Recruiting appropriate and engaged respondents is arguably the most fundamental and challenging component of market research for the life sciences. Traditional qualitative and quantitative recruitment strategies not surprisingly utilize traditional approaches, which are single-sourced, laborious, expensive, and difficult to scale. Inclusivity and diversity have also remained significant ongoing obstacles, biasing results and making them less representative.

Here at inVibe, we take tremendous pride in adapting cutting-edge techniques and technologies to transform and optimize every aspect of the market research process, from recruitment to data collection, analysis, and reporting. Sensitive to legacy recruiting problems, we’ve developed innovative processes that are analogous to our other tech-enhanced omnichannel, multi-sourced, asynchronous, inclusive, and scalable capabilities. Here’s how we do it…

Step 1: Create an Audience Profile & Establish Screening Criteria

Finding optimal respondents begins with precisely defining whose voices need to be heard for our clients to achieve their market research goals. For example, if study teams  want to determine the effectiveness of patient educational materials for a clinical trial, then the audience profile for an inVibe study must generally match the inclusion-exclusion criteria of the trial itself: proper age, specified condition, prior therapies, and all other relevant qualifiers.

These prerequisite characteristics are then translated into screening criteria to ensure all participants are relevant for the inVibe study. Screening questions vary in number and depth based on the specificities prescribed by the audience profile and are administered through the same smartphone-delivered tech the recruited subjects use to complete the study. The inVibe experience is therefore seamless for participants from recruitment through data collection.

Step 2: Multi-Source Subjects & Dynamically Vet Them

How are candidate patients, caregivers, and healthcare professionals found? inVibe’s recruitment technology (our “Bat Signal”) allows us to instantly reach out to multiple sources, primarily dozens of vetted panel partners, but occasionally opinion leaders, advocacy groups, online communities, and expert consultants as well. Clients may also provide lists, sites, and participants. We team closely to ensure all candidates precisely match the study parameters; while outreach on mobile tech helps ensure inclusivity, diversity, and proportional representation.

The sheer ubiquity of smartphones enables otherwise marginalized and frequently disenfranchised patient communities to actively participate in market research. Increasing representation from minority populations is especially important for clinical studies, and can meaningfully influence and benefit trial designs – where recruitment and retention remain chronic and arduous challenges, too, precipitated by neglecting patient needs.

Step 3: Data Collection & Quality Assurance

Once qualified candidates are found, the inVibe platform seamlessly accommodates and scales into a sophisticated data collection interface. Vetted respondents receive various stimuli directly on their phones, and are encouraged to record their candid voice responses. A 

hybridizes AI and machine learning engineering with linguistic experts to ensure these responses translate into meaningful insights and actionable recommendations.

Response quality is continuously evaluated

 to make sure data originates from the precise target audience and satisfies basic criteria, including completeness, relevance, richness, and emotional resonance. The dynamic nature of the recruitment and data collection also enables inVibe and our clients to flexibly tweak the evaluation criteria through increasing honoraria, extending field duration, changing the screening filters, and other quick adjustments.

By transforming market research for life science companies with cutting-edge voice-response, analytics, and reporting technology, inVibe has redefined each milestone of the process. From recruiting through data collection and reporting, inVibe empowers participants and the clients eager to hear from them with omnichannel, multi-sourced, asynchronous, and scalable tools reflective of how consumers are already engaging with personalized, on-demand services.

As patient and HCP populations are increasingly nuanced, demanding, and diverse, effective recruitment for market research becomes proportionally more challenging. Utilizing tech already successfully adopted by Apple, Google, Amazon, and other Big Tech giants, inVibe has revolutionized insight gathering for life sciences companies, while ensuring the privacy of its data for subjects and clients alike. 

Reach out to our client services experts to learn how

How inVibe Finds the Voices You Need to Hear

Revolutionizing Market Research Recruitment

Patient-Focused Drug Development: Methods to Identify What Is Important to Patients

" as its second in a series of four guidance documents about incorporating patient voice into the drug development process. The resource highlights the benefits and drawbacks of various qualitative, quantitative, and mixed-method research types. In response, Head of Client Services, 

how inVibe supports and enhances this mission of listening to patients

 with our proprietary Listening Platform, enabling clients to gather deep and nuanced qualitative insights with the efficiency and scalability of quantitative research.

Another key takeaway from this guidance is the need to alleviate the research participation burden on respondents. While hearing patient voices is essential to the drug development process, patients may be deterred from participating in research activities if the requirements are particularly cumbersome. To that end, research should be as easy and unobtrusive as possible to encourage engagement. Fortunately, the inVibe platform is the perfect tool for capturing the patient voice conveniently and confidentially.

Collecting rich qualitative data appears to be a fundamentally inconvenient endeavor for all parties, particularly patients. From the administrative perspective, traditional qualitative methods require finding a time that works for multiple parties, one-on-one in-depth interviews, or a focus group. Once the headache of setting a time is taken care of, patients must plan around this event, which can interfere with competing priorities. Then, they may have to travel to a location for an in-person engagement. Finally, the actual interview takes time, perhaps an hour or so. Hence, a "one-hour interview" can quickly require a more significant time investment and cause more inconvenience than initially indicated.

With the asynchronous inVibe approach, much of the logistical burden disappears. The prompts are pre-recorded and programmed into the voice response study on our platform. Therefore, patients must call in, listen to the prompts being read, and record their answers, like leaving a voicemail. Since it's not a live interview, patients can participate whenever and wherever they please. Whether it's more convenient for them to call from the bleachers of their kid's softball practice on a Saturday afternoon or their living room couch on a Tuesday evening, or if they felt too tired on Sunday morning but ready to call in on Monday morning, inVibe allows patients the flexibility to join a market research engagement on their terms and when they feel up to it.

Furthermore, the asynchronous inVibe platform saves patients time with our designed automated prompts. Since we don't "probe" as an interviewer would, we combine a couple of similar questions into one prompt, encouraging patients to elaborate on their own. Therefore, instead of having an interview that chips away at eight topics over an hour, each of our eight prompts immediately goes deep, leading respondents to answer all eight prompts in a matter of 15-20 minutes on average. Manager 

 that asking just eight targeted prompts concisely captures a breadth and depth of insights while avoiding respondent fatigue.

But don't just take our (written) word for it! Earlier this year, inVibe conducted a study among patients, caregivers, and HCPs comparing inVibe's voice response studies to traditional moderated in-depth interviews. We heard across stakeholders that they prefer our platform for how it facilitates easy and quick participation. In the video below, listen to one patient and one HCP reflect on how convenient it is.

Besides the time pressures in traditional qualitative research, there can also be an emotional burden when discussing sensitive subjects face-to-face with strangers. For example, medical history is often very personal, so asking patients to be vulnerable about the journey to diagnosis or what a bad day looks like with their condition can be fraught. Moreover, fearing judgment from interviewers or focus group attendees, patients may withhold information, painting only a limited picture of their experience. Conversely, we know from 

 that patients are more willing to speak about "embarrassing" topics on social media (Facebook, forums, etc.) than through traditional methods; the anonymity afforded by such platforms makes it easier to share specific intimate details.

inVibe's asynchronous platform solves this trade-off between collecting sensitive voice data and maintaining patient comfort by enabling patients to participate anonymously. When they call in, they do not see or speak to anyone. The recording patients listen to for each question is the only voice, and we only collect audio recordings in their responses. There is no interviewer they interact with in live time; it's just them, and they have all the time they need to answer the prompts without interruption. In addition, patients don't have to worry about a moderator's or fellow panelist's disapproving reaction, so they can speak freely without judgment. While opening up about challenging topics may never be easy, the inVibe approach works to remove common barriers that inhibit honest communication.

Listen to the video below to hear a couple of patients explain how speaking to a recorded voice is more comfortable than a moderator, reducing self-consciousness and vulnerability.

At inVibe, understanding the patient voice is at the heart of what we do. Our asynchronous Listening Platform makes it logistically and emotionally more accessible for patients to speak with us about their experiences. Collecting rich data while avoiding friction points familiar with traditional qualitative methodology enables us to deliver deep insights with low impact on patients' daily lives, just as the FDA advises. Are you interested in seeing it for yourself? 

‘inVibing’ qualitative research to alleviate logistical and emotional patient burdens

Imagine: A Patient-Centric Listening Platform

 has had a busy year; for the fourth year in a row, joining the ranks of the Inc. 5000 list of fastest-growing private companies and merging with the decentralized clinical trial platform, 

. Earning the rank of #3,519 on the annual list, inVibe continues to revolutionize healthcare-focused market research.

“Digital innovation has helped companies deeply understand the needs of customers, and in no industry is that more important than healthcare,” insists Fabio Gratton, inVibe Co-founder, CEO, and Chief Experience Officer at THREAD. “We built inVibe with the goal of removing all the barriers between discovering the needs and expectations of patients and professionals and the life science companies that serve them. Ranking on the Inc. 5000 list validates our success, and merging with THREAD paves the way for even greater public health benefit.”

Through a mix of human expertise and technology, inVIbe has created a new paradigm for market research. By seamlessly integrating voice-based data collection from smartphones, linguistic and machine learning analytics, and dynamic reporting techniques, inVibe provides invaluable end user insights across the entire drug development and distribution life cycle. And by providing these capabilities to clinicians managing decentralized clinical trials, the industry is further empowered to create cutting-edge therapeutics for increasingly diverse populations.

At the heart of the inVibe market research revolution is their ability to tap into the depth and emotional resonance of the human voice. Conventional market research surveys and even observational studies collect a limited amount of data, which is often biased. inVibe instead collects megabytes of voice data and then fed into the industry’s most advanced analytical platform. The multidimensional voice input is the source of unique insights that drive actionable recommendations for optimizing clinical trials and downstream communications.

“Apple, Google, and Amazon are valued at over a trillion dollars thanks to their unprecedented ability to understand the consumer experience,” adds Fabio. “inVibe has adapted many of these same tools for healthcare market research. If Alexa can drive billions in eCommerce, then there’s no reason inVibe can’t offer similar innovation and power to better understand consumers for pharma. We’re honored to be ranked for the fourth year on the Inc. 5000, and feel our merger with THREAD adds a new dimension to our proven impact on public health.”

For more information about inVibe and how you can listen to your customers in a new way, please visit 

. And for more information about their new parent company, THREAD, visit 

inVibe has revolutionized market research for healthcare companies through voice data collection, machine learning, linguistic analytics, and dynamic reporting. Their unique approach has empowered major pharmaceutical companies, marketing agencies, universities, and healthcare startups with the capabilities to better understand patients, caregivers, and healthcare professionals—and translate those insights into actionable recommendations for brand growth. For more information, please visit 

THREAD® is the industry-leading decentralized clinical trials technology and consulting service provider, helping biopharma and CROs decentralize clinical research and enable electronic clinical outcome assessments (eCOA) for sites, participants, caregivers and home health professionals. Through its unified platform, THREAD is making studies 30% more efficient and five times more inclusive and diverse. Backed by health care investors Water Street Healthcare Partners and JLL Partners, THREAD is recognized as a leader by Everest Group’s Decentralized Clinical Trial Product PEAK Matrix® Assessment 2021, Frost & Sullivan’s 2021 Customer Value Leadership Award, as well as a long list of accolades. Visit 

Its prestigious Inc. 5000 list, produced yearly since 1982, analyzes company data to recognize the fastest-growing privately held businesses in the United States. The global recognition that comes with inclusion in the 5000 allows the founders of the best business an opportunity to engage with an exclusive community of their peers and the credibility that helps them drive sales and recruit talent. The associated Inc. 5000 Vision Conference is part of a highly acclaimed portfolio of bespoke events produced by Inc. 

Companies on the 2022 Inc. 5000 are ranked according to percentage revenue growth from 2017 to 2021. To qualify, companies must have been founded and generating revenue by March 31, 2017. They must be U.S.-based, privately held, for-profit, and independent—not subsidiaries or divisions of other companies—as of December 31, 2021. (Since then, some on the list may have gone public or been acquired.) The minimum revenue required for 2017 is $100,000; the minimum for 2021 is $2 million. As always, Inc. reserves the right to decline applicants for subjective reasons. Growth rates used to determine company rankings were calculated to three decimal places. There was one tie on this year’s Inc. 5000.  Companies on the Inc. 500 are featured in 

’s September issue. They represent the top tier of the Inc. 5000, which can be found at 

Market Research Innovator inVibe Joins Inc. 5000 List of Fastest Growing Companies in America for 4th Year in a Row, and Merges with THREAD 

Why study HCP reactions to new data releases at conferences?

Whether you are a newcomer to a disease state, an established force in the market, or even an interested outsider, it is not enough to just know the treatment landscape as it is. You have to know what is coming up in the field and to be in the midst of the innovation that drives every therapeutic area forward. Of course, manufacturers participate in this innovation most directly through clinical trials. However, as treatments continue to be developed and researched, understanding how new data is being socialized among professionals can provide valuable insights into the future of the market landscape.


Fortunately, we can capture the socialization of and reaction to new data at the many professional conferences that occur every year for all manner of disease states. By assessing providers’ thoughts on new data, we can better understand how it could impact their practices and decision-making.

At most medical conferences, new data about treatments naturally take center stage, and inVibe’s 

 studies often use these abstracts as stimuli. However, it would be reductive to say that we are truly studying the abstracts themselves. Our job is to gauge reactions to these abstracts from the HCPs who might (or might not) eventually act on that information. In our experience, the best way to elicit those reactions is to simply get these HCPs talking, which inVibe’s voice response methodology is built to do.


As a result, we have a very straightforward process for developing a new data intelligence study to fit the client’s needs. First, we collaborate with the manufacturer to see what abstracts they most want to gauge reactions to, whether their own treatments or potential competitors. Then, we design our study around those abstracts in order to get at the heart of whatever strategic question we are trying to answer.

Despite the straightforward process we use to build our new data intelligence studies, our methodology can be quite flexible to whatever will best serve the sponsor’s strategic needs. Abstract reactions are always a component of this research, but new data intelligence is also a golden opportunity to trace broader trends and attitudes driving current and future treatment decisions. With inVibe’s framework, we can balance our core goals of following reactions to new data and understanding the treatment landscape this new data is affecting. In addition, our flexibility means that we can emphasize one or the other goal in order to best serve your needs.


For our abstract-based new data intelligence research, we conduct the study immediately after the conference and allow HCPs to review the abstracts before and during their response.  Our team designs the questions to allow HCPs to react to the abstract on its own terms and then put it in the context of their own practice.


This process allows us to gain a deeper understanding of when there are disconnects between positive study outcomes and a lack of any predicted impact, due to factors beyond the results themselves. Let’s think about oncology for an example. Perhaps a new treatment or endpoint being used is not accessible for all practice settings, or perhaps HCPs are already satisfied with a treatment regimen they currently prescribe and are uninterested in alternatives until it shows there is a mature, definitive advantage. We can uncover these less obvious issues simply by listening to these HCPs, and understanding both what they’re telling us and how they say it.

While we are more than capable of partnering with clients on treatment landscape work at any point in a treatment’s trajectory, perhaps one of the most compelling times to do this work is right when that landscape is shifting - when new data about treatments are released and discussed among professionals. At conferences, HCPs think about the future of their practice and interrogate their own strategies. While they are in this mindset, they can share some incredible insight with us outside of the context of abstract reactions.

We can ask HCPs about their current treatment strategy for a patient in a specific subpopulation, and their answer will always be useful in some way to you. However, when we ask this question as a part of conference intelligence, we can capture this answer while it is changing, which can sometimes provide a clearer strategic picture than if we were simply asking about the treatment itself. This is how we find pain points and insufficiencies in current practices, and we can hear how eager HCPs are for solutions that would resolve those problems. It’s not only a fascinating listen, but also an extremely valuable insight.


How do these studies work in a remote world?

One major advantage of inVibe’s study methodology is that it works regardless of whether the conference is held in person, remotely, or some hybrid of the two. HCPs attending a conference remotely can simply use the same tools they used to access the conference to participate in our studies. There is no need to stack travel pressures on top of existing stress for traveling attendees; all they have to do is call and share their thoughts. We can field, analyze and report quickly enough that the insights are still topical, significant, and valuable for any conference in any therapeutic area.

It is an exciting, if kinetic, time to be involved in the development of new treatments. Keeping up with the flow of information can be intimidating.

inVibe is uniquely poised to find the most important and actionable elements of new data, condense that information into a digestible format, and offer strategic partnership to stay on top of the shifting landscape. Whether you have questions about how prescribers react to new data or what priorities are driving their current strategies, we can work with you to answer them.

How inVibe finds the most important and actionable elements of new data

New Data Intelligence: An ear to the future

“Making data collection more efficient, analysis more effective, and insights more actionable.” Such core tenets of inVibe sound pithy and exciting, but perhaps also opaque. How does inVibe truly actualize these aspirations?

The short answer is: We rely on a harmonious blend of skilled humans and cutting-edge technology throughout the project lifecycle, but especially in the analysis phase. On the human side, we have our expert linguists critically investigating the data, forming initial hypotheses, and gleaning deep nuances across responses. Technologically speaking, our bespoke software solutions facilitate and augment our linguists’ discoveries. Together, we’re able to dig deeper into three main areas: what is said, how it’s said, and how it sounds.

Understanding on the most basic level what information our participants conveyed to us is the first step in the analysis journey. After our fielding closes and all responses are in, our linguists set aside dedicated time to simply listen to the data, discover trends and notice anything particularly intriguing or surprising. We also account for any budding hypotheses that we’re interested in exploring further. This initial pass-through of the data and concurrent notetaking ensures we have a sense of each question’s big picture and a rough idea of what key aspects we may want to investigate further in subsequent listens.

With this vague roadmap in hand, we begin to further investigate the responses, breaking them up into meaningful categories in a process known as “tagging.” While we could categorize the data with existing tools like Microsoft Word and Excel, that can be inefficient and inflexible. Luckily for us, the inVibe product team has built a custom online dashboard that allows tagging responses in a clear, quick, and user-friendly way. Once we tag all the data, we can easily sort through tags to see what themes are most prevalent across participants, which allows us to focus our analysis and reporting accordingly. Here you can see tagging in action.

After listening to and tagging all responses for content, we want to dive into the nuances of the language participants use in their answers. This is because as linguists, we know that so much of what we mean is implicit, existing beneath the surface of the literal message. To more deeply understand how we should interpret responses, we “read between the lines.” On a broad level, our linguists analyze how participants 

 their responses. What information do they bring up first? What ideas do they repeat? What are those “noisy silences,” or things left unsaid? Narrowing in, we listen for the 

of language participants employ to express their thoughts. Do they vocalize doubt through hedging – words like “guess” or “unsure”? Are they enthusiastic in their responses, indicating positivity through words like “excited” or “great”? Do they use intensifiers (e.g. “so,” “very,” “extremely”) to emphasize certain points? Taken together, participants’ answer structures and specific language add color and validity to 

 is said, illuminating what is top of mind to participants and how they actually feel. 

Alongside our linguists’ expertise in the realm of “how it’s said” comes 

our AI-powered sentiment analysis algorithm

, which our product team co-built alongside Edge Analytics. Sentiment analysis is a natural language processing (NLP) technique performed on textual data that determines whether data is positive, negative, or neutral. Our algorithm is particularly adept at “subject-aware” sentiment analysis, meaning it specifically considers whether the language used in relation to the subject of the phrase is positive or negative rather than the response on the whole. Such a tool reinforces and supplements our team’s human-powered analysis by scrutinizing language sentiment in context, contributing to a more accurate interpretation of responses.

The final piece of the analysis puzzle is to zoom out above the level of what content is conveyed and what words and structure are used to convey it to understand how it’s conveyed acoustically. In other words, how do “contextualization cues” — features like pitch, tone, and pauses — clue us in to how we should perceive these responses? 

 covers this topic much more in-depth, but simply put, this is once again a partnership between humans and tech. First, our sociolinguists are especially trained to deeply listen for and note these nuances, which validate and enhance our existing analysis. Our intuitions are expanded upon by our established, rigorously tested speech emotion recognition (SER) algorithm, which tracks these contextualization cues present in each response and “translates” them into approximate emotions by scoring valence (positivity), activation (interest), and dominance (confidence). Our tools enable us to plot these emotions on a graph for each prompt, with one dot corresponding to one respondent. Such technology allows us to “see what we hear,” painting an even clearer, more definitive picture of language data for our clients.

This graph represents multiple HCP respondents in terms of their dominance "confidence" (x-axis) and activation "interest" (y-axis) for one prompt. Most responses are falling to the right side of the x-axis, indicating respondents’ more confident and assured as opposed to wavering and unacceptable

At inVibe, we embrace a partnership between human and technological expertise to simultaneously simplify and strengthen the analysis process. We see the value in building unique analysis tools for our researchers because that enables us to deliver more pragmatic insights for our life science clients. If you’re interested in learning more about the inVibe approach, reach out to 

How the inVibe Listening Platform makes data collection more efficient, analysis more effective, and insights more actionable

Imagine: A tech-enhanced, human-led analytical approach 

If you’re familiar with market research, chances are you have a good idea of what an excellent response 

 like. The participant is emotionally engaged and clearly demonstrates their feelings through the speed, volume, and tone of their voice. They talk at length about relevant topics and supply information that directly serves your research goals, addressing every aspect of each question in depth. In short, not only do their answers dazzle—so too does their delivery.

Responses like these can easily stand alone as persuasive testimonials for a wide range of stakeholders. But at inVibe, we don’t just capture what people say—we also help clients strategically harness the power of their words. The better the data we get, the more actionable the insights we can produce. This is why we’ve established rigorous data quality control (QC) procedures that ensure that the responses we collect meet our high standards. Years of honing our process based on research and experience has enabled us to develop a robust, multi-tiered screening system to maximize data quality for analysis.

Our data QC process begins long before we’ve even collected anything, during our study design phase.

Over the past decade, inVibe has presented participants with over 9,000 voice prompts, each of which has been engineered to elicit the richest possible responses. In addition to drawing on our linguistic and behavioral expertise to inform design, we also maintain a comprehensive prompt library where we catalogue and score each prompt based on relevant parameters (such as topic, research goal, and quality of responses elicited). This allows us to repurpose previously successful prompts from similar projects and customize them as needed when designing new studies.

The next portion of our QC process takes place during data collection. We typically over-recruit participants by about 10% and only close the field after we’ve evaluated the quality of the responses we’ve received. This leaves us room to screen out those that don’t satisfy our high standards while still comfortably meeting our quotas. What’s more, our automated technology allows us to collect additional responses speedily and efficiently, while other qualitative methods require a significant investment of time and resources for each interview.

After we have sent out our study, our QC process culminates with our team of trained data validators. Two or more validators may evaluate each response to ensure consistent data quality within and across projects. The end result is a dataset that comprises only on-target, detail-rich responses that our analysts can draw the most useful insights from. Before we begin our analysis, though, we listen to each and every recording in order to assess the quality of the answers and of the audio.

Our validators begin by assessing answer quality. We score responses to each question on a scale from 1-5, with 5 being “excellent,” 3 “acceptable,” and 1 “poor.” These comprehensive scores take into account the following criteria:

1. COMPLETENESS: Does the participant answer the main question? Do they answer each of the follow-up questions?

2. RELEVANCE: Does the participant provide relevant information? Do they talk about what we want them to talk about?

3. RICHNESS: What level of detail does the participant delve into? How nuanced is their response?

4. EMOTIONALITY: To what extent does the participant demonstrate emotion? How personal is their response?

High-scoring responses demonstrate high compliance, relevance, richness, and emotionality, while those that score low exhibit poor quality or lack of usability. Instead of accepting low-scoring responses, we send participants invitations to re-record that contain broad instructions on how to improve the quality of their answers (e.g., “Please provide more detail on the decision-making process you discussed in Question 2.”).

When all responses have been scored for a participant, the average score across responses makes up their “overall rating.” This rating serves as a benchmark for final screening decisions, when validators use it to sort participants into one of 3 buckets: “good,” “border,” and “poor.” Good responses enter the final data set, while poor responses are filtered out. Border responses, which meet our baseline of acceptability but do not exceed it, are filed away as a backup. Our team only includes them in the final data set if we are unable to fill our quota entirely with “goods” after undertaking every possible effort to do so.

We perform audio quality checks to make sure that our analysts can clearly hear all of the voice data. (After all, this is the cornerstone of what we do!) We want to make sure that the audio has high fidelity so that our Speech Emotion Recognition software will produce accurate analyses. Too much background noise can throw off its careful acoustic measurements.

There are several criteria that each response must meet to pass audio screening:

No distortion or other audio interference

Responses that do not meet the above criteria are marked accordingly and withheld from our final data set. However, rather than throwing them away, we give participants the chance to re-record. If they choose to do so, their responses once again undergo the same QC procedures. 

Having successfully passed through every check in our QC process, the final set of responses are published to our platform. Using our interactive project dashboards, clients and analysts are able to engage with the high-quality data that results from our rigorous data validation process.

At inVibe, we always operate with our client’s end goal in mind. This means that we are not only a team of language experts, but also a team of innovators, modernizing traditional qualitative methodologies to maximize client research outcomes. Baking QC measures into every step of our research process is only 

 of the many ways that we do this. Innovations like these—client-centered and science-driven—are what enable us to remain at the forefront of research. 

How inVibe collects top data for deeper insights 

Imagine: Ensuring Only the Highest Quality Voice Responses

inVibe turns traditional qualitative research on its ear through our easy and accessible Listening Platform. Our platform provides a solution for participants to share their stories in their own time, on their own terms, and without fear of judgment by eliminating the need for a moderator.

inVibe has created a convenient, efficient, and systematic platform to collect these important participant stories. We capture narratives that address our clients’ objectives with our thoughtful and intentional study design, focused on the participant experience and leveraging our team’s expertise.

, one of our Senior Analysts, shared in a 

 that the goal of our Voice Response Studies is to prompt respondents to answer a series of questions thoughtfully and thoroughly. We specifically craft our prompts to be thought-provoking and to encourage respondents to pull from personal experience in their unbiased and authentic voice. Starting with the inVibe Prompt Library, which contains thousands of carefully crafted prompts we’ve asked over the years and measured to determine which delivered the most robust response, we design each prompt to meet the objective of our clients.


An example prompt might be something like the following: “Please describe how your condition impacts your day-to-day life. What frustrations or challenges do you experience? And what have you done to adjust to these challenges?” We phrase the prompts as a series of questions to be linear, easy-to-understand, and reflective of how respondents have approached similar questions in prior studies in order to solicit a complete narrative around a central theme.

We collect data in a way familiar to participants: it’s just like leaving a voicemail. Our studies use a real human voice to read the prompts aloud, like the recording in a voicemail box. Participants respond, often with a goal in mind of what to say, but then they may start to ramble. This shift to stream-of-consciousness may result in a “confessional” way of talking. ‘The Confessional Effect’ allows the participant  to speak more openly and authentically, touching on the questions in the original prompt before expanding in a less-prepared, more-improvisational manner. This stream of consciousness is also free from judgment as respondents are more able to quasi-monologue their stories.

Listen to how this caregiver feels as they reflect on the naturalness and ease of using our automated voice response study:

“[When] I did an automated interview for the first time, I was actually surprised how natural it felt to answer a question with an automated response. So, while the moderated response was very normal and typical and natural, I think that then trying the automated response, I was pleasantly surprised to how easy it was to answer questions and then hit accept. Because I think with new technology now, and even just with leaving voicemails, it was easy to answer a question and leave a message kind of idea, how you can leave people voice messages. It was not out of the ordinary to do an automated response with the automated interview. While the moderator was natural, I was pleasantly surprised at how natural it was to do the automated response as well.”

One of the unique aspects of 'inVibing’ research is that it is, by default, carefully controlled for consistency since the questions are pre-programmed. This highly structured way of conducting qualitative research  allows for responses between participants to be directly compared. It gives our analysts a quantitative element along with the rich qualitative data to draw actionable insights from including less obvious themes that are as notable for their absence as for their presence.

To get a better sense of our methodology, 

 to how a patient answers the question “If your experience living with this condition were a book, what would its title be and why? And what would you name the chapter you are currently in?” Notice how she elaborates on why she’s called the book “The Journey to the Summit,” explaining the metaphor for her journey with rheumatoid arthritis, but also rationalizing the decision for her titles as she goes into detail. You can hear how she not only answers the prompt but gives in-depth descriptions.

To demonstrate how much of her answer is devoted to answering and expanding, we’ve highlighted direct answers in 

so I would say I would call this "The Journey to the Summit," the summit of the mountain being like having a great life, and living the best life you can.

 You know, when you're climbing and hiking there are parts of it where you're like, "I feel amazing. I'm killing this hike, I'm doing it." And you feel great. Then there are some parts of the hike where you're down, you're tired, you're hungry, you're not sure if you're going to make it to the top. 

I think that that very much symbolizes arthritis, because there are days when I forget I have it, and I do everything I've ever wanted. And then there are days, or weeks, that go by where you're just debilitated. You can't move, you can't do what you want to be, and you're wondering if it's always going to be like that

. So, I think it is an up and down, but at the end of the day, when you get to the top at the end of your great life, you'll realize that you made it, you could do it, and you had a great journey. And so, I think that that's kind of what I would call it. 

I would say the chapter I'm in now is like "A Restart of the Ascent" because I'm still going up, but the last two years have been really tough.

 I've had a lot of RA flares, I couldn't get it under control. I had to take a ton of Prednisone, had some other medical issues come into it, and so it's just been a really rough two to two-and-a-half years. And so, I finally just found this Humira that's working for me. I'm finally off Prednisone, which is amazing, so I feel like I'm starting to feel more normal and forget that I have arthritis every day. So, I'm starting that climb back up, where I'm feeling great, and I've got this. And I'm going to crush it.”

Patients are not the only ones who go into great detail. Listen

to this caregiver answer the question, “Imagine if you could travel back in time and meet the person you were when you or your loved one were first diagnosed. What advice would you give them? How would you describe to that person how you feel now?” Here, her emotions come out as she reflects on a touchy subject and grapples with some of the decisions she’s made and the realities she’s faced as the parent of a child with epilepsy.

Once again, we’ve highlighted direct answers in 

I would just tell myself that to just keep searching, to keep fighting, to keep learning, and doing what's best for my daughter. 

I feel we have done so. I would advise myself to... I guess I would just maybe give what medications we're on now because the journey has been difficult because she wasn't seizure-free if you will. And now, because of the combination of medication that she's on after years of searching, now we're in a good place. 

So maybe I would just tell myself, try these medications at this dosage, because this is what works for her. I would also tell myself to be patient when it comes to friends that are outgrowing her and she doesn't communicate with the same way anymore because she can't keep up with them.

They're at a different level. That's been hard, I think on me. She has a very good circle of friends, but kids are kids and they notice the differences and she's just different and they know. And so I would say, be patient with that. But other than that, I mean, it's been a difficult journey, but we've always just done what's best for our daughter and we've always just taken on the next challenge fully and done very well with it, I feel. 

So maybe just the medication part would be the only thing that would be really heavy for me to say to myself.

In both instances of patient and caregiver, we hear so much more detail and have so much more clarity. They describe significantly more than just what the prompt asks, which helps our researchers understand the full story and tease out linguistic nuances more effectively.

Through inVibe’s proprietary technology and  methodology, we are able to 

 by providing participants the opportunity to tell their story in their own words without fear of judgment or without worry of expectation. In so doing, we challenge the norms of traditional qualitative research. You can hear participants’ experiences and feel their emotions, and that is exactly what we strive for at inVibe: to listen with empathy.

 and we will show you how it works and why it can give your insights an edge.

'inVibing' research to get richer in-depth participant insights

How inVibe Collects the Authentic, Unscripted, Confessional Participant Story

Imagine getting a ton of great insights from just a few questions. Imagine figuring out how to ask a patient or a doctor a question that will really get them talking. This is the main goal of voice response design at inVibe, and the process we undertake to achieve that goal needs to account for how people interact with each other and how they will interact with us.

There are two main “whys” of inVibe’s design process - why do we limit the number of questions we ask in a single study, and why do we use linguists to compose those questions?

When looking at inVibe’s voice response offerings, one question that likely springs to mind is “wait, why do we ask so few questions?” Indeed, when looking at a set of eight questions relative to the tens of questions that are common in most quantitative studies, it seems like there’s less opportunity to ‘go broad’ and cover all of the ground there is to cover in a given market research topic. Eight questions seems more like a probe or a follow-up rather than a useful first step.

This perspective is certainly understandable, however it couldn’t be further from the reality of the data those eight questions retrieve. The content we gain from our voice response platform, in addition to providing a great depth of insights on a single topic, can easily capture stakeholder opinions on several different parts of a treatment landscape or patient journey. This has everything to do with the fact that, fundamentally, we are not asking respondents closed-ended questions. We’re asking them what (and, often, how) they think.

This seemingly simple shift in approach, giving respondents control over the boundaries of the conversation, allows them to talk as much as they want. While the devil’s advocate view would be that people would give an extremely brief response and get on with their day, that simply does not match our years experience.

In 2021, the average respondent talked for about five and a half minutes. This is not the length of the entire engagement; it does not count them listening to questions. It is five and a half straight minutes of speech – voices of patients, caregivers, and doctors telling us what they think. This translates to hours of perspectives – enough to get immersed in, and certainly enough to derive powerful insights from. It is also in comparison to hours of in-depth interviews where less insight is gained.

Of course, there is a natural follow-up question: “if eight questions provide this much good insight, why not go for more?” The simple answer to this comes down to practicality. While a respondent tends to give a good deal of useful information with only eight prompts to focus on, there is a drop-off in response quality past that point, where people become fatigued, inattentive, and terse. Once we reach that threshold of when a respondent is starting to check the time, we lose thoroughness and depth. Frequently, we see respondents start to frame responses as repetitive, “like I said previously.” Those speech markers are a good sign that the respondent has lost their patience and that we would gain deeper insights by sticking with our methodology of eight questions.

How can we get respondents talking without making them feel like they’re being forced to talk, while using as few prompts as possible? Easier said than done. This is where it is important to have a good working knowledge of how interactions work and why we utilize the expertise of our trained linguists who both compose and analyze our voice response questions. We combine this theoretical background with experience in research design. With backgrounds in conversation analysis and discourse studies, our linguists have a sophisticated understanding of how people talk, which we can then match to the client’s goals to understand what kind of speech we want to draw out of stakeholders.

For example, if we want to understand more about HCP/patient interactions, we can prompt one or both of those audiences to reconstruct what a normal conversation at the doctor’s office sounds like. If we want to test claims that depend on disruptive new clinical data, we can ask a polarizing question that will prompt strong, honest opinions from experts.

In essence, our linguists have access to a large toolbox, in addition to the field experience to know what tool is right for the job. With these resources at our fingertips, the goal of getting respondents talking becomes much less daunting. This way, we can literally shape the discussions respondents have – not by introducing bias, but by giving them a loose structure through which they can speak their mind and provide valuable insights.

And once that part is taken care of, all we need to do is listen. When you are ready to listen, reach out to 

The why’s behind inVibe’s voice response collection process

Imagine: Gaining Deep and Meaningful Insights from just a Few Questions

As published in Drug Development and Delivery on April 5, 2022

Fabio Gratton began his career as a Hollywood scriptwriter. There, he learned that storytelling is difficult, but can be made easier by listening to people to discover their innermost needs and desires. And when he co-founded his first healthcare marketing company about 15 years ago, he quickly realized that pharma had an enormous unmet need — listening to patients and their impassioned stories about illness, treatment, and recovery.

Fast forward to inVibe, a voice research company founded in 2013 (and as of January 2022 has become a division of THREAD), where Gratton, as CEO, has applied this same empathy to market research. Somewhere between traditional quantitative (e.g., online surveys) and qualitative (e.g., focus groups and in-depth interviews) research was a gap where patients were not being sufficiently heard. He realized that innovative uses of digital technology could be adapted to collect, analyze, and deliver these stories back to clients.

 recently spoke with Gratton about patient-focused drug development (PFDD), inVibe’s language model, and the value this technology brings to a patient’s treatment journey.

Q: What progress has been made in patient-focused drug development and what are the continued challenges?

 The good news is that numerous governmental and industry-based initiatives have spawned a new era in patient-focused drug development. Although just getting started, PFDD has documented approaches to data collection, identified best practices and benefits/risk tradeoffs, and analyzed input on patient communications preferences

These efforts tap into the reality that patients are willing and oftentimes enthusiastic to share their feelings about the disease burden and their treatment journey with experts, and actively assist with the generation of evidence and actionable data. Unfortunately, company culture, limited cross-functional collaboration, and leadership hesitancy can create barriers for organizations. But even if those challenges are circumvented, the listening process itself is difficult and demands a new approach.

Human communication is messy. At inVibe, we realized early on that even after we got patients to share their deepest thoughts and feelings, we had another problem: How to extract key insights we could then report back to clients in a way that offers a chance to ask more questions, and provide actionable recommendations.

Q: What is GPT-3 technology and how is it extracting those key insights?

 Our solution is a combination of human expertise and next-gen technology. Trained linguists sort through the data and help organize it; and the latest machine learning algorithms, such as Generative Pre-trained Transformer 3 (GPT-3) enable unprecedented semantic analysis and search capabilities. Our clients benefit from a more thorough analysis and dynamic reporting, fulfilling our mission for clients to actually hear from patients and listen to them, rather than merely process and regurgitate data.

GPT-3 technology was created by OpenAI and is the most expansive machine learning model of its kind. Without exaggeration, the tech literally scans nearly the entire Internet to contextualize and extract meaning from our voice data inputs. The richness of qualitative data is also what can make organizing and processing that data such a challenge. With GPT-3, we are able to design algorithms for specific tasks that reduce busy work and allow analysts to quickly get to meaningful insights.

 By integrating GPT-3 technology, we have developed an algorithm to identify and extract patient concerns from open-ended questions that lead to increasingly specific and nuanced answers — often revealing concerns never before considered. With our machine learning capabilities and human-powered linguistic analysis, the industry has an unprecedented opportunity to listen to and extract key insights from patients throughout the drug development process. This mitigates potential downstream setbacks, and proactively enables study designers to focus on the needs and concerns of patients before drugs even hit the market.

To cite a specific use case, we recently applied the firepower of GPT-3 to the lupus clinical trial landscape, seeking to reveal patients’ preferences for study design and endpoints, and comprehension of patient-facing study materials. By offloading these tasks to a powerful language model, we were able to reveal rich qualitative insights in a much more streamlined fashion. Our technology worked like this: Patients were recruited and screened directly from their own smartphones; they viewed stimuli; listened to automated open-ended questions; responded by simply speaking; then their voice responses were analyzed using a combination of sophisticated software and human expertise. The results were shared with the client through dynamic dashboards that revealed key insights, and suggested actionable recommendations for the brand team.

Q: How are pharma and patients responding to this drug development approach?

 Clients have embraced the concept, and inVibe quickly demonstrated value across disease states ranging from diabetes to oncology. By empowering patients to record their candid feelings directly into smartphones and then analyzing it with a hybrid of human linguistic expertise and advanced machine learning technology, we have changed the game in research.

With proven success across the post-launch life cycle of pharma brands, we also soon realized the importance of applying this novel approach to the drug development process. Our hunch that providing a platform where patients could share their perspectives without friction was correct — and so was our belief that regulators would see it the same way, eventually proven by the FDA Patient Focused Drug Development (PFDD) guidance, and Congress recently passing the Cares Act that created new guidance to ensure patient voices are heard early in clinical trials.

Not only are the government and advocacy groups standing behind technology and linguistic integration into the drug development process, but patients appreciate their voices finally being heard. The end result is empowered healthcare stakeholders — and improved therapeutics. Because key decisions at the development phase have a cascading effect throughout the life cycle of a drug, companies can save considerable money and time — and provide better treatments — by accurately understanding the needs and expectations of their end users: the patients.

That excitement and rationale have also been instrumental in our decision to become a division of THREAD, a technology platform helping to decentralize clinical trials. Together, we’re best positioned to infuse the drug development phase with the power of the patient voice.

Q: What will this mean for the future of patient-focused drug development and personalized medicine?

 I have a Pollyanna outlook on life that permeates all the work that I do in healthcare. Despite the ongoing challenges to listening and understanding patients, I’m confident that the industry will evolve, and along with it so too will our capacity to improve the patient experience to the point where we’re not simply better at managing disease, but preventing it.

The key to accomplishing that goal is to embrace technology so that we empower our humanity. Researchers too often consider what they do, and how they do it, a pure numbers game, mistaking map with territory. In contrast, everything we do is ultimately designed to improve and extend human life. Technology is a means to that noble end. That’s why at inVibe we always start with the problems to be solved on our way to better listening to, and understanding, patients. As we tackle obstacles to data collection, analysis, and reporting, we also keep our minds and hearts on the vision of what an idealized future could and should be like for a healthy society. The future of patient-focused drug development is inspirational.

By better understanding end-users through patient-reported outcomes measures, researchers are already able to integrate these critical insights directly into their processes, methodologies, and even their study designs. The end result is to create more patient-centric trials with increased participation and retention, better study designs, and clinical results that precipitate more effective and safer treatments for all. By combining their dedication to patients and embracing the next-gen in market research capabilities, pharma is poised to catch up to the tech firms paving the way for the ideal consumer experience.

Drug development is only one of many opportunities for personalized medicine to come into its own. The patient experience must be integrated across every touchpoint and milestone in the patient journey. Thanks to this already proven combination of innovative technology and human-powered analytical expertise, those voices are not only being heard, but listened to, allowing for better understanding. Identifying differences between patients and heightening sensitivity to their needs, we are able to create a more personalized experience that improves the entire healthcare system.

Given how healthcare is often a matter of life and death, no initiative is more significant than improving public health. Patients are speaking, and pharma is, with the help of innovative market research, listening more.

An interview with Fabio Gratton

inVibe: Changing the Research Game With Voice

” as the second in a series of four guidance documents that describe how patients, researchers, medical product developers, and others can collect and submit patient experience data and other relevant information from patients and caregivers to be used for medical product development and regulatory decision-making.

The new guidance covers the various approaches to identifying what is most important to patients related to their experience with the burden of disease/condition and treatment. Essentially, the document covers a few core qualitative and quantitative research methodologies, with a focus on their respective strengths and limitations. Particularly compelling is the government’s focus on the importance of infusing drug development with patient voices.

The specific goals of the new guidance are to elicit what is important to patients, which may in turn help inform understanding of disease/condition and clinical trial design. The guidance also hopes to help the generation and use of patient experience data, including clinical outcome assessments and patient preference information, and also inform benefit-risk assessment. Let’s take a look, and discover how inVibe can help fill in some of the blanks.

Limitations of Qualitative Market Research: Cost, Comfort, and Computing

The new guidance breaks down qualitative research modalities into one-on-one interviews and focus groups delivered in-person, through telephone, and online/virtual meetings. In terms of strengths, in-person experiences empower researchers with the greatest flexibility, including the collection of verbal and non-verbal responses. But these sessions tend to be expensive, and inconvenient for patients who may have to commute, or during work hours, etc.

SImilarly, telephone interviews offer the benefits of lower costs and heightened convenience compared to in-person sessions, but are often fraught with technical difficulties and data collection challenges. Virtual meetings have become increasingly common thanks to the pandemic, yet are also compromised by tech and access issues, particularly for disadvantaged patient communities. Patient comfort is also a factor, as clinical settings can prove intimidating.

Limitations of Quantitative Market Research: Anonymity, Applicability, and Analysis

Quantitative research has the distinct advantage of scalability, speed, and cost, and typically comes in the form of surveys that ask closed- and open-ended questions. The former consists of a picklist that patients select from; the latter encourages subjects to submit their own written answers. Response options include yes/no, ratings, rankings, and visual scales. Surveys can be distributed in hardcopy or online, and processed singly or in batches.

Although relatively easy to administer, surveys not only lack the dimensionality and nuance of qual methods, but impose additional limitations on test subjects and market researchers. These include patient challenges with language, interpretation, and the sheer anonymity and depersonalization of the approach. Devoid of feedback or human interaction, results can be incomplete, compromised, or inaccurate – especially for underserved populations.


Supplementing Qual & Quant with inVibe: Voice, Value, and Virtue

The new guidance encourages patient-focused drug development through its broad overview of market research techniques, and implicit encouragement of the industry to infuse every aspect of clinical development with patient insights. By better understanding patient needs throughout, clinical trial design, recruitment, and retention can be heightened, ultimately cascading through the development trajectory to maximize public health benefits.


The inVibe voice-response platform empowers patients from all socio-economic backgrounds to candidly answer questions on their own devices, at their own pace, own their own time, and without the implicit bias of a moderator. Voice responses are collected and analyzed through a combination of machine learning algorithms and human linguistic expertise. Reports are dynamically presented and insights-driven, precipitating actionable recommendations for clinicians to improve processes throughout the development drug development lifecycle. It’s a simple, systematic, and scalable solution for the industry to collect, analyze, and understand the true voice of the patient.


“The new PFDD guidance from the FDA is an expression of the government continuing to encourage our industry to take a more patient-centric approach,” insists inVibe’s co-founder and CEO, 

. “Both quantitative and qualitative market research methods are proven effective, and inVibe was created to apply the latest technology and human expertise to overcome the limitations of each by bringing clinicians the depth and nuance of qual, with the efficiency and scalability of quant.”


All of us at inVibe are thrilled by the ongoing PFDD initiative and are eager to continue partnering with sponsors to ensure their patients are heard and understood throughout the process. Nothing is more natural to people than talking, and no device is more ubiquitous and easy to use than a phone. By encouraging patients from all walks of life and backgrounds to speak, pharma is finally listening at the critical points in the life cycle their voices are needed the most.

How inVibe Supports and Enhances the new FDA Guidance on Patient-Focused Drug Development

As humans, we have natural instincts about how to interpret speech. For instance, when we suggest to our friend we should pick up sushi for dinner and they say “…Sure?”, that long pause and questioning intonation might make us feel like they aren’t that excited about the proposition. We’d probably feel better about ordering sushi for dinner if they said “Sure!” with complete enthusiasm and without a moment of hesitation. In both cases, we’re tuned in to their contextualization cues, or features like pitch, tone, and pauses that help convey the intent behind someone’s words.

The inVibe Listening team is comprised of sociolinguists who are particularly trained to listen “between the lines” for these acoustic nuances. While we’ve all got good ears for this kind of deep listening, technology thankfully exists to reinforce our intuitions in the form of an established, rigorously tested speech emotion recognition (SER) algorithm. In the analysis phase of our work, we turn to this algorithm which tracks the physiological changes – those contextualization cues – in voice that are prompted by stimuli and reactions. These vocal fluctuations are then “translated” into the approximate emotions behind a response by scoring valence (level of positivity or negativity), activation (level of interest and/or excitement), and dominance (confidence and control). Finally, for each prompt, we can illustrate all respondents’ scores on a graph, visualizing the response distribution on a per-question basis. This feature is a valuable asset in the inVibe tool belt, as it allows us to “show” what we as linguists are picking up on.

This graph represents multiple HCP respondents in terms of their dominance (x-axis) and activation (y-axis) for one prompt. Most responses are falling to the right side of the x-axis, indicating respondents’ confidence in their answers.

Acoustics in Practice: The Analysis Phase

While our projects always consider acoustic metrics, we find them to be especially illuminating in concept and message testing studies to help us better understand respondents’ attitudes and reactions. One recent concept testing project that benefitted from acoustic analysis was for an eye care treatment already on the market. The client was looking to reposition this existing treatment and wanted to evaluate how three potential concepts fared with eye care providers (ECPs). To answer these questions, we designed a mixed methods quantitative and voice response study aimed at uncovering concept reactions and perceptions to best position the treatment moving forward.

In the analysis phase, the quantitative findings came in first and laid out a vague framework for us to build on. Concept A scored the highest for resonating with ECPs and motivating them to prescribe the treatment, with Concept B and Concept C resulting in the middle and lowest scores, respectively. These results gave us a sense of ‘what’ ECPs’ general attitudes were but not ‘why’ that was the case, so we then turned to the voice responses, where we had probed participants to explain why they found each concept un(relatable) or un(motivational). Through these responses, we heard ECPs praise and criticize various aspects of the visuals and messaging, which helped us make sense of their quant scores.

Perhaps sharing ‘what’ ECP attitudes were and ‘why’ they felt that way would have been sufficient, but we wanted to go one step further and show ‘how’ the ECPs sounded to fully substantiate and ensure client confidence in our analysis. We used our SER technology to plot ECPs’ answers about each concept’s relatability and motivation on the axes of activation (excitement/boredom) and valence (positivity/negativity). These two parameters are typical in our concept testing measurements, as they best depict participant reactions and feelings. From the following graphs, we see that what they said neatly corresponds with how they said it, justifying the quant rankings that we started with.

Concept A had the highest levels of acoustic activation and valence, indicating that it was positively received and attention-grabbing.

Revolutionizing Market Research Recruitment

imagine

A Patient-Centric Listening Platform

Market Research Innovator inVibe Joins Inc. 5000 List of Fastest Growing Companies in America for 4th Year in a Row, and Merges with THREAD

New Data Intelligence: An ear to the future

imagine

A tech-enhanced, human-led analytical approach

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