Product Analyst (M/W/D)

As a Product Analyst (M/W/D) at AVIV, your main responsibilities will include providing ad-hoc analyses to help prioritize projects, designing experiments, analyzing user behaviors, constructing monitoring dashboards, conducting and analyzing AB tests, and fostering a data-driven culture across product teams.

To be a successful Product Analyst (M/W/D) at AVIV, you should have a deep passion for data, strong analytical skills, and experience with tools such as SQL, Google DataStudio, and Google Analytics. Proficiency in Python is a plus, along with effective communication skills in English.

AVIV is committed to the growth of its Product Analysts (M/W/D) by providing access to training, a supportive team environment, and opportunities to collaborate on high-impact projects that drive product innovation. Flexible working conditions also contribute to their professional development.

Product Analysts at AVIV commonly use SQL (Athena, BigQuery), dashboarding tools like Google DataStudio, and tracking applications such as GA4 to analyze user behavior and to improve products through data-driven insights.

The recruitment process for the Product Analyst (M/W/D) role at AVIV consists of an initial phone call with a recruiter to discuss expectations, followed by an interview with the Hiring Manager that includes a case study, and finally, a meeting with the team to assess fit.

When analyzing user behavior for product improvement as a Product Analyst (M/W/D), I focus on gathering qualitative and quantitative data through tools like GA4, then I identify patterns and insights that indicate potential enhancements. I prioritize changes that align with user needs and business goals.

In my role as a Product Analyst, I have conducted numerous AB tests using tools such as AB Tasty and Kameleoon. I plan the tests by setting clear objectives, ensuring data quality, and analyzing results to make informed recommendations that drive product decisions.

Absolutely! There was a project where my analysis of user journey data revealed that users were dropping off at a specific step. I presented my findings to the product team, and we implemented changes that significantly increased conversion rates.

I have created various dashboards using Google DataStudio and Tableau that provided real-time insights on user engagement and project impacts. These dashboards helped to visualize KPIs for product teams and enabled data-driven decision-making.

I actively collaborate with cross-functional teams by fostering open communication and understanding each team’s perspective. By using data to bridge gaps, I ensure all teams are aligned on goals and strategies for product enhancements.

To ensure data quality, I implement a thorough validation process that includes checking for discrepancies in data entry, monitoring data flows regularly, and using automated tools to cleanse data. This ensures that we are working with accurate and reliable data.

I leverage storytelling techniques to communicate my findings clearly and concisely. Visual aids such as graphs or dashboards help illustrate key points, and I tailor my approach based on the audience, whether they're technical or non-technical stakeholders.

I prioritize projects based on their potential impact on user experience and business outcomes. I use a data-driven approach to identify high-priority opportunities that align with strategic goals, always balancing urgency with importance.

SQL is essential in my analytics process as it allows me to extract and manipulate data efficiently from databases. I use it to query datasets for in-depth analyses, ensuring I can derive actionable insights for product improvements.

I stay updated with the latest trends in product analytics by engaging in continuous learning through online courses, following industry leaders on platforms like LinkedIn, attending webinars, and actively participating in professional communities.