{"id":13671,"date":"2023-09-29T13:28:23","date_gmt":"2023-09-29T17:28:23","guid":{"rendered":"https:\/\/leaphumanx.com\/?p=13671"},"modified":"2024-07-09T16:19:43","modified_gmt":"2024-07-09T20:19:43","slug":"the-human-the-tool-pt-3-market-research-with-dr-timothy-sauer-and-rachael-roland","status":"publish","type":"post","link":"https:\/\/leaphumanx.com\/insights\/news\/the-human-the-tool-pt-3-market-research-with-dr-timothy-sauer-and-rachael-roland\/","title":{"rendered":"The Human + The Tool, Pt. 3: Market Research with Dr. Timothy Sauer and Rachael Roland"},"content":{"rendered":"\t\t
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Brands must understand their audiences to find success. But it isn\u2019t enough to collect the data, you must understand it. And when it seems like the data is too much to handle, artificial intelligence just might help.<\/p>

In the past year, marketing interest in AI has boomed. Every discipline is looking for ways to employ the latest technology. Market researchers have even found ways to uncover human insights with AI.<\/p>

Researchers are employing chatbots to brainstorm research ideas and conversation prompts. Once their surveys, focus groups, and interviews are complete, they turn to unstructured data processors to make sense of daunting mountains of content. While these technologies aren\u2019t what make human insights special, they are cutting down laborious and repetitive tasks, leaving professionals with more freedom and energy to elevate their work.<\/p>

To get a hands-on understanding of how researchers are using AI, we sat down for a Q&A with Timothy Sauer, Ph.D., director of research and account strategy at (human)x and Rachael Roland, (human)x consultant and cofounder of Enable AI.<\/p>

This blog is the final installment in a three-part series called \u201cThe Human + The Tool\u201d on the real human applications of AI with subject matter experts at (human)x in search engine optimization, UX, and market research.<\/p>

*Author\u2019s note: This interview was edited and condensed for clarity.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Brands must understand their audiences to find success. But it isn\u2019t enough to collect the data, you must understand it. And when it seems like the data is too much to handle, artificial intelligence just might help.<\/p>

In the past year, marketing interest in AI has boomed. Every discipline is looking for ways to employ the latest technology. Market researchers have even found ways to uncover human insights with AI.<\/p>

Researchers are employing chatbots to brainstorm research ideas and conversation prompts. Once their surveys, focus groups, and interviews are complete, they turn to unstructured data processors to make sense of daunting mountains of content. While these technologies aren\u2019t what make human insights special, they are cutting down laborious and repetitive tasks, leaving professionals with more freedom and energy to elevate their work.<\/p>

To get a hands-on understanding of how researchers are using AI, we sat down for a Q&A with Timothy Sauer, Ph.D., director of research and account strategy at (human)x and Rachael Roland, (human)x consultant and cofounder of Enable AI.<\/p>

This blog is the final installment in a three-part series called \u201cThe Human + The Tool\u201d on the real human applications of AI with subject matter experts at (human)x in search engine optimization, UX, and market research.<\/p>

*Author\u2019s note: This interview was edited and condensed for clarity.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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What is your background with AI?<\/h3>

TS:<\/strong> With AI, my role on the team is toe-dipper. AI has emerged in popularity quickly in the last year, and I\u2019ve had to stay on top of its constant development and try things out.<\/p>

Integrating AI into our work process has involved a lot of experimentation and looking for efficiencies that can be gained. I look for ways to integrate cutting-edge AI programs in appropriate ways. For example, I can\u2019t use ChatGPT as a resource database. I can\u2019t ask it \u201cHow do people currently use Tik Tok?\u201d The data might be two years old and inaccurate. But I have used it for efficiency, like generating prompts or jumping off points for writing prompts. I\u2019ve also used ChatGPT to help process documents and data. It\u2019s cut down the number of working hours on a lot of projects for my team.<\/p>

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RR:<\/strong> I started the company Enable AI a little over six years ago. We were working with unstructured data, such as text and images. Many of the projects I did related to product reviews. I would scrape Amazon, Walmart, and other retailer websites, and pull reviews on my client\u2019s products to understand what people were talking about, what they cared about, what was driving one-star reviews or five-star reviews, and so on. We also did competitive analyses with social media i.e., Facebook versus Instagram.<\/p>

As Timothy mentioned, about six months ago AI rose in popularity and the world shifted under my feet. All the things I had been doing the old-school, machine learning way, I could suddenly do in ChatGPT. When I say old school, I mean techniques from three years ago \u2014 that\u2019s the olden days now.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Rachael, to the average person, it feels like just six months to a year ago AI exploded in popularity. What inspired you six years ago to start working in AI?<\/h3>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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RR:<\/strong> At that time, AI wasn’t a common term. It was often referred to as the \u201cdeep learning revolution.\u201d My interest was piqued when I connected with friends at Georgia Tech who were taking online courses in computer science, machine learning, and AI. Through them, I got a glimpse of the exciting developments in machine learning and the potential of working with unstructured data. It was clear that this field was rapidly expanding, and I saw an opportunity to be part of it.<\/p>\n

While conducting research, what AI programs are you using?<\/h3>\n

TS:<\/strong> ChatGPT is the hub for me. I use several plugins, including AskYourPDF and WebPilot, as well as the advanced data analysis tool available in GPT-4.<\/p>\n

We have to be careful with using ChatGPT and open-source AI because we work with some private client insights. A lot of research is taking primary data, owned data by a client that we\u2019ve gathered with focus groups, surveys, or some other research. We don\u2019t want it going into ChatGPT itself because of privacy and security issues.<\/p>\n

With Rachael’s help, our team is essentially taking the ChatGPT model and building our own on Microsoft Azure that is self-contained, and we can engage with. All the data that we put in and everything it puts back out to us is contained on our server. Security is our main concern. The last thing we want is for our clients to lose trust in us.<\/p>\n

Can you describe a research project where you used AI?<\/h3>\n

RR:<\/strong> With ChatGPT, I discovered the ability to extract summarization. For example, if you get a long email and you say, \u201cI don\u2019t want to read all this,\u201d you can tell ChatGPT to read it and give the main bullet points.<\/p>\n

One of (human)x\u2019s current clients sells fire starters and fire logs. We scraped online reviews of their products and processed it with AI. We uncovered major topics of interest of concern. It\u2019s a long-lasting product, but some people think it smells plasticky when it burns. It\u2019s a quality product, but it can be expensive. Businesses want to know about public opinions, and by utilizing AI we were able to present that information quickly and easily.<\/p>\n

When I started Enable AI, we worked with a nationwide, long-term healthcare company with about 10,000 employees. They would do an employee survey every year with multiple choice questions and three open-ended questions at the end. Every year, they would get the surveys, analyze the multiple-choice answers, but do nothing with the open-ended answers, because it\u2019s daunting to read 10,000 responses.<\/p>\n

The first thing we did for them was utilize our program, designed to make sense of unstructured data, to analyze all these open-ended responses. We came to the meeting with the major themes our program had gathered. We told them: \u201cblack scrubs.\u201d We found out that there were hundreds of occurrences in the survey results of people saying they\u2019d prefer to wear black scrubs to hide stains throughout the workday. They didn\u2019t know that their employees wanted this until we really started delving into those open-ended responses.<\/p>\n

One of the fundamental things that we\u2019ve done with unstructured data is pull up unknown unknowns. There are things that you don\u2019t know about. You can find these things if you really look. Machine learning and AI is powerful in its ability to pull out those sort of things \u2014 even simple things like topic extraction, sentiment, named entity recognition, and figuring out people, places, data, times, and things that seem simple but can be daunting and time-consuming when done manually.<\/p>\n

Timothy and other research specialists at (human)x may go through transcripts from interviews or focus groups, reading all these things to annotate of label them. It can be time-consuming. That\u2019s a great use case for ChatGPT or some other AI program, because it\u2019s tireless. AI is happy to sit there and read 10,000 responses or an eight-hour transcript.<\/p>\n

TS:<\/strong> Building on what Rachael said, the \u201caha\u201d moment in the research comes from us probing and asking important questions in a focus group. The beauty of AI is that the 40-page transcript that our eyes gloss over, ChatGPT can go in and pull information for us to help elevate our work.<\/p>\n

AI not to the point yet where we\u2019re using it for hard research. It might get there. We\u2019re mostly using it to help prompt conversations, build briefs, or pull major themes.<\/p>\n

In research, there are projects where I know our work is 98% confirmation for what our clients already know. But there is that 2% of information they don\u2019t know. That\u2019s what I want to find. That\u2019s what I want to bring them.<\/p>\n

Tell me about (human)x\u2019s process of adopting AI.<\/h3>\n

\"\"TS:<\/strong> There is a community atmosphere of learning in our team when it comes to AI. (human)x, and the entirety of Leap Group, is invested in it.<\/p>\n

We have dedicated Slack channels for talking about AI and sharing our experiences. There is so much to say and learn that no one person can keep track of what\u2019s happening. We use that channel quite a bit to gather all our progress.<\/p>\n

There is an AI ethics committee. Some team members across disciplines have created a separate AI club, where we meet about once a mother to explore how we will use AI. We have developers, strategists, researchers, creatives, and project managers gathering to see how our teams will approach new challenges with AI.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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(human)x just launched a new data-enrichment product that uses predictive technology. Can you tell us about humanView?<\/h3>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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TS:<\/strong> I had a conversation with ChatGPT to help me describe humanView. After some back-and-forth with the chatbot, I came to a version that best explains our new product. Here it is:<\/p>\n

ChatGPT: humanView\u2122 goes beyond the traditional boundaries of data enrichment. While its core feature revolves around appending first-party data by adding hundreds of relevant psychographic and demographic variables, it delves deeper into understanding an audience’s nuances. This enriched data provides a multi-dimensional view of an audience, painting a more detailed and holistic picture of their preferences, behaviors, and tendencies.<\/p>\n

But what truly sets humanView\u2122 apart is its adeptness at harnessing the power of AI and machine learning. In today’s digital age, a significant portion of valuable data comes in unstructured forms, like customer reviews, feedback, and open-ended survey responses. Processing this unstructured data manually is not only time-consuming but also prone to oversight and errors. humanView\u2122 utilizes advanced AI and machine learning algorithms to sift through this vast sea of unstructured data, extracting meaningful insights and patterns. By analyzing customer reviews, for instance, businesses can gain a deeper understanding of their customers’ pain points, preferences, and sentiments. This capability transforms raw, often overlooked data into actionable insights, empowering businesses to fine-tune their strategies and offerings based on genuine customer feedback and experiences.<\/p>\n

AI + Market Research with (human)x<\/h3>\n

Timothy Sauer and Rachael Roland\u2019s experiences showcase the opportunity AI can afford to researchers interested in exploring new technologies. Here is what we learned.<\/p>\n