Lenovo taps Taste Analytics to gain insights from online chat, proves value supporting a better customer experience


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Using data mining, company improves sales and support for customers in North America

Charlotte, NC – March 24, 2016 – Online customer service chat channels open the lines of communication between brands and consumers, from solving service issues to answering product questions, but the value shouldn’t stop there. To better anticipate and refine strategies in customer service and sales,Lenovo , a global PC maker and retailer, is working with Taste Analytics to deliver actionable insights in real time from its online chat session data logs in the North American market, which was put to the test over the busy holiday shopping season.

Today’s consumers are turning more to online channels to share feedback, complaints, or make requests to a brand or service. To meet and exceed this increasing demand, Lenovo is leveraging Taste Analytics’ Signals platform to automatically process textual data from its customer service online chat portal to help identify key patterns, behaviors and potential issues hampering the overall online experience in both macro and micro views. The ability to drill down and focus on a specific day, or evaluating sessions over days, weeks or even months, allows Lenovo sales and customer support teams to quickly identify trends and issues and address them head on, while ensuring agents are following protocol and delivering top-notch service.

“We switched to Taste Analytics from another Text Analytics/Customer Experience Management Vendor because Taste Analytics frees us from using taxonomies. We can now leverage Taste Analytics’ theme detection and no longer need to manually build out taxonomies to listen to our customers. This tremendously reduces our time to gain meaningful insights,” said Dan Bieber, Analytics Architect at Lenovo.

The Taste Analytics Signals platform processes large volumes of unstructured and structured textual data from almost any source – emails, chat sessions, text files, e.g. Word and Evernote, blog posts, app reviews, social media and more. It produces quick and actionable insights in seconds by incorporating predictive modeling, machine learning, and robust statistical Natural Language Processing (NLP) algorithms to create visualizations of behavior communities, trends, patterns and outlying themes. Key aspects of the Taste Analytics Signals platform include no complex integration, intuitive dashboard, and advanced functionality. The Signals dashboard offers drag-and-drop data importing and drill-down options – such as temporal trends, category overview, or buzzword and geospatial analysis.

“The digital transformation is providing many challenges for companies and today’s online shoppers expect an optimized experience at every touchpoint,” said Derek Wang, CEO and founder of Taste Analytics. “We help analyze data in real time, allowing the customer service and customer experience teams uncover potential issues and opportunities in real time without complex IT integrations or by taxing data science teams. Our product has been able to quickly process all the data for Lenovo and present it in a way that allows the company better manage the overall customer experience.”

To see how Taste Analytics Signals can help turn your unstructured data into actionable insights, visit: www.tasteanalytics.com .

About Taste Analytics

Taste Analytics changes the way people gain invaluable and actionable insights from textual data. Incorporating predictive modeling, machine learning, and robust statistical NLP algorithms, Taste Analytics helps to create visualizations of behavior communities, trends, patterns, and outlying themes. We are a team of computer scientists and engineers with one simple goal in mind – to help companies make fact-based decisions from their unstructured data sources. Founded in 2012, Taste Analytics is headquartered in Charlotte, NC. Visit us at www.tasteanalytics.com or follow us on Twitter @TasteAnalytics.

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