Introduction: It’s Not Enough to Know “Good” or “Bad”
In the bio-tech industry, where health and innovation are at stake, understanding public opinion is invaluable. But is a simple statement that brand perception is “positive” or “negative” enough? It turns out, it’s not. Human reactions are complex – a whole palette of emotions, from hope and trust, to concern or even skepticism. So how can we get to the heart of these sentiments and use this knowledge for the good of the company and its customers?
This case study shows how modern emotion analysis, supported by artificial intelligence (AI), helps bio-tech companies look deeper and truly understand how they are perceived.
The Challenge: What’s Hidden Behind the Numbers?
Imagine a bio-tech company creating breakthrough diagnostic solutions. It wants to know how it compares to others and what sentiments prevail around health topics related to its products. Standard tools show how many times it’s been mentioned online, but they don’t reveal what feelings accompany these mentions. The company needed answers to questions like:
- What specific emotions – joy, trust, or perhaps fear – dominate conversations about us and our technologies?
- Do people react differently to our communications on Twitter/X versus YouTube?
- How do we build trust compared to other players in the market?
- What emotions accompany discussions about specific diseases, which could influence the perception of our solutions?
The Solution: Intelligent Emotion Analysis in Practice
To answer these questions, a detailed analysis of internet content was conducted: social media, portals, forums, and blogs. Technology was used that can recognize not only the general tone (positive/negative) but the entire spectrum of human emotions – from joy, through trust, to fear or anger – and measure their intensity.
Importantly, advanced artificial intelligence (so-called GenAI) was used here. It helped process vast amounts of text and “catch” subtle emotional patterns that would be difficult to detect with traditional methods. It’s like having a super-sensitive emotion radar.
The Findings: What Did the Analysis Uncover?
The deep emotion analysis yielded many valuable insights:
Different Companies, Different Emotions: It turned out that each of the surveyed companies evokes slightly different associations. Some appeared more frequently in the media and generated a stronger emotional “stir.” Others, although communicating more calmly, gained in other areas. For example, one of the companies, despite a smaller number of publications, enjoyed the highest level of trust (28%) and joy (29%) among recipients. Interestingly, it also generated the fewest negative opinions (only 6%) and rarely evoked anger or dislike. This shows that calmer communication can effectively build an image of a solid, trustworthy brand.
The Power of Different Communication Channels: The analysis showed that while platforms like X (formerly Twitter) generate many short mentions, videos (e.g., on YouTube) can reach a huge number of people. However, it’s important for video content not just to be technical, but to tell stories and engage viewers.
Emotions Around Health Topics: Conversations about specific health problems (like antibiotic resistance or diabetes) are imbued with different emotions depending on the country or language. For example, in one country a given topic may primarily evoke fear, while in another – hope for new solutions. This is crucial knowledge when planning product communication.
[Insert Slide from page 21 (as an example, emotion charts for Diabetes)]
How Products Are Perceived: By comparing emotions around different products on the market (e.g., diagnostic systems), one can see which ones are associated with trust and joy, and which ones raise concerns, often related to technical problems, for instance. These are valuable tips when introducing your own solutions.
Why Is This So Important for the Bio-Tech Industry?
The bio-tech sector operates in an area that naturally evokes strong emotions and expectations. Understanding these nuances helps to:
- Care for a Good Reputation: Early detection of negative emotions allows for quick reactions and avoidance of image crises.
- Communicate More Effectively: Adapting language and content to the emotions of recipients (patients, doctors, investors) makes communication better understood and received.
- Learn from Others: Analyzing emotions around competitors shows what communication strategies work.
- Better Introduce New Products: Knowledge of the market’s emotional background facilitates the effective presentation of new technologies.
Conclusions: Understand to Act Better
Modern emotion analysis, supported by artificial intelligence, is much more for bio-tech companies than just “listening” to the internet. It is, above all, an understanding of the deeper moods and feelings that shape opinions.
As this study shows, such insight allows for building a stronger, trust-based image, better communication planning, and more effective operation in a challenging market. This is technology that provides real value to companies seeking in-depth information about how their brand and products are perceived.