How To Use AI For Market Research In 2024: Elevate Your Research Game

Introduction

Market research can be difficult. You need to do competitive analysis, figure out market trends, and understand customer sentiments about your business or potential product with a handful of data. In some situations, you have no data to work with.

I’ve done it a couple of times as a product manager, and it’s a very stressful venture, but it doesn’t have to be. In this article, we will discuss how you can use AI for market research in 2024 to elevate your research game. 

Let’s begin!

Understanding artificial intelligence in market research

One of the coolest things I’ve learned recently is how to use AI to get a handle on sentiment and predictive analysis. Honestly, I believe these are the two main goals of market research, and everything in between is just an extra step. In this section, we’re about how AI market research tools can help you with these two things and how they are revolutionizing traditional market research techniques. 

What is AI-powered market research?

AI-powered market research means you’re using AI to handle sentiment and predictive analysis.

AI-powered sentiment analysis

Sentiment analysis through AI means you don’t really have to spend a lot of time manually sifting through customer comments because AI can do it for you in a fraction of the time it can take you to do the job, and they’re also getting really great at picking up nuances in language and speech that you’ll probably have issues picking up. 

Here’s the thing, though: using AI in sentiment analysis isn’t exactly science. It has the tendency to misunderstand sarcasm as positive feedback. Is it possible for AI to reach the point where it perfectly understands sarcasm one day? Maybe, but that day is not today. So, you need to be careful.

AI-powered predictive analysis

Another area of market research where AI is absolutely killing it is in predictive analysis. Seriously, it’s freaking amazing. At the moment, I’m working with a company that basically leverages the benefits of predictive analysis in virtually every way you can think of.

Some of the areas they have previously used and are currently using artificial intelligence for predictive analysis are banking, health, security, music, education, and law. 

But just like in sentiment analysis, AI in predictive analysis isn’t exactly 100% hands-off. While AI can analyze numbers and give you results in a snap just like that, it takes a human mind and experience to know what questions to ask in the first place.

Believe me, I’ve tried to use AI to generate survey questions before for a personal project I was working on and they came off pretty disappointing and lost in context.

What I’m trying to say, in essence, is that while AI in market research is pretty powerful, it’s not a magic bullet. It’s a tool, and like any tool, it’s only as good as the person using it. So, my little nugget of advice is that while you’re embracing AI, you shouldn’t forget that it’s only as good as the person using it.

And for the love of God, if you really like your job, always double-check your AI-generated results before showing them to clients or stakeholders. Trust me on this one – it’ll save you from a lot of awkward situations where you feel super dumb and want to kick yourself. 

How has AI transformed traditional market research methods?

It’s a no-brainer at this point that AI has definitely shaken up how market research is traditionally being handled in a lot of ways that many people thought were impossible in the past. Before, where everything used to be handled in an analog way. The market research process is now as simple as the one below:

Data input

Here’s where you do a little bit of leg work or brain work, as the case may be. You can give any AI tool of your choice (could be ChatGPT or any AI tools for market research) some research data you’ve previously collected on your competitor through tweets, proposals, business documents, social media posts, and customer reviews to get started.

Remember, your outcome can only be as good as the quality and amounts of data you feed into the engine. So, try to get quality data if you can.

Natural language processing (NLP)

This is where things get really cool and maybe a little technical. The AI tool you use, which should ideally support natural language processing, will help you understand the language used in the data you’ve shared, break them down into understandable forms, and also check for connections between your queries and data. It can even read emojis. 🤯

Fun fact, my current company is actually working on a product that has the capacity to do this quite well. It’s pretty exciting, and when it’s finally where we want it to be, it’s going to change the way research teams everywhere analyze the current data they have on hand.

Pattern recognition

While your chosen tool understands, analyses, and possibly summarizes the data you’ve fed into it, it also tries to understand the patterns and trends in the data you’ve provided. It can also help understand how often your customers use certain words, how they use them, and how those words change over time, which makes conducting market research a breeze.

Automated insights: save some time

With all the clues the tool has extracted from the data you provided, it can help you discover emerging trends and topics in the market, understand the customer sentiment towards current products if you’re just starting out with the process of creating and figure out market gaps where your business can truly thrive. 

How to use artificial intelligence for market research

Now, you’re probably thinking, sure, AI for sentiment and predictive analysis is great, but that’s too generic; in what practical ways can I apply AI in market research? Well, that’s what this section is about. We’re going to go in-depth into these two main concepts and give you can actually practically use them:

Predicting market trends

This is where artificial intelligence truly shines. It gives you actionable insights into where the market is possibly going. It’s like creating a time machine that can look into the future. I particularly love the way Glimpse does this. It’s a powerful tool that can actually predict trends years before they become mainstream.

Honestly, in my opinion, using AI-powered predictive analytics to forecast consumer demand is like having a portable time machine for your business strategy.

Another great market research platform in this category is ClickUp Brain. It can help you analyze current market trends, streamline your ideation process, and fine-tune whatever product you eventually decide to put on the market. Just feed it some prompts about your sector, and it’ll extract data and give you great insights faster than you can say “competitive advantage.”

Customer research and profiling

AI has the capacity to help you create effective consumer profiles that will make marketers red with envy. It’ll look at the demographics, behavior, and buying history of people who currently interact with and like your product, as well as potential customers, to give you a bird-eye view of your customers and develop your marketing strategies.

I use this to get a better understanding of who I should be creating a product or optimizing it for. Trust me, nailing the target audience is half of creating a good product.

Competitor analysis

Let’s face it, keeping tabs on the competition in the market can be a full-time job. You have to make sure they’re not doing anything that could disrupt the market and convert a large percentage of the customers like Netflix did to Blockbuster or Google to Bing and Yahoo. You also want to make sure that if they are, you’re on the new market-disrupting trend faster than the speed of light, but that can be difficult.

Now, AI tools can help you track your competitors’ strategies, pricing, and even social media engagement. It’s like having a spy in their boardroom, but it’s totally legal.

Market research surveys

AI-powered tools have changed the way we conduct surveys. They can help us create more engaging questions and analyze responses in real-time. This one is a tricky use case, though, because you want to confirm every output you get to be sure the tool is not just doing its thing and ignoring what you tell it to do. 

The prompt I usually use that actually works for me is:

“You are a product manager for [Insert Company Name], working on a product in the [Insert Industry and Product Details] space. Your goal is to create an effective customer survey to gather authentic and actionable insights from potential users. Keeping in mind the principles of the Mom Test for user research, craft a set of survey questions that avoid leading, biased, or direct inquiries. These questions should encourage honest feedback and uncover real user needs, concerns, and behaviors.”

It’s not perfect, and you can make it better; it can help a bit.

Fraud detection

This one’s actually pretty important. AI can help you spot fraudulent responses that might skew your data. For instance, SurveyMonkey, a very popular market research company, has incorporated AI into its systems to make detecting fake responses easier. 

Look, as a business owner, product owner, or product manager, our job is to create products people love. AI in market research can help us do that more effectively than ever before. It’s not about replacing human insight; it’s about enhancing it.

My advice? Start small. Pick one manageable part of your market research to apply AI. It could be competitor analysis or tracking. Once you see the results, you’ll wonder how you ever did things without it.

Key AI technologies driving market research

Let’s look into AI tech, which is actually turning the field of market research on its head, so you can have a better understanding of what goes on with your data and how the tools can achieve these goals.

Machine learning: how does it enhance data analysis?

Machine learning is like that smart intern who knows a lot about what’s going on everywhere and never sleeps. Its job is to help you spot the patterns in data that even humans may miss, and that’s because it has access to a larger reservoir of data than you can possibly feed it. 

One awesome thing about machine language is that it has the capacity to get smarter over time. The more data you feed it, the better it gets. It’s like it’s constantly learning on the job. So, if you feed it large amounts of data over time, you’re bound to get better results.

Natural language processing: what role does it play in sentiment analysis?

Natural language processing, or NLP as it’s popularly called by the cool kids, is the universal translator that makes analyzing customer feedback easy. It doesn’t just read text but also understands context and even emojis. 

The cool thing about NLP, in my opinion, is that it can handle massive amounts of text data. You can feed it social media posts, customer support tickets, and survey responses, and it will eat them all up and spit out actionable insights. 

Computer vision: how is it revolutionizing visual data interpretation?

Computer vision is the equivalent of giving your research team superhuman eyesight, kinda like Hawkeye (the superhero), but fifty times better because it can help you analyze images and videos faster and more accurately than any human.

Free AI market research tools in 2024

The great thing about the best AI market research tools is that some of them are free, while you can take advantage of those that don’t have free trial sessions. I’ll mention some of them in this section and how you can use them.

ChatGPT

ChatGPT is one of the biggest OGs in the AI game, and it has a very powerful natural language processing capacity. It can help you easily perform in-depth research, collect statistics, and generate summaries. What I like the most about ChatGPT is its simple chat interface, which makes it accessible for doing everything from gathering consumer opinions to analyzing complex data.

I’ve also used ChatGPT to help me come up with front-end design conceptualization for some data sets before. It’s really good and enough for anything you need to do, in my opinion.

What I Like About The Tool

• In-Depth Research: Can process vast amounts of information to deliver insightful summaries for research projects.
• User-Friendly Interface: Simplifies complex tasks with an intuitive chat-based interaction.

Use Cases

• Market research
• Data analysis
• Consumer opinion gathering

Pricing

• Free plan available with GPT-3.5
• Paid subscription required for GPT-4 access

Learn More: openai.com

Browse AI

This platform uses AI to automate the process of scraping and extracting data from websites, which makes it an invaluable tool for market researchers, business owners, and product managers who want to gather and analyze structured information. With Browse AI, you can easily create web scrapers with defined parameters without needing to code to help you retrieve data from platforms like LinkedIn, Reddit, or any other website.

What I Like About The Tool

• No-Code Web Scraping: Helps to create web scrapers without programming knowledge.
• Automated Data Extraction: This can simply be how you collect structured data from various online sources.

Use Cases

• Data scraping and extraction
• Market research
• Competitive analysis

Pricing

• Free plan available

Learn More: browse.ai

Perplexity AI

Just like ChatGPT, Perplexity AI is a versatile research tool that stands out from other tools because of its ability to access real-time information directly from the internet. It also uses multiple large language models (LLMs) like GPT-3.5 and Claude 3, which means it has the benefits of both language models and the flexibility to switch between them.

Perplexity shines the most when you’re using it to summarize findings, track trends, and conduct market research. It also has a Pro Search feature, which personalizes results based on previous queries. So, the more you use it, the better it gets.

What I Like About The Tool

• Real-Time Data Access: Fetches up-to-date information directly from the web.
• Personalized Insights: Pro Search remembers past queries for more tailored results.

Use Cases

• Market trend analysis
• Competitor research
• Information summarization

Pricing

• Free plan with GPT-3.5 access
• Paid plans available for additional LLMs

Learn More: perplexity.ai

Claude

Claude is an innovative AI platform by Anthropic that has great capacities for research and data analysis. The latest model, Claude 3, has an in-built advanced language analyzing and understanding capacity as well as the ability to process large datasets efficiently. Claude also has a user-friendly chat interface, which makes it easy to extract valuable insights quickly.

In addition, Claude 3 has the option to upload files like images or PDFs, which makes it versatile for various research needs.

What I Like About The Tool

• Advanced Language Processing: Great at analyzing complex data and generating accurate summaries.
• File Upload Capability: Supports uploading and analyzing files like PDFs and images.

Use Cases

• Research and analysis
• Data processing
• Strategy formulation

Pricing

• Free plan available

Learn More: anthropic.com

Elicit

Elicit specifically works for academic research. It looks through the documents or data you give and spits out a summarized version. It is particularly useful for market researchers who want to get evidence-based insights on a particular topic. Elicit 

What I Like About The Tool

• Academic Research Simplification: Helps to transform detailed academic papers into accessible summaries.
• Keyword-Based Search: This makes it easy to search for relevant studies or methodologies.

Use Cases

• Data-driven development strategy
• In-depth research

Pricing

• Free plan available

Learn More: elicit.org

Final thoughts on AI for market research

Alright, we’ve covered a lot of ground till this point. While this article is not perfect yet, I’ll continue to update it in the future for prompt ideas that work for me and how to use the tools. 

In my opinion, AI market research is not that difficult. You don’t even need good prompts. What you need is enough data and information, and AI will handle the rest for you. 

However, don’t forget that AI is just an assistant, and for AI to be useful, you still need the human factor.

That said, what are you still waiting for? It’s time to level up your market research game!