Web Analyst

5 days ago

Bengaluru, Karnataka, India Infogain Full time US$ 90,000 - US$ 1,20,000 per year

Responsibilities:


• Assess, interpret & analyze data to deliver insight and understanding of customer behavior on


• Review test hypotheses, help develop comprehensive test plans and success metrics, performing quality assurance on test cells, and calculating the final test results and deep dive analysis of the test results and craft Test Summaries using both behavioral and voice of the customer analytics to provide actionable insights for key business stakeholders.


• Proactively identify and analyze trends within the data to understand visitor behavior, market dynamics, and site performance metrics.


• Utilize best-in-class analytics tools, including the Adobe Marketing Cloud (eg. Target, Analytics, Ad Hoc Analysis etc.) to analyze test results and provide interpretation, guidance and recommendations to aid marketing decision making.


• Partner with Marketing, Finance, Product team and eCommerce teams to support RTB process, Launch measurements etc.


• Ability to understand different Adobe data sources to drive all the cross-surface journey optimization.


• Partner with Data engineering team to create comprehensive reports and dashboards to visually communicate insights effectively, presenting findings in a clear format. Make complex findings easily understandable, by highlighting key takeaways and actionable recommendations.

Skills/Qualifications:


• Bachelor's degree required along with practical business experience in analyzing data. MBA or Masters in a quantitative field like Economics, Statistics, Engineering, or IT a plus


• 3+ years of experience in analytics and/or marketing analytics. Experience in B2C and eCommerce is preferred.


• Experience with web analytics tools such as Adobe Analytics (strongly preferred), CJA, Google Analytics, or CoreMetrics


• Candidate must know programing languages like R, Python or SQL for data extraction and data stitching work.


• Expert in A/B and Multivariate testing, design of experiments, the mathematics of statistical hypothesis testing coupled with the ability to draw meaningful business insights across multiple tests.


• Knowledge of test design and combining disparate data sources is a plus.

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