AI for Market Research: Driving Efficiency, Insights, and Key Takeaways

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"DIY dog food" is trending

Artificial Intelligence (AI) is transforming market research, enabling marketers to gather, analyze, and interpret vast amounts of data more efficiently than ever before. From customer development to competitive analysis to market trends, in this blog post we'll explore how marketing professionals can leverage AI for market research.

Market research is a critical process for marketing professionals, as it enables them to understand their target audience, competitors, and market dynamics comprehensively. This involves the systematic collection, analysis, and interpretation of data about a market, including information about the customer, competition, and market. This process informs strategic decision-making by providing insights into customer needs, preferences, behaviors, and the competitive landscape.

Is there AI for market research? 

While Artificial Intelligence can assist in the key components of market research (customer development, competitive analysis, market trends), a human is still needed to fit all the pieces together. Here is an overview of the key components of market research, as well as the areas that can be made more efficient with AI tools.

Key Components of Market Research

Customer Development 

This is market research with the goal of understanding the demographics, psychographics, needs, and behaviors of potential customers. Customer development traditionally involved publishing surveys or questionnaires, holding focus groups, demand testing through pre-sales and LeadGen, keyword research, and more. 

With the introduction of artificial intelligence to the field, we are marching towards a future where AI models will be able to produce synthetic datasets that are representative of population samples. In that case, a marketer could theoretically submit their survey to a synthetic audience and receive statistically representative results, without needing to source survey participants. 

However, until that day comes, here are three simple ways you can use any LLM (like ChatGPT) to perform customer development today:

ai assisted customer segmentation

Identify customer segments 

Ask AI to identify segments you may not have considered. Example prompt,

"My brand, Bark Bits, sells organic, high-quality dog treats. Please help me identify three new and novel customer segments, and explain your reasoning behind each suggestion."

Assess customer satisfaction and loyalty

Copy+paste customer reviews, social media comments, customer service emails, and more into an LLM to quickly assess sentiment and pull out key takeaways. Example prompt,

"Can you look at these Amazon reviews for my dog treats, and tell me the top three things customers liked and disliked about the product?"

Explore customer pain points and motivations

Explore customer personas in-depth by feeding an LLM data about the customer, and asking it to take on their personality. Then, ask the "customer" about their wants, needs, their opinion of your four taglines, or even if they would think your joke is funny. 

Keep in mind that all of these AI-assisted hypotheses about your customer segments are exactly that—hypothesis—and require validation through testing in real life.

Competitive Analysis

Marketers are constantly evaluating current and potential competitors. This process helps businesses understand their market position, identify gaps in the market, and develop strategies to gain a competitive edge. Traditionally, competitive analysis has relied on manual research methods such as analyzing public financial reports, mystery shoppers, social media monitoring, and industry events and trade shows. 

On the digital front, AI-powered tools are enabling businesses to gather and analyze competitive intelligence more efficiently and accurately than ever before. Here are three ways to use any LLM to assist with competitive analysis:

ai competitive analysis, "people think your brand is more expensive than your competitors"

Profile competitors

Feed an LLM with publicly available information about your competitors (e.g., website content, press releases, social media posts) and ask it to create comprehensive competitor profiles. Example prompt:

"Based on the following information about our competitor 'Pawsome Treats', can you create a detailed profile including their product range, target market, unique selling propositions, and SWOT?"

Discover new competitors

Use AI to identify potential competitors you might not have considered. This can include companies in adjacent markets or startups that might disrupt your industry. Example prompt:

"Our company, Bark Bits, sells organic dog treats. Can you identify five potential competitors we might not be aware of? These could include human food companies or innovative startups. Please explain your reasoning for each suggestion."

Analyze marketing strategies

Leverage AI to dissect and understand competitors' marketing tactics. You can input competitors' ad copy, social media content, or email campaigns and ask the AI to break down the strategies being used. Example prompt:

"Here are three recent marketing emails from our competitor 'Pawsome Treats'. Can you analyze their messaging, offers, and call-to-actions, and suggest how we might differentiate our own marketing approach?"

You will notice, however, the onus is still on the marketer to source the research material for AI to analyze. Hopefully one day there will be a good all-in-one tool that both sources reliable data and then analyzes it for you. However, we haven't found one yet.  In the meantime, you can still take your competitive analysis beyond ChatGPT with AI tools such as Crayon, Brand24, or Browse.ai to get more high-powered AI features such as real-time monitoring and analysis of competitors' online activities, or advanced sentiment analysis of customer feedback across multiple competitors. 

Market Trends

This component of market research involves monitoring emerging trends, technological advancements, regulatory changes, and economic shifts that could impact your industry. Traditionally, analyzing market trends has involved methods such as reading industry publications and reports, analyzing sales data and consumer behavior over time, or tracking economic indicators relevant to the industry. 

As we know, AI-powered tools can process vast amounts of data from diverse sources in real-time, providing more comprehensive and timely insights. Here are three ways you can leverage AI to enhance your market trend analysis:

example ai market trend insight, "the pet food industry is experiencing sustained interest in human-grade food for dogs and cats"

Synthesize information from multiple sources 

Feed an LLM with recent news articles, industry reports, and social media trends related to your market. Ask it to synthesize this information and identify key trends. Example prompt:

"I've provided several recent articles and reports about the pet food industry. Can you analyze this information and identify the top 5 emerging trends that could impact our organic dog treat business?"

Predictive trend analysis

Use AI to extrapolate current data and predict future trends. Please note that most LLMs such as ChatGPT cannot do math ("how many R's are in 'strawberry'?") so any number-based analysis must be delegated to an AI tool that does, such as Tableau or Power BI

Impact analysis of external factors

Leverage AI to assess how external factors like regulatory changes or economic shifts might impact your market. Example prompt:

"A new regulation on pet food ingredients is being proposed. Can you analyze the potential impacts this might have on the organic dog treat market, considering consumer behavior, production costs, and competitive landscape?"

Predictions for AI in Market Research 

The future of AI is already here. Here are several key ways the field of market research will be transformed by AI in the near-future: 

  1. Qualitative Analysis: While it has been possible to automate quantitative analysis for some time, qualitative (think: audio transcripts) have been much more elusive… until now. From sentiment analysis of customer reviews to identifying patterns in competitor strategies, qualitative analysis with AI saves hours of work.
  2. Synthetic Datasets: As mentioned earlier, statistically representative synthetic datasets of populations, and synthetic customer personas are quickly becoming reality.
  3. Augmenting Human Expertise: Rather than replacing human researchers, AI serves as a powerful tool to augment their capabilities. It can handle routine tasks, process large volumes of data, and generate initial insights, freeing up human experts to focus on strategy, interpretation, and decision-making.

As AI technology continues to advance, its integration into market research processes will become not just an advantage, but a necessity for businesses looking to thrive in an increasingly competitive and fast-paced market environment. Fortunately, any marketing professional from novice to expert can begin leveraging AI for market research today, with simple LLMs, even on free accounts. 

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