Traditional measures that rely on both qualitative and quantitative data do still make sense despite the audience becoming more fragmented. They make sense because they provide actionable insights and overall consumer trends, which have proven to be effective in professional practice as well as on a theoretical level.
However, the metrics are only effective for media buyers and planners if the data set as a whole is taken into account–something that most traditional media fail to do in the modern era of media. As with any research or analysis, this “Bias can cause estimates of association to be either larger or smaller than the true association. In extreme cases, bias can cause a perceived association which is directly opposite of the true association.” (Pannucci, CJ and Wilkins, EG. Identifying and Avoiding Bias in Research. 2011).
BARB is inherently biased because of their position as an analyst of television reporting data. To combat this they have taken steps to ensure the veracity of their data by verifying that at least one registered person is in the room, is watched a normal speed, and is visible when viewed online (BARB, “BARB explained” 2018). But, the platform doesn’t mention as to whether they monitor those using a cell phone while the TV plays passively in the background–something that they plan to initialize later in 2018, according to their site. Therefore, media planners should take BARB’s analysis with some skepticism and cross-reference findings with other verifiable sources.
Pannucci, C.J. & Wilkins, E.G., 2010. Identifying and Avoiding Bias in Research. Plastic and Reconstructive Surgery, 126(2), pp.619–625.
Anon, BARB Explained. BARB. Available at: https://www.barb.co.uk/barb-explained/barb-explained-the-viewability-question/ [Accessed July 22, 2018].