Who runs the world?
Data!
Slightly less catchy than Beyoncé’s 2011 hit, but still very true – data is king. Without it, great market research is impossible.
So, with artificial intelligence (AI) becoming omnipresent in businesses around the world, it makes sense that many organisations are using AI for market research and, more specifically, marketing data analysis.
In fact, 90% of businesses have stated that they will increase their investment in AI across 2025 and beyond. It’s undeniable that AI and market research are now intrinsically linked, but what exactly are businesses using AI for in market research, and how can you use AI tools to better understand your market?
Today, we’re taking a deep dive into how AI is transforming market research. We’ll look at both the benefits and the challenges faced by marketers, highlighting powerful AI tools that you might want to add to your arsenal, and running through some real-world examples of how businesses are using AI right now.
Learn More: Optimising your website for AI
What is AI in market research?
AI in market research refers to the use of advanced algorithms and machine learning to automate tasks traditionally done by humans, such as data collection, analysis and insight generation. AI is used to speed up monotonous tasks, making marketers more efficient and allowing them to focus on strategy.
It would not be hyperbole to say that AI has truly changed the way market research is done forever – it’ll never be the same.
This begs the question – how exactly is AI being used?
Four ways AI is used in market research
In theory, AI sounds great, but how is it actually being implemented in practice? Here are four examples:
Automating repetitive tasks (data collection and processing)
According to this study, machine learning and AI has two key functions:
- “Enhance data analysis by uncovering complex patterns and trends that may not be apparent to human analysts.”
- Allow “organisations [to] deliver targeted recommendations, personalised marketing campaigns, and tailored customer experiences.”
AI tools streamline market research processes such as survey analysis and social media monitoring, tasks that are traditionally resource-intensive and time-consuming. AI’s ability to sift through massive datasets and identify meaningful patterns effectively saves time and enhances the accuracy of results. Machine learning algorithms can then analyse consumer data across demographics, psychographics and online behaviours, uncovering hidden insights.
Not only this, but AI can also streamline data collection. AI-powered chatbots and virtual assistants are redefining how surveys are conducted. These tools can engage respondents in real-time, collecting data seamlessly and offering a more personalised experience.
Automating these tasks allows marketers to focus on strategic decision-making, planning and execution. AI becomes a data analysis tool that makes marketers dramatically more efficient.
Making use of natural language processing (NLP)
NLP allows AI market research tools to process open-ended survey responses, turning qualitative data into quantifiable insights.
This is a job that, in the past, needed to be performed manually, with a researcher taking hours (often days or weeks) to trawl through qualitative data. AI can now perform sentiment analysis and create detailed customer profiles almost instantly. In fact, 40% of researchers expect AI to explain survey findings as well as humans within 10 years.
AI and NLP are truly changing the marketing landscape. It is now, more than ever, essential that your organisation is embracing AI and its ability to empower your marketing efforts.
Performing predictive analysis
AI is unbeatable when it comes to data analysis.
It can, almost immediately, identify trends and patterns in data and effectively predict future customer behaviours or preferences with a high degree of accuracy. Predictive models powered by AI can forecast market trends, helping businesses adapt to consumer needs before they arise.
Businesses are using AI to understand their audience better than ever before. AI tools like Brandwatch can trawl search engines and social media platforms, quickly and efficiently analysing qualitative and quantitative data, before delivering trends and patterns for your marketing team to use.
Conducting market research ideation and planning
Finally, AI is transforming the way marketing teams are planning their market research. AI can (almost instantly, as if that still needs mentioning):
- Analyse trends and suggest research topics
- Identify target audiences based on demographics
- Name your key competitors and how they’re tackling the market
- Forecast potential outcomes to help you refine your strategy
- Visualise data to help you spot trends and gaps in the market
- Free up time for marketing personnel, allowing them to focus on creative and strategic ideation
Can it do everything itself? No, of course not – every suggestion made by AI should be vetted and amended by a human specialist. The robots aren’t fully taking over (yet).
The benefits and challenges of using AI for market research
While, yes, AI in market research seems, at surface level, to be all positive, there are cons as well as pros when it comes to any emerging technology.
Here are five benefits of using AI for market research, as well as three unique AI-based challenges facing the marketing industry.
5 Benefits of using AI for market research
1. Speed & efficiency
AI analyses data in real-time, reducing the time it takes to generate actionable insights from weeks to days – or even minutes.
Say, for example, you want to assess target audience sentiment across all your social media channels.
Historically, your marketing team would need to trawl posts, mentions and more, combing through trends and more to create a complete customer profile.
Now, AI can do this in moments, identifying trends and allowing you to capitalise on them immediately.
2. Accuracy and reducing human error
While AI isn’t perfect, algorithms can be used to eliminate manual errors (especially in data entry).
Humans are prone to mistakes, it’s kind of our thing. Using AI to check data and ensure that mistakes are automatically rectified can make a big difference. AI can also detect anomalies in your data, ensuring that outliers don’t skew results.
3. Cost-effectiveness
Market research isn’t cheap, but it is essential.
By automating data collection and analysis, AI reduces overheads and costs associated with traditional research methods (such as focus groups or field surveys).
This means that, when paying for market research, more of your budget goes towards the human minds that will ultimately ensure the success of your ongoing marketing strategy.
4. Scalability
Looking to grow, or to expand into new territories/industries? AI’s got your back.
AI tools are designed to scale alongside your business. Whether that’s handling datasets from diverse geographies, or handling a larger number of inputs, using AI and market research provides your organisation with a global perspective without any added complexity. In a way, AI is making the world much, much smaller.
5. Enhanced consumer understanding
AI can quickly and efficiently uncover the emotions behind customer feedback, providing insights into customer preferences. However, as we’ll get into momentarily, this may be something that AI is not yet up to scratch on…
3 Challenges and ethical concerns when using AI in market research
AI isn’t perfect – most of us are aware of this. There are a few challenges that you should consider when opting to use AI for market research, including:
1. AI can be biased
AI models are trained using data. If the data used to train them is biased, they will have a bias, too.
For example, a predictive model might overlook certain demographic groups if its training data lacked diversity.
It’s also worth noting that, since the advent of large language models (LLMs) and answer engines powered by programs such as ChatGPT and Google Gemini, many users report information produced by AI that is completely false – AI can sometimes make stuff up!
Researchers are calling these falsities “hallucinations”, moments where AI doesn’t have an answer, so it just creates something that answers your question, regardless of whether it’s true or not.
This means that it’s incredibly important that you check any mission-critical market research data produced by AI; ensure that your marketing team give everything a once over to ensure it looks good. AI “hallucinations” are likely something we’ll see less as the technology develops, but do keep this in mind as you’re using any generative AI tools.
2. Data privacy concerns
Collecting and analysing consumer data raises questions about consent and security. Jennifer King, a privacy and data policy fellow at Stanford University, had this to say about the risks of data being used by AI systems:
“First, AI systems pose many of the same privacy risks we’ve been facing during the past decades of internet commercialization and mostly unrestrained data collection. The difference is the scale: AI systems are so data-hungry and untransparent that we have even less control over what information about us is collected, what it is used for, and how we might correct or remove such personal information. Today, it is basically impossible for people using online products or services to escape systematic digital surveillance across most facets of life—and AI may make matters even worse.”
Your organisation must comply with regulations (particularly GDPR); it’s your responsibility to protect user information, which means using AI for market research purposes poses a conundrum: how can you protect your customers’ data privacy and still benefit from the efficiency of AI?
This is an ongoing quandary that’s unlikely to be answered any time soon. For now, as before, we recommend that you carefully check what data you’re feeding to AI, and where your market research AI is gathering data from to cover your back.
3. The over-reliance on AI
While AI can process data, it lacks the emotional intelligence and contextual understanding that human researchers bring to the table.
As mentioned earlier, AI can help to enhance customer understanding, but it cannot do this alone.
Context is incredibly important when conducting market research – how is your industry faring? What issues are your target decision-makers facing? Has the individual respondent answered emotionally, or objectively?
AI, naturally, struggles with this. As a result, AI should be seen as an enabler rather than a replacement for human expertise in market research. AI is fantastic at quickly handling the grunt work and top-level analysis. Everything else should be left to the market research specialists.
How is generative AI being used in market research?
Generative AI, such as ChatGPT, has had a profound impact across the business world. No matter your industry, chances are that you’ve had a run-in with generative AI in one form or another.
As it can dynamically create content and analyse data, it’s being used to:
- Collect data – Generative AI can respond on the spot to a customer response, creating dynamic, conversational surveys that adapt to respondents in real-time.
- Manage data – Once collected, generative AI can clean data, monitor quality and preserve data integrity. Generative AI may be able to solve data privacy concerns, however, more research is needed.
- Analyse data – Generative AI can help with data analysis in two ways: 1) quickly produce summaries of data that are easy to understand and 2) instantly visualising data and trends.
- Report on findings – Generative AI can create a narrative from reports, telling stories through data and creating compelling narratives from complex datasets.
Generative AI is learning incredibly quickly. For now, it serves as a powerful tool that supports human skill sets. However, as the technology is changing and improving at such an unbelievable pace, we expect that in the next five to ten years, generative AI for market research will be significantly more powerful; who knows what it’ll be able to achieve. Learn more about the current stats of AI here.
16 AI tools that make market research easier
There are hundreds, if not thousands of AI tools that are entering the market, with more seeming to pop up every single week.
So, to help you get started, we’ve collated some of the best AI tools, broken down into their market research roles:
All-in-one market research tools
These are your all-rounders; tools designed to help growing SMEs and larger enterprises to scale their market research efforts with a complete suite of tools:
- Zappi – Offers AI-driven insights for concept testing, product development, and advertising campaigns.
- quantilope – Automates the entire market research process, from survey creation to data analysis and reporting.
Survey automation tools
Understanding your customers’ wants and needs is essential to any market research efforts. These tools allow you to better get to know your customers:
- Qualtrics XM – Offers AI-driven survey creation and analysis to help businesses understand customer behaviours and preferences.
- Typeform – Uses conversational AI to design interactive surveys and collect more engaging responses.
Sentiment analysis tools
Sentiment analysis is the process of identifying how your brand is perceived among your target markets. Much of this is conducted on social media, checking mentions of your brand and your products. Products include:
- MonkeyLearn – Analyses text data from surveys, social media and reviews, categorising sentiment into positive, negative or neutral.
- Lexalytics – Utilises NLP (natural language processing) to process customer feedback and identify trends in sentiment.
Predictive analytics platforms
While AI isn’t omniscient, it does a fantastic job of predicting what might happen next, using past trends and other modelling to make accurate predictions:
- RapidMiner – Provides machine learning models for forecasting trends and consumer behaviours.
- DataRobot – Automates predictive modelling, helping businesses make data-driven decisions quickly.
Social media analytics tools
Social media is a powerful tool that many organisations neglect. These AI tools are designed to learn from social media (your competitors’, and your customers’):
- Brandwatch – Monitors social media platforms for brand mentions, analysing consumer sentiment and emerging trends.
- Hootsuite Insights – Offers real-time analytics and insights for brand perception and audience preferences.
Competitive intelligence tools
Understanding what your competitors are up to, and how they’re being perceived in comparison to your brand is essential. These tools provide a peek behind the curtain:
- Crayon – Tracks competitor activities, marketing strategies and market positioning using AI.
- Similarweb – Provides insights into competitors’ online traffic, audience behaviour and market trends.
Customer feedback tools
We all love a bit of feedback. These tools make gathering and analysing customer feedback quick and easy:
- Medallia – Collects and analyses customer feedback across multiple touchpoints using AI.
- SurveyMonkey Genius – Uses AI to provide recommendations for better survey design and predicts response rates.
Voice and image recognition tools
Tools to analyse both voice and images, providing unique, possibly never-before-seen insights into your target markets:
- Nielsen NeuroFocus – Combines AI with neuroscience to analyse consumer reactions to ads and products.
- Clarifai – Provides AI solutions for image recognition, helping businesses analyse visual content trends.
How are real brands using AI right now?
This is all well and good, but how are real-world brands using AI right now to improve their market research efforts?
Bayer
Bayer, a German multinational pharmaceutical and biotechnology company, uses machine learning and AI tools to predict cold and flu trends.
The prediction model it developed using Google’s AI and machine learning products gave its marketing team “additional time to plan and activate more effective campaigns” – insights it would not have had without AI market research tools.
Volkswagen
German car manufacturer Volkswagen uses AI market research to help automate its ad buying decisions.
By using data and AI analytics, the Volkswagen marketing team were able to cut ad spend and increase conversion rates, increasing dealership sales by 20%!
Netflix
Netflix famously uses its AI tools to great effect in its app.
How?
Netflix states that, “We gather data about what content our members watch and enjoy, along with how they interact with our service.” This allows the service to get better at figuring out what the next movie or TV show a user would be interested in, keeping them engaged with the app and more likely to resubscribe.
The reams of data that its AI market research tools generate allows Netflix to provide a highly personalised experience for each and every user, while informing marketing decisions about how to target non-users. Clever!
How can you get started using AI?
Getting stuck in with AI and market research can be daunting. As you can see, there’s an awful lot of options you need to consider!
Our recommendation is simple:
Start with a single tool, integrate it and learn from its usage before adding any more.
A one-at-a-time approach helps to avoid your AI tools becoming too overwhelming to manage. Alternatively, if you’re looking for the most convenient way to integrate AI into your market research process, then it’s time to talk to our specialists at Catalyst.
As a commercially focused digital marketing agency, we’ve been following AI marketing tools very closely for the last few years. Over this time, we’ve become incredibly familiar with AI tools and how to get proper value from them. By partnering with us, you’ll have access to a team of digital marketing experts, all of whom know exactly how to balance AI value with human expertise.
This means that we build digital marketing strategies that deliver both tangible ROI and business growth for our clients.
Ready to get started? Book a no-obligation call with a member of our specialist team by clicking the link below.
