lookerstudio or Tableau for presenting your findings. These technologies will aid you in transforming raw data into actionable insights that help drive the decisions of both the Poki team and our game developers.

At Poki, Business Intelligence Analysts will enjoy a vibrant work environment in Amsterdam, characterized by a hybrid setup that allows for both in-office collaboration and remote work. Our culture emphasizes personal responsibility, continuous learning, and team activities, ensuring that analysts not only contribute significantly but also enjoy a fulfilling work-life balance surrounded by a supportive and motivated team.

To effectively analyze data, I first identify my key questions and objectives. Then, I gather relevant data points and clean the dataset to ensure accuracy. I utilize SQL for structuring and querying, followed by employing statistical analysis or visualization tools like Tableau to uncover trends and patterns. The most effective insights stem from a thorough understanding of user behavior and market trends.

In my previous role, I analyzed user engagement data, which highlighted underperforming areas within our app. By restructuring our marketing tactics based on my findings, we improved user retention by 30%. This experience reinforced my belief in the power of data-driven decisions and demonstrated how critical insights can align with strategic goals.

When communicating data findings to non-technical stakeholders, I focus on storytelling methods. I break down complex data visualizations into simpler concepts and relate them to business objectives. By using analogies and clear visualization, I ensure that my audience can easily grasp the implications of the data and understand the proposed actions.

In a fast-paced environment, I prioritize tasks by assessing their urgency and impact on core business objectives. I create a list of tasks, categorize them based on deadlines, and regularly communicate with my team to realign our priorities. This helps maintain focus on high-impact projects while allowing flexibility for unforeseen tasks.

I have over four years of experience with SQL, specifically using BigQuery to manage and analyze large datasets. I am proficient in writing complex queries that can manipulate and transform data based on analytical needs. I have also worked with tools like Snowflake for cloud data warehousing, giving me experience in handling big data effectively.

To measure the success of a business intelligence initiative, I assess both quantitative and qualitative outcomes. Key metrics might include the adoption rate of insights across teams, the impact of decisions based on my analysis on revenue or user engagement, and feedback from stakeholders about the relevance and usability of the findings.

To evaluate game discoverability, I would analyze player interaction patterns, like clicks and session durations. I would also review user search behaviors and compare them against the metadata of games. Utilizing A/B testing, I could optimize game placements and ad strategies to enhance discoverability, ensuring players more easily encounter new and engaging content.

One of the biggest challenges for a Business Intelligence Analyst in the gaming industry is balancing player experience with monetization strategies. It’s crucial to provide players with a fun and organic gaming experience while integrating advertisements effectively. Understanding player behavior and preferences is essential in achieving this balance.

I stay updated on industry trends and BI advancements by regularly reading articles, attending webinars, and participating in online forums related to data analytics and business intelligence. Following thought leaders on platforms like LinkedIn and engaging in community discussions also provides insights into emerging practices and technologies.

Ensuring data accuracy begins with meticulous data cleaning processes to remove errors and inconsistencies in datasets. I also implement validation checks at various stages of data handling, using scripts or software tools to confirm data integrity. Regular audits and collaborating with data engineers further ensure that we maintain a high standard of data cleanliness.