Business Impact

  • Single Source of Truth

  • Customer Profiling & Segmentation

  • Improved Data Quality

Customer Key Facts

  • Location : North America
  • Industry : Staffing & Recruiting

Problem Context

Kelly Services is a global leader in office staffing and professional services. They had disparate data sources spread across website analytics, CRM, internal databases, marketing, campaign, and an enterprise data warehouse which did not allow them to get a holistic view of their customers. They had to manually download and upload reports to a dashboarding tool using Excel files and spreadsheets. As a result, there was a lack of actionable insights as manual process could not track important KPIs.



  • Data siloed across different platforms and sources
  • No automated pipelines existed for ingesting and updating data from sources into a single warehouse
  • No stitching of data across the various AdTech & MarTech platforms
  • Data cleaning and data consistency

Technologies Used

Google's BigQuery Data Transfer Service
Google Analytics
Google Cloud Storage
Google Cloud Composer
Google Cloud Source Repositories

Building a Marketing Data Warehouse and Creating Automated Power BI Dashboards


Quantiphi helped in building a marketing data warehouse to automate the process of analyzing data from various sources. First, the challenge of disparate data sources was addressed by building a Marketing Data Warehouse in Google’s BigQuery and designing a data architecture comprising of the rules, standards, and models that will both govern and define what data is to be collected and how that data is to be used, stored, managed, and integrated.

The data warehouse designed in BigQuery was further used as a primary and single source of truth for designing dashboards in Microsoft Power BI. This provided one consolidated view of all the marketing data sources through visualizations that highlight KPIs, such as lead conversion funnels and top performing ad campaigns, as well as other important metrics like return on ad spend (ROAS). This also presented an overview of the entire talent journey and customer journey to enable them to take data-backed actions.


  • End-to-end automation of data ingestion from different sources to BigQuery
  • The Marketing Data Warehouse in BigQuery was used as a single source of truth for all analytics and reporting
  • Automated update of dashboards and reports that utilized data from the Marketing Data Warehouse
  • Availability of advanced insights about customer journey from connected data
  • Clear visibility of the revenue derived from their marketing efforts and other important KPIs

Published on November 11, 2020

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