At inVibe, we talk a lot about “what is said,” “how it’s said,” and “how it sounds.” 

 is evaluated using discourse analysis, and 

 is measured using our machine learning models. Until recently, our language experts had to manually integrate these three aspects of the response to uncover “why it matters,” but now anyone using our dashboard—not just those of us with expert training—can use our new Topic Analysis tool to produce actionable insights.

Topic Analysis combines three core features of the inVibe platform to help any user quickly uncover the emotions associated with individual topics of interest: 1) 

computational analysis of emotion in the voice

, 2) automatic detection and tagging of naturally emerging topics and themes, and 3) 

, our model works like a literary detective that groups words often found together in and across responses into “topics.” For example, words like 

 might form a ‘Treatment Efficacy’ topic. Responses are composed of many topics in varying proportions as an individual naturally moves from one topic to the next.

Topic Analysis allows us to examine the voice data to see patterns across respondents at a glance as well as to zoom in to uncover underlying patterns across topics. For example, let’s say we want to get a quick sense of HCP reactions to new data released at a major oncology conference. Topic Analysis identifies the key topics in HCP responses (e.g., ‘Efficacy of Targeted Therapy,’ ‘Toxicity Profile,’ and ‘Treatment Decision-making’) and aligns them with their associated emotionality in the voice (e.g., 

Just looking at the most discussed topics in reaction to these two data releases, we see pretty equal time spent discussing ‘Clinical Trial Data Impact’ but with very different emotional tones. HCPs are more 

 about the Sabari study’s clinical impact than the Reckamp study’s impact, which they are more 

toward. This leaves us with the obvious question “What’s driving this optimism?”

To begin to answer this question, we just click the topic of interest to have immediate access to all the responses where this topic is discussed. This page includes an AI Smart Summary of how HCPs in aggregate discuss the topic and a fully interactive chart that allows users to drill down into how it is discussed in individual responses.

If we want a more in-depth comparison between topics, we turn to the Compare Topics feature, which plots all discussions of one or more topics of interest within and/or across questions. When we click an individual response, the tool highlights which portions of the response align with that topic and situates them in their original context, which allows anyone to quickly see what’s driving differences in emotionality and how those differences manifest in the language used.

Upon inspection, we see that HCPs are more optimistic about the Sabari study because of the promising efficacy outcomes in a difficult-to-treat patient type while they are more neutral toward the Reckamp study because they view the data with greater uncertainty, viewing it as more preliminary and in need of confirmation. In just a few clicks, we provided the sponsor of the Sabari study with insight into the “why” behind HCPs’ reactions to their data and with the assurance that their competitor’s data reported in the Reckamp study is still years away from having an impact on treatment decision-making.

Topic Analysis transforms complex voice data into clear, actionable intelligence for anyone and empowers commercial and clinical teams to move beyond surface-level insights by revealing not just what people are talking about, but how they feel about it—enabling faster, more nuanced decision-making grounded in real human emotion.

Are you interested in learning more about how our AI-enabled platform can make your qualitative research simpler, more systematic, and more scalable? 

Learn how our new AI-enabled tool has simplified voice analysis to empower commercial and clinical teams to quickly and easily distill rich insights without expert training.

Introducing inVibe’s Topic Analysis Tool: Transforming Complex Voice Data into Actionable Insight Grounded in Real Human Emotion

Quantitative and qualitative data are powerful on their own—but when you bring them together, that’s when the real magic happens. Numbers can tell you what’s happening, while voices and stories help you understand the ‘why.’ That’s why we’re excited to introduce a new update to our inVibe dashboard—bringing quant and qual together in one seamless experience. We’re taking things to the next level by adding new 

We’ve made it easier than ever to see both 

—giving you a fuller picture of your research findings. Here’s what you can expect:

 – Instead of having to flip between different files or reports, you can now access the qualitative responses and most quantitative data all on the inVibe dashboard.

 – We’ve introduced clear, easy-to-read visualizations for quant data, including 

, so you can quickly grasp key metrics at a glance.

 – Need a high-level snapshot of your quant findings? The new overview page helps you see the most important data points all in one spot.

 – As you listen to qualitative responses, you’ll now see corresponding 

 right alongside them. This added context makes it easier to connect the dots and get deeper insights.

Check out the video below for a walkthrough of the updates from inVibe’s CTO, Jeremy Franz

Quant Overview

At inVibe, we know that some of the most powerful insights come from 

combining quantitative and qualitative data

—because understanding market trends is about more than just numbers. Quantitative data can help you see the patterns, while qualitative data gives you the context behind them.

, making it easier to connect the dots, validate key takeaways, and bring more confidence to your decision-making. Whether you’re tracking brand perception, evaluating messaging effectiveness, or uncovering unmet needs, our new update helps you get 

We’re excited for you to try it out firsthand. Current customers can log-in today and explore the new features. New to inVibe? 

 to see how our dashboard can enhance your research process.

—so you can uncover insights faster, spot patterns more easily, and make more informed decisions.

Ready to see it in action? Log in to your dashboard and explore the new features today!

Read on to see how our latest dashboard update brings quant and qual data together—making it easier to visualize key metrics, explore insights, and analyze research in one seamless experience. 

See More, Understand More: New Quant Views on the inVibe Dashboard

The Next Evolution of AI-Driven Qualitative Insights

At inVibe, we’ve always believed that the true power of qualitative market research lies not just in collecting voices, but in connecting them. Today, we’re excited to announce a breakthrough feature that redefines how clinical and commercial teams generate insights across studies: 

Built for life science and pharma companies conducting clinical or commercial market research, this upgrade expands our AI chat capabilities beyond single-study analysis. Now, you can explore patterns, compare findings, and validate themes across your entire library of inVibe studies—all through a seamless conversational interface.

But this isn’t just another chatbot. Let’s dive into why.


How inVibe’s AI Chat Differs: Thematic Saturation Over Needle-in-a-Haystack Queries

Most AI tools treat data like a puzzle to solve: 

 But qualitative research isn’t about isolated facts—it’s about understanding 

How prevalent is a perception across participants?

Does a finding hold true across disease states or patient cohorts?

Are emerging themes consistent over time?

Traditional chatbots fail here. They prioritize speed over depth, often omitting critical context to fit token limits. inVibe’s AI, however, is engineered to 

 while preserving conversational flexibility.

Our single-project chat already solved this challenge

 (questions, verbatims, metadata) into the context window without sacrificing token space for dialogue.

Now, we’re scaling this rigor to multi-project analysis.


How Multi-Project Chat Works: Precision at Scale

“How have patient perceptions of treatment side effects evolved post-pandemic?”

, our system doesn’t guess—it reasons. Here’s the technical backbone:

Step 1: Intelligent Source Data Retrieval

Your query triggers our most advanced LLM to scan your entire inVibe study library.

It identifies every dataset related to your question—

This ensures the most critical verbatims, themes, and metadata are prioritized, even across dozens of studies.

The selected data is embedded into a fresh context window, and our AI analysis tool generates insights grounded in the aggregated source material.

Multi-project Chat Demo

Prefer hands-on curation? Use our manual selector to pick projects or questions to include to combine automated rigor with human expertise.

Why This Matters: Turning Data Libraries into Strategic Assets

For clinical and commercial teams, the implications are transformative:

: Track shifts in respondent sentiments and opinions over time without manual data stitching.

: Confirm if a theme exists across research engagements, i.e., does your psoriasis study align with rheumatoid arthritis insights.

: Forget hunting for “that one study from 2022.” The AI surfaces relevant data 

every new inVibe study enriches your insights ecosystem

. The more research you conduct, the richer the context for future queries—whether about a specific drug launch or broader market trends.

The Technical Breakthrough: Mastering Context Window Economics

Large context windows (like GPT-4’s 128k tokens) still have limits. Off-the-shelf tools waste tokens on redundant or irrelevant data. inVibe’s system optimizes them by:

: Balancing depth (verbatim coverage) and breadth (cross-study representation).

: Enhancing search accuracy through pre-embedded codes (e.g., “patient journey stage: adherence”).

: Decoupling data retrieval from analysis to avoid token spillover.

Build Your Library, Future-Proof Your Insights

Multi-Project Chat isn’t just a feature—it’s a paradigm shift. By centralizing and connecting qualitative data, life science teams can:

Turn archived studies into living assets.

The more you build your inVibe library, the smarter (and faster) your analysis becomes.

Current customers can access Multi-Project Chat in their dashboard today. New to inVibe? 

 to see how AI-driven analysis can transform your research.

Discover how our AI-powered chat evolves to help life science teams explore themes across studies—not just within them.

Unlocking Cross-Study Insights: Introducing inVibe’s Multi-Project AI Chat for Deeper Market Research Analysis

on June 2020 by Beth Baldys and Tiffani Shovlin.

Can the way healthcare professionals speak reveal their attitude about specific medical treatments?

What if you could evaluate the market opportunity for a rare cancer treatment by decoding the acoustic and linguistic data from hematologists and nurses to understand how they truly feel about an upcoming cancer treatment?

Well, you actually can. But don’t take my word for it. Listen to 

 as they explain how inVibe helped Taiho get rich insights from stakeholders by leveraging their deep listening voice research platform.

 and tap into the world’s top language experts and the industry’s most advanced speech emotion recognition algorithm to get actionable linguistics insights from the spoken word.