[Editor's Note: Written by Magnet's Senior VP of Business Development, this article asks marketers interested in video the crucial question: is your video campaign based on assumptions or derived from data?]
Many, if not most, marketing organizations do research into customer (or prospect base) demographics, into the buying motivations of those groups, and into other relevant data meant to inform the marketers and help development of a targeted, efficient marketing strategy.
Once the strategy is developed and ready to go, tactics are employed to accomplish the organization’s objectives. One of the increasingly common and key components of most strategies is video marketing, as marketers are recognizing that B2C and B2B clients and prospects are not only viewing video, but are also being influenced to take action after viewing the video.
When it comes time to implement video into an overall marketing strategy, it’s suddenly time for production. At this point, the marketer has already set budget parameters, which leads to the next and crucial point at which the following question arises: is your video Assumption-Based or Data-Informed?
Many naturally gravitate toward on an Assumption-Based model, meaning there’s heavy reliance on internal assumptions about what messages should be communicated to the target audience and how. These decisions are often based on assumptions about clients or prospects and/or gathered from general marketing research done during strategic development.
Assumption-Based video has higher potential to miss key information that could contribute to the success of your video campaign. Information like how the target audience consumes video content, what video content they like to consume, what messages resonate with the target audience, on which platforms they consume video content, and much more.
For an example of a video created based on assumptions, see below. The European Commission aimed to create a video encouraging women to get more involved in science and mathematics, but packaged and delivered it in such a way that left women feeling stereotyped and marginalized. Increased data analysis could have indicated the targeted audience wouldn’t respond well to the message delivered as it was.
Or read here for more about the outcry over Hyundai’s video depicting a failed suicide attempt (in order to showcase a new car’s low emissions). In both of these examples, the companies managed to reach their target audiences, but delivered the wrong messages.