Research shows ability of neuroscience to predict sales resultsStaff writer ▼ | June 14, 2016
In a major study of integrated consumer neuroscience tools, a combination of EEG, biometric and facial coding consumer responses was shown to have extremely high explanatory power of in-market sales.
Groundbreaking Audience Measurement 2016 conference
The five-month study, which was released at The Advertising Research Foundation's Audience Measurement 2016 conference, used multiple neuroscience measures, ad exposure and actual retail purchase data.
The results showed meaningful, statistically significant relationships between individual neuroscience measures and in-store sales for the same creative executions.
When used separately, the relationship to sales of the individual metrics ranged from a low of 9% for facial coding to a high of 62% for electroencephalography (EEG).
The study showed that the integration of multiple neuroscience measures results in up to 77% explanatory power with in-store sales, providing marketers with unprecedented research potential. Because of this work, Nielsen Consumer Neuroscience is able to calibrate these neuroscience measures for clients’ creative to predict in-market success.
“As a result of the partnership with Nielsen at our Television City Research Center in Las Vegas, we are excited to now offer an array of new neuroscience measures for pre-testing advertising,” said David Poltrack, Chief Research Officer, CBS Corporation and President, CBS Vision.
“These tools enable us to offer advertisers a unique opportunity to assure that their creative will deliver before they move forward with their campaigns.”
In the first formal study using Nielsen Consumer Neuroscience’s new Video Ad Explorer solution, the study represents the most comprehensive look at connecting neurometric, biometric and facial coding responses to advertising with what consumers purchase in the store.
Nearly 60 video ads from consumer packaged goods companies, ranging from adult beverages and soft drinks to women’s beauty products and diapers, were evaluated in multiple lab locations across the U.S.
The incremental sales generated by the specific TV schedules for those same ads were then determined by Nielsen Catalina Solutions using their single source dataset. This dataset included 4.3 million cable set-top-box households and retail purchase behavior from more than 90 million households and is nationally representative.
There are hundreds of different metrics within EEG, core biometrics, and facial coding that can be generated for a single ad based on complex brainwave patterns, heart rate, skin conductance and patterns of facial expression.
The study confirmed the importance of multiple measures and gives new insights into the right combination to predict in-store sales.
“We believe this is the holy grail for marketers: confidence in knowing creative’s potential impact on the bottom line – before it ever enters the market,” said Dr. Carl Marci, Chief Neuroscientist at Nielsen Consumer Neuroscience. “However, not all neuroscience measures are created equal. We’ve learned that only a few key combinations have the predictive power for in-market sales.”
Ad reactive is complex and difficult to measure, with many points of view, methods and measures, but it also remains central to in-market success. In today’s increasingly cluttered landscape, with billions of dollars in advertising at stake, the pressure to break through is immense, and marketers needs to get all of the marketing mix elements correct, including distribution, promotion and pricing.
For advertisers, agencies and media partners, these results demonstrate the tools that can effectively evaluate the most critical element of advertising – the ad creative – before reaching the market.
"Every marketer wants to be able to answer the question 'But did it work?' with a definitive 'Yes.'" Now, there's no doubt that neuromeasures can actually predict whether an ad will drive in-store sales," said Leslie Wood, Chief Research Officer at Nielsen Catalina Solutions.
“A key piece of this analysis was to be able to isolate the sales impact of the creative from the media tactics, using advanced machine learning to do the heavy lifting." ■