Emotion AI also known as affective computing is rapidly changing how businesses undertake a market study. Unlike other business intelligence methods, Emotion AI can analyse and interpret facial expressions, vocal intonation, as well as other physiological signs of consumers’ emotional state. This technology lets marketing and advertising departments learn customers as human beings with ideas, needs, and feelings, which in turn leads to a smarter approach to marketing and consequently, more satisfying experiences for the consumers. In this blog, we shall discuss how Emotion AI can be deployed to drive a more superior market research outcome.
Understanding Emotion AI
Emotion AI is the process of analyzing and recognizing emotions with the help of technologies such as algorithms or machine learning. This technology is able to take information in the form of a video showing people or an audio clip or a text and deduce how people feel under certain circumstances. Realizing these emotions is important for a business organization in that these highlight the matters of consumer choice, behavior and even the response to products or services by such an organization.
Improving Survey Accuracy
Standard approaches like using questionnaires and surveys are based on respondents’ subjective information. Honesty can be an issue from the side of respondents or people might have difficulties in expressing themselves honestly. Emotion AI improves the reliability of surveys by measuring the subjects ‘ emotional reactions.
For instance, when a person is in the middle of the product testing session, Emotion AI can determine what that person is actually feeling depending on their frowns, smile, the pitch of the voice, etc. They can help uncover potential buying motives that may be overshadowed by the responses gained by direct interview or questionnaires, thus giving a better picture of the consumers’ attitude.
Enhancing Focus Groups
In general, focus groups are widely used for the purpose of collecting the qualitative data; however these also have certain drawbacks. The participants might feel pressed into the compromises of the group views, while the facilitators themselves might unconsciously bias the answers. The problems can be solved with the help of Emotion AI, which gives the exact picture of participants’ emotions without prejudice.
In focus group sessions, participants’ emotions can be recognized using Emotion AI at the same time while people are discussing something. This technology can recognize difference between fake/impressive smiles and real smiles, hesitation/crossing of legs when the person is confused or bored during presentation or discussion, and thus, the facilitators are able to gain much more detailed information about the participants’ perception of certain topics. Therefore, identifying the emotions of a focus group allows the business to get more candid feedback and adjust the offerings in their portfolio as a result.
Real-Time Emotional Feedback
Another major benefit that is perceived from Emotion AI technology is that it offers real-time feedback on the feelings and emotions of the people. This capability will especially help in the assessment of marketing communications programs, Adverts, and promotional tools.
For instance, using Emotion AI a company can understand how its commercial is received by the viewers. Therefore, it can differentiate between which aspects of the commercial are most appreciated and which aspects of the commercial that would require alteration. The real-time results also give marketers insights and enable the modification of a campaign in a short while to what will trigger a positive response from the audience.
Understanding Customer Journeys
Emotion AI can also be used to plan out the Customer Journey Map as well as to check the emotional comments. The accumulation of feelings of customers at different levels of their life cycle provides significant directions on what makes the most impact in loyalty.
For instance, Emotion AI may be useful to a retailer who wants to assess the level of happiness of shoppers who are browsing a website of products. If the facial expressions show that the customer is frustrated while check out, the retailer can look into the problem and fix the problem that is causing the frustration. Thus, grasping and improving such a type of contact can contribute to achieving more satisfying and memorable customer experiences.
Enhancing Product Development
New product creation is a priority for most firms nowadays and knowing the customer needs and wants is critical, to which Emotion AI can greatly contribute. Evaluating the emotional stimuli toward the prototypes and newer additions in the product, the business can make evidence based decisions about its design and functionality.
For example, a tech firm designing a new smartphone can employ Emotion AI in identifying which features beta or focus group users are responding warmly to. So, if the testers give positive affect towards a specific feature, the side of the company can give emphasis on the creation for that feature. On the other hand, when the testers display negative feelings towards the product, the company can change something to suit the clients during the launch.
Personalising Customer Experiences
Emotion AI assists companies that want to use the information about emotions to adjust customer interactions to fit the client’s emotional state. This can be advantageous to the customer where they get products that they want and this helps to encourage them to remain loyal to the business.
For instance, an e-commerce platform may employ Emotion AI to determine the customers’ reactions towards the recommended products. It also has the capability to recommend more articles for the given category if the displayed technology shows positive emotions towards the given category. The use of talk thereafter individualizes the customer and makes them feel special, hence, inclining them to the prospects of making a purchase.
Monitoring Brand Perception
This is because brand reputation concerns how customers perceive their brands and hence the need for mastery of those aspects in order to avoid negative perception. Emotion AI can help in analyzing the posts, review and other content shared on social media, and blogs, and capture the perception people have of the brand.
Thus, by tracking emotions in the posts that are connected to the brand, businesses can determine the sentiment towards it and analyze possible problems. For instance, if Emotion AI recognizes a rise of negative emotions regarding a certain product, the company needs to look into the situation and probably fix it before it gets worse. This is efficient in ensuring that organizations do not get the wrong reputation while at the same time building the reputation of their brands with the clients.
Predicting Market Trends
They also comprise emotional data analysis from different sources to support the prediction of the market’s trends. Overall, it is possible to note that research on consumers’ attitudes towards various forms of products, services and trends will help companies to formulate accurate strategies for the future.
For instance, while using Emotion AI, a fashion retailer shall be able to filter out the numerous social media posts and get to know the new trends in the fashion market. In this way, the specific styles and products that create particular emotions shall be included in its assortment and the retailer shall outcompete rivals.
Improving Employee Engagement
Thus, Emotion AI is not only good for understanding customers but employees as well to improve their performance. Self-awareness as to how employees respond emotionally to these events means that necessary changes can be made to make work situations less of a burden or stress to the employee.
For instance, an organization can use Emotion AI to give the feeling of the employees during training sessions or during any meeting. This way, the technology in the organization can be able to capture signs that depict boredom or frustration whereby the organization can have to change its approach in conducting the sessions. Hence, prioritizing of employee health improves morale and performance in business organizations.
Conclusion
This is a useful methodology for improving the findings of market research by pointing to deeper feelings and emotions of any given consumer. From increasing the efficiency of surveys and the quality of focus groups up to real time feedbacks and customer individualization Emotion AI helps to support decisions and create content that a target group is interested in. Over time the use of this technology in market research is likely to expand and will thus provide businesses with additional means to experience a ‘deeper’ relationship with their customers. In other words, the use of Emotion AI can help an organization outcompete others, retain customers and thus achieve sustainable business outcomes in today’s global market that is rapidly evolving.
