Illuminating the Consumer Journey: Real MTA Using Neuro
As I pointed out in last week’s article, the promise of MTA (MultiTouch Attribution) was stifled by not having continuous interim measures of incremental branding effect. This led to Bayesian (to lipstick it a bit) guesswork about the power of the last touch, the first touch, and the touches in between. There were no data by which to judge whether the TV impression that came third in the journey was what closed the deal. Or was it the YouTube impression on CTV that was eight days before the purchase event—all this for a brand that customer had not bought before, looking back three years. More likely it was a synergy effect with certain of the impressions having moved memory and later ones improving consideration—and still later ones improving purchase imaginings. My work with Jerry Zaltman, Chuck Young, and Jerry Nevins has led me to suggest this as a new branding metric worth using.
Before buying a brand never bought before, each of us will, at some time, have a sudden flash of seeing ourselves buying that brand – what I mean by “purchase imaginings.”
In my prior report I gave a methodology for estimating the power of each impression along the way. But who wants an estimate? I also mentioned EEG in the home as a way of measuring those small moves from impression to impression.
We will have that soon, for certain: RMT and Wharton are planning in-home EEG. What will it mean for CMOs and brand managers?
It will mean that they will, for the first time, be able to see anonymous humans in natural environments move toward and adopt their brand step by step.
As the data build up, the CMOs and brand managers will uncover deep insights about creative strategies and media strategies. They will also have line extension ideas.
They will be able to show early wins based on increases in quarterly earnings.
The creative work will be more creative. And more successful.
They will be able to show better long-term growth.
They will gain a more complete understanding of what their job is. Talents and skills that will be applicable to other work they may be doing. They might even become more introspective and try to understand themselves through the lens of enlightenment of being able to follow a brand through a successful conversion.
There will be four separate EEG metrics by which to track the impression-to-impression changes:
- Attention as measured by the brain, not just visual attention
- Memory encoding
- Approach, a measure showing attraction and positive emotion
- Synchrony, the strongest predictor of brand equity and incremental sales and brand growth, a measure of how the many brains have moved into synchronized swimming, moving up and down millisecond by millisecond, as if all coming from one brain.
This is the sign of a maximally successful ad impression. When AI MTA sees this in the data, those particular impressions – all of which happened at different times, but the system lines them up by the second of the commercial itself – are identified as positive turning points in the many journeys involved.
There will also be 265 “feelings” within the metadata, feelings which have baffled all other AIs in the past but which all human beings completely understand almost from birth. These are from the RMT work. A report might say something like “creative execution A, which is evoking strong synchrony, is subconsciously communicating Competency”. This palette of colors will translate scientific measurements into nuggets of deep understanding which lead to actionable decisions and positive outcomes.
Growing Brands Through Consumer Motivation
Most CMOs and brand managers are steeped in the notion of the brand. It is their fiduciary client. They have sworn to best efforts for that brand to grow and last as long as possible.
When a CMO or brand manager looks at the results of an advertising campaign, it is through the lens of how they and the agency came up with it. Nowadays, it is based on certain notions about the motivations of segments. Taking the form of: “We need more X in our ads” aimed at the Y segment.
RMT has already taken this into deeper waters. The motivations/need states in mass usage are based on the verbal minds of respondents and product benefits which fall into the classification of product features. What it is, what it does. Cure for X. Tastes good. Really cleans.
RMT moves beyond that to the total (not just verbal) minds of BD populations and passively measures with AI their deepest motivations based on their content consumption behavior. These deep motivations are Security, Achievement, Belonging, and so on. What really drives us. RMT with partner Samba Semasio is doing this now for all 300,000,000 minds in the USA, under all privacy laws and standards. These are those same 265 “feelings” indicators.
The 265 feelings themselves were derived empirically by use of an AI program recommender and set-top box data in 1997, the latter an innovation for which we won an Emmy.
We are on a mission to install in-home EEG with RMT to the current toolset. NIQ and Media Science have led the way on the EEG part, and we plan to expand with continuous natural-exposure measurement. Watch this space for updates. All guidance welcomed, thanks!
Posted at MediaVillage through the Thought Leadership self-publishing platform.
Click the social buttons to share this story with colleagues and friends.
The opinions expressed here are the author's views and do not necessarily represent the views of MediaVillage.org/MyersBizNet.
Bill Harvey
Bill Harvey, who won an Emmy® Award in 2022 for his invention of set top box data, has spent over 35 years leading the way in media research with pioneer thinking in New Media, set top box data, optimizers, measurement standards, privacy standards, the A…
