Natural language processing is a very powerful tool that enables us at Monte to analyze large volumes of text to look for hidden patterns and “data mine” it to summarize opinions and feelings. We use NLP to understand trends, market segmentation, and compute correlations between brands and specific terms, such as product quality or specific feature words.
Replacing Surveys with NLP & Data Mining
This NLP-based opinion signal lets us derive an understanding of how ad campaigns, events, tradeshows, and PR are impacting the public. We make this data understood by producing well-designed visualizations, including semantic network diagrams, multidimensional plots, and employing best practices from data science.
Comparing our Sentiment Models to Benchmark Business Metrics
Our proprietary NLP methods for investigating consumer sentiment provide insights that are actionable on short timescales, whereas the University of Michigan Consumer Sentiment Index is only published once per month. We validate our monthly mean values against this benchmark, however, to monitor our monthly performance.
Diverse Text Sources
We analyze data mined from social media platforms and websites such as Twitter, Reddit, and MarketWatch. Furthermore, we have published academic research on natural language processing for marketing purposes with collaborator Dr. Jun Min. Publishing NLP research ensures that we remain at the forefront of both technology and market direction. In 2021 our presentation to the Society For Marketing Advancements was awarded best paper. Our most recent peer-reviewed manuscript was published by the American Marketing Association and analyzed the social impact of sponsoring the Olympics by Samsung, Visa, and Coca-Cola.
Language Research is Business Science
The market research and analytics we provide, sometimes called “business science,” gives our clients the advantage of studying the broader mind of the market – monitoring key topics in the public ‘conversation’ and being able to recognize when opinions shift, permitting them to respond quickly to positive events and maximize their benefit, as well as when the news is negative, to mitigate the impact on their brand. We give them a new pair of eyes, which can “see into the mind” of the public reflected in patterns of word use. Using NLP, we can score sentiment on a simple positive/negative scale or assign categories of sentiment and score how many words align with each category. For example, Innovation is a topic of interest to us, so we can review the feelings correlated with tweets containing this word.
Machine Learning for Language Analysis
By utilizing the most appropriate methods in machine learning for text analysis, we can evaluate content from external sources, like customer or social comments, or from company internal text sources, such as sales calls or customer service. Of course, data without interpretation is not useful, and at Monte we take great pride in developing highly effective visualizations. We have decades of experience creating powerful graphics, and ensure the output of our analytical tools is understood and interpretable by our clients.
More than Research: Creating with Technology
We develop new technologies to give our clients a creative edge as well as deep insights: generative tools that help us discover word candidates for naming products and companies. The example seen here is a network diagram showing words related to food as input terms. Our software looks for related word use patterns derived from 6 billion terms, that’s big data by anyone’s definition.
Custom Lexicon Development
Custom lexicon development is a service to generate scoring mechanisms to research specific aspects of product design or service quality. For example, below is part of a network of terms related to modern electronics product design and interface. This type of lexicon is a special area of language processing and enables us to engineer metrics that identify how the public feels about specific product features, such as useability or design aesthetic. Contact us to discuss your custom language analysis and research needs.