Automation of reports, faster time to insights, cost savings.
A leading CPG company collected and leveraged data from various retailers and e-commerce sites to obtain the latest sales trends in near real-time across different geographies. Sigmoid created a Data Lake to capture and automate diverse data from different retailers and stored it on Google BigQuery, enabling faster reporting and insights into sales and forecasting trends.
The client is a leading American CPG operating in multiple categories including household, and personal care products. Their products are stocked by all leading retailers both online and in brick-and-mortar stores.
As the company was trying to have real-time access to sales trends, they faced the following challenges:
• Lack of customer-level data from multiple retailers.
• Data pipelines were monolithic and teams across geographies were downloading the data manually before exporting it to BigQuery to observe the trends.
• Several missing data elements for events like holidays and weekends.
• Availability of data to a chosen few members of the organization, making it difficult for the people on the ground to understand how their business was performing.
• Manual report generation process that made the whole process of generating insights slow. It typically took a week’s time to access specific data from the retailers.
To know how Sigmoid solved customer's business problems, solution architecture using GCP and the business impact please download the case study.
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