How Tredence Empowered a Global Retailer with Holistic Campaign Analytics Using GCP


One of the largest fashion retailers in the USA wanted to gain holistic learnings from their marketing campaign implementations to improve their strategies in customer selection design to improve conversion rates. There is also a need for a system that can track changes in customer behavior. 

For years, by following traditional reporting methods using Tableau for dashboards and Marketing Analyst working on deep dives. The marketing learnings are unorganized and often time taking, despite the significant investment in large Hadoop and Teradata environments. 

To tackle this problem, Tredence has come up with TALP platform to augment the decision-making of campaign owners & marketing managers by providing a 360-degree view of campaign’s performance by highlighting critical metrics, analyze lift and provide cross sectional insights. These insights are used as inputs for better campaign design & audience selection process.? 

The Goal 

The customer’s challenge was that existing on-premises technology could not support the analytics capabilities required to analyze the holistic campaign performance. Previous capabilities of AEO, requires Marketing managers and Campaign Owners to interact with multiple analysts, who would manually collate the data and derive insights, which is a very cost ineffective process. Also collating multiple analysis is often tedious and has long turnaround time. With TALP in place, Stakeholders have ability to perform real time analysis on holistic campaign data.  

The demand on legacy hardware was always high, and the capacity to support new, large scale analytical workloads did not exist.  

Enter GCP. 

Over the course of several months, Tredence worked with the customer to build a new hybrid platform that leveraged the power of Google’s Cloud to enable never-before-achieved analytical capabilities.  

World Class Insights, Powered by GCP 

The primary objective was to create a tool powered with measurement metrics to evaluate Campaign performance.  These included Marketing channel engagements, Transactional and Digital behavior. 

By tying each of these source systems together into a single analytical environment, we could all derive new insights from TALP that could be used in designing marketing strategies like  

  • Automated Customer Retention campaigns 
  • Personalized Product category Marketing 
  • Competitive discounting strategies 
  • Identifying Customer Segments for better Product launches  

As part of their Marketing Management, AEO has been on a path to modernize their IT infrastructure investments on the cloud platform. Prior to taking on modernizing their Campaign Measurement solution and engaging with Tredence, AEO was using Teradata DB for data storage and Tableau for visualization. 

AEO’s Marketing Analytics Pod within AEO Inc. is responsible for identifying various customer journeys, segmentation, and valuation of various customers based on their purchase patterns, revenue and loyalty, and to provide valuable business insights for better business decisions. 


Tredence worked with the customer to design and implement a large scale, hybrid on prem and cloud solution using Google Cloud Platform.  The solution was designed for campaign owners & marketing managers for better campaign design & audience selection process.? 

The TALP Platform, as it came to be known, ingested processed data from the customer’s large on premise of Big Query, and stored this data in GCS.  Tools like BigQuery, Vertex AI Notebooks, Node JS, and others allowed data scientists and analysts to do their work using scalable compute environments that could match the demands of large-scale machine learning workloads.  

The diagram below showcases the solution architecture for the platform.

Our solution addressed several client’s key challenges in building a holistic view of Campaign Performance: 

  • Leveraging the GCP environment to build a cost-optimized ecosystem to cater to both the business users and the data-scientist community 
  • Merging customer, marketing channel, clickstream & transaction data to create a Holistic Measurement of Campaign Performance

GCP Services Used 

We used a number of services native to Google Cloud Platform, in addition to a variety of 3rd party solutions that were already in use across the organization, including Node JS and React.  With respect to GCP, the following services were included in the original solution architecture on GCP.  Over time, those services have continued to improve and evolve, but they largely remain the same today.  

  • Cloud Storage 
  • Big Query 
  • Compute Engine
  • IAM
  • Cloud Logging
  • Secret Manager 
  • Google Kubernetes Engine  
  • Vertex AI Notebook 

Key Benefits

The TALP Platform has been a landmark achievement for the client, a solution that has enabled them to understand their marketing effectiveness in ways they could not imagine only a few years ago.  The solution exists today with hundreds of users who regularly feed valuable insights across the organization about their customers, so they are able to optimize many parts of the designing the campaign, driving value from acquisition and beyond.   

On the platform side, the TALP Platform has several achievements:  

  • We developed an auto-scalable infrastructure on GCP to manage variable workloads thus reducing cost
  • Ability to track customers behavior holistically in Marketing Channel engagement, Digital Activity, Transactions and Lifecycle stages.
  • Analyze Campaign performance at multiple granularities namely Online vs Store, Web vs App, SKU hierarchy etc.
  • Self-serve platform helping users skip the complicated data management and aggregation activities.


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Since inception, the TALP processes 10+ TB of data every week

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Overall costs reduced by 30 – 35%

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Workload processing times were reduced by 80%+ for many of the analytics workloads

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