Last week, I attended the Media Research Group (MRG)’s June content session and listened to some fantastic presentations by the7stars, Reuters, and the Trade Desk. 

The session began with the 7stars’ presentation, on the waning effectiveness of social grade classification in market research. This classification system, in use since the 1950s, is based on the occupation and employment status of a household’s chief income earner and is used throughout the advertising industry, including our own Route Research’s Travel Survey. This sparked a lively discussion about the need for an industry-wide effort to redefine these classifications. The solution for this isn’t straightforward, and requires industry-wide initiative, from media owners to the MRS, to market research companies to come together and drive change.

The second presentation was by the Reuters Institute for the Study of Journalism on public sentiment, awareness, and usage of generative AI. The study was conducted across multiple countries and provides global insights into attitudes towards generative AI use. Specifically in news media and social media, the public believes that generative AI will have a high impact on the industry but is not confident that the industry will use AI responsibly.

Finally, the last presentation was by The Trade Desk and PA Consulting, where they drilled into the importance of omni-channel advertising, and the impact of a connected campaign on brand performance and consumer experience. The research found that connected omni-channel campaigns were 1.5 times more persuasive than disconnected campaigns, and 2.2 times less fatiguing.

What I found particularly interesting – though was slightly sceptical about - was their use of “electroencephalography-style” (EEG) readings to measure participant brain activation when exposed to ads across multiple different channels, including digital OOH. Understandably, they used a consumer-grade EEG headset rather than an academic research-grade EEG set up.

As someone who studied neuroscience and psychology at university and worked as a lab manager and research assistant in a cognitive neuroscience lab, I have conducted multiple 128-electrode EEG tests. In the presentation there was an image of (multiple) participants each with a headset on, watching ads, and walking around the room. In actual EEG tests that is not possible as people are wired in.

The thing is, EEG is an incredibly involved method. EEG, standing for electroencephalogram, is a measurement of brain electrical fields via electrodes placed on the head. These electrical fields are caused by the electrochemical signals between neurons when they fire. In academic research settings, EEG is done in a Faraday cage (a room that blocks electromagnetic fields), where the participant has a cap on with at least 24 to 128 electrodes and sits still in a chair, doing the study’s task. The whole preparation for EEG tests, from squirting gel into electrodes, to then cleaning every single electrode after the test using a toothbrush, is incredibly time consuming. Also, the gel gets into participants’ hair, which is obviously not a fun time for them!

EEG provides excellent temporal resolution but weak spatial resolution, meaning it can accurately measure WHEN neurons fire but not precisely WHERE. That is why in neuroscience studies, EEG is often combined with methods like functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to get a more complete picture. None of these are possible to do ‘properly’ while people are wandering around a viewing studio together. Consumer-grade EEG headsets have fewer electrodes which likely means less accurate data. This is likely further exacerbated within environments with multiple electronic devices (such as the DOOH screens, video cameras and multiple mobile devices). These are likely to produce artifacts which may distort EEG signals.

As you can probably tell already, academic level EEG is EXPENSIVE, and is a very involved process. Conducting proper EEG just isn’t going to be feasible on a media research budget, so I after my initial “OMG this isn’t EEG!!” thoughts relented a little and after doing some further research into these consumer-grade EEG headsets, I accept how this can be a more practical way of conducting “neuroscience-type” testing in the advertising and marketing space. I would say to proceed with caution and not jump to conclusions from the data of these tests in isolation, because even with 128 electrodes and all the fancy equipment of Johns Hopkins University, EEG alone doesn’t provide the whole picture of brain activation. As media researchers, it is crucial to consider why we even have the need for brain activation data, what we are using this for, what it means, and how it informs advertising strategy.

Overall, it was a very thought-provoking session and one that I’m pleased took me back to the very complex and evolving landscape of neuroscience research!

Click here to view the presentation slides: https://www.mrg.org.uk/events/244