Case Study Details

 

Developed a Customer Data Platform for the world’s largest furniture manufacturer to streamline data management operations

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Client Background

Client Background

Founded in 1945, the client’s company is the leading furniture manufactures in the world.

Objective

The client already had a system in order to execute their data management task. But it was not performing as per their expectations. Hence, they onboarded KCS with a demand to develop a Customer Data Platform that can help the client in simplifying several data management processes.

  • Country
    USA

  • Industry
    Manufacturing & Engineering

  • Solution
    Machine Learning, Microsoft Azure Services,
    Artificial Intelligence, Big Data, Cloud

Challanges

Challenges

  • Previously, the client was using a traditional system in order to execute data management tasks
  • In our analysis phase, we found that the previous system was outdated and needed a complete revamp
  • The client also faced various issues like scalability, high availability, data security, and performance with the previous system
  • As the previous system was old, it lacked modern technology integration such as Artificial Intelligence, Machine Learning, Big Data, Cloud, etc.
  • Also, the previous system was static and worked on pre-defined fixed conditions
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Solution

  • After analyzing the client’s existing system, our experts decided to develop a Customer Data Platform that will help them in merging customer’s data for analysis and follow-up by making all the information available
  • Based on the available data, the client can conduct more targeted marketing campaigns
  • This Customer Data Platform is capable of loading the data from the third-party service providers so that it can be merged with the client’s server
  • The platform also contains a method of de-duplicating the customer information from multiple internal and external sources
  • A unique ID is assigned to each customer or prospective customer in the Customer Data Platform
  • The platform will crosswalk a table of customer ID information that maps and updates the unique, global ID to each of the customer’s IDs within the various source systems
  • The Customer Data Platform aims to be customer-centric and data-driven to provide an Omni-channel customer experience and influence purchase decisions earlier in the sales cycle
  • Our solution uses unique Global Customer IDs generated using Machine Learning data modelling techniques to reference customer activity data clusters in near-real-time
  • This portal will help the company to look for customer details with having different search options to get more idea about customer history and customer buying pattern observations

Case Study Solution

Project Highlights

Customer Data Platform

Customer Data Platform

Omni-channel customer experience

Omni-channel customer experience

Machine Learning

Machine Learning

De-duplication of customer data

De-duplication of customer data

Power BI Reports implementation

Power BI Reports implementation

KCS Approach

KCS Approach

Leveraging modern technologies, experts at KCS developed a cutting-edge Customer Data Platform that streamlined all the data management tasks of the client. Azure Kubernetes Services simplified cluster maintenance along with automated upgrades and scaling. Azkaban Hadoop resolved the ordering via job dependencies and provides an easy-to-use web user interface to maintain and track your workflows. Apache Accumulo provided fast retrieval of data when specifying either an individual key or a small range of keys.

Outcome

Outcome

  • The Customer Data Project is the initial focus of a larger Big Data initiative to help the client become a data-driven enterprise
  • The portal showcases and measures each Customer Journey evaluating the nature of transactions and purchase patterns
  • It will provide an Omni Channel Experience for all the customers enhancing buying experience which will influence purchase decisions earlier in the sales cycle
  • The Customer Data Project will create one central repository for all the customer-related data avoiding fragmented data
  • The platform is capable to achieve customer data analytics at a larger scale in near real-time
  • It can also achieve CCPA compliance by protecting Personally Identifiable Information (PII) of each customer
  • The client can get 360 Degree Customer view using the deduplication process with Machine Learning
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Tech Stack

Microsoft Azure Kubernetes
Apache Accumulo
Spring Boot
Java Microservices
Apache Zookeeper
Apache Nifi
Microsoft Azure Services
Python
Machine Learning

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