Predictive Analytics World March2011 SF

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Message from PAWCON-

 

Predictive Analytics World, Mar 14-15 2011, San Francisco, CA

More info: pawcon.com/sanfrancisco

Agenda at-a-glance: pawcon.com/sanfrancisco/2011/agenda_overview.php

PAW’s San Francisco 2011 program is the richest and most diverse yet, including over 30 sessions across two tracks – an “All Audiences” and an “Expert/Practitioner” track — so you can witness how predictive analytics is applied at Bank of America, Bank of the West, Best Buy, CA State Automobile Association, Cerebellum Capital, Chessmetrics, Fidelity, Gaia Interactive, GE Capital, Google, HealthMedia, Hewlett Packard, ICICI Bank (India), MetLife, Monster.com, Orbitz, PayPal/eBay, Richmond, VA Police Dept, U. of Melbourne, Yahoo!, YMCA, and a major N. American telecom, plus insights from projects for Anheiser-Busch, the SSA, and Netflix.

PAW’s agenda covers hot topics and advanced methods such as uplift modeling (net lift), ensemble models, social data (6 sessions on this), search marketing, crowdsourcing, blackbox trading, fraud detection, risk management, survey analysis, and other innovative applications that benefit organizations in new and creative ways.

Predictive Analytics World is the only conference of its kind, delivering vendor-neutral sessions across verticals such as banking, financial services, e-commerce, education, government, healthcare, high technology, insurance, non-profits, publishing, social gaming, retail and telecommunications

And PAW covers the gamut of commercial applications of predictive analytics, including response modeling, customer retention with churn modeling, product recommendations, fraud detection, online marketing optimization, human resource decision-making, law enforcement, sales forecasting, and credit scoring.

WORKSHOPS. PAW also features pre- and post-conference workshops that complement the core conference program. Workshop agendas include advanced predictive modeling methods, hands-on training and enterprise decision management.

More info: pawcon.com/sanfrancisco

Agenda at-a-glance: pawcon.com/sanfrancisco/2011/agenda_overview.php

Be sure to register by Dec 7 for the Super Early Bird rate (save $400):
pawcon.com/sanfrancisco/register.php

If you’d like our informative event updates, sign up at:
pawcon.com/signup-us.php

Zen and the art of applying T tests to Spam Data

Decisionstats traffic seemed up mmm but Spam is way way up

Whos spamming my dear bloggie

hmm

is it the russians doing a link spam. unlikely they dont bot against Akismet that much (as they fail)

And Captcha can be failed by python (apparently. sigh)

Is there a co relation of certain tags of posts, and count of spam- hoping to distort say blogs’s search engine rankings for SAS WPS Lawsuit in Google or jet ski across  pacific in Google.

Sigh- an old retired outlaw black hat is never kept in peace. Try doing a blog search for R in Google- Revo  is now down to number 7 (which is hmm given Google Instant)

Of course I think too much about SEO, but I dont run CPC ads- I made much more money when traffic is low – say 5-10 small businesses needing to forecast their sales .

and enjoy your Thanksgiving. Remember the Indians bring the Turkeys.

 

PAWCON -This week in London

Watch out for the twitter hash news on PAWCON and the exciting agenda lined up. If your in the City- you may want to just drop in

http://www.predictiveanalyticsworld.com/london/2010/agenda.php#day1-7

Disclaimer- PAWCON has been a blog partner with Decisionstats (since the first PAWCON ). It is vendor neutral and features open source as well proprietary software, as well case studies from academia and Industry for a balanced view.

 

Little birdie told me some exciting product enhancements may be in the works including a not yet announced R plugin 😉 and the latest SAS product using embedded analytics and Dr Elder’s full day data mining workshop.

Citation-

http://www.predictiveanalyticsworld.com/london/2010/agenda.php#day1-7

Monday November 15, 2010
All conference sessions take place in Edward 5-7

8:00am-9:00am

Registration, Coffee and Danish
Room: Albert Suites


9:00am-9:50am

Keynote
Five Ways Predictive Analytics Cuts Enterprise Risk

All business is an exercise in risk management. All organizations would benefit from measuring, tracking and computing risk as a core process, much like insurance companies do.

Predictive analytics does the trick, one customer at a time. This technology is a data-driven means to compute the risk each customer will defect, not respond to an expensive mailer, consume a retention discount even if she were not going to leave in the first place, not be targeted for a telephone solicitation that would have landed a sale, commit fraud, or become a “loss customer” such as a bad debtor or an insurance policy-holder with high claims.

In this keynote session, Dr. Eric Siegel will reveal:

  • Five ways predictive analytics evolves your enterprise to reduce risk
  • Hidden sources of risk across operational functions
  • What every business should learn from insurance companies
  • How advancements have reversed the very meaning of fraud
  • Why “man + machine” teams are greater than the sum of their parts for
  • enterprise decision support

 

Speaker: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World

Top of this page ] [ Agenda overview ]


IBM9:50am-10:10am

Platinum Sponsor Presentation
The Analytical Revolution

The algorithms at the heart of predictive analytics have been around for years – in some cases for decades. But now, as we see predictive analytics move to the mainstream and become a competitive necessity for organisations in all industries, the most crucial challenges are to ensure that results can be delivered to where they can make a direct impact on outcomes and business performance, and that the application of analytics can be scaled to the most demanding enterprise requirements.

This session will look at the obstacles to successfully applying analysis at the enterprise level, and how today’s approaches and technologies can enable the true “industrialisation” of predictive analytics.

Speaker: Colin Shearer, WW Industry Solutions Leader, IBM UK Ltd

Top of this page ] [ Agenda overview ]


Deloitte10:10am-10:20am

Gold Sponsor Presentation
How Predictive Analytics is Driving Business Value

Organisations are increasingly relying on analytics to make key business decisions. Today, technology advances and the increasing need to realise competitive advantage in the market place are driving predictive analytics from the domain of marketers and tactical one-off exercises to the point where analytics are being embedded within core business processes.

During this session, Richard will share some of the focus areas where Deloitte is driving business transformation through predictive analytics, including Workforce, Brand Equity and Reputational Risk, Customer Insight and Network Analytics.

Speaker: Richard Fayers, Senior Manager, Deloitte Analytical Insight

Top of this page ] [ Agenda overview ]


10:20am-10:45am

Break / Exhibits
Room: Albert Suites


10:45am-11:35am
Healthcare
Case Study: Life Line Screening
Taking CRM Global Through Predictive Analytics

While Life Line is successfully executing a US CRM roadmap, they are also beginning this same evolution abroad. They are beginning in the UK where Merkle procured data and built a response model that is pulling responses over 30% higher than competitors. This presentation will give an overview of the US CRM roadmap, and then focus on the beginning of their strategy abroad, focusing on the data procurement they could not get anywhere else but through Merkle and the successful modeling and analytics for the UK.

Speaker: Ozgur Dogan, VP, Quantitative Solutions Group, Merkle Inc.

Speaker: Trish Mathe, Life Line Screening

Top of this page ] [ Agenda overview ]


11:35am-12:25pm
Open Source Analytics; Healthcare
Case Study: A large health care organization
The Rise of Open Source Analytics: Lowering Costs While Improving Patient Care

Rapidminer and R were the number 1 and 2 in this years annual KDNuggets data mining tool usage poll, followed by Knime on place 4 and Weka on place 6. So what’s going on here? Are these open source tools really that good or is their popularity strongly correlated with lower acquisition costs alone? This session answers these questions based on a real world case for a large health care organization and explains the risks & benefits of using open source technology. The final part of the session explains how these tools stack up against their traditional, proprietary counterparts.

Speaker: Jos van Dongen, Associate & Principal, DeltIQ Group

Top of this page ] [ Agenda overview ]


12:25pm-1:25pm

Lunch / Exhibits
Room: Albert Suites


1:25pm-2:15pm
Keynote
Thought Leader:
Case Study: Yahoo! and other large on-line e-businesses
Search Marketing and Predictive Analytics: SEM, SEO and On-line Marketing Case Studies

Search Engine Marketing is a $15B industry in the U.S. growing to double that number over the next 3 years. Worldwide the SEM market was over $50B in 2010. Not only is this a fast growing area of marketing, but it is one that has significant implications for brand and direct marketing and is undergoing rapid change with emerging channels such as mobile and social. What is unique about this area of marketing is a singularly heavy dependence on analytics:

 

  • Large numbers of variables and options
  • Real-time auctions/bids and a need to adjust strategies in real-time
  • Difficult optimization problems on allocating spend across a huge number of keywords
  • Fast-changing competitive terrain and heavy competition on the obvious channels
  • Complicated interactions between various channels and a large choice of search keyword expansion possibilities
  • Profitability and ROI analysis that are complex and often challenging

 

The size of the industry, its growing importance in marketing, its upcoming role in Mobile Advertising, and its uniquely heavy reliance on analytics makes it particularly interesting as an area for predictive analytics applications. In this session, not only will hear about some of the latest strategies and techniques to optimize search, you will hear case studies that illustrate the important role of analytics from industry practitioners.

Speaker: Usama Fayyad, , Ph.D., CEO, Open Insights

Top of this page ] [ Agenda overview ]


SAS2:15pm-2:35pm

Platinum Sponsor Presentation
Creating a Model Factory Using in-Database Analytics

With the ever-increasing number of analytical models required to make fact-based decisions, as well as increasing audit compliance regulations, it is more important than ever that these models can be created, monitored, retuned and deployed as quickly and automatically as possible. This paper, using a case study from a major financial organisation, will show how organisations can build a model factory efficiently using the latest SAS technology that utilizes the power of in-database processing.

Speaker: John Spooner, Analytics Specialist, SAS (UK)

Top of this page ] [ Agenda overview ]


2:35pm-2:45pm

Session Break
Room: Albert Suites


2:45pm-3:35pm

Retail
Case Study: SABMiller
Predictive Analytics & Global Marketing Strategy

Over the last few years SABMiller plc, the second largest brewing company in the world operating in 70 countries, has been systematically segmenting its markets in different countries globally in order optimize their portfolio strategy & align it to their long term country specific growth strategy. This presentation talks about the overall methodology followed and the challenges that had to be overcome both from a technical as well as from a change management stand point in order to successfully implement a standard analytics approach to diverse markets and diverse business positions in a highly global setting.

The session explains how country specific growth strategies were converted to objective variables and consumption occasion segments were created that differentiated the market effectively by their growth potential. In addition to this the presentation will also provide a discussion on issues like:

  • The dilemmas of static vs. dynamic solutions and standardization vs. adaptable solutions
  • Challenges in acceptability, local capability development, overcoming implementation inertia, cost effectiveness, etc
  • The role that business partners at SAB and analytics service partners at AbsolutData together play in providing impactful and actionable solutions

 

Speaker: Anne Stephens, SABMiller plc

Speaker: Titir Pal, AbsolutData

Top of this page ] [ Agenda overview ]


3:35pm-4:25pm

Retail
Case Study: Overtoom Belgium
Increasing Marketing Relevance Through Personalized Targeting

 

Since many years, Overtoom Belgium – a leading B2B retailer and division of the French Manutan group – focuses on an extensive use of CRM. In this presentation, we demonstrate how Overtoom has integrated Predictive Analytics to optimize customer relationships. In this process, they employ analytics to develop answers to the key question: “which product should we offer to which customer via which channel”. We show how Overtoom gained a 10% revenue increase by replacing the existing segmentation scheme with accurate predictive response models. Additionally, we illustrate how Overtoom succeeds to deliver more relevant communications by offering personalized promotional content to every single customer, and how these personalized offers positively impact Overtoom’s conversion rates.

Speaker: Dr. Geert Verstraeten, Python Predictions

Top of this page ] [ Agenda overview ]


4:25pm-4:50pm

Break / Exhibits
Room: Albert Suites


4:50pm-5:40pm
Uplift Modelling:
Case Study: Lloyds TSB General Insurance & US Bank
Uplift Modelling: You Should Not Only Measure But Model Incremental Response

Most marketing analysts understand that measuring the impact of a marketing campaign requires a valid control group so that uplift (incremental response) can be reported. However, it is much less widely understood that the targeting models used almost everywhere do not attempt to optimize that incremental measure. That requires an uplift model.

This session will explain why a switch to uplift modelling is needed, illustrate what can and does go wrong when they are not used and the hugely positive impact they can have when used effectively. It will also discuss a range of approaches to building and assessing uplift models, from simple basic adjustments to existing modelling processes through to full-blown uplift modelling.

The talk will use Lloyds TSB General Insurance & US Bank as a case study and also illustrate real-world results from other companies and sectors.

 

Speaker: Nicholas Radcliffe, Founder and Director, Stochastic Solutions

Top of this page ] [ Agenda overview ]


5:40pm-6:30pm

Consumer services
Case Study: Canadian Automobile Association and other B2C examples
The Diminishing Marginal Returns of Variable Creation in Predictive Analytics Solutions

 

Variable Creation is the key to success in any predictive analytics exercise. Many different approaches are adopted during this process, yet there are diminishing marginal returns as the number of variables increase. Our organization conducted a case study on four existing clients to explore this so-called diminishing impact of variable creation on predictive analytics solutions. Existing predictive analytics solutions were built using our traditional variable creation process. Yet, presuming that we could exponentially increase the number of variables, we wanted to determine if this added significant benefit to the existing solution.

Speaker: Richard Boire, BoireFillerGroup

Top of this page ] [ Agenda overview ]


6:30pm-7:30pm

Reception / Exhibits
Room: Albert Suites


Tuesday November 16, 2010
All conference sessions take place in Edward 5-7

8:00am-9:00am

Registration, Coffee and Danish
Room: Albert Suites


9:00am-9:55am
Keynote
Multiple Case Studies: Anheuser-Busch, Disney, HP, HSBC, Pfizer, and others
The High ROI of Data Mining for Innovative Organizations

Data mining and advanced analytics can enhance your bottom line in three basic ways, by 1) streamlining a process, 2) eliminating the bad, or 3) highlighting the good. In rare situations, a fourth way – creating something new – is possible. But modern organizations are so effective at their core tasks that data mining usually results in an iterative, rather than transformative, improvement. Still, the impact can be dramatic.

Dr. Elder will share the story (problem, solution, and effect) of nine projects conducted over the last decade for some of America’s most innovative agencies and corporations:

    Streamline:

  • Cross-selling for HSBC
  • Image recognition for Anheuser-Busch
  • Biometric identification for Lumidigm (for Disney)
  • Optimal decisioning for Peregrine Systems (now part of Hewlett-Packard)
  • Quick decisions for the Social Security Administration
    Eliminate Bad:

  • Tax fraud detection for the IRS
  • Warranty Fraud detection for Hewlett-Packard
    Highlight Good:

  • Sector trading for WestWind Foundation
  • Drug efficacy discovery for Pharmacia & UpJohn (now Pfizer)

Moderator: Eric Siegel, Program Chair, Predictive Analytics World

Speaker: John Elder, Ph.D., Elder Research, Inc.

Also see Dr. Elder’s full-day workshop

 

Top of this page ] [ Agenda overview ]


9:55am-10:30am

Break / Exhibits
Room: Albert Suites


10:30am-11:20am
Telecommunications
Case Study: Leading Telecommunications Operator
Predictive Analytics and Efficient Fact-based Marketing

The presentation describes what are the major topics and issues when you introduce predictive analytics and how to build a Fact-Based marketing environment. The introduced tools and methodologies proved to be highly efficient in terms of improving the overall direct marketing activity and customer contact operations for the involved companies. Generally, the introduced approaches have great potential for organizations with large customer bases like Mobile Operators, Internet Giants, Media Companies, or Retail Chains.

Main Introduced Solutions:-Automated Serial Production of Predictive Models for Campaign Targeting-Automated Campaign Measurements and Tracking Solutions-Precise Product Added Value Evaluation.

Speaker: Tamer Keshi, Ph.D., Long-term contractor, T-Mobile

Speaker: Beata Kovacs, International Head of CRM Solutions, Deutsche Telekom

Top of this page ] [ Agenda overview ]


11:20am-11:25am

Session Changeover


11:25am-12:15pm
Thought Leader
Nine Laws of Data Mining

Data mining is the predictive core of predictive analytics, a business process that finds useful patterns in data through the use of business knowledge. The industry standard CRISP-DM methodology describes the process, but does not explain why the process takes the form that it does. I present nine “laws of data mining”, useful maxims for data miners, with explanations that reveal the reasons behind the surface properties of the data mining process. The nine laws have implications for predictive analytics applications: how and why it works so well, which ambitions could succeed, and which must fail.

 

Speaker: Tom Khabaza, khabaza.com

 

Top of this page ] [ Agenda overview ]


12:15pm-1:30pm

Lunch / Exhibits
Room: Albert Suites


1:30pm-2:25pm
Expert Panel: Kaboom! Predictive Analytics Hits the Mainstream

Predictive analytics has taken off, across industry sectors and across applications in marketing, fraud detection, credit scoring and beyond. Where exactly are we in the process of crossing the chasm toward pervasive deployment, and how can we ensure progress keeps up the pace and stays on target?

This expert panel will address:

  • How much of predictive analytics’ potential has been fully realized?
  • Where are the outstanding opportunities with greatest potential?
  • What are the greatest challenges faced by the industry in achieving wide scale adoption?
  • How are these challenges best overcome?

 

Panelist: John Elder, Ph.D., Elder Research, Inc.

Panelist: Colin Shearer, WW Industry Solutions Leader, IBM UK Ltd

Panelist: Udo Sglavo, Global Analytic Solutions Manager, SAS

Panel moderator: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World


2:25pm-2:30pm

Session Changeover


2:30pm-3:20pm
Crowdsourcing Data Mining
Case Study: University of Melbourne, Chessmetrics
Prediction Competitions: Far More Than Just a Bit of Fun

Data modelling competitions allow companies and researchers to post a problem and have it scrutinised by the world’s best data scientists. There are an infinite number of techniques that can be applied to any modelling task but it is impossible to know at the outset which will be most effective. By exposing the problem to a wide audience, competitions are a cost effective way to reach the frontier of what is possible from a given dataset. The power of competitions is neatly illustrated by the results of a recent bioinformatics competition hosted by Kaggle. It required participants to pick markers in HIV’s genetic sequence that coincide with changes in the severity of infection. Within a week and a half, the best entry had already outdone the best methods in the scientific literature. This presentation will cover how competitions typically work, some case studies and the types of business modelling challenges that the Kaggle platform can address.

Speaker: Anthony Goldbloom, Kaggle Pty Ltd

Top of this page ] [ Agenda overview ]


3:20pm-3:50pm

Breaks /Exhibits
Room: Albert Suites


3:50pm-4:40pm
Human Resources; e-Commerce
Case Study: Naukri.com, Jeevansathi.com
Increasing Marketing ROI and Efficiency of Candidate-Search with Predictive Analytics

InfoEdge, India’s largest and most profitable online firm with a bouquet of internet properties has been Google’s biggest customer in India. Our team used predictive modeling to double our profits across multiple fronts. For Naukri.com, India’s number 1 job portal, predictive models target jobseekers most relevant to the recruiter. Analytical insights provided a deeper understanding of recruiter behaviour and informed a redesign of this product’s recruiter search functionality. This session will describe how we did it, and also reveal how Jeevansathi.com, India’s 2nd-largest matrimony portal, targets the acquisition of consumers in the market for marriage.

 

Speaker: Suvomoy Sarkar, Chief Analytics Officer, HT Media & Info Edge India (parent company of the two companies above)

 

Top of this page ] [ Agenda overview ]


4:40pm-5:00pm
Closing Remarks

Speaker: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World

Top of this page ] [ Agenda overview ]


Wednesday November 17, 2010

Full-day Workshop
The Best and the Worst of Predictive Analytics:
Predictive Modeling Methods and Common Data Mining Mistakes

Click here for the detailed workshop description

  • Workshop starts at 9:00am
  • First AM Break from 10:00 – 10:15
  • Second AM Break from 11:15 – 11:30
  • Lunch from 12:30 – 1:15pm
  • First PM Break: 2:00 – 2:15
  • Second PM Break: 3:15 – 3:30
  • Workshop ends at 4:30pm

Speaker: John Elder, Ph.D., CEO and Founder, Elder Research, Inc.

 

New Google Ad Planner

Dusan's User Interface challenge
Image by moggs oceanlane via Flickr

The new Google Ad Planner is really nice-seems better than old Adwords interface, though needs a UI redesign before it can complete with the clean cut slice and dice of Facebook Ad Planner.

It’s the interface, stupid that makes an Iphone sell more than the Symbian even with 90% functionality. Same reasons why Google Storage is okay but Google Prediction API gets slower liftoff than Amazon Console (now with FREE instances) – though the R interface to Prediction API sure helps.

Prediction API is a terrific tool dying for oxygen out there (and will end up like Wave- I hope not)

Sometimes you need artists as well as engineers to design query tools, G Men- and guess the Double Click anti trust rumours have quietened down enough because why the heck did double click interface integration take so loooong.

( and btw why cant Google just get into the multi billion dashboard business if they can manage ALL the data IN THE INTERNET ——they sure can do it for specific companies- – but wait-

they are probably waiting for AsterData to stop sucking thumbs ,chanting on MapReduce SQL,  MapReduce SQL nursery rhymes and start inventing NEW STUFF again (or atleast creating two product brands from nCluster (when you and I were in school together giggle)

Btw the time Google make up their mind to enter BI or wait for Aster to finish- IBM would have gulped and burped all there it is- and thats the way that market rolls.

Back to Ad s and Mad Men.

Here are some screenshots-of the new Google Ad Planner-

I found it useful to review traffic for third party websites (even better than Google Trends) and thats a definite plus over Facebooks closed dormitory world of ads.

Click on them for some more views or go straight to http://google.com/adplanner and Enjoy Baby!

Which websites attract your target customers?

View a site listing: 

Ad Planner top 1,000 sites

Refine your online advertising with DoubleClick Ad Planner, a free media planning tool that can help you:

Identify websites your target customers are likely to visit

  • Define audiences by demographics and interests.
  • Search for websites relevant to your target audience.
  • Access unique users, page views, and other data for millions of websites from over 40 countries.

Easily build media plans for yourself or your clients

  • Create lists of websites where you’d like to advertise.
  • Generate aggregated website statistics for your media plan.

and

Take charge of your DoubleClick Ad Planner site listing

View a site listing: 

Ad Planner top 1,000 sites

DoubleClick Ad Planner is a media planning tool where advertisers find sites for their media buys. As a site owner, you can access the DoubleClick Ad Planner Publisher Center and
Market your site
Write a site description to present your audience and unique value to advertisers.
Help advertisers search for you
Choose categories for your site and ad formats you support.
Improve the data that advertisers see
Share your Google Analytics data to reflect the most accurate traffic numbers for your site.

 

Google Raise What

Google recently did the following-

1 Raised salaries by 1000 $ across board, and gave a 10% increase at lower levels to reportedly 30% increase at higher levels.

The surprise 1000$ cash bonus , was a simple application of expectation management, people love a surprise 1000$ raise, but hate if told they would be getting a 90$ raise in their monthly salary from next quarter.

Ex Googlers or GoogleX as the groups is called have helped create a lot of not so evil value at Facebook, and at Twitter. Even the rest of the World made more money on Map Reduce than Google itself did

And Google refuses to do simple things like sell Android )s at 10 bucks a pop, or Google Maps at 0.99 cents a pop. Not even a paid content search by integrating syndicating sources like Factiva, Bloomberg etc

The book scanning project would be out soon , hey when, but they could better get some health record scanning contracts to help cut digital costs

And the A/B experiment to move to pay per conversion rather than pay per click will hurt spamboy advertisers in Facebook or Bing more than Google.

and will someone remove the 100$ limit in Adsense minimum revenue-the internet long tail doesnt end at the round number

But Google ‘s rumors of firing the guy who leaked the raise rumor is totally deception –

seems they are just plugging the leaks for hot new features to counter Gmail killers (where did we heard this phrase before) by

Mark “Still dont have a diploma from Harvard”

speaking of which if Facebook has 500 million unique customers logging and clicking ads (right)- how many unique customers search and click ads on Google. A histogram using a Monte Carlo would be nice- 🙂

 

 

Image using png package courtesy Romain Francois at http://romainfrancois.blog.free.fr/

Cisco SocialMiner

A highly simplified version of the RSS feed ic...
Image via Wikipedia

A new product from Cisco to mine social media for analytics on sentiment-

http://www.cisco.com/en/US/products/ps11349/index.html

Cisco SocialMiner is a social media customer care solution that can help you proactively respond to customers and prospects communicating through public social media networks like Twitter, Facebook, or other public forums or blogging sites. By providing social media monitoring, queuing, and workflow to organize customer posts on social media networks and deliver them to your social media customer care team, your company can respond to customers in real time using the same social network they are using.

Cisco SocialMiner provides:

  • The ability to configure multiple campaigns to search for customer postings on the public social web about your company’s products, services, or area of expertise
  • Filtering of social contacts based on preconfigured campaign filters to focus campaign searches
  • Routing of social contacts to skilled customer care representatives in the contact center or to experts in the enterprise–multiple people can work together to handle responses to customer postings through shared work queues
  • Detailed metrics for social media customer care activities, campaign reports, and team reports

With Cisco SocialMiner, your company can listen and respond to customer conversations originating in the social web. Being proactive can help your company enhance its service, improve customer loyalty, garner new customers, and protect your brand.

Table 1. Features and Benefits of Cisco SocialMiner 8.5

Feature Benefits
Product Baseline Features
Social media feeds

• Feeds are configurable sources to capture public social contacts that contain specific words, terms, or phrases.

• Feeds enable you to search for information on the public social web about your company’s products, services, or area of expertise.

• Cisco SocialMiner supports the following types of feeds:

• Facebook

• Twitter
Campaign management

• Groups feeds into campaigns to organize all posting activity related to a product category or business objective

• Produces metrics on campaign activity

• Provides the ability to configure multiple campaigns to search for customer postings on specific products or services

• Groups social contacts for handling by the social media customer care team

• Enables filtering of social contacts based on preconfigured campaign filters to focus campaign searches
Route and queue social contacts

• Enables routing of social contacts to skilled customer care representatives in the contact center

• Draws on expertise in the enterprise by allowing multiple people in the enterprise to work together to handle responses to customer postings through shared work queues

• Enables automated distribution of work to improve efficiency and effectiveness of social media engagement
Tagging

• Allows work to be routed to the appropriate team by grouping each post or social contact into different categories; for example, a post can be marked with the “customer_support” tag; this post will then appear on a customer support agent’s queue for processing
Social media customer care metrics

• Provides detailed metrics on social media customer care activities, campaign reports, and team reports

• Measures work and results

• Manages to service-level goals

• Supports brand management

• Optimizes staffing

• Includes dashboarding of social media posting activity when Cisco Unified Intelligence Center is used
Reporting for social contacts

• Provides a reporting database that can be accessed using any reporting tool, including Cisco Unified Intelligence Center

• Enables customer care management to accurately report on and track social media interactions by the contact center
OpenSocial-compliant gadgets

Representational State Transfer (REST) application programming interfaces (APIs)

• Provides flexible user interface options

• Enables extensive opportunities for customization
Optional integration with full suite of Cisco Collaboration tools

• Allows you to take advantage of the full suite of Cisco Collaboration tools, including Cisco Quad, Cisco Show and Share, and Cisco Pulse technology, to help your social media customer care team quickly find answers to help customers efficiently and effectively

• Easy to maintain with existing IT personnel
Operating Environment
Cisco Unified Computing System(UCS) C-Series or B-Series Servers

• Requires a Cisco UCS C-Series or B-Series Server.

• Server consolidation means lower cost per server with Cisco UCS Servers.
Architecture
Scalability

• One server supports up to 30 simultaneous social media customer care users and 10,000 social contacts per hour.
Management
Cisco Unified Real-Time Monitoring Tool (RTMT)

• Operational management is enhanced through integration with the Cisco Unified RTMT, providing consistent application monitoring across Cisco Unified Communications Solutions.
Simple Network Management Protocol (SNMP)

• SNMP with an associated MIB is supported through the Cisco Voice Operating System (VOS).
Reporting
Cisco Unified Intelligence Center

• Create customizable reports of social media customer care events using Cisco Unified Intelligence Center (purchased separately).

 

 

John Sall sets JMP 9 free to tango with R

 

Diagnostic graphs produced by plot.lm() functi...
Image via Wikipedia

 

John Sall, founder SAS AND JMP , has released the latest blockbuster edition of flagship of JMP 9 (JMP Stands for John’s Macintosh Program).

To kill all birds with one software, it is integrated with R and SAS, and the brochure frankly lists all the qualities. Why am I excited for JMP 9 integration with R and with SAS- well it integrates bigger datasets manipulation (thanks to SAS) with R’s superb library of statistical packages and a great statistical GUI (JMP). This makes JMP the latest software apart from SAS/IML, Rapid Miner,Knime, Oracle Data Miner to showcase it’s R integration (without getting into the GPL compliance need for showing source code– it does not ship R- and advises you to just freely download R). I am sure Peter Dalgaard, and Frankie Harell are all overjoyed that R Base and Hmisc packages would be used by fellow statisticians  and students for JMP- which after all is made in the neighborhood state of North Carolina.

Best of all a JMP 30 day trial is free- so no money lost if you download JMP 9 (and no they dont ask for your credit card number, or do they- but they do have a huuuuuuge form to register before you download. Still JMP 9 the software itself is more thoughtfully designed than the email-prospect-leads-form and the extra functionality in the free 30 day trial is worth it.

Also see “New Features  in JMP 9  http://www.jmp.com/software/jmp9/pdf/new_features.pdf

which has this regarding R.

Working with R

R is a programming language and software environment for statistical computing and graphics. JMP now  supports a set of JSL functions to access R. The JSL functions provide the following options:

• open and close a connection between JMP and R

• exchange data between JMP and R

•submit R code for execution

•display graphics produced by R

JMP and R each have their own sets of computational methods.

R has some methods that JMP does not have. Using JSL functions, you can connect to R and use these R computational methods from within JMP.

Textual output and error messages from R appear in the log window.R must be installed on the same computer as JMP.

JMP is not distributed with a copy of R. You can download R from the Comprehensive R Archive Network Web site:http://cran.r-project.org

Because JMP is supported as both a 32-bit and a 64-bit Windows application, you must install the corresponding 32-bit or 64-bit version of R.

For details, see the Scripting Guide book.

and the download trial page ( search optimized URL) –

http://www.sas.com/apps/demosdownloads/jmptrial9_PROD__sysdep.jsp?packageID=000717&jmpflag=Y

In related news (Richest man in North Carolina also ranks nationally(charlotte.news14.com) , Jim Goodnight is now just as rich as Mark Zuckenberg, creator of Facebook-

though probably they are not creating a movie on Jim yet (imagine a movie titled “The Statistical Software” -not just the same dude feel as “The Social Network”)

See John’s latest interview :

The People Behind the Software: John Sall

http://blogs.sas.com/jmp/index.php?/archives/352-The-People-Behind-the-Software-John-Sall.html

Interview John Sall Founder JMP/SAS Institute

https://decisionstats.com/2009/07/28/interview-john-sall-jmp/

SAS Early Days

https://decisionstats.com/2010/06/02/sas-early-days/