It’s no secret that Artificial Intelligence (AI) is completely reshaping the workforce. In sectors like market research, many are questioning how AI will help or hurt how research is conducted.
In this piece, we’re discussing the potential advantages of using AI technology in this field, as well as the downfalls of using AI for market research.
Defining AI in the Market Research Space
AI is a general term used to describe tasks that machines can perform by themselves. It includes technologies like machine learning, natural language processing, and computer vision.
Within the market research space, AI provides the ability to automate more complex processes while helping to identify patterns in data faster and more accurately than ever before.
With this data, companies can refine and analyze, making business decisions accordingly. For example, deciding where to roll out a new product based on survey results farmed by AI.
Artificial Intelligence’s Roll in Market Research (Examples)
- Collecting Data
- Synthesizing Data
- Organizing Data
Will AI Hurt or Help Market Research?
The next big question that enters the AI and market research discussion is whether it will be a positive or negative change. The answer is murky.
Artificial intelligence is set to change the way market research is conducted in some big ways – and it’s coming quickly, quicker than anyone thought.
According to a study done by Qualtrics, initial findings from a survey conducted among market research professionals indicated that
- 93% of researchers see AI as an industry opportunity and 7% see it as a threat, and
- 80% say AI will make a positive impact on the market research industry. Both older and younger researchers share this view.
But the reality is that artificial intelligence can impact sectors both positively and negatively.
In fact, a few core factors on when and how market research is conducted: cost, manpower, and intent, are all vulnerable to AI’s implementation.
Let’s dive into some potential benefits and drawbacks of AI in the market research space to get a better idea of its influence.
Common Benefits of AI Use in Market Research
There’s no doubt that AI is changing, but the verdict on whether it’s good or bad varies. Here are a few common positive benefits mentioned when it comes to artificial intelligence in market research discussions.
1. More Equitable Access for Businesses
One of the most exciting benefits of using AI for market research is that it gives businesses access to better data, regardless of their size.
AI eliminates the need for large teams and expensive software solutions, meaning even smaller companies or startups can have access to reliable information about customer needs, purchasing habits, and preferences.
This also means that businesses don’t need to rely on expensive, resource-draining focus groups and surveys. In other words, artificial intelligence is slowly leveling the playing field of equitable access to meaningful data.
2. Narrowing Down Quality Respondents
One of the toughest components of data collection and refining is that there are too many low-quality responses out there.
Whether it’s a quick response to get extra credits in a game or because an employer said to do it, low-quality answers are all too common.
While companies like ProductLab have built-in parameters to detect and exclude low-quality responses, AI may also offer capabilities of sifting through and determining the quality.
Rather than having a person sift through and separate quality responses, AI technology can help to narrow down a list of potential respondents based on their demographics and interests.
This helps businesses focus on those they think would be most likely to respond accurately, reducing the risk of inaccurate data or skewed results.
3. Eliminating Personal Biases in Market Research
Biases in AI are a hot topic. AI is said to help eliminate personal biases on behalf of researchers when conducting market research.
By automating processes, AI removes the need for manual input, which reduces the chance of personal opinions and beliefs affecting results. This means businesses can get far more accurate data that is not skewed by any one person’s opinion.
Even if a company does not believe biases are a threat to its data collection, the reality is that if there is a human involved in the process, biases are possible.
Artificial intelligence can help to reduce that burden and potentially data-threatening thoughts and impulses. However, some research has shown that AI may be subject to its own biases.
4. Better Handling of Large-Scale Surveys
When it comes to larger-scale surveys, AI can be instrumental in helping businesses sort through the data faster and more accurately.
With AI capabilities, companies can quickly analyze large amounts of survey data and identify trends that could indicate potential issues or opportunities.
This helps businesses save time and money by allowing them to focus their attention on areas with the most potential or market research tasks that are vulnerable to artificial intelligence (more on that in the drawback section).
5. How AI Can Help with Data Collection and Analysis
AI can be used to automate data collection and analysis for market research projects. AI algorithms are able to automatically detect, collect, and sort through large amounts of data quickly and for the most part, accurately.
But just like a human, there is no way to zero out a potential margin of error completely. This means businesses no longer have to manually enter each piece of data or manually analyze the results of a survey or focus group.
Instead, AI algorithms can take care of the process for them, allowing them to focus on more important tasks that require brainpower.
Mining through data is cited as being one of the biggest pain points for market researchers.
Entrepreneur India points out that “manually scanning through the data is cumbersome and tough. Many existing techniques to juggle around add to the challenge of getting the right data.”
6. A Focus on Secondary Research
AI can be used to quickly and accurately comb through large amounts of secondary research data. This can be particularly useful for businesses that need to make decisions based on existing literature or market surveys.
With AI algorithms, businesses can quickly and easily identify trends, patterns, and opportunities in the data they have collected.
This helps them save time and money while still being able to make informed decisions based on relevant data, allowing for market research teams to focus on things like primary research where necessary.
For more information on the difference between secondary and primary research, visit here.
7. AI Can Help Researchers Analyze Data Efficiently
AI algorithms can quickly process and identify trends in large datasets, allowing researchers to draw connections between data points that would have otherwise taken much longer to recognize.
This helps businesses save time and money by providing them with the insights they need without having to manually analyze every piece of data.
In addition, AI algorithms can be used to detect anomalies or outliers in data sets that could have been overlooked by manual analysis, allowing for more accurate results.
8. AI Can Help Businesses Synthesize Data
AI algorithms are able to take large amounts of complex data and synthesize it into simpler, easier-to-understand insights.
This helps businesses make sense of the information they collect and quickly identify opportunities. Additionally, AI can be used to synthesize data collected from multiple sources, allowing businesses to make use of data they may not have had access to before.
By using AI algorithms, businesses are able to make more informed decisions based on comprehensive and up-to-date information.
Potential Drawbacks of AI in Market Research
Despite the benefits that can come with automation and other features of AI, there are also a host of potential drawbacks too.
1. Reducing or Redirecting Research Teams’ Jobs
With the introduction of AI into market research, there is a potential to reduce or redirect jobs that are currently falling under the purview of traditional market research teams.
As AI is able to automate certain tasks and processes, it can also replace some roles and functions that were once fulfilled by human teams.
“The effects of AI-based technologies in the context of the labour market may be even more pernicious. Labour market inequality has increased in the US and several other advanced economies, and much evidence suggests that this is caused in part by rapid adoption and deployment of automation technologies that displace low and middle-skill workers from the tasks they used to perform…”
VOXEU
This could lead to job loss for those in the industry and could potentially put a dent in the overall market research sector.
Though some believe that jobs within market research will simply be readjusted to do what AI cannot.
For example, a research assistant for collection may not be necessary, while a person who can sit down, analyze the data, and make suggestions based on business dealings will be.
2. Understanding Cadences and Varying Vocab
AI algorithms are not perfect and have some limitations. For example, AI has trouble understanding natural language or recognizing the context of some conversations, which is important for market research.
While AI has tons of resources to pull from on sturdy, academic language, it has much fewer colloquial examples to pull from – the exact kind (abbreviations, explicative, and all) that people are likely to plug into a survey answer.
This data is sometimes referred to as dirty data and can throw AI programs for a loop or put a cog in the machine – two sayings AI may misinterpret when sifting through data.
3. Unable to Suggest or Refine on a Human Level
AI is unable to suggest or refine on a human level. This means that it can’t offer creative insights or make recommendations based on personal judgment, which is something that traditional market research teams are able to do.
For example, a team of researchers may recognize a potential issue with the data or be able to spot trends in the data that AI is unable to detect.
This means that while AI can be used to help with the collection and analysis of data, it cannot replace human judgment when it comes to making decisions or suggesting solutions based on the results of the analysis.
Because one of the greatest uses for market research is to expand a company’s reach product or offering wise, this step is crucial.
4. AI Is Outpacing Safety Research
AI is being used in a variety of applications, from autonomous vehicles to healthcare. However, it’s important to remember that AI is still relatively new and has the potential to cause some unforeseen issues.
The rapid development of AI has led to concerns about safety and security. For example, there are worries that an AI system may be prone to making mistakes or may be vulnerable to malicious actors.
As a result, it’s important for companies to ensure that robust safety and security measures are in place when using AI for market research and other applications.
“Frankly, this is to me the worst-case scenario we’re on right now — the one I had hoped wouldn’t happen. I had hoped that it was going to be harder to get here, so it would take longer. So we would have more time to do some AI safety. I also hoped that the way we would ultimately get here would be a way where we had more insight into how the system actually worked, so that we could trust it more because we understood it…”
80,000 Hours
5. Difficulty Problem Solving
AI is only as good as the data it’s given, so if the dataset is incomplete or contains inaccuracies, then the results of the analysis will be affected.
In other words, artificial intelligence lacks the ability to spot issues on a human level which will leave the need for human interaction at some level throughout the entire process of a market research project.
If AI does not know how to detect a problem early on, it may finish collecting or analyzing the data as instructed incorrectly and send that off as accurate.
What may then happen is a lot of backtracking to try and undo the incorrect actions, assumptions, or decisions an AI program did not know to avoid.
Final Thoughts: AI in Market Research
Overall, the introduction of AI into market research can offer many benefits, but there are also some potential drawbacks too.
It’s important for companies to weigh the pros and cons and decide if it’s the right choice for their business, as there is no blanket implementation option.
What works for some companies will not work for others depending on the intent and method of the market research but also the limitations and abilities set forth by an individual company.
By carefully considering how artificial intelligence fits (or doesn’t) into an individual business plan, businesses can ensure that they are making the most of AI while avoiding any potential pitfalls.