Copyright 2019, Converseon, Inc.

If You Want More Insight From Your Unstructured Social and Voice of Customer Data...This Complimentary eBook is for You.  

Applications of AI for extracting insight from social and other customer data are usually long on "buzz" but short on specifics.

This new eBook, written with contributions with some of the world's leading market research, data science, and machine learning experts, provides the answers you are looking for on how to effectively build, evaluate and apply machine learning models to this unstructured data for accelerated and accurate insights.

In this eBook you will learn:

  1. How machine learning is truly transforming the analysis of insight-rich language data. 
  2. The difference between general machine learning models and "intelligent" models (and why this matters). 
  3. Essential steps in evaluating and improving model performance, and machine learning model vendors. 
  4. How auto MLaaS is enabling even general analysts to build, validate and deploy sophisticated models in areas ranging from customer experience to trend discovery and brand tracking.

We hope you find this eBook useful and of interest. If you would like to discuss further and/or get a demo of the Conversus.AI platform (and how it can work with your current social listening platform for more advanced analysis) please contact us at hello@converseon.com.


Download  the eBook

"If you want a simple guide to how AI works when analyzing social data, this is the guide for you. Coming from a market research background I’ve always had a healthy skepticism towards AI in text analysis – I like to be in full control of my data segmentation. Understanding more about the different stages in building a high performing text-based machine learning models has been great to understand more where my skills can feed into the process. One of the things we should all remember is “every model will contain errors, and yours is no exception” – this guide from Converseon.AI helps you to understand how to fix and reduce these errors." 

- Dr. Jillian Ney,  Digital Behavioural Scientist, The Social Intelligence Lab