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The Role of Primary Research in the World Of AI and Data Analytics with Tim Lawton

Roles will evolve in terms of daily tasks, but few will disappear overnight.

Primary research is crucial in the rapidly evolving landscape of AI and data analytics. By directly collecting fresh data through surveys, interviews, and experiments, organizations gain unique insights and a competitive edge. This firsthand information allows for the development of tailored strategies, validation of hypotheses, and the discovery of trends not visible through secondary sources. As AI and data analytics continue to transform industries, the role of primary research in guiding these advancements is indispensable.

This week we have Tim Lawton, co-founder and co-CEO of SightX. Tim’s innovative approach to solving complex problems in data analytics has uniquely positioned SightX to address the gaps in consumer and market research, despite his background in investment banking and the military.

We’ll uncover the inspiration behind SightX, how generative AI has opened new opportunities for early-stage companies, and the unique problem they set out to solve. We’ll also delve into the role of primary research in data analytics, its impact on decision-making, and the evolving trends shaping this industry. Join us as we explore how SightX is democratizing data analysis and empowering companies to compete at scale with their innovative solutions.

AIM Media House : What inspired you to start SightX with your Co-CEO?

“All of a sudden, last year, when generative AI became so public-facing and ubiquitous, it opened up another interesting opportunity for any company, particularly for earlier-stage companies.”

Tim Lawton: Interestingly, neither my co-founder, Naira Musallam, nor I came from this industry. Her background is in academia and, for a time, in consulting, running an R&D and Innovation team, but not specifically in the world we live in now. Before that, I was in investment banking and was actually in the military before that. When we met and became friends we would share ideas, and discuss this bigger picture idea that we always had. There was an opportunity to apply this new workflow automation to market research. Capturing data from an end user, who could be a consumer, a patient, an employee, a fan, and doing that at scale and speed, and more importantly, automating the analysis and insights, has historically been a very fragmented and opaque process handled mostly by market research agencies and other relationships.

It’s evolved, and I think it’s one of the few industries that have yet to be pushed to be tech-enabled and tech-forward, which presents a lot of exciting opportunities for companies like ours. We saw that there was a need. From my experience with similar types of tools being used, it really struck us as a fascinating problem to solve and an opportunity. Initially, it wasn’t specifically about consumer and market research; it was really about process improvement. As we began to narrow down towards the consumer space, we focused on the application and who our end users were. This then informed the software, user interface, and features.

As we have grown the company and the industry, we continue to see the evolving problems and how technology applications like ours can solve them. It’s exciting because there’s a lot of change happening in the industry. Suddenly, last year, when generative AI became so public-facing and ubiquitous, it opened another interesting opportunity for any company, particularly for earlier-stage companies. It levels the playing field for us to compete at scale and develop those applications for our customers so they can compete at scale with much larger companies.

AIM Media House: When you started your company, what unique problem did you decide to solve to establish your USP, given the many challenges already addressed in the industry?

“Initially, our focus was on the analysis and making it more accessible, democratizing it, for lack of a better word.”

Tim Lawton: A great question. For us initially, and even to this day, it’s always been about the automation of the process, but more importantly, the analysis and insights, and doing that at speed and scale. Even now, sometimes it’s like, “Oh, we use Excel for this,” or “We use Tableau for this,” or “We use this tool for this use case and that tool for that use case.”

Initially, our focus was on the analysis and making it more accessible, democratizing it, for lack of a better word. So, you don’t have to be a PhD statistician or a data scientist. That type of analysis, information, and insights is important and should be widely shared. Even nowadays, with the speed of consumer behavior and the economy, that was the initial idea. Then, we had to evolve the platform to meet the needs of the industry, which meant also focusing on data capture. So, we evolved the platform to build a survey tool, enabling us to own the data structure and automate it.

Obviously, technology and artificial intelligence have made that easier. As a company, one of our biggest value adds is the flexibility in the types of analysis we can do at scale and speed. The power we provide our users is significant. Again, it helps if you’re a trained statistician, but you don’t have to be. You have access to these types of tools and analysis that you previously didn’t.

Initially, I think what’s interesting about our journey is that the initial 30,000-foot view hasn’t changed. We’ve simply narrowed our focus towards how we’re going to apply it in the consumer space and market research. In that sense, it’s changed considerably in terms of the features, functions, and applications the platform is designed for.

So, we never really pivoted in that sense but have continued to evolve and improve. We’ve taken that initial idea and refined and improved how it’s applied.

AIM Media House: How did you envision the role of primary research in the world of data analytics, and has it met your expectations in terms of impact and decision-making?

“The primary piece, however, is the “why” behind the data.”

Tim Lawton:
I think we still consider the connection between primary and secondary research, and the different data sets, as crucial. The scale of some of these secondary data sets, whether it’s operational data, sales data, data lakes, or whatever it may be, is incredibly important. There are trends and insights within these data sets that businesses of any shape or size should be examining to extract valuable trends or information relevant to their business or consumers.

The primary piece, however, is the “why” behind the data. As we’ve discussed, you can see the trends and patterns, but understanding the reason behind them is key. One of our advisors highlighted this a few years ago with an analogy: he mentioned a post on Facebook about a death in the family. People clicked “like” not because they liked the news, but as a form of acknowledgment. The action of liking the post wasn’t about liking the content but engaging with it. Understanding why someone engaged is crucial—why did they purchase something, why did they engage with a piece of media, was it an accident, was it for themselves or a friend?

These larger data sets can provide incredibly insightful information, but at the end of the day, you need to know why things happened to make truly impactful decisions about your company and its direction. Without this understanding, you’re not completely blind, but you lack the clarity needed to guide your business effectively.

AIM Media House: Can you provide an example of how primary research has significantly impacted your business? What are the best practices for gathering high-quality consumer data, and do you conduct this research internally or through external agencies?

“But the baseline is to think forward and think through the types of analysis you want to do and how many cuts of the data you need.”

Tim Lawton:
And that’s one thing. Where does that data come from? What is the Sample and how is the sample quality? That sort of stuff will always be top of mind, and for good reasons. 

These sample providers essentially organize communities of consumers, which could include business leaders, doctors, regular consumers, anybody who opts into these communities. They say, “I’ll take some surveys for you if you reach out to me,” and there are different ways they are incentivized. But where, you know, that’s not our business, we’re agnostic to it. So we have APIs into and relationships with a lot of these companies around the world. 

If you’re in India, for example, we want to pair you with sample providers that we know are best in class in that region or field, and so on and so forth. 

In terms of connecting, again, we have API connections, but if you need to DIY it yourself, you can do that if you have your own audience. That’s possible. What we offer is not only the connection but also the data quality checks and similar services as part of the platform. The sample size itself is really project-dependent and based on the needs of the project.

If it’s just a couple of insights for something directionally correct, you often hear the word “agile” thrown around a lot in this industry, referring to quick, short, and not complex studies, all the way through large brand tracking studies that run over time with thousands of responses. So, it depends on what the project is and what the intent is.

The methodology and how and where we, you know, I think the general rule of thumb is, energizing for what our value proposition is, is like the analysis side of it. So if you want better analysis, obviously, the more sample, the more data, the better. But the baseline is to think forward and think through the types of analysis you want to do and how many cuts of the data you need.  As long as those smaller subsegments are big enough for you to get some statistical significance out of it, or enough data to where it is actually valid.

AIM Media House: What are the benefits for industries that haven’t heavily focused on primary research if they start to implement it? Can you also share some effective methods for conducting primary research, especially for companies trying to identify sales patterns or other critical data insights?

The combination of the two is particularly valuable for primary research because it helps figure out the “why.”Why are they buying your product? Why did they not buy a product?”

Tim Lawton: One, you should do it. Any industry should. Regardless of the industry, size of the customer base, or whatever, the benefits of market research coupled with the benefits of artificial intelligence make the work all that more valuable and necessary.

The combination of the two is particularly valuable for primary research because it helps figure out the “why.” Why are they buying your product? Why did they not buy a product? Everything from pricing to design, reactions, and more—it doesn’t have to be consumers; it could be business leaders, healthcare professionals, or others. Understanding these benefits in a data-driven way allows for informed decisions about your company strategy, go-to-market plans, product launches, pricing, and more. If you’re guessing, good on you. But having data to back up your decisions is invaluable.

The artificial intelligence component helps with speed and cost, like any technological application. This is why we build these tools—to do things faster, better, and cheaper. On the primary research side, the way it’s being democratized allows anyone to come into SightX, use preset templates we’ve designed, or design their own questions if they have ideas or are working with an agency.

Using Ada, specifically our Generative AI assistant, Ada, which was the first of it’s kind in the industry, you can query Ada for things like knowledge transfer, understanding best practices, executive summaries, analysis, and more. This capability enhances the research process from top to bottom.

AIM Media House: In industries with varying opinions, do you think technology will soon replace the traditional method of asking direct questions to gather data, or will it always remain essential to have direct conversations with consumers?

Roles will evolve in terms of daily tasks, but few will disappear overnight.”

Tim Lawton:
Never say never, but I think that looking at secondary data sets—like sales trends and extrapolating insights from them—will always be necessary. However, asking “why” won’t go away. Even ChatGPT and similar tools generate unique outputs based on historical data. They are not sentient yet. So, while I never say never, the fundamental premise of primary research is having a human in the equation. We need to ask someone; otherwise, we’re just guessing or basing our conclusions on historical data, like secondary data sets.

For two reasons, I believe the human element must remain. First, in how we communicate with our users and clients, and second, any form of technology, whether it’s Excel or Ada, will analyze data and indicate whether something is important or significant. It might tell you what price to charge or whether a concept is winning, but determining if it’s insightful to your business and strategy is up to you. You know your business best.

The roles of data scientists and data analysts are evolving. Instead of performing grunt work, like processing spreadsheets and manual tasks, they are now focusing on reaching end states quickly. One of our taglines is “automating curiosity.” It’s hard to be curious when you’re bogged down with calculations and spreadsheets. Our goal is to get you to that end state as fast as possible so you can be curious about the data and your business, ask questions, and determine what’s insightful or important. 

Technology helps you reach that end state faster. It provides important information about your project and goals, but it’s up to you to decide if it’s truly insightful and whether to implement it. Even if many consumers say one thing, take it with a grain of salt. Evaluate it in the context of your current business, past projects, and future plans.

Roles will evolve in terms of daily tasks, but few will disappear overnight. At SightX and with Ada, our tools augment your team to help you scale and do things better and faster, allowing you to avoid tedious busy work. Very few people are hired to sit in an Excel sheet all day; most are hired to think strategically and creatively, and to figure out how to apply those creative, insightful decisions to their business.

AIM Media House: What trends and technologies do you see shaping your industry in the next six months, and how do you plan to integrate these into your product? How do you envision your product evolving in the near future?

“With so many things happening overnight, like the recent releases of ChatGPT 4.0 and Gemini updates, we remain AI-agnostic. We aim to take the best applications available and apply them to our field.”

Tim Lawton:
Since our inception, we’ve had AI driven insights, which I jokingly call “old school AI.” Now, with generative applications, we’ve really started to work on and implement them over the past year. It’s really exciting with a lot of opportunities. We’ve taken the automation of advanced physical types of analysis, research, and outputs and layered that with the generative piece, going all the way back to the beginning of the research equation for knowledge transfer. This includes what to ask, which methodology to use, data capture, and analysis.

What’s really cool now with Ada is that it continues to evolve, making everything better, faster, and cheaper, and getting you to the end state more quickly. Ada can perform quantitative and qualitative analysis and generate executive summaries. With AI, you can just press a button based on your data, and while you need to determine if it’s insightful, it will give you an executive summary of your research project. It can also generate blog posts, suggest ad campaigns, and create collateral.

You can query Ada at the beginning or end of a project about the analysis. You can jump to the dashboard to do it yourself or qualitatively query Ada, and she’ll run the analysis for you. This capability is continually evolving, with more functionalities being added. In the next few months, we’re planning to implement features like text, image, and video translation and video analysis.

Who knows what’s next in terms of consumer engagements? Some near-term developments include getting into creative assets to scale marketing or creative teams, so you don’t need another platform for that and can conduct new research within our system. With so many things happening overnight, like the recent releases of ChatGPT 4.0 and Gemini updates, we remain AI-agnostic. We aim to take the best applications available and apply them to our field.

Our product teams take existing tools and curate them to ensure they provide relevant information for this industry and your type of company. We offer these in a prepackaged, streamlined way, so you can utilize these technologies without having to adapt another platform to fit your specific use case. We do a lot of that work for you within our application, with Ada making suggestions to help you along the way.

Picture of Mansi Singh
Mansi Singh
Mansi's interest centers around use of Gen AI in enhancing daily lives and she is dedicated to exploring the latest trends and tools in AI.
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