AI in Market Research — Three Real-Life Examples

What is AI in Market Research?

AI in market research refers to the use of machine learning, natural language processing, and other advanced analytics tools to collect, analyze, and interpret large volumes of market data.

Instead of relying solely on manual research, AI systems can scan supplier websites, news, reports, catalogues, and social media to extract key information, track trends, and identify risks.

This allows procurement teams to gain a clearer understanding of suppliers, product markets, pricing patterns, and external factors such as regulatory changes or geopolitical events. 

In practice, AI supports market research by enabling tasks such as automated supplier discovery, sentiment and reputation monitoring, price benchmarking, demand forecasting, and summarisation of long documents or reports.

These capabilities help procurement teams identify alternative suppliers, detect early signs of disruption, understand market dynamics, and make more informed sourcing decisions.

5 Steps For Market Research Using AI 

In procurement, market research is essential for understanding products, prices, suppliers, and market trends. AI provides a smarter, faster, and more effective way to conduct this research, streamlining the process and improving decision-making.

1. Find Data Sources

Look at the latest news, industry reports, supplier databases, and government sources. In these areas, you’re likely to find the necessary insights for market research.

With AI tools, you can also find information from websites and news articles to further your knowledge of the latest market dynamics.

2. Prepare to Analyze Data

Before you use AI to study the data, it’s ideal to fix any errors, such as duplicates and typographical mistakes. 

Preparing the data this way unifies data before it is uploaded to the AI model. This ensures professionals get the best results from the collected data.

3. Divide the Market

When using AI, it’s better to break down data for more accurate readings. Additionally, all markets are nuanced and have stark differences from others. 

Using AI to divide the market into smaller parts, you can tailor your procurement process to navigate these nuances and the different needs of each subcategory. 

This applies to geographical categories, industry-specific differences, consumer analysis, and others.

4. Decision Support

AI-driven decisions can further market research by offering actionable information on the market.

You can ask conversational AI to assist with supplier selection, negotiations, and inventory management decisions. AI can evaluate suppliers, potential risks, and sourcing strategies for a smarter approach to navigating the market.

5. Predictive Analytics

Predictive analytics provides a glance into future market dynamics and windows for opportunity. AI and machine learning models can forecast demand and predict price dynamics to avoid supply chain disruptions.

Professionals can look at the predictions in analytics and use it to inform how they source products and select suppliers among others.

Companies That Offer AI for Market Research

AI in market research can be incredibly complex, and every procurement professional needs the right tools to navigate this process efficiently. Below are five AI platforms for market research.

1. LevaData

LevaData uses machine learning algorithms to study past procurement data about the market to drive cost savings and optimize supplier relationships. 

Moreover, LevaData uses predictive analytics to allow organizations to grasp the impacts of geographical risks and market fluctuations on their product or the supply chain.

2. Scoutbee

Scoutbee offers an AI-driven supplier discovery platform to help teams find the ideal supplier for their procurement needs. 

Scoutbee uses natural language processing (NLP) and machine learning to study supplier data, supplier capabilities, and potential risks.

3. Tamr

Tamr’s AI-driven data mastering platform lets organizations unify their procurement data. Machine learning algorithms help procurement teams understand their supplier data to find potential duplicates and make the data quality more efficient.

4. Keelvar

Keelvar’s AI-powered sourcing optimization platform helps procurement professionals optimize their market research by studying supplier bids, sourcing events, and negotiations.

Furthermore, Keelvar’s solutions offer 70-100% workload automation and help reduce maverick spending by 5-10%. 

5. Suplari

Suplari offers an AI spend analytics platform to help teams find cost-saving opportunities. Their platform uses machine learning algorithms to study spend patterns and find anomalies so it can recommend strategies to improve procurement processes.

AI in Market Research — Three Real-Life Examples

AI is increasingly shaping the way organizations conduct market research, enabling faster insights, better predictions, and more accurate analysis of trends and consumer behavior. Below are three real-life examples showing how AI is applied in procurement and market research.

1. Predictive Analytics for Consumer Demand

Companies use AI-powered predictive analytics to forecast consumer demand and optimize procurement strategies. By analyzing historical sales data, market trends, and seasonal patterns, AI models can anticipate shifts in demand with high accuracy.

This helps businesses reduce overstocking or stockouts and make informed sourcing decisions. AI tools can also simulate “what-if” scenarios, allowing procurement teams to evaluate multiple strategies before committing resources. Ultimately, predictive analytics improves efficiency, reduces costs, and enhances responsiveness to market changes.

2. Competitive Intelligence with Natural Language Processing (NLP)

AI systems equipped with NLP can scan vast amounts of public information, such as news articles, patents, press releases, and social media, to extract insights about competitors’ strategies.

This allows procurement teams to identify new products, emerging suppliers, and market shifts faster than traditional methods. AI can also summarize complex reports and detect trends that may influence sourcing decisions. By providing real-time competitive intelligence, organizations gain a proactive edge in planning procurement activities. NLP-driven tools streamline research, making the process more accurate and less time-consuming.

3. Supplier Risk Assessment Using Machine Learning

Machine learning models help procurement teams evaluate supplier risks by analyzing financial health, delivery performance, and external factors such as political instability or natural disasters. AI can predict potential disruptions and highlight high-risk suppliers before problems arise. These insights allow organizations to diversify sourcing strategies, negotiate better contracts, and ensure business continuity. Additionally, AI continuously learns from new data, improving risk assessments over time. This proactive approach enhances resilience in the supply chain while minimizing operational disruptions.

My Insights on AI in Market Research

For this article, I will share my insight on AI in market research.

AI in Market Research: Benefits and Limitations

Conclusion

To sum up, we should embrace AI and use it to our advantage in market research. It speeds up the process, makes it more accurate, and allows procurement professionals to work more efficiently overall.

Its capabilities in automation, predictive analysis, and other tasks make it the ideal tool for helping organizations shape smarter procurement and sourcing. 

While manual work is still necessary, AI is set to redefine the way we approach traditional methods of handling procurement-related tasks.