Text analytics is a linguistic data set where customer comments (both on and offline and within CRM records) are analyzed to find patterns and extract common information to better serve the business and its customers.
I recently wrote a blog post focused on how companies are using social CRM. Everyone seems to be using social customer service to gauge customer sentiment, manage product and service issues, and follow up with customer service complaints. The focus on social media strategies is overwhelming to many organizations but of even more significant is the lack of Social Media Business Intelligence. Why are you monitoring and gathering all of that consumer data if you cannot do anything valuable with it? For any business project don’t you need to prove the value of the effort and investment?
Along with your consumer data gathering, consider text analytics to help you organize unstructured text-based data in your CRM systems (and in social media), survey and emails into a form that can be analyzed to uncover patterns or trends. Do you notice a spike in online customer complaints about the lifespan of one of your new products? What do you do to prove the need for action? Text analytics supports, for example, the need for the manufacturing department to reevaluate the intended use for the product and the Warranty/Finance Department to alter the current product warranty.
Many companies may offer the complaining customers a quick refund or replacement to stop further brand badgering. Dealing with one vocal and hostile customer at a time is not harnessing the power of the customer intelligence available. Digging deeper into the mountains of information with text analytics or text BI uncovers the larger issues and builds a business case for a successful remedy, instead of putting a band-aid on one customer at a time. Continue reading “Text analytics makes the most of consumer data.” »
Last week we formally announced Text BI™, our latest managed service offering. In advance of the announcement, I spent some time talking with Denise Deveau from E-Commerce Times about this news, as well as the general challenge of harnessing unstructured data. In a story that she published based on our conversation, Denise explained the basics of Text BI:
“Text BI enables companies to take unstructured text-based data from surveys, emails, social media, CRM systems and other applications, and organize it into a format that makes it easier to analyze.”
She also included some of my thoughts about the human element of the big data equation, and the lack of skilled analyst talent that is making it extremely difficult for some companies to truly take advantage of the data at their fingertips.
For more information from our interview, check out Denise’s full story, “Customer Relationship Metrics Takes on the Unstructured Data Challenge.” And for additional details on our Text BI offering, check out the full press release below.
What do you do when one of your best selling products, your cash cow, your go-to, has decreasing sales revenue and can no longer be counted on to save the sales figures? Worse, what if most of the ones being sold are quickly returned? The call center has the answers, and they lie within the call logging and coding data, and the metrics from social customer service. Companies can mine their ‘big data’ by using text analytics and uncover the root issue of this terrible trend.
The company Twitter feed and Facebook page supports the discovery that customers perceive the product to not be as fast as the competition, and lacks some additional functions they know are possible now. When the CRM records are analyzed the hypothesis is confirmed, as each return highlights the product speed as the main reason for the return.
While the problem may not be a quick fix, the answer was found significantly faster through text analytics than waiting until the Annual Report or The Street, reports the loss of earnings. The business intelligence through text analytics can lead to the creation of a new process for the product development group, a new product roll out, and before you know it that cash cow product is back on top in the market place. Continue reading “Text analytics adds the ‘why’ behind the numbers.” »