The AI researcher market is hot, and AI research companies represented by Outset.ai are changing the industry pattern. Outset.ai AI researchers can make video calls, extract key points, and generate insights, reducing research costs by 81% and increasing users by 10 times. Its success has attracted the attention of investors such as Sequoia Capital, indicating that the market research industry is undergoing AI-driven changes.
“Data is the new gold”, this saying has never been more true than it is now.
A revolution around “high-quality user data” is quietly unfolding in the market research industry. At the forefront of this change is an AI-native company that is exploding – Outset.ai.
The company has created an AI researcher that can really go on the field: it supports video calls, can conduct in-depth interviews with users in real time, and automatically extract key points and generate structured insights during the conversation.
Research projects that would have cost thousands of dollars and took months can now be completed in a matter of days, saving 81 percent of costs.
Nestlé used it to complete in-depth interviews with hundreds of people in 1-2 days, which would take at least 6 weeks with traditional methods.
With just 14 employees, Outset.ai has seen a 10x increase in customer usage over the past year, with more than 50 enterprise customers and millions of dollars in annual recurring revenue. In June this year, Outset.ai completed a $17 million Series A financing, led by 8VC.
It is worth mentioning that this is not the first financing of the AI research track. Just in April this year, AI research company ListenLabs just received $27 million in financing led by Sequoia Capital.
Sequoia pointed out in its investment logic that research and consulting is a large $40 billion market that has long been dominated by expensive manual services, and now, the entire industry is in urgent need of AI reshaping.
To achieve these three challenges, product managers will only continue to appreciate
Good product managers are very scarce, and product managers who understand users, business, and data are still in demand when they go out of the Internet. On the contrary, if you only do simple communication, inefficient execution, and shallow thinking, I am afraid that you will not be able to go through the torrent of the next 3-5 years.
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Both Outset.ai and ListenLabs are obviously stepping on this trend window – using AI to reconstruct the research process and upgrade from “handicraft workshop” to “smart factory”.
01 AI unlocks the truth of the market at 10x speed, and the cost is reduced by 80%
When the market enters the era of “weekly iteration”, traditional research methods are being severely crushed by reality.
In the past, a standard in-depth research project often took 6-10 weeks from design to delivery, and the process of 25 in-depth interviews + manual analysis was long and costly, and it often couldn’t keep up with the decision-making rhythm.
Forrester Research shows that organizations often only make critical decisions based on “lagging and surface” data, while the underlying drivers that truly influence user behavior are often overlooked.
And now AI is rewriting all of this.
Taking the AI research tool Outset.ai as an example, it can complete 250 interviews + full-process analysis delivery in less than a week, which is 8 times faster than traditional methods, only 19% of the cost of traditional solutions, and more than 10 times that of traditional solutions.
Not only is it amazingly efficient, but the key is that it completes not only “faster”, but “deeper” – each interviewee is a freestyle in-depth interview with AI, which generates not the result of the selection of preset questions, but real user language and emotional clues.
To make matters worse, Forrester Research shows that traditional research platforms still rely on scripted questionnaires, tedious focus group discussions, and manual labeling of qualitative data. Brands often end up acting on stale or superficial data, ignoring the reasons behind customer behavior.
AI can completely change this situation, subverting a traditional industry that has existed for more than a decade.
The AI research tool Outset.ai can complete 250 interviews and entire projects in less than a week, 8 times faster than traditional methods, at a cost of only 19%, and 10 times more coverage than traditional methods.
Traditional giants like Qualtrics and UserTesting have now learned to use AI and are starting to move from “fixed questionnaires” to “dynamic interactions”.
Qualtrics will launch the AI-powered XM/OS2 platform in 2023, which can automatically adjust follow-up questions based on user answers to achieve “dynamic surveys”; UserTesting has launched AI Summary, which can automatically generate summaries of test videos, identify user facial emotions, and mark “high friction points” operations;
But in essence, these “AI upgrades” are still on the surface of the original process. The reason is that they only superimpose AI modules on the original process, and their core relies on humanly designed questionnaire frameworks, fixed data analysis rules, and fragmented system architectures.
In contrast, startups are poised to revolutionize the field in disruptive ways.
The protagonist of this article Outset.ai AI native. It is not “adding AI” to the original process, but is completely driven by large models. In terms of interaction mode, immediacy, initiative, insight generation speed, analysis depth, and scale cost, it beats the AI methods of traditional survey enterprises.
Prior to this, another AI research company, Listen Labs, also received a $27 million investment from Sequoia Capital.
In one sentence, it can be summed up:Traditional solutions are “efficiency tools”, while Outset.ai are more like “AI-driven research experts”. It not only makes the research faster, but also makes the research more understanding.
02 Top 500 adopted, and revenue is expected to increase by 5 times this year
If I were to describe Outset.ai’s style, it would be more like a “curious, highly executed product manager”.
It’s not just a tool, it’s an “AI researcher” that works alongside you in real time – responsible for asking questions, asking questions, refining, analyzing, and even delivering a clear and usable research report in advance.
Specifically, it uses GPT-4 to host in-depth interviews, supports voice/video calls and screen sharing, so that AI is no longer just a text assistant, but a research partner that can “chat face-to-face”. During the conversation, it can ask questions in real time according to the user’s intention, ensuring that the topic is not deviated or superficial.
During the interview, Outset.ai worked proactively, in real time: automatically analyzing the content, categorizing the interviewees’ perspectives, and refining the core themes. At the end of the conversation, users will receive a clear report with key interviewees’ original words, sentiment analysis, and highlights from the interview.
In addition to the advantages of dialogue and automatic analysis, Outset.ai has completed the automation closed loop. Outset.ai the entire process from interview design, sample recruitment, data collection, and insight generation requires no manual intervention.
Nestlé used it to test new concepts with hundreds of consumers in 1-2 days, while traditional methods could take 4-6 weeks.
Microsoft uses Outset.ai to study how users interact with AI products. User thoughts and experiences are very nuanced and detailed, and it takes special care to figure out these nuances. Outset.ai uses AI to study the user experience of AI products, thereby accelerating and expanding the ability to learn from user feedback.
Behind this is its enterprise-level platform. The platform includes security authentication, admin permissions, a data-isolated workspace, and interviewer customization features. This is very important for large corporate client users such as the Fortune 500.
Outset.ai solutions meet the needs of businesses for depth and speed, leading to significant business growth:
- Revenue doubled in four months, up nearly 20% month-on-month, and investors expect revenue to grow more than 5 times this year.
- It has more than 50 enterprise customers, and the customer usage has increased by 10 times in one year.
- The total budget addressable market for user experience research software is about $140 billion.
Today, Outset.ai covers major time zones around the world, operating 24 hours a day in 5 time zones and 7 languages.
The company, founded in 2022, has achieved what it is today, thanks to the support of its early core team. More noteworthy, its employee turnover rate has remained at 0% to this day.
Of course, AI is not a panacea, and it is important to understand its advantages and applicable boundaries.
Human researchers have the advantage of building deep relationships, being highly emotionally connected, and dealing with extremely complex or sensitive situations. In contrast, taking Outset.ai as an example, the advantages of its AI researchers are reflected in:
- Never tired listeners: No personal bias, anonymity, so that the interviewee can easily answer questions in depth
- Multi-dimensional execution expert: Multilingual, cross-time zone, multi-project simultaneous and consistent quality
- Real-Time Insight Excavator: Respond to real-time adjustment of problem strategies, unearthing deep insights without missing important questions
It can be seen that Outset.ai this type of AI performs best in scenarios that pursue deep learning, value scale and speed, and have generally clear learning goals, such as concept testing, usability research, market strategy research, and longitudinal research.
Outset.ai not only redefines the speed and depth of user insights, but also quietly reshapes the genes of market research – allowing deep understanding of users to change from an expensive and highly manpower-dependent knowledge service to a scalable-driven core business engine.
At the same time, its successful financing confirms that the market research industry is transforming from labor-intensive to AI-driven. The popularity of AI research will integrate deep customer insights into the daily operations of enterprises, which means that product managers and even front-line sales can directly obtain and apply deep user insights.
