Client:
The Conversion Finder team initially managed data using a combination of Excel files, emails, and Google Sheets, drawing on data from clients, BigQuery, and other sources. This decentralized approach led to inefficiencies, data quality issues, and a lack of comprehensive documentation on data flows and processes.
The implemented project aimed to centralize and automate the team's data management, bringing together data from different sources and standardizing the data flow. Key components:
Consolidation of Data Sources: The project consolidated data from daily client submissions, CSV files, BigQuery, and other sources into a centralized data storage. For instance, data from daily exports from Paragon were combined and processed in BigQuery.
Standardized Data Management: The implementation of standardized data flows and processes improved data quality and reduced redundancy and complexity. This included defining relationships between tables such as "Leads," "Transfers," and "Retainers," and ensuring consistency across data tables.
Monitoring Dashboard: A monitoring dashboard was created to provide detailed insights into campaigns, vendors, and client performance. A "mockup" was developed to visualize possible deliverables, helping to identify data needs and guide the creation of the final dashboard.
Enhanced Data Granularity: The project increased data granularity, enabling more detailed analysis and insight generation, such as drilling down into specific campaigns, vendors, and leads.
Process Automation: Processes were automated to reduce manual effort and potential errors. For instance, data extraction and transformation tasks were automated using scripts to move data from Gmail to BigQuery.
The Clients Performance Platform transformed Conversion Finder's data management by improving efficiency, accuracy, and decision-making capabilities. The new system empowered the team with actionable insights and a more strategic approach to managing campaigns and client relationships.
