SCIENCE IS AT THE CORE OF MAVENMAGNET
From data collection to conducting analysis to garnering insights, science and technology form the backbone of our efforts to dig actionable insights from unlimited data. MavenMagnet has developed proprietary technology platform that empowers our solutions.
Developing a tool to track what people are discussing on social media is easy: You shortlist the relevant keywords and search for all the conversations with a mention of these keywords. The challenge arises when you try to derive insights out of them by adding context to meet specific business objectives.
A large part of data collected through the keywords search is irrelevant. Not only that, you also miss out on a lot of insightful contextual conversations that do not contain the specified keywords.
MavenMagnet Digital Mapping™ technique is developed to solve this problem. We do not use keywords search to extract data. Instead we form a digital map pertaining to the business objectives for which data is being aggregated from digital sources including blogs, forums, news, reviews, video logs, audio files, and social networks. MavenMagnet Digital Mapping is based on statistics fundamentals to eliminate irrelevant data and organize the information that is contextual and relevant to the business objectives.
The precision of the data collected before running the clean-up process to eliminate irrelevant data averages 0.20. Typical recall is 30-35% higher than normal search engines and social media monitoring tools because of our aggregation process.
A key element of Digital Mapping technology is the "noise" elimination process that increases the precision measure, post clean-up, to 0.95, keeping intact the high recall.
Key advantages of our data aggregation technique
- MavenMagnet’s digital mapping based data aggregation technique maintains a high quality of data repository free of noise, bias and posturing to do the study.
- Our proprietary technology platform aggregates and contextually analyzes data from a wide range of digital sources to extract qualitative insights on a quantitative scale. We go broader and much deeper than social listening. Typically, more than 75% of the data we collect is sourced from outside the popular social networks.
- MavenMagnet’s methodology eliminates the need for questionnaires because we use digitally-sourced conversations to do market analysis. This also provides a big discovery component because we are not constrained by questionnaire limitations.
- We have also developed the technology to analyze the context of conversations, thereby eliminating the need for awkward Boolean pairing.
- We do not recruit respondents but instead leverage the conversations on digital platforms to conduct the study.
MavenMagnet has developed a proprietary technology infrastructure to analyze data aggregated using innovative AI/ML models.
MavenMagnet AI/ML models power the analysis process and harnessing insights from a unified digital landscape. With transfer learning from best-in-class models, we solve customer challenges by delivering them an AI-assisted system to help make critical business decision. We follow a cyclic process to train our AI/ML models using trustworthy data, mult-level analysis and insights, and customer feedback, continuously making the models more efficient.
Insights Mining Framework™ is an innovative MavenMagnet technology to set the framework to enable multi-level deep dive analysis and extract actionable insights from unlimited datasets. We use customize multi-labeling ML models extensively trained across categories. Our framework is efficiently operational in more than 103 categories in over 25 markets globally.
Image, Audio and Video analysis is a critical piece of our technology infrastructure to provide wholesome insights from the unified digital landscape. Through transfer learning and significant advancements in AI/ML models in areas such as Computer Vision application, Object Detection technology, Optical Character Recognition technology, and Facial Expression Recognition, we have developed efficiency in analyzing data across formats. Our customized models in the space of Speech-to-Text, Speech Emotion Recognition, and Speech Segmentation are efficiently trained to enable us analyze audio calls as well as videos.
Theme Identification Engine™ discovers core conversation themes. We use customized topic modeling ML models to identify the themes and develop the Insights Mining Framework to extract insights. The AI/ML models are trained at category cluster level, capturing the nuances of the category, leading to more accurate and granular insights.
The sentiment associated with the themes is identified by Vibe Sensor™ , a technology developed based on natural language processing and machine learning techniques to associate the right sentiments to the right themes in a conversation. Sentiment Analysis processes text data and assigns polarity as well as an emotional state to the themes. While our goal is to get the system to a state where unsupervised machine learning can do the analysis, the current process is based on semi-supervised machine learning where expert human input plays an interpreter’s role to remove ambiguity and train the model. This is critical to handle cases such as slang, sarcasm, technical terminology and mixed sentiments.
MavenMagnet Predictive Modeling identify data patterns in historical data and provide leading indicators for future outcomes and accompany it with an action plan consisting of tactical and strategic recommendations. We use advanced data aggregation, machine learning and custom predictive analytics models to drive actionability.
MavenMagnet Ethnography defines consumer persona by following digital footprint of customers. Our unique approach to ethnography quantifies every element of consumer persona and we do this without violating privacy of individuals or interfering with their digital life.
- MavenMagnet has developed cutting-edge technology that uses information generated by digital conversations to garner insights keeping intact the core fundamentals of market research. MavenMagnet brings a new thinking to the market analysis process and implements it with the help of AI/MML technology supervised by strategists. We do not moderate discussions or ask questions. Instead we use the Digital Mapping technique to aggregate information from the conversations people have with their associates on interactive platforms. This information is completely random and representative of the overall base data. The quantum of data available digitally ensures that the sample size for the study is robust to provide quantifiable insights.
- Our system uses our proprietary Influencer Mapping™ technique to define the demographic profile along with geographical and linguistic orientation. Influencer Mapping along with MavenMagnet Correlation Mechanics™ are used to determine the psychographic profile of the target consumers. MavenMagnet Theme Identification Engine and Vibe Sensor provides holistic thematic analysis and corresponding vibe perceptions.
- MavenMagnet analytics process is a combination of state-of-the-art technology and strategic human supervision. This helps us perform study at close to 100% accuracy (+/- 1%) on every business objective and makes MavenMagnet insights richer and more efficient as compared to other forms of insights generation.