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Trends and Outliers

TIBCO Spotfire's Business Intelligence Blog

Category Archives: Real-Time Analytics

12/10
2013

Predictive Analytics to Detect and Mitigate ‘Customer Rage’

The number of households experiencing “customer rage” or outright anger at their experiences with various companies rose from 60% in 2011 to 68% this year.

shutterstock 489065981 150x150 Predictive Analytics to Detect and Mitigate ‘Customer Rage’Meanwhile, the number of people who yell at customer service reps has jumped from 25% to 36% over the same time period, according to a recent study.

The findings carry a number of implications for companies. Despite efforts by many firms to improve customer service, US consumers are less happy with purchases when they end up complaining to companies.

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10/30
2012

A Data Analysis of Foreign Policy

Last Monday night, we witnessed the last of three presidential debates for the 2012 election. The topic was foreign policy and we thought it would be interesting to explore the data analytics of foreign policy in the aftermath of the final debate.

“Walmart Moms” Not Big on Foreign Policy

Let’s start with an interesting sentiment analysis gauged by ABC News. During the first 30 minutes of the debate, ABC’s Elizabeth Hartfield examined the sentiment for each candidate with a group of “Walmart Moms.”

The overall result?

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03/15
2012

Using Analytics to Create a Sense-and-Respond Organization

FollowCustomers1 150x150 Using Analytics to Create a Sense and Respond OrganizationMany business forecasters believe that the most successful companies in the future will be those that develop sense-and-respond type approaches for listening to and responding to customer needs and preferences. This includes the use of predictive analytics to anticipate and address customer issues before they’ve reached out to contact centers.

As R “Ray” Wang (@rwang0), principal analyst and CEO of Constellation Research Inc., points out in a recent Forbes article, a growing number of companies are shifting from transactional systems to engagement technologies to help improve interactions with customers and to provide better and more relevant customer experiences across the various customer channels.

The drivers behind this are simple: as companies seek new ways to grow revenues and expand their customer bases, they’re devoting greater attention to delivering solid, multichannel customer experiences. The quality of customer experience can have a profound impact on an organization’s business performance.

According to The Business Impact of Customer Experience report from Forrester Research (@forrester), improvements in the experiences delivered to customers can generate more than $1 billion in revenue for wireless carriers and hotels. This can be measured by a customer’s willingness to do more business with a company, the likelihood of switching their business to another company and their willingness to recommend a company to others.

When companies strive to become more customer-centric, one of the things that many organizations need to improve on is proper tracking of customers as they move from one channel (e.g. web) to another (voice). As it stands, too many companies struggle to do this. Rather, they make customers feel as if they’re working with multiple companies instead of a single organization.

This leads to customer frustration and churn. Plus, when customers have poor experiences with companies, they often share their frustrations with thousands of other people on Facebook and other social channels, resulting in lost business opportunities.

As companies gain experience in sensing and responding to customer needs, they can also use analytics to help identify potential customer issues before customers reach out to their contact centers for help. By reaching out to customers proactively, companies can strengthen customer trust by demonstrating that they’re proactively looking out for their customers’ best interests.

For example, let’s say a wireless carrier notes that a customer is about to reach his monthly data limit. An alert can be sent to a customer to let him know that he’s about to reach his limit before additional fees are assessed.

Companies that make greater use of analytics to identify and respond quickly to customer needs and preferences will be able to leapfrog their competitors and position themselves to be more successful.

Next Steps: Download our complimentary 5-Minute Guide to CRM Analytics to learn how agile analytics technologies can help companies answer critical questions about their customers and deliver more value to executives and front-line marketers.

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01/27
2012

TIBCO Spotfire- Social Analytics Tracking Disease

disease 150x150 TIBCO Spotfire  Social Analytics Tracking DiseaseThere’s evidence that real-time data from social media is a better source for tracking disease outbreaks when compared to traditional data sources.

For instance, two years after the devastating earthquake in Haiti, a new study shows that Twitter and HealthMap (a project at Children’s Hospital in Boston that creates a worldwide data visualization of disease outbreaks on an interactive map in nine languages) tracked the cholera epidemic, which killed 7,000 people and affected over 500,000, up to two weeks faster than traditional reporting methods.

The research team led by Dr. Rumi Chunara, a research fellow at HealthMap and Harvard Medical School, had a simple goal – to determine if social media analytics could tell us more about epidemic disease faster than traditional reporting.

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01/06
2012

Differentiating Through Event-Driven Analytics

event driven analytics 300x199 Differentiating Through Event Driven AnalyticsA growing number of companies are taking advantage of event-driven analytics to help identify event patterns and their impacts on business trends and key performance indicators. Savvy companies are tracking and acting quickly on such information via complex event processing in order to position themselves ahead of competitors or in some cases to identify and act quickly on customer or operational issues they’ve uncovered.

For example, let’s say a regional transportation company discovers that customer satisfaction has dropped five points in three of its key markets. A closer examination of the data reveals that customers are unhappy with a recent policy change that no longer allows them to purchase monthly bus passes in advance online, forcing them instead to wait on line at bus stations to obtain the passes on the first business day of each month.

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03/28
2011

Deloitte’s Top Technology Trends for 2011: Data Visualization and Real Analytics

Data Visualization and Deloitte 300x175 Deloittes Top Technology Trends for 2011: Data Visualization and Real Analytics Last week, Deloitte released its annual technology trends report in which it discusses the top IT trends that will impact business over the next 18 months. The 2011 Tech Trends report puts trends into two categories this year, (Re)Emerging Enablers and Disruptive Deployments. In both categories, the #1 trend has to do with applying information and analytics to solve business problems.

The first category, (Re)Emerging Enablers, consists of trends that CIOs have probably spent time on in the past that deserve a fresh look in 2011. Topping the list of five enablers is Data Visualization. According to Deloitte, “organizations with solid information foundations can use visualization to leap-frog competitors.”

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01/14
2011

How Data Visualization and BI Put An End To Dilbert-Style Meetings

dilbert and data visualization How Data Visualization and BI Put An End To Dilbert Style Meetings According to a study commissioned by Verizon, 91% of professionals admit to daydreaming in meetings, 95% say they miss all or part of meetings, almost 75% say they bring other work to meetings and almost 40% say they have actually dozed off during a meeting. Yet in the same survey, people say the number of meetings is increasing. Is there a better way?

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12/16
2010

Real-Time Analytics Is A People-Centric Process

checkout 150x150 Real Time Analytics Is A People Centric ProcessReal-time analytics is about detecting and responding to events as they happen to gain competitive advantage. In real-time analytics, an event occurs that requires a decision: What action, if any, should be taken to respond to this event? Simply notifying someone that an event has occurred doesn’t qualify as analytics because it doesn’t provide any decision support — at best it provides “situational awareness”.

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12/15
2010

Data Analytics: The Potential Benefits of Real-Time Decisions

wallstreet3 300x243 Data Analytics: The Potential Benefits of Real Time DecisionsWe live in an “instant” world where we’ve gotten very good at being able to tell when an “event” occurs. For example:

  • News from a government agency could affect the price of a company’s stock.
  • The stock of a key product at a store is rapidly dwindling .
  • A valuable customer is shopping your website right now.
  • A competitor has just reduced the price of your best-selling item.
  • Purchases on a customer’s credit card seem to indicate fraudulent use.
  • There has been a surge of tweets about your company in the last 15 minutes.

However, knowing about an event has little value unless we act on that information. According to an article in Information Management magazine, companies are now focusing significant attention trying to improve their ability to react to real-time events using data analytics.

“Real-time analytics” offers speed, flexibility, and the potential to gain competitive advantage by responding to an event soon after it occurs. Just as the early bird gets the worm, acting quickly to respond to an event can help a company get a “leg up” on the competition.

For some organizations, real-time analytics has already demonstrated its value in the form of real profits and improved customer relationships. For example, real-time analytics is being used by brokers to make decisions about stock trades, – impacting profits – and by retailers to make decisions about marketing and customers – impacting sales and customer relationships.

Real-time analytics sounds straight forward. An event occurs, data relevant to the event is collected, the data is analyzed, and a decision is made whether or not to act in response to the event. But the entire process needs to happen quickly – in “real time” – which makes implementing real-time analytics more difficult than traditional BI decision support focused on longer-term strategic decisions.

In an upcoming post, we’ll discuss more about what real-time analytics is – and what it isn’t.  Remember to subscribe to our blog to stay informed on real-time analytics and other topics in data analytics.

Steve McDonnell
Spotfire Blogging Team

Image Credit: Getty Images

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