February 12-13, 2019
Once upon a time, there was data…
Our success as researchers, and the legacy of our work, depends not on our ability to analyze and number-crunch but on how we craft stories which resonate with our audience. It is only then that data becomes insight, becomes ideas, becomes action.
It’s often difficult to tell a good research story in the business-to-business world, with faceless protagonists and story arches navigating procurement policies and vendor-managed inventory. But as Ken Kesey, the great American novelist, once said:
“To hell with facts! We need stories!”
This presentation details the keys to telling a story which will unlock insight from its shackles and propel it towards action.
To aid in understanding what storytelling means in the context of research, this presentation will introduce a framework consisting of five levels of analysis, each adding more value to the underlying data set by creating greater clarity or interpretation.
The highest level of analysis requires the highest level of skill and also produces the most coherent, memorable and engaging insights. This is storytelling or story-based analysis and usually takes place after initial analysis is conducted.
Storytelling involves the following four steps (each introduced in detail in the presentation):
Over the last decade, the research sector has increasingly focused on automation and outsourcing of analysis, leading to commoditization of the processes and techniques used to generate outputs. Storytelling instead brings back the importance of the skilled researcher as an integral driver of any project.
By following these principles of storytelling in research, researchers can empower clients to confidently make decisions based on insight. In other words, the researchers, the marketers and the data all lived happily ever after.
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