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One of the Largest Global Media Companies Automates and Deepens Consumer and Campaign Insights with Real-Time Marketing Cloud Platform on GCP

case study

CUSTOMER OVERVIEW

The Client is an award-winning global communication and marketing agency employing over 20,000 people in over 100 countries worldwide. The company is committed to making a meaningful difference to brands, to businesses, and to people worldwide. It is also the most integrated group in its sector with a regional structure that places the client at the center of the organization. The client-centric approach enables the company to better satisfy and anticipate its clients’ needs.

THE CHALLENGE

Media brands face more pressure than ever from the industry and their customers to create seamless experiences across multiple devices and channels while delivering better campaign results. This outcome is only made possible by collecting and meaningfully analyzing data from every source and channel to provide a 360-degree view of the consumer journey and buying behavior.

Today’s increasingly digital-centric business world demands a real-time connected data ecosystem accessible by key stakeholders and data analysts alike that enable both to make informed, business-critical decisions quickly.

Due to the nature of its business, this Client collects vast amounts of data from various sources: campaign data, 1st, 2nd and 3rd-party data, ad server data, etc. However, much of the data wasn’t being used to its full potential in providing seamless, real-time insights to both internal analysts and clients to improve marketing campaigns and to better understand the consumer’s journey to purchase.

With disparate data being received and stored in multiple formats, databases and internal systems, analyzing and processing it proved time-consuming and complicated. Internal analysts manually extracted data into Excel spreadsheets. As a result, it required significant effort to bring all this data together and to produce a complete and meaningful picture of consumer behavior.

The Client had contacted Kanda with the goal of exploring possible solutions that could help to automate manual processes, to reduce the amount of human error and to provide real-time analytics capability. The Client wanted to start with the Proof-Of-Concept solution based on the data of one of the company’s customers before developing a fully functional platform.

THE SOLUTION

The Client was looking to develop a Cloud Proof-of-Concept Data warehouse and Data visualization solution that would:

  • Integrate complex digital advertising datasets from various sources and in various formats (MediaMath, AppNexus, DCM, publisher-aggregated data, etc.) into one unified Marketing
  • Scale with ease and on Demand
  • Offer a stellar ML engine to explore predictive analytics options

Why Kanda?

The Client’s internal team lacked experience in developing data platforms and on GCP.

Kanda was chosen based on its in-depth skills for architecting and developing on Google Cloud Platform; having experienced ETL and Big Data specialists, Architects and Developers on staff who could provide guidance and implement data collection; setting up robust ETL processes to provide real-time data visualization; having experience integrating and transforming complex data from multiple sources; and building an efficient and scalable architecture.

In developing a Proof-Of-Concept Marketing Data Platform for the Client, the Kanda team explored technology specifically suited for architecting a scalable marketing data warehouse on Google Cloud Platform with a particular emphasis on providing a holistic view of the customer journey, the ability to track consumer lifetime value (LTV) and provide real-time marketing insights and predictive analytics capabilities.

Google’s BigQuery Data Transfer Service was utilized to automate data transfer and injection from various sources (MediaMath, Appnexus, DCM, 1st, 2nd, and 3rd party data, etc.) on a scheduled, managed basis. Cloud DataPrep was used to automate data cleaning and anomaly detection to effectively prepare the data for the analysis. Cloud DataFlow provided the means to easily transform and enrich data in real-time. After this step, the data was ready for ML Engine and the use of custom Tensorflow libraries to enable the Client to perform predictive analytics.

Finally, the POC solution was visualized in Data Studio via elegant reports and interactive dashboards.

TECHNOLOGY STACK

  • Cloud Storage
  • BigQuery
  • Cloud Functions
  • BigQuery Data Transfer Service
  • Firebase
  • DataPrep
  • DataFlow
  • Cloud ML Engine
  • Data Studio

RESULTS

The Kanda team proved that it was possible to automate a complex, time-consuming and error-prone data analysis process by building a successful, scalable and cost-efficient Proof-Of-Concept Marketing Data platform on GCP.

The Client’s analytics team can now explore and create reports to uncover better consumer insights, improve campaign performance across different advertising channels, and provide elegant visualization of the results to customer brands.

Kanda’s Proof-Of-Concept solution has received positive reviews from the Client’s stakeholders, and the decision to proceed with the large-scale core project to add more functionally and deepen the analytics capabilities has already been made.

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