Posts Tagged ‘sentiment analytics’

How To Really Hear The Voice of the Customer

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Image courtesy: https://www.flickr.com/photos/carbonnyc/

There’s a whole lot of customer information out there, including the verbatim comments companies record as part of customer call center surveys or other voice-based interactions. At Verizon Wireless, for example, more than 190 million customers call in daily, weekly and monthly, and sound bites from them during after-call surveys, each a few seconds long, added up to about a ton of data that wasn’t being factored into its customer analytics efforts.

“We had the information, the WAV files, but we couldn’t analyze them with the same lens and same tools” Verizon was bringing to the text – emails, social media, surveys, and so on – commentary from its customers, according to Lorraine Schumacher, Director of Operations Customer Business Intelligence at Verizon, during a recent webinar hosted by customer experience management vendor Clarabridge. Verizon had been using Clarabridge’s technology to monitor its various listening posts to drive strategic business decisions based on analyzing text and sentiment in social media and other sources.

Now, it saw an opportunity to transcribe its WAV files of direct customer feedback so that the information in them could be processed and analyzed to support those same ends. Speech recognition and analytics vendor Voci Technologies partnered with Clarabridge to support those goals.

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Lexalytics’ Semantria Accommodates Text Analytics Abroad

lexsemInternational expansion has been a focus for cloud-based text and sentiment analytics vendor Semantria since its acquisition by text mining vendor Lexalytics over the summer. This week, that’s being addressed by adding enterprise text analytics servers in Europe, to address compliance with EU privacy laws around the location of personal data, as well as making its services available in Arabic, Russian, Japanese and Malay.

Lexalytics’ Semantria SaaS and Excel text-mining platform has a few clients in Europe so far, including among them several large social media monitoring and voice-of-the-customer clients that it’s signed up in the last quarter, according to Seth Redmore, VP Product & Marketing Lexalytics.  eDigitalResearch in the UK is one of them. English, French, German, Spanish, Portuguese and Italian are already among its supported languages, and Dutch should be next on board.

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Turn Your Text Analytics Findings Into Story-Telling Visualizations

SA ChartOnce the complicated job of analyzing text is done, well, it’s not. The next step is to share the findings with others – marketers, sales and additional business personnel who are experts in their domain but not necessarily in text analytics themselves. How to turn that analysis into pictures that can be worth a thousand words?

Visualizing text analytics results is what ChartExpo is all about. Shahbaz Anwar, who is CEO of text analytics vendor PolyVista (see coverage here), is also behind the new visualization library, which was built for PolyVista’s use but now is available for others to leverage. Anwar says that many of the typical, garden-variety visualization tools out there aren’t a good fit for showcasing text and survey analytics results, so the decision was made to leverage the D3.JS framework to build its own libraries upon, which others can now license for use.

“Really what we’re after is how to tell your story with one visualization,” Anwar says.

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RoadMap Your Text Analytics Initiative

analyticspixWhat best practices should inform your company’s text analytics initiatives? Executive Lessons on Modern Text Analytics, a new white paper prepared by: Geoff Whiting, principal at GWhiting.com and Alesia Siuchykava, project director at Data Driven Business provides some insight. Contributors to the lessons shared in the report include Ramkumar Ravichandran, Director, Analytics, at Visa and Matthew P.T. Ruttley, Manager of Data Science at Mozilla Corp

One of the interesting points made in the paper is that text analytics can be applied to many use cases: customer satisfaction and management effectiveness, product design insights, and enhancing predictive data modeling as well as other data processes. But at the same time, a takeaway is that it is better for text analytics teams to follow a narrow path than to try to accommodate a wide-ranging deployment. “All big data initiatives, and especially initial text analytics, need a specific strategy,” the writers note, preferable focusing on “low-hanging fruit through simple business problems and use cases where text analytics can provide a small but fast ROI.

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Clarabridge Goes Straight To The Customers’ Mouth To Analyze Call Center Interactions

cbridge logoCustomer experience management vendor Clarabridge wants to bring the first-person narrative from call center interactions to life for marketing analysts, customer care managers, call center leaders and other customer-focused enterprise execs. With its just released Clarabridge Speech, it now brings via the cloud a solution that integrates Voci Technologies’ speech recognition smarts with its own capabilities for using NLP to analyze and categorize text, sentiment and emotion in surveys, social media, chat sessions, emails and call center agents’ own notes.

Agent notes certainly are helpful when it comes to assessing whether customers are having negative experiences and whether their loyalty is at stake, among other concerns. But, points out Clarabridge CEO Sid Banerjee, “an agent almost never types word for word what the customer says,” nor will they necessarily characterize callers’ tones as angry, confused, and so on. With the ability now to take the recorded conversation and turn it into a transcript, the specific emotion and sentiment words are there along with the entire content of the call to be run through Clarabridge’s text and sentiment algorithms.

“You get a better sense of the true voice of the customer and the experience of that interaction – not just the agent perspective but the customer perspective,” Banerjee says.

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Alta Plana Takes The Pulse Of Text Analytics

wordcloudSeth Grimes, president and principal consultant of Alta Plana Corp. and founding chair of the Sentiment Analysis Symposium, has put together a thorough new report, Text Analytics 2014: User Perspectives on Solutions and Providers. Among the interesting findings of the report is that “growth in text analytics, as a vendor market category, has slackened, even while adoption of text analytics, as a technique, has continued to expand rapidly.”

Grimes explains that in a fragmented market, consisting of everything from text analytics services to solution-embedded technologies, the opportunities for users to practice text analytics is strong, but that increasingly text analytics is not the main focal point of the solutions being leveraged.

Reflecting the diversity of options, respondents listed among their providers a number of open-source offerings such as Apache OpenNLP and GATE, API services such as AlchemyAPI and Semantria, and enterprise software solution and business suite providers like SAP. The word cloud above was generated by Alta Plana at Wordle.net to show how users responded to the question of companies they know provide text/content analytics functionality. Nearly 50 percent of users are likely to recommend their most important provider.

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Corporate Social Media: Sentiment Tracking Is Up, But Other Metrics Are Out of the Mix

insightThe State of Corporate Social Media is … well, strong might be too strong a word for it. The recently released State of Corporate Social Media Briefing 2014, from USM (Useful Social Media) finds – among other things – that social media team sizes are being reduced, fewer budgets are increasing, and fewer key performance indicators are being measured.

It’s not all negative. In fact, report author and USM founder Nick Johnson concludes that all together, its results could be interpreted as indicating that “social media within companies is beginning to mature, and the drive to leverage social to its full extent is undiminished.”

That said, the data equally could be interpreted to mean that “social media within companies is stagnating, and there’s an increasing lack of resources available to those within business to move forward to full leverage social’s potential.”

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Daedalus Takes Meaning-As-A-Service To Excel, GATE And CMS Systems

meaningasaserviceDaedalus (which The Semantic Web Blog originally covered here) has just made its Textalytics meaning-as-a-service APIs available for Excel and GATE (General Architecture for Text Engineering), a JAVA suite of tools used for natural language processing tasks, including information extraction in many languages. Connecting its semantic analysis tools with these systems is one step in a larger plan to extend its integration capabilities with more API plug-ins.

“For us, integration options are a way to lower barriers to adoption and to foster the development of an ecosystem around Textalytics,” says Antonio Matarranz, who leads marketing and sales for Daedalus. The three main ecosystem scenarios, he says, include personal productivity tools, of which the Excel add-in is an example, and NLP environments, of which GATE is an example. “But UIMA (Unstructured Information Management Applications) is also a target,” he says. The list also is slated to include content management systems and search engines, among them open source systems like WordPress, Drupal, and Elasticsearch.

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Big Data Challenges In Banking And Securities

Photo courtesy: Johan Hansson, https://www.flickr.com/photos/plastanka/

Photo courtesy: Johan Hansson, https://www.flickr.com/photos/plastanka/

A new report from the Securities Technology Analysis Center (STAC), Big Data Cases in Banking and Securities, looks to understand big data challenges specific to banking by studying 16 projects at 10 of the top global investment and retail banks.

According to the report, about half the cases involved e petabyte or more or data. That includes both natural language text and highly structured formats that themselves presented a great deal of variety (such as different departments using the same field for a different purpose or for the same purpose but using a different vocabulary) and therefore a challenge for integration in some cases. The analytic complexity of the workloads studied, the Intel-sponsored report notes, covered everything from basic transformations at the low end to machine learning at the high-end.

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Load-Control: Semantria Takes On The Social Media Surge Infrastructure Challenge

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Image courtesy: Flickr/Webtreats

Semantria is tackling some of the challenges that come with being a cloud-based social media services provider startup. The company offers a text and sentiment analysis service (which you can read about here) to clients and partners. That includes companies like Sprinklr, which manages the social customer experience for other brands with the help of Semantria’s API for analyzing social signals about those clients.

The good news is that with growing social data volumes, there’s a growing need for semantically-oriented services like Semantria’s that help businesses make sense of that information for themselves or their clients. The downside is that a huge surge in volume of social mentions around a company, its product, or anything else can hit such services hard in the pocketbook when it comes to acquiring the cloud infrastructure to handle the tidal wave.

“Everybody suffers from this kind of thing,” says Semantria founder and CEO Oleg Rogynskyy. “We experience it daily.”

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