Analyze.Agency
Christopher Daniel is an experienced data professional currently serving as the Chief Executive Officer at Analyze.Agency since December 2022, specializing in data migration, warehousing, and analytics. At Analyze.Agency, Christopher has implemented data solutions using tools like Hightouch, Python, and SQL for reverse ETL and data visualization. Previously, Christopher held positions including Analytics Manager at STAND 8 Technology Services, where leadership and collaboration were emphasized, and Head of Analytics at Upwork, focusing on building data stack infrastructure. Additional experience includes roles as Lead Data Scientist at Good Money, where substantial user scaling was achieved, and Senior Data Scientist at MoneyLion, notable for developing a multi-touch attribution model for marketing campaigns. Christopher's career began at Google as a Data Scientist, analyzing Google Indoor Maps data. Educational background includes a Master’s degree from the University of South Florida and a Bachelor’s degree in Computer Science from Meenakshi College of Engineering.
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Analyze.Agency
We provide analytical & data engineering services. Following is a sample. *Scenario* - A company has ads on one or multiple platforms like Google, LinkedIn etc. including offline marketing. - We will see to that we can accurately measure - Customer Acquisition Cost [1:1 matching – no generic aggregation] - Cost per Lead [1:1 matching – no generic aggregation] - Traffic to site [unique visits & over all visits] - Which channels / Sources bring better ROI - Measuring churn broken by popular cohorts - Engagement on platform by Ad source - Multi- touch attribution Tools Used - To get this done in the past we have used the following tools - Segment / Rudderstack/ mparticle as CDPs - Fivetran / Hevodata as Data migrating tools - Snowflake / Big Query / Redshift as Data Warehouses - Mode Analytics / Power BI / as Business Intelligence tools