Lead Digital Business Analyst

As a Lead Digital Business Analyst at Glossier, your primary responsibilities will include analyzing the shopping funnel and site journeys, collaborating with various teams to drive business performance, executing A/B testing, and providing insights on both physical and digital product launches. Moreover, you will be responsible for CRM reporting related to customer acquisition and retention.

To qualify for the Lead Digital Business Analyst role at Glossier, you should have a minimum of 4+ years of professional experience in retail or eCommerce analytics. Familiarity with e-commerce platforms like Shopify, proficiency in data visualization tools, and strong communication skills are essential. Experience with SQL, Looker, and Google Analytics is also highly desirable.

Success for the Lead Digital Business Analyst at Glossier is measured by your ability to discover performance opportunities within the shopping funnel, enhance customer journeys, and provide actionable insights based on the data you analyze. Additionally, your contributions to the strategic roadmap and your proficiency in delivering custom reporting will play crucial roles in evaluating your performance.

The Lead Digital Business Analyst plays a pivotal role in shaping Glossier's strategy by identifying key trends in customer behavior and product performance. By leveraging strong data analytics skills and influencing cross-functional teams, you will ensure that data-driven decisions are integrated into the company's strategic roadmap, ultimately enhancing customer experience and driving business growth.

Lead Digital Business Analysts at Glossier commonly use platforms like Shopify, FullStory, and Optimizely for data analysis and A/B test execution. Additionally, proficiency in SQL, Looker, Google Analytics, and data reporting tools is integral to the role, enabling effective visualization and analysis of complex data sets.

In my previous roles, I have conducted multiple A/B tests using tools such as Optimizely and Google Optimize. I developed a hypothesis based on user behavior data, implemented tests to validate it, and thoroughly analyzed the results to inform decisions moving forward. This systematic approach ensured our strategies were data-driven and aligned with business goals.

I prioritize projects by assessing their impact on business goals and deadlines. I leverage project management tools to organize tasks and focus first on high-impact initiatives. Regular communication with stakeholders is key to ensure alignment and managing expectations as priorities may shift.

To communicate complex data findings to non-technical teams, I focus on storytelling, contextualizing the data within the business strategy. Utilizing visuals, such as graphs and charts, helps to illustrate key points effectively. I avoid jargon and focus on how the findings translate into actionable insights that everyone can understand.

Customer feedback is essential in my analysis as it provides real-world data that reflects user experiences. I incorporate insights from surveys, reviews, and direct feedback into my analytical framework to better understand customer pain points and areas for enhancement in the shopping journey.

In a previous role, my analysis of drop-off points in the shopping cart led to identifying a specific design issue that frustrated users. By presenting my findings, we adjusted the user interface, resulting in a measurable increase in conversion rates over the following months. This shows the direct impact of data analysis on customer experience.

I am very comfortable using SQL for data analysis. I frequently use SQL to query databases, clean data, and derive insights for business reporting. This skill allows me to handle complex datasets and streamline reporting processes effectively.

I measure the effectiveness of marketing campaigns through key performance indicators (KPIs) such as click-through rates, conversion rates, and ROI. I analyze pre- and post-campaign data to understand performance trends and to adjust future strategies accordingly.

Certainly! In my last role, I used data visualization tools like FullStory to create dashboards that illustrated user engagement metrics. This improved visibility helped cross-functional teams understand user behavior patterns and made data more accessible for decision-making, enhancing our strategic planning.

To track customer acquisition and retention, I employ a mix of CRM tools and analytics platforms to monitor user journeys from entry points to exit rates. I analyze metrics like customer lifetime value and churn rates, which provide insights into the effectiveness of our acquisition strategies.

My passion for data in the eCommerce field stems from its ability to uncover actionable insights that directly enhance customer experiences. I'm fascinated by how data can illuminate consumer behavior trends and inform strategies that lead to better business outcomes, ultimately creating a more engaging shopping experience.