Director of Finance saves 16 hours per month with Mito | Mito

Director of Finance saves 16 hours per month with Mito

Ready to write Python code 4x faster?

To build weekly KPIs for my sales team, I need to quickly generate insights from our massive set of Salesforce opportunities. Instead of fighting with Excel to analyze my data, I’m using Mito to generate Python scripts myself and saving four hours per week. — Tom Bellis, Director of Finance @ Enigma

Enigma builds world-class datasets that tell the story of small businesses across America. These datasets are used by some of the world’s largest financial institutions, like Capital One, who use it to improve the accuracy of their marketing segmentation. Enigma’s data helps companies understand their customers. For example, that 20% of the small businesses they send mail to are about to go out of business!

Building these datasets is not easy. Enigma’s team of data scientists pull data from public websites, transform it into standardized business attributes, and constantly refresh it to ensure their customers receive the most up to date data.

Automating repetitive reporting with Excel

As the Director of Finance at Enigma, Tom was inspired by his data science colleagues, and tried to leverage Enigma’s data for their own sales and marketing. A year ago, Tom started teaching himself Python all the usual ways — taking Udemy courses, using Kaggle. But Python wasn’t clicking, and Tom was forced back to Excel.

Tom used Excel to build a report that showed how long it had been since Enigma had contacted each potential customer.

Because we have so many Salesforce opportunities, the file took a few minutes to open, and another few minutes each time I wanted to recalculate the workbook. Now that I’ve developed a Python script with Mito, I just open Jupyter and press run all. — Tom Bellis, Director of Finance @ Enigma

Tom used Mito to build a script that pulls the most up to date data from Salesforce, filters it, and uses spreadsheet formulas to figure out which potential customers should be prioritized that week. The script downloads the result as an Excel file that Tom sends to his sales team.

Tom was able to automate his weekly sales opportunities report even without becoming a Python pro. Mito’s spreadsheet environment made it easy for him to build the Python script just by following the same process he used each week to build the Excel report.

With those newly available sixteen hours a month, Tom is taking other Excel reports and transitioning them to Python scripts using Mito.

Ready to write Python code 4x faster?