Quantzig’s Advanced Analytics Helps a Renowned Consumer Products Manufacturer Develop an Aggressive Growth-Centric Data Strategy
What the Client Wanted A leading consumer products manufacturer wanted to understand the capabilities and data needed to create insights and opportunities that would support a strategic go-to-market transformation for their customer segment in focus. The Outcome The client developed an aggressive growth-centric data strategy that focused on data management and analysis activities around customer […]READ MORE >>
What the Client Wanted
A leading consumer products manufacturer wanted to understand the capabilities and data needed to create insights and opportunities that would support a strategic go-to-market transformation for their customer segment in focus.
Consumer Products Industry
Over the last couple of decades, the consumer products industry has demonstrated high growth rate in comparison with other goods industries. The constantly increasing demand for consumer products across the globe is drawing the attention of manufacturers, management authorities, and retailers to invest in this industry. Additionally, rapid urbanization coupled with lifestyle shifts is raising the requirements of consumer products by end users. The global consumer products industry also holds a high share in social as well as economic growth of a country as it creates a bulk of employment opportunities. Furthermore, the latest technology like the Internet of Things (IoT) is helping manufacturers to make better use of the data.
Consumer Products Industry Challenges
Data Visibility and Granularity: With regulations and compliance becoming stricter, traceability functionalities are more appropriate and essential than in the past. Consumer products companies need robust data granularity to provide high quality and compliant products, reduce operational risk, and avoid counterfeiting issues associated with global trade.
Regulatory and Compliance Pressures: The global regulatory environment is dynamic. Consumer products companies are faced with the challenges of managing nonconformances and mitigating operational risks. Moreover, as manufacturers rely on the global supplier network to meet international compliance, battle shrinking operating margins, and regulations, creating excessive pressure becomes an issue.
About the Client
The client is an American multinational consumer products company in the United States.
The client wanted to understand the capabilities and data needed to create insights and opportunities that would support a strategic go-to-market transformation for their customer segment in focus. Additionally, to apply advanced analytics and address opportunities related to the transformation objectives, the client had to develop a comprehensive data strategy and roadmap as part of the overall transformation journey.
Summary of our advanced analytics engagement
To gain in-depth insights into our advanced analytics solutions for consumer products brands
The consumer products manufacturer able to develop an aggressive growth-centric data strategy that focused on data management and analysis activities around customer identification and needs with the help of Quantzig’s advanced analytics. Additionally, the client:
- Introduced a loyalty scoring and attribute system that could be used to assess potential customers’ likelihood to convert
- Identified buying patterns of core customer segments within one of the largest US markets
- Identified potential customers that have the most likely buying attributes
Advanced Analytics Solution Insights
With the help of Quantzig’s advanced analytics, consumer products manufacturers can shift from a defensive data strategy to an offensive data strategy designed to track the true customer journey. Advanced analytics can also help manufacturers:
- Create new methodologies to increase data capture and utilization from existing capabilities to better cater to their customers.
- Develop proof of concepts that offer a greater analytics-driven approach and further improve the comfort level with advanced analytics using clustering machine learning processes.
To know more about how advanced analytics helped the renowned consumer products manufacturer
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