Biometrics & Cognitive Neuroscience
Cognitive Brand and Consumer Insights from Unstructured big data
TEXTIENT ANALYTICS - India
Our Cognitive Analytics decodes deeper consumer-truth for predictive insights faster from the growing unstructured (text) data from voice of consumers to develop emotionally engaging products,services,brand and marketing at an affordable cost.
Development Stage: Growth Mode
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The hugely growing of consumer generated unstructured  data contains a significant intelligence about the changes taking place in Consumers lives & Intricacies. Often missing in such data is deep insights about the human psyche (minds & hearts) and leveraging it for business at scale.We fix this intelligence gap.
Brand position & Differentiation
Consumer profiling, segmentation
Consumer Behavior
Category Analysis / Trend
Brand to Consumer Emotional connect
Brand Health
Marketing performance
Product testing, Innovation
Risk Sensing
Market Potential

  • IDG: Unstructured data is growing at the rate of 62% per year.By 2022, 93% of all data in the digital universe will be unstructured. Gartner: Data volume is set to grow 800% over the next 5 years and 80% of it will reside as unstructured data.
  • According to the recent ESOMAR Global Market Research Industry report, 2016 , The Market size for NEW Market Research methods including Analytics was pegged at USD 28.2 billion.
  • The text analytics market size is estimated to grow from USD 2.65 Billion in 2015 to USD 5.93 Billion by 2020, at a CAGR of 17.5% 

Scalability & Ease of Implementation

Our Cloud based Self-service Analytics architecture is built for dynamic scalability . We provide a user friendly web interface. It just takes 3 steps to get started with the insights. 

Originality of the Concept:

Key aspects of our Analytics platform

  1. The ability to harness complex unstructured text data that is typically noisy, ambiguous and having varied nuances in the linguistic sense from various sources and Quantifying it to produce meaningful outcomes is a critical part of our original concept.

  2. Bringing deeper brand and consumer insights with qualitative dimensions from the unstructured data that are based on standard and established scientific principles practiced widely in the world of traditional market and consumer research world . Few examples are a) Brand position and promise through brand personality archetype model b) Well known Consumer Motivations and its profile C) Comprehensive Consumer personality trait orientations .

  3. By combining our intimate knowledge in Human Behavioral sciences combined with our expertise in Big data and Cognitive computing and further by applying the State of the Machine learning and Cognitive AI technologies from IBM Watson, we have been able to make a deep dive in to the data to find meaningful and valuable intelligence actionable for the business. 

  4. The *Overall software engineering and computational Process* that is involved in producing the outcomes (i.e lifestyle of the cognitive analytics) with an affordable pricing and Ease of use for users is a complex one.This requires thoughtful and sophisticated Cloud based software Architecture and design that factors in a lot of automation and orchestration to process and analyse data, make predictive analytics and  to dynamically scale at any time. These big data and analytics process complexities are completely hidden to an End user who uses our platform on a self-service model They can just focus on acquiring and specifying the data aspects and running the analytics flexibly to get qualitative brand or consumer insights report in a matter of minutes. 

A Global Personal care company generating a lot of Consumer feedback in the form of Unstructured (text) data had challenges to turn it in to actionable insights for their product development and innovation. With TEXTIENT, They can now gain strategic insights based on the consumer truth and how its driving their products and brand.

Our platform has enabled the customer to accelerate their strategic initiatives from their Voice of consumer data and to gain higher value and returns at a significantly lower cost. 
We have an automated cloud based data acquisition, mining and cognitive analytics pipe-line to generate qualitative insights as reports with an easy to use web based user interface.
Author
Sankar Nagarajan
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