Consumer research is not overrated. Traditional methods of doing consumer research, however, are another story. Up until now researchers depended heavily on quantitative and qualitative findings when it came to studying their consumers. With the advances in technology and artificial intelligence, researchers can now delve into behavioral research.
Behavioral research is the most important but often ignored owing to the many misconceptions surrounding it. And for good reason. However, these reasons are not valid today, thanks to AI-led behavioral research.
But we’ll get into that later. Let’s talk about why behavioral research was often ignored?
Behavioral Research – A Flashback
Behavioral research evolved from behavioral neuroscience and cognitive science studies. These studies were either equipment heavy or depended on surveys interactions from which researchers drew inferences. Bias played a huge role in behavioral research.
One of the early practitioners of applied behavioral analysis was Ivan Pavlov, a pioneer in classical conditioning in the late 1800s. He used to insert test tubes into the dogs’ mouths to measure the production of saliva when they’re fed. There was another famous or infamous self-proclaimed behaviorist – John Watson. He is “known” for this controversial study ‘Littel Albert’, 1919, where he wanted to test if Pavlov’s methods would work on a human. However, the experiment was regarded highly unethical as Albert was only a boy of 9-months, when John Watson was testing if he could condition fear into Albert.
As technology advanced, around the late 1920s, there were EEG (electroencephalography) machines to monitor the brain’s electrical signals. There was also a bulky eye-tracking device that was invented in 1908.
In short, the history of behavioral research was murky and drenched with time-consuming methodologies, bulky equipment’s and whole lot of room for bias.
Today’s Behavioral Research – Brought to you by AI
Since the history of behavioral research was not colorful, researchers and marketers are still skeptical on adopting and implementing it.
Behavioral research and studies have come a long way from John Watson terrorizing a baby to study fear conditioning. With AI in the picture, it has made its way into the cloud, promising accessibility to researchers around the world.
AI technologies Scaling Behavioral Research
With artificial intelligence on the frontier, behavioral research is now available to the researchers as cloud-hosted online platforms. Embedded with AI technologies such as facial coding, eye tracking and voice AI, behavioral research today is much easier, quicker, more accessible, massively scalable and user friendly.
In the mid 1960s, a couple of researchers set out to test if computer could be programmed to recognize human faces. Unfortunately, the experiment was a failure. Woodroe Bledsoe, the research lead, said: “The face recognition problem is made difficult by the great variability in head rotation and tilt, lighting intensity and angle, facial expression, aging, etc.”
Behavioral research platforms equipped with AI algorithms to recognize, understand, and analyze emotions behind the facial expressions. All researchers need is a panel who has access to webcams or mobile cameras, and they can measure expressions in real-time. Facial coding technologies these days do not need hardware, are highly accurate, and can churn our actionable insights in no time. Researchers can come up with campaigns driven by behavioral data, ensuring increased engagement and response.
Have a look: Behavioral Research for Product Testing
Loius Emile Javal, back in the last 1800s noticed that people, while reading, pause on few words and skim through others. Fast forward to the 1900s, Edmund Huey built the first eye tracking device. It was a very intrusive device where the lens in the apparatus had a tiny hole which had a pointer attached to it. They helped Huey recognize where the reader paused and where they skimmed.
Eyes tracking is now done through webcams and mobile cameras. The respondents eye movement is first studied and the algorithm re-calibrates itself to gather insights from the particular respondents eye movements. Computer-vision-based data capturing technology measure eye movements and gaze in real-time. Researchers can now optimize logo/product placement in campaign collaterals to ensure higher brand association and recall.
The 1950s saw the first speech recognitions system. Designed by bell laboratories, Audrey system was built to recognize a single voice that narrated digits out loud. Later, in 1961, William C.Dersch developed Shoebox, at IBM. It could recognize 16 spoken words, which included digits 0 to 9. I
Ai technologies such as speech recognition and natural language processing has advanced the capabilities and scope of voice AI. AI-led behavioral technologies can now recognize emotions and intent behind spoken words across languages. These technologies are also capable of both transcriptions and translations. Understanding sentiments behind speech, with voice AI, can help researchers gauge the consumer’s actual feelings regarding their product/solutions.
Before We Wrap Up
Coupling AI with behavioral research has opened researchers to a whole new world of possibilities. Researchers can run multiple research campaigns at the same time and receive consumer insights in just 2 weeks. The faster TAT encourages agile research methodologies, helping researchers and brands scale their operations while improving the quality and reliability of insights.
Ignoring behavioral research is no longer an option. More than 90% of a person’s purchase decisions are influenced by the sub-conscious; to try to study the sub-conscious we’ve got behavioral research. it delivers both quality and speed, and researchers have run out of excuses have. Adopt AI-led behavioral research and scale your projects to include the sub-conscious!
If you’d like to know more, look up our article on all about AI-led Behavioral Research