{"id":48192,"date":"2020-06-04T23:51:35","date_gmt":"2020-06-05T03:51:35","guid":{"rendered":"https:\/\/3c98cd88ae.nxcli.io\/?p=48192"},"modified":"2023-03-23T11:19:36","modified_gmt":"2023-03-23T15:19:36","slug":"diving-deep-on-creative-development","status":"publish","type":"post","link":"https:\/\/staging.sago.com\/de\/resources\/case-study\/diving-deep-on-creative-development\/","title":{"rendered":"Diving Deep on Creative Development"},"content":{"rendered":"

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How an Advertising Agency Combined Qual Methods and Methodify to Improve Its Creative Decision-Making<\/span><\/h2>\n

The Challenge<\/h4>\n

\"sago\"John St. is one of the top advertising agencies in Canada, and it works with a wide variety of clients. Chasson Gracie, currently Group Planning Director for Omnicom\/Dieste, played a key role at John St. to optimize brand messaging that resonated with each client\u2019s audience.<\/p>\n

When evaluating different possible campaign directions, the research team adds value by not only identifying which idea is the \u201cwinner\u201d, but by providing insights on why and how best to optimize it. To do this, the researchers need qualitative research as much as quantitative \u2013 and they need it quickly and within budget.<\/p>\n

The challenge of time is a constant for creative teams, and if the research can\u2019t be completed quickly it is of little value. In this particular case, John St. was developing new brand positioning to rejuvenate an alcohol brand that had not seen any media against it for years. The team had developed four different territories and wanted to get feedback from category consumers about which one resonated most, and why. With this information, John St. could begin creative development with a solid strategy in place.<\/p>\n

Our Solution<\/h4>\n

\"sago\"John St. has utilized Methodify<\/a>, Sago’s automated quantitative research engine, for a long time. It provides the research team the ability to get the account teams the information needed to optimize creative quickly and efficiently. As John St. wanted to go deeper in this instance, it reached out to see if Sago could help incorporate a qualitative component to this research project.<\/p>\n

The answer was simple \u2013 incorporate CRIS, an AI-enabled virtual moderator, with a quantitative study. This combination allowed John St. to employ an agile approach to testing the territories.<\/p>\n

The process was simple:<\/p>\n

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  1. John St. ran Methodify\u2019s sequential monadic concept test with a qual component from CRIS. This provided quant findings and detailed qualitative feedback on each of the territoriesHere\u2019s how it worked:\n