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Market
research data analytics platform

Market researcher teams leverage GiQ, equipped with powerful neural graphs and Generative AI, to transform rapidly growing volumes of data into applicable insights.

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Customer insights and behavior analysis

Understand customer buying patterns

By analyzing historical order data, businesses can uncover purchasing patterns, identify customer preferences, and detect seasonal trends. Using graph analytics, they can map relationships between customers, products, and orders, revealing deeper insights that allow for creating personalized marketing strategies and product bundling recommendations.

Analyze sentiment and brand affinity

By leveraging LLMs, businesses can analyze customer sentiments connecting data from social media, reviews, and purchase history. Neural graphs help visualize sentiment and brand loyalty, highlighting shifts in customer attitudes. Predictive techniques further enhance the analysis by forecasting future brand affinity trends, allowing businesses to proactively adjust their strategies.

Generate personalized product recommendations

Graph-based analytics enables businesses to offer personalized product recommendations by detecting patterns in consumer behaviors and product relationships. Similarity detection within graphs uncovers complex connections between products often purchased together or with similar attributes, which increases opportunities for cross-selling and up-selling.

Competitive intelligence

Get a clear view of your competitive landscape

GiQ is an effective tool for understanding competitor activities and mapping relationships between companies, products, and markets. Leveraging LLM-based content processing and visual insights provided by graph analytics, organizations can track market overlaps, uncover emerging competitors, and stay ahead of the competition with dynamic market intelligence.

Monitor competitor activity via web content extraction

GiQ’s platform can process large volumes of web content, blog posts, and reports to extract key information about competitor activities. By building neural graphs that link competitor products, strategies, and market positioning, businesses can gain a clearer understanding of their competitive landscape and adapt accordingly.

Discover competitor strengths and weaknesses

GiQ allows companies to analyze unstructured data sources like reviews, press releases, and industry reports to identify where competitors are excelling or falling short. This deeper understanding is derived from the platform’s ability to connect seemingly unrelated data points and offers a more nuanced view of competitor strengths and weaknesses to inform strategy.

Market trend analysis

Predict future market trends faster

GiQ accelerates market trend analysis by automatically identifying patterns within large datasets, such as sales data, consumer sentiment, and industry reports. Businesses can forecast future trends with greater confidence, which allows them to make informed strategic decisions ahead of their competitors.

Detect emerging market opportunities

Identify underserved or emerging markets by analyzing geographic data combined with customer behaviors, regional demand, and competitive presence. Graph structures can highlight patterns in market penetration and reveal promising areas for expansion.

Track innovation and technology adoption

Track the adoption of new technologies or innovative products on the market by monitoring consumer preferences, usage trends, and competitor activities. Graphs can detect the diffusion of innovations and identify early adopters who may influence broader market trends.

FAQ: learn more about sentiment analysis, market data research, and analysis of consumer behavior

Explore answers to some of the most intriguing market research questions and discover how AI is transforming data analytics for market researchers.

What is a consumer behavior analysis?

Consumer behavior analysis involves studying how individuals decide to purchase and use products and services. It focuses on identifying and understanding the psychological, social, cultural, personal, and situational factors that influence these decisions. By analyzing consumer behavior, market researchers can gather insights into consumer preferences, motivations, and purchasing patterns, enabling businesses to develop targeted marketing strategies, improve product offerings, and enhance customer satisfaction to drive sales and achieve a competitive edge in the market.

What is a sentiment analysis?

Sentiment analysis identifies and quantifies the emotional tone and opinions expressed in textual data. This method involves analyzing customer reviews, social media posts, survey responses, and other text sources to determine whether the sentiment is positive, negative, or neutral. By understanding customer sentiments, market researchers can gauge public perception of products, services, and brands, allowing businesses to respond proactively, tailor their marketing strategies, improve customer satisfaction, and make informed decisions to enhance their market position.

How do LLMs improve sentiment analysis?

LLMs significantly enhance sentiment analysis by utilizing their vast training on diverse datasets to understand and interpret human language with high accuracy. LLMs can grasp context, detect subtle nuances, and recognize complex emotions in textual data.

What is supply chain optimization?

Supply chain optimization is the process of enhancing the efficiency and effectiveness of a supply chain to ensure products are produced and delivered cost-effectively and on time. This involves minimizing costs, managing inventory levels, accurately forecasting demand, coordinating with suppliers, and optimizing logistics. It also includes risk management, sustainability efforts, and the integration of advanced technologies like AI and IoT to improve data visibility and decision-making.

What is a market segmentation analysis?

AI enhances supply chain optimization by improving demand forecasting, inventory management, supplier relationship management, and logistics through advanced data analysis and predictive algorithms. It enables predictive maintenance to reduce downtime, automates repetitive tasks, and provides comprehensive data integration for better decision-making. Additionally, AI identifies and mitigates risks, optimizes routes for cost and time efficiency, and supports sustainability initiatives. These applications lead to a more efficient, resilient, and agile supply chain, resulting in reduced costs, improved service levels, and a stronger competitive edge.

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