Showing posts with label social media analytics. Show all posts
Showing posts with label social media analytics. Show all posts

Friday, January 14, 2011

What things may come… Text Analytics, Customer Experience Predictions for 2011

http://www.clarabridge.com/ClarabridgeBlog/tabid/189/EntryId/60/What-things-may-come-2011.aspx

2010 has been a banner year, not only because as a company, Clarabridge has passed many significant milestones, but because sentiment and text analytics have passed from infancy to adulthood over a very short, intense period of time. Market forces have converged to provide us with the opportunity and the means to push sentiment and text analytics into many mainstream applications across a variety of industries. You can see the tangible results in our year end press release, and the rush of interest from the analyst community, with folks like Gartner, Hurwitz’s Fern Halper, Constellation’s Ray Wang, Bruce Temkin, Paul Greenberg all talking about the key role multichannel text and sentiment analytics will play in 2011.

2010 has been a banner year, not only because as a company, Clarabridge has passed many significant milestones, but because sentiment and text analytics have passed from infancy to adulthood over a very short, intense period of time. Market forces have converged to provide us with the opportunity and the means to push sentiment and text analytics into many mainstream applications across a variety of industries. You can see the tangible results in our year end press release, and the rush of interest from the analyst community, with folks like Gartner, Hurwitz’s Fern Halper, Constellation’s Ray Wang, Bruce Temkin, Paul Greenberg all talking about the key role multichannel text and sentiment analytics will play in 2011.

So, that all said, I’ve decided to put out my own predictions for 2011 in the sentiment and text analytics space.

  • In 2011 expect to see the beginnings of the merging of text analytics and predictive analytics technology stacks. Vendors of text analytics solutions will begin to move beyond looking back, or analyzing the moment, and move into the realm of identifying the predictors of positive outcomes in a campaign, identifying and tracking the drivers of loyalty using advanced predictive models, and using predictive techniques to help prioritize and manage changes to customer experiences. This will happen in a variety of industries including financial services, hospitality, retail, and healthcare industries.

  • The value of text analytics, especially related to customer experience monitoring, analysis, and action, is amplified when the content being analyzed is sourced from a broad, representative data set of customers. In 2010, while pure play social media monitoring and analysis was exploding across the scene, a small but rapidly growing set of Fortune 1000 organizations began to recognize that multichannel customer analytics, from a wide variety of text based sources (online, offline, call center, and community/survey), provided a much fuller, much more accurate view of customer emotion, customer intent, and loyalty than single source solutions. In 2011 expect to see solutions that fuse multiple channels of customer interaction, engagement, and support to be a dominant growth area for semantic analysis.

  • Text mining and sentiment analysis is evolving as analysts become more sophisticated and demanding of insights. Over the past few years text analytics solutions focused on “structuring” the unstructured, fusing it with structured data, then on applying industry or domain specific classification models for further refined analysis and investigation, and most recently on instrumenting the data for robust monitoring, analysis, and alerting of past or current conditions. In 2011 expect use cases to continue to be analyst driven and facilitated through a business intelligence (BI) reporting framework, but expect the latency of solutions to decrease, and the automation of insight assessment, delivery, and action to increase. For leading edge users expect to see text analytics solutions assess customer problems and automatically suggest communications to customers, or to automate the recommendations of customer support representatives. In short, look for text analytics to become more “real time” and to become more automated in distilling and disseminating insights.

  • Vendors of text analytics solutions have typically focused on the 80/20 rule in the past few years – supporting the languages and markets closest to their home bases that provide 80% value for 20% of the effort. But enterprises collect and analyze content from around the world, in many languages, and over time they are demanding that more content from more sources be integrated into their solutions, and that insights be made available to more users across the globe. In 2011 expect to see North American vendors to add European, Latin American and Asian language support to their offerings to expand their business footprints internationally through direct and indirect sales and marketing efforts, and expect to see enterprise applications be deployed across multiple user communities worldwide using localized application interfaces and analytics.

  • Over the past few years customer experience analytics solutions have grown – bigger data volumes, more content sources, more end users across an organization. Vendors who have stepped up to the challenges of enterprises have responded by creating more scalable, more powerful solutions and underlying solution architectures. Expect the enterprise trend to continue in 2011, but just as the web has allowed consumers to create instantly personalized, tailored online experiences, expect in 2011 text analytics applications will also be offered to the individual analyst and information worker though more customizable, more self-service interfaces and functionality. In short, expect the solution space to scale the enterprise while also being designed and deployed to the individual knowledge worker on a one to one basis.

  • Over the past few years text mining and analytics solutions have not been seamlessly integrated into operational systems or processes. In 2010 a number of vendors started offering robust APIs and frameworks for integrating information into operational systems – CRM, Call Center, Campaign Automation, and Social Media engagement spaces. In 2011 expect to see these operationally integrated solutions come on line from many pioneering solution providers, and to see text insights automatically driving recommendations, actions, or process improvements into operational systems and platforms. Enabling this trend, expect to see partnerships and collaborations between historically analytic vendors and historically transactional vendors in the customer support, customer experience, and customer intelligence spaces. Clarabridge and Verint’s integrated speech/text offering is a leading indicator of creative collaborations to come.

With this all said, what can businesses do to prepare? Invest in voice of the customer pilot programs if you don’t have one, and if you do, invest in bringing in more employees with analytics backgrounds. Look forward, and spend time and money now to understand how all of your systems are going to interact with each other. Put together an action plan. Make your organization customer centric, and the commitment has to be from the top down. Leaders set the tone for how people act and react. Your company culture will define your ability to succeed, so don’t underestimate the value of making sure everyone in the company is focused on listening to the customer.

Data is the present and the future, those who know how to use it, will benefit the most, Knowledge is power is a mantra for a reason.

Wednesday, September 23, 2009

If a Customer Comment Falls in a Forest and No One is Around to Hear it, Does it Make a Sound?

Note: This blog post was originally published on the Clarabridge Blog - you can find the original post here.

I visit customers, prospects and partners fairly regularly, and during those visits a number of common topics come up – updates on our product releases, new partner activity, best practices and project reviews. We also discuss the business impacts of the Clarabridge solution - what customer insights they find, and how our customers use text analytics insights to improve customer value, customer experiences, and customer loyalty.


The conversations have veered into provocative territory on two recent occasions, where we have considered some interesting ethical implications of mining customer experience data.


Obligations as a listener


In one meeting at a healthcare company (attended by business, technical, and legal representatives of the company), they wanted to know how much they could mine, sort, and even “filter” text content before it was delivered to business analysts. The company has strict protocols for identifying and communicating safety and quality issues that originate from patients and providers, but they weren’t sure what to do if they found unsubstantiated information on a social media site. And they weren’t sure if they wanted all insights to go to all analysts. Generally, healthcare companies are obligated to reach out to patients and doctors to provide guidance and support if there’s a problem, and depending on the problem, they need to also report findings to an appropriate federal agency.


When it came to text mining of customer content; however, the company had questions. What is the reporting requirement, if the feedback comes from an anonymous survey? Or from a consumer posting on twitter? How much obligation does a company have to monitor, mine, and intervene in the social media world? At present there are no rules, federal guidelines, or even well defined best practices for using social media monitoring, to identify and counsel customers if they identify safety or quality issues. Should companies get out ahead of the government to develop progressive practices? Or should they wait?


Executive Compass for Customer Experience Management (CEM)


More important, once you start “listening” to the voice of your customers using text analytics and monitoring technology, are you now obligated to act on the insight? Or if you don’t listen, are you not obligated to act? What’s the moral or ethical imperative of using text mining technology to understand your customers better if they’re talking about product quality, safety, side effects, and even morbidity? Should a company be seeking to quantify this feedback?


These questions occur in many industries, not just in the healthcare sector. If a client in the financial services sector believes a contract has been broken and threatens to litigate in a blog post, an angry call to a call center, or in a survey rant – how seriously should a company take the threats? If a patron walks into a retail franchise location and spies what they believe to be a violent felon, or sex offender working behind the cash register, what is the obligation of the parent company - to notify, or enforce an HR action on the franchise? These insights are often latent in “voice of the customer” feedback, and have been found by our customers using Clarabridge – prior to using Clarabridge the information was latent and largely invisible.


Ultimately, text mining helps a customer listen, analyze and measure the extent of a problem or the outcome produced by an action. But taking action – whether it’s a sales, marketing, support, or (in the cases outlined above) safety, risk management, or criminal prosecution decisions, to me, ultimately depends on the will, and commitment of the organization to act on the insight. What do you think? What policies has your company incorporated?

Sid