The Business Intelligence Blog

Slicing Business Dicing Intelligence

Archive for the ‘Predictive Analytics’ tag

101 – Data Mining and Predictive Analytics  

In today’s world mining of text, Web and media (unstructured data) plus structured data mining, the term information mining is a more appropriate label. Mining a combination of these, companies are able to make the best use of structured data, unstructured text and social media. Static and stagnant predictive models of the past don’t work well in the world we live in today. Predictive analytics should be agile to adapt and monetize on quickly changing customer behaviors in our world, which are often identified online and through social networks.

Better integration of data mining software with the source data at one end and with the information consumption software at the other end has led to improvement in the integration of predictive analytics with day-to-day business. Even though there haven’t been significant advancements in predictive algorithms, the ability to apply large data sets to models and the ability to enable better interaction with business has led to improvements in the overall outcome of the exercise.

There is a great introduction to the world of data mining and predictive analytics here.

The article has

no responses yet

Written by Guru Kirthigavasan

January 24th, 2012 at 7:31 am

101 Ways to Sabotage Your Predictive Analytics Project  

And there is the first five here. Interesting Read, I liked it.

The strategic approach and project design for predictive analytics is substantially different than the other areas of business intelligence. Unlike a data warehouse design, which is similar to an engineering project, predictive analytics and data mining are a discovery process. And while several consortiums have standardized formal processes to accommodate discovery and iterative process, the practice remains riddled with common pitfalls.

Those who make the effort to educate themselves on the industry-standard approach to predictive analytics are nearly assured to reap residual returns – long before their counterparts who typically rush to acquire a tool and dive headlong into the data.

The article has

9 responses

Written by Guru Kirthigavasan

May 18th, 2010 at 6:22 pm

Portrait Software Utilizes Analytics to Provide PA/DM  

From Press Release -

Forrester evaluated the top nine predictive analytics and data mining (PA/DM) solution vendors across 53 criteria, segmenting them into the three categories including current offering, product strategy, and market presence. As a leader offering “mature, high-performance, scalable, flexible, and robust PA/DM solutions,” Portrait received the 3rd highest score for Product Strategy & the 6th highest score for Current Offering.”

Among the vendor products the Forrester(TM) Wave evaluated were Portrait Customer Analytics, Portrait Uplift Optimizer, and Portrait Self-service Analytics. According to the Forrester(TM) Wave, “Portrait provides a user-friendly, feature-rich PA/DM solution portfolio in support of real-time scoring, interaction optimization, uplift optimization, and campaign management for customer analytics.”

“Powerful customer analytics have always been the core driver of Portrait’s innovative marketing solutions, but analytics itself only takes you so far,” said Luke McKeever, CEO, Portrait Software. “Portrait’s ability to not only incorporate analytics but to action the insights they deliver enables us to provide our customers with highly intelligent solutions that help them operate as a customer-centric organization, differentiating them from their competitors while simultaneously improving their marketing ROI.”

The article has

one response

Written by Guru Kirthigavasan

February 16th, 2010 at 2:06 am

CIOs take BI Apps, strategy to next level  

Chris Brady, CIO at 450-employee Dealer Services Corp., a Carmel, Ind.-based financer for car dealerships, is starting to play with predictive analytics as well. In particular, she is looking at a forecasting tool by SPSS Inc. to gather and model data from the data warehouses in order to analyze what is happening at a dealership before deciding whether to approve a loan.

A dealership’s credit worthiness is not as black and white as a consumer’s, Brady explained. “Sometimes what looks like a bump in the road is just that — it’s not a sign that they are going out of business, and if we take the wrong action without the right information we could put them out of business,” she said. “We need to be able to see patterns in our customers’ behavior to predict what may happen next, and take the right course of action based on those patterns.”

From Search CIO article.

The article has

no responses yet

Written by Guru Kirthigavasan

June 20th, 2009 at 6:14 am

SPSS Rebrands Its Analytical Offerings  

The new version of the SPSS modeling product — the erstwhile Clementine — is now known as PASW Modeler 13; its text analysis product (formerly Text Mining for Clementine) is now PASW Text Analytics 13. SPSS says that, over the course of the year, the rest of the SPSS product line will update under the PASW umbrella — including Statistics and Data Collection.

David Vergara, director of product marketing for SPSS, explains that the change was intended to help customers and prospects understand what the products are doing and how each offering pieces together within the broader portfolio.

Aside from the name change, the new versions of SPSS products focus on usability — and not just for data experts. Wettemann says that SPSS has “recognized that moving beyond the data analyst audience is where you get the real power.” PASW Modeler 13 features a drag-and-drop interface, and functionality that will appeal to business users. Two integral updates include a “comments” tool, in which users can flag notes within the software, and automated data preparation. Data automation mitigates human error and avoids common issues in data quality.

From Destination CRM.

The article has

no responses yet

Written by Guru Kirthigavasan

April 14th, 2009 at 6:11 am

Varolii Unveils Next-Gen Predictive Analytics  

Varolii Corporation today announced Varolii Predictive Analytics(TM), an on-demand service that helps organizations understand, analyze and strategically target more effective customer outreach for collections, customer service and loyalty programs. Varolii unveiled Predictive Analytics at Interaction ’08, the company’s inaugural customer conference.

Combining client data with the behavioral insight gleaned from billions of Varolii-led customer interactions, Varolii Predictive Analytics helps companies identify who to contact, when to contact them, through what channel, using which treatment, and how frequently in order to generate the greatest response. This combined data offers much more than a simple success or failure measurement; it’s a complete record of customer interaction and response on an individual level. The application is designed to gain intelligence from these conversations and progressively “learn” to predict customer behavior.
..
..
At the highest level, Varolii Predictive Analytics can help companies analyze contact strategy options (e.g., automated communications, an in-house call center, outsourced agents, or a combination of them) and select which will work best to solve their specific needs. At a more tactical level, it can help decide such things as an appropriate collection strategy based on Varolii and customer history, including probability to pay, days delinquent, and other metrics for improved results.

Read more from the Press Release.

The article has

one response

Written by Guru Kirthigavasan

May 14th, 2008 at 5:30 pm

MS in Verticals – Buys Predictive Analytics company, Farecast  

Seattle Pi’s Venture Blog has the full story from the start to the end.

Farecast was started by University of Washington computer scientist Oren Etzioni, initially bankrolled by Madrona, built with people from local companies such as Alaska Airlines and AdRelevance and, ultimately, acquired by Microsoft.

Though Farecast had multiple bidders, McIlwain said Microsoft was a good fit since the two companies had worked together in the past and had a similar vision for online search. The proximity of the two companies also played a part, he said.

The acquisition follows the merger of Kayak.com and SideStep, the market leader in next generation travel search. That deal led to new opportunities for Farecast, including discussions with Microsoft which heated up in the past 90 days.

“That consolidation presented opportunities for Farecast … partly differentiated because of their predictive capabilities but also because of who they might have been able to align with in the industry to be a strong and differentiated number two, hoping some day to overtake and become number one,” he said.

Madrona has produced a number of hits recently, with the sales of ShareBuilder, World Wide Packets and iConclude.

Also a quick analysis from Motel Fool on this buy -

Microsoft needs more deals like this one, especially if the Microhoo deal comes undone, and the software giant has the means to go shopping. I’ve suggested that Microsoft pursue potential buyout candidates like The Knot (Nasdaq: KNOT) and Bankrate (Nasdaq: RATE) for the same reason that Farecast works. Whether it’s wedding planning, home refinancing, or booking that flight to visit your parents in Chicago, this is the quality traffic that Microsoft and Yahoo! lack right now.

The article has

no responses yet

Written by Guru Kirthigavasan

April 18th, 2008 at 8:41 am