Background
Web XB has introduced a Conversational AI assistant, offering organisations an engaging and innovative way to collect valuable, insightful data through natural, vocal interactions. By facilitating these conversations, we aim to gain a deeper understanding of people’s experiences and emotions, complementing traditional methods like surveys and enhancing the richness of the insights gathered.
Scope
To put this to the test, we partnered with StratEdge IQ and spoke with 50 students in the U.S. about their experiences searching for jobs after completing their education and their outlook on career prospects.
Using our Conversational AI assistant to conduct the interviews, we posed 12 pre-defined questions, with the AI generating 8 additional follow-up questions based on the flow of the conversation. We aimed to gain a deeper understanding of their experiences, needs, and feelings about the future.
We then analysed the interview transcripts using Web XB’s emotional intelligence solution, extracting the most prominent emotions from the students' responses and identifying the key drivers behind their feelings.
The Study
Using our intuitive web application, students were redirected from a Qualtrics survey to participate in a hands-free, vocal conversation. With the help of our Conversational AI assistant, students shared their personal experiences, discussing their time in education, their post-graduation goals, and how they’ve approached the job search so far. They highlighted specific strategies, frustrations, and areas where they’ve found success.
The data generated from these conversations was rich and insightful, reflecting high levels of engagement. It provided a clear window into the students' experiences and emotions, offering valuable perspectives on their journey.
On average, each conversation lasted 12 minutes, during which 20 questions were answered, with responses averaging 40 words. Some responses, however, stretched to hundreds of words, with the longest single response containing 301 words. Throughout these conversations, we identified 10 prominent emotions and explored a total of 33 different topics.
AI Questioning
We harnessed the conversational capabilities of Generative AI to create contextually relevant follow-up questions, allowing us to dive deeper into the participants' thoughts during the conversations. Here’s an example from one of the conversations with a student:
In this example, the student discusses the challenges they faced during their initial job search, mentioning that a low response rate forced them to change their application strategy. In response, our Conversational AI assistant generated a follow-up question, probing deeper into what specific changes they made while keeping the low response rate in context. This led to a detailed, insightful response from the student, explaining their revised strategy.
Emotional Overview
At Web XB, we specialise in understanding emotions to uncover the 'why' behind behaviour and decision-making. To achieve this, we use a Hybrid-AI approach, blending the analytical power of AI with human emotional intelligence to extract meaningful insights. Applying this methodology to the student transcripts, here’s what we discovered:
Over 45% of the emotions expressed were related to desire, reflecting students' needs and wants.
Frustration made up 24% of the emotions, highlighting the challenges and negative experiences students faced.
Fear also played a significant role, with nearly 10% of the emotions reflecting worry and nervousness about the job search.
What Students Spoke About
The students discussed more than 30 diverse topics during their conversations with our AI assistant, indicating how comfortable they felt speaking openly. Here are the 15 most frequently mentioned topics:
Nearly 14% of the discussions focused on the need to enhance knowledge and awareness through additional learning and courses to improve job search outcomes.
Over 10% of the conversations highlighted the importance of having a strong support network, especially within relevant communities and families.
Other notable topics included the state of the economy, prospects, and mental well-being.
A Dive into Desire
Desire reflects the expression of wants and needs, and understanding it is essential. Without knowing these needs, we risk improving and innovating blindly. By combining conversational topics with our emotion analytics, we can uncover the key factors behind why students feel the way they do, particularly what drives their desires. Here’s what the data revealed:
At the forefront of students' minds were the desire to learn and acquire new knowledge, the aspiration to secure a prosperous future, and the need to build strong relationships to jump-start their careers. But what can colleges and universities take away from this?
The job market remains highly competitive, especially in the wake of widespread redundancies following COVID-19. The current economic climate is still uncertain, with global conflicts and the now-easing cost of living crisis. Students need more support than they are currently receiving. While their eagerness to learn is unmatched, they require more opportunities during their educational journey to help ease their transition into the job market.
About Web XB
Headquartered in North Cornwall, UK, Web XB partners with the world’s leading organizations to drive innovation. We combine conversational AI with emotional intelligence to provide a deep understanding of behaviour and decision-making, delivering impactful insights that make a difference. Our solutions span several industries, including:
Market Research
Employee Experience
Student Experience
Society Experience
Have a challenge we can help solve? Get in touch to learn more.
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