Taming the data organization mess

MissionSource is a boutique digital marketing agency with 8 full-time employees and a handful of regular contractors. They specialize in paid advertising, SEO, and marketing analytics. Prior to finding Grist, MissionSource used Stackby and Google Sheets for internal data visualization and management. By integrating Google Sheets with Stackby, MissionSource could force a relational structure on their spreadsheet data.

However, they could not move fully away from Google Sheets, because data entry in Stackby was too limited by the product’s layouts. Stackby’s UI lacked the flexibility of a spreadsheet. Though working in Google Sheets had its problems, too. The spreadsheets were scattered across many folders, and sometimes the same data had many copies. Still, the unconventional data flow worked — or so they thought.

MissionSource’s co-owner and Director of Strategy, Chris Scott, likes software and is always game to try something new. He found Grist on AppSumo and decided to give it a try. After importing his data to Grist, he immediately saw what it solved: data organization. Their internal data was messy. The Stackby-Google Sheets solution was generating more mess, not less. Grist shined a light on that problem and offered a great solution.

Data visualization for the agency and their clients

Mission Source started off by using Grist to track the time employees spent on projects. Chris liked that it was a source of truth that could be built collaboratively, with everyone seeing the same data. His co-owner liked that he could use Grist to build a business dashboard that gave him a detailed view of which market segments yielded the best leads that converted for the agency.

What I like about Grist the most is its focus. It appears simple, but it’s very powerful in a focused way. There’s a lot of Grist competitors like Airtable and Stackby that are messy and distracting which is why I never used them consistently.

Chris Scott

As a digital marketing agency, MissionSource already uses many marketing tools that generate a lot of data. With Grist, Chris could export data from those tools and build a more centralized picture. For example, Chris uses Grist to track SEO rankings and meta tags in a layout that makes sense for his workflow.

On the client-side, Grist transformed paid advertising data from clients’ campaigns into insightful charts and reports that drill into the data in new and illuminating ways.

Grist as a data processor

Chris has also built a series of data cleaning processes in Grist. His templates take data from marketing tools, then clean and transform the data into lists which can be used in other marketing campaigns. He also imports data from cold callers and sales representatives to extract valuable insights in a simple, but powerful and fast tool.

I consider Grist a no code data analysis platform. All spreadsheet data is going into Grist, because it’s really the only tool that makes it easy to compile all this data and transform it into something I can export to complete other tasks either in other Grist docs or in another marketing tool.

Chris Scott