How is AI used for advertising?
How is AI used for advertising?
The pace of the AI revolution has been unprecedented. You can find an AI tool for almost any task that you can do on your laptop and there’s a good reason for it. AI can replicate the same tasks with greater speed and accuracy. So it’s only natural that the $600 billion advertising industry wouldn’t be untouched by AI. The use of AI in advertising began with simple tools for ad budget optimisation on platforms like Facebook.
However, with advancements in technology and the integration of techniques like FACS, eye tracking, speech recognition and transcription, the use cases of AI in advertising have evolved. According to Harvard Business School professor Gerald Zaltman, 95% of consumer purchase decisions occur in their subconscious mind and since emotion AI lets advertisers tap into the subconscious that drives purchase decisions, the use of emotion AI in advertising is unquestionable.
In this blog, we will look into how emotion AI is revolutionising the world of advertising and we will also look at some real-world examples of emotion AI in advertising. But before we get into the intricate applications, let’s start by answering the most basic question.
What is Emotion AI?
Emotion AI, also known as affective computing, is an AI subset that can recognize, interpret, and respond to human emotions. It uses complex facial recognition algorithms like FACS, speech recognition, eye monitoring, and tracking head movements to do so.
Capturing emotions through Emotion AI is a four-step process.
Step 1- Acquire an image or set of images from a camera (Webcam, USB camera, CCTV)
Step 2- Processing the image(resizing, cropping, compressing, and optimising for better quality)
Step 3- Extracting insights from the images through neural network models and connecting data points
Step 4- Segregating emotions and reporting actionable feedback
Emotion AI uses modern AI tools like:
FACS– The Facial Action Coding System(FACS) is a system that facilitates emotional intelligence by breaking down emotions into groups of facial muscle movements called action units.
Eye-Tracking- Emotion AI clubs visual heatmaps with the emotional profiles of users to segregate positive visual elements from negative ones.
Gestures and behavioural physiology- The system tracks gestures and body movements to identify emotions more accurately.AR and VR- To make remote interactions feel more real and accurate.
Three Game-Changing Use Cases of AI in Advertising
1. Better ROAS with Creative Testing using Emotion AI
Creativity plays a huge role in hooking customers and driving them to the product page of a website where the sale takes place. It’s the interface layer between the advertiser and the customer where the advertiser has less than 3 seconds to communicate the desirability of a product. Therefore these creatives must elicit positive emotions from a customer.
Advertisers rely on creative testing to ensure that this happens and use methods like A/B testing where they compare two creatives side-by-side and observe metrics like CTR and CPC to identify areas that need improvement. And that is where all conventional creative testing methods are rendered useless because the creative changes are entirely based on intuition. No data tells marketers about the specific areas that need change.
This changes completely with emotion AI. A specialised tool for creative testing can couple AI techniques like eye tracking and FACS to generate attention and emotion heatmaps. These heatmaps highlight the areas that draw maximum attention and the emotion your customer feels when they interact with these areas.
Advertisers can use this data to optimise the creative for maximum positive emotional output from a prospect and increase the likelihood of a sale. In simpler terms, these changes increase the ROAS and facilitate maximum efficiency in ad-budget optimisation.
We recently did a case study where we used one of our products called Insights Pro to analyse the trailers of popular TV shows on Netflix and suggested changes based on emotional insights. You can look at it here.
2. AI in Advertising with Emotion Trackers
According to a report by Geenbook, an average customer sees around 4,000 ads regularly and he/she has 12 alternatives for the same product. So how does one ensure that their ad stands out?
Simple, by using emotional trackers to identify people with the right emotional profile and then placing ads in front of them. This technique ensures that the people viewing your ads are in the right mood to make the purchase and it is likely that they will react positively to the ad. According to a study, brands experienced 2x sales when an advertisement had a personalised emotional effect on consumers.
One example of this is how the Sao Paulo Metro Yellow Line uses interactive screens with interactive advertising, which millions of people engage with. These screens gather information on the emotional responses of daily passengers to ads, providing valuable insights for ad agencies. With these insights, ad agencies can curate better ads. If a customer frowns on the price of a product, the agency can adjust the pricing. If customers don’t like the packaging, the agency can modify it as well. If customers exhibit frustration with the store layout, the agency can make changes to enhance the shopping experience.
3. Market Research with Emotion AI
Advertising involves placing ads in front of the right people, in the right place, at the right time. But how do advertisers and marketers identify the right people and the right place?
The answer lies in market research. Brands test their product with a proxy audience that closely resembles their target customer base and record their insights to conclude. However, the current research methodologies do not take into account the real-time emotional activity of the participants. The problem lies with the genuineness of the data obtained from conventional market research settings. Since the respondents are aware of the artificial scenario, the response may be dishonest and there’s no way to track emotional state and body language to differentiate between honest and dishonest responses.
That’s where emotion AI steps in and saves the day. Brands can record and analyse remote interactions between the research participants and their products and run them through emotion AI analytics tools to obtain emotional insights. Brands can then co-relate these insights with regular insights to identify honest and dishonest responses. These analytics tools analyse voice, visuals, and text simultaneously to generate richer insights by creating a holistic emotional profile of the research participant.
One example of emotion AI being used in the space of market research is Affectiva, a Boston-based Emotion AI company that specialises in automotive AI and advertising research for 25% of Fortune 500 companies.
About Insights Pro
Insights Pro is an AI-based ad testing tool that combines emotional intelligence with new-gen AI tools like speech transcription, facial coding, text sentiment analysis, and eye tracking to generate an emotional heatmap, area of interest, engagement score and others of an interaction between a viewer and a creative. It helps in creative optimisation by accelerate the creative testing process.
This tool has taken AI-backed creative testing one step ahead of the competition by integrating emotional intelligence into the AI equation, facilitating quicker decisions backed by real data and insights.
You can request a free demo of the product here.
In the realm of advertising, the integration of Emotion AI marks a paradigm shift. This subset of AI, utilising tools like FACS and eye tracking, deciphers human emotions, offering profound insights for brands. By analysing facial cues, gestures, and reactions, Emotion AI unveils subconscious triggers that drive consumer decisions.
The insights derived from emotion AI analytics tools combine the emotional profile of users with regular insights to improve the quality of decisions that these insights drive. The advertising industry is all about reaching the right people and if the authenticity of the insights that drive advertising decisions cannot be verified, likely, the advertisers won’t reach the people they’re looking for.
That’s exactly why these three transformative applications of emotion AI in advertising stand out: Creative Testing employs emotion heatmaps for precise adjustments, optimising Return on Ad Spend. Emotion Trackers enable personalised ads that resonate with viewers’ emotional states, yielding notable sales enhancements. Market Research embraces genuine emotions, disrupting traditional methodologies for more authentic insights.