Blog Coveo Insights

Understanding the Evolution from Disparate Data to Informative Insights

Posted by Diane Berry on February 17, 2012

Data, by its very nature, is difficult to find and analyze because it’s stored in so many places, with no way to search through it or correlate it across systems to derive meaning from it.

As a recent Fast Company interview with Coveo CEO Louis Têtu stated, people who could remember all of this information, and easily correlate it—mentally—were those who succeeded most often. However, the amount of unstructured data makes it impossible for an individual to know everything that’s occurring related to a specific topic, at any point in time. Add in social media channels which contain up to the minute data, and you have an unbelievably complex information mess. How can an individual, much less all employees in a company, gain insight from such widespread, diverse data in disparate systems? Read more and comment »

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Steps to Unstructured Data Nirvana

Posted by Diane Berry on December 19, 2011

In my last blog we looked at the nature of mercurial data and identified two truths: 1. It is constantly changing; and 2. It exists in silos. Here, we will talk about what some companies are doing to use diverse and ubiquitous unstructured data to transform their businesses.

Monitor. This is the first step that most companies have taken to get involved with unstructured, social media data related to their business. Listening can provide certain benefits, too, such as helping you to understand what people are saying about you. However, listening without responding doesn’t do much for your business. Many organizations use text analytics on individual social media streams and communities, which again may be a good first step (Zach Hofer-Shall, an analyst with Forrester who covers Customer Intelligence, refers to this step as “crawling” – as in crawl-walk-run – in his Roadmap to Integrating Social and Customer Data). This analysis generally creates more data around a single data stream (the social platform) which is subject to data characteristic #2 – it is siloed, generally within marketing or customer support, and also #1, it grows old and requires updating. This first step is generally inadequate because it does not relate the social data (or other data that is being monitored, such as phone calls or chat logs in the call center) to other data that will lend it meaning and provide the insight to take action. Read more and comment »

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