A major international consumer packaged goods (CPG) brand with more than $6 billion in revenue depends on the data provided by customers when they register products purchased from independent retailers to engage with customers and grow through repeat business. The brand intended to slice and dice its 300 million row dataset by product information, customer cohorts, etc., to enable the marketing team to target customers with personalized email campaigns and identify which campaigns drove the most business. They also wanted to identify the campaigns that led customers to opt out, which limits the brand’s ability grow through its existing customer base.
However, the BI team hit scale limitations with Tableau and analyses would often fail , preventing the BI team from providing the data needed to create customer profiles and a functional customer database. As a result:
With Sigma, the marketing team now has a comprehensive customer database that they can rapidly filter to create customer cohorts, as well as highly targeted and personalized campaigns that drive revenue for the brand.
Sigma was purpose-built for Snowflake and cloud data warehouses. The marketing team now has direct access to live data in Snowflake, ensuring that everyone is always working with the same current data - no more stale extracts, data sprawl, or conflicting insights - and the data stays safe in Snowflake.
Sigma is a cloud-native solution delivering unlimited scale at cloud speed - no summaries or aggregates necessary. The marketing team can now easily analyze and filter billions of rows of customer data , enabling them to rapidly drill down into data without rendering or latency delays.
Sigma’s spreadsheet interface makes iterative data exploration accessible to anyone, especially those that are accustomed to analyzing data in spreadsheets. Today, the marketing team analyzes data and creates pivot tables in Sigma , enabling them to quickly create customized campaigns that convert to sales.
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