Building Efficient Internal Tools Using Sigma

Sigma embarked on a project aimed at streamlining workflows and improving efficiency by identifying inefficiencies across various teams and developing internal tools to address them, focusing particularly on the GTM team's BDR group. The BDR team faced challenges due to the multitude of tools used for gathering information, which often contained overlapping data. The solution involved creating a "Customer Match Generator" using Sigma, which centralized data about prospect accounts and provided essential information like industry details, competitors, and potential fit for Sigma. Data centralization was achieved through a massive base table that joined data from relevant sources and was materialized nightly, with additional questions answered by leveraging Snowflake's Cortex function. To enhance the process, a tool to identify the most similar customer to a prospect was developed, using normalized data and weighted columns to generate similarity scores. The ability to override outdated or missing data ensured accuracy, while example emails were generated to facilitate communication with prospects. This initiative allowed Sigma to consolidate data effectively, automate repetitive research tasks, and enhance the BDR team's efficiency, allowing them to focus more on engaging with prospects rather than data gathering.