Marketing and Technology

BirTugladaSenKoy

2006-07-22T18:40:00.000-07:00

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They are trying to raise fund's for the endowment by selling pixel ads...

Hyperion MDM (System 9 Master Data Management ) Update

2006-06-12T12:13:00.000-07:00

Hyperion a leader in Business Performance Management software, announced that a growing number of companies are using Hyperion System 9 Master Data Management (Hyperion MDM) to enable visibility and collaboration between Information Technology (IT) and business users in defining, implementing and managing change across systems.

As an integral part of Hyperion System 9 Foundation Services, Hyperion MDM is the industry's first solution dedicated to Business Performance Management. With its easy to use "point and sync" thin client interface, Hyperion MDM enables non-technical users to directly manage change of BPM master data. Through a formal, rule-driven process, Hyperion MDM synchronizes BPM master data such as business dimensions, reporting structures, hierarchies, attributes and business rules across Hyperion System 9 applications and enterprise systems, including data warehouses, data marts, analytic applications, and transactional systems. Hyperion MDM provides robust master data lifecycle and versioning capabilities, in conjunction with a powerful business rules engine and audit capabilities for validating and verifying changes in master data, both in real time and after the fact.

"Hyperion MDM helps companies tackle the innumerable challenges and costs of operating in today's constantly changing and competitive global environment," said Rich Clayton, vice president of product marketing at Hyperion. "By synchronizing data across all systems, Hyperion MDM not only provides users with a single version of the truth but also dramatically reduces development cost and risk and reduces the cost of implementing and maintaining business intelligence and data repository processes."

Some of the customers who have purchased Hyperion MDM include Avago Technologies, FirstRand Bank, HBOS, Mentor Graphics, Symantec Corporation, Verizon and Xerox Corporation.

FirstRand, a financial services group based in South Africa, will leverage Hyperion MDM within its banking division to increase user productivity, lower security risk, and protect the company's data integrity.

"With Hyperion MDM, we can eliminate all costly manual master data management processes within our company," said Tim Green, IT manager at FirstRand. "Hyperion MDM will serve as FirstRand's central environment to manage master data and automate the changes we make across our organization, which will speed essential processes and ensure data integrity throughout our operations."

Mentor Graphics, a leading manufacturer of electronic design solutions, implemented Hyperion MDM to maintain the accuracy of master data within its various financial, analytic and transactional systems.

"In our fast-paced and growing business, we need to have confidence in the data across our enterprise," said Jan-Willem Beldman, team lead for analytical applications and data quality at Mentor Graphics. "The integration of MDM within our BPM system facilitates collaborative data management between our IT department and business owners of data. As a result, we are able to consolidate, correlate and standardize our master data, businesses processes and analytical capabilities so that reporting data is readily available, consistent and accurate."

MicroStrategy Expands Relationship with Microsoft with Direct Access to Microsoft SQL Server 2005 Analysis Services

2006-06-12T11:02:00.000-07:00

MicroStrategy Incorporated, a leading worldwide provider of business intelligence (BI) software, announced that it is expanding its relationship with Microsoft Corp. by extending access to multidimensional data sources with support for Microsoft SQL Server 2000 and SQL Server 2005 Analysis Services. MicroStrategy 8 uses the industry standards of Web Services and XML for Analysis (XMLA) to connect to SQL Server Analysis Services.

With MicroStrategy's BI software, companies are able to make better business decisions by standardizing and tapping into information stored in multiple locations across their enterprise. MicroStrategy transforms vast amounts of data into actionable dashboards, reports, and comprehensive analyses that companies use to monitor and improve business performance. MicroStrategy's support for SQL Server 2005 Analysis Services will allow customers to report and analyze Analysis Services data and join it with data from other sources, enabling deeper insights to uncover problems and trends previously unseen.

In addition to a highly intuitive and visual web interface, users also inherit the advanced technical capabilities of MicroStrategy, including outstanding data and user scalability, integrated architecture, and Pixel Perfect reporting. This support expands MicroStrategy's multiple integration points with Microsoft, including Microsoft SQL Server 2005, Microsoft Office, Microsoft Office SharePoint Portal Server, and the Microsoft Windows operating systems. MicroStrategy plans to continue enhancing its integration with SQL Server 2005 Analysis Services to take advantage of the latest capabilities in the Analysis Services release.

Microsoft Office PerformancePoint Server 2007

2006-06-11T12:47:00.000-07:00

Microsoft officially added a new server to its business-intelligence (BI) line up on June 6, announcing plans for a back-end application that will support business scorecarding, budgeting, forecasting and other performance-planning activities.

The new product, Office PerformancePoint Server 2007, is the latest piece of Microsoft's evolving family of analytics products to get the official nod. PerformancePoint is slated to go to beta test this fall and ship by mid-2007, according to Microsoft officials. Microsoft itself has been dogfooding PerformancePoint since September 2005, company officials said, to manage all of the company's cost and revenue forecasting.

Microsoft is slated to share the latest iteration of its business-intelligence roadmap and more details about PerformancePoint during a Webcast on June 6.

In March 2006, at the company's Convergence conference, Francois Ajenstat, General Product Manager for SQL Server, explained Microsoft's BI strategy. Ajenstat presented to press and analyst attendees an architectural diagram to describe Microsoft's BI infrastructure.

The bottom layer consisted of what Ajenstat called "the business intelligence platform," which, in Microsoft's world view, is SQL Server, reporting services, analysis services and data-transformation services. On top of that layer sits "end user tools," specifically, Microsoft Office's Excel, Excel Services (in Office 2007) and SharePoint Server 2007. The very top layer consists of "analytic applications," which, in Microsoft parlance, equates to the Dynamics CRM/ERP family plus current and future Office Business applications.

Office Business apps include Microsoft Business Scorecard Manager 2005, as well as other performance-management applications, code-named Biz#, that are under development.

PerformancePoint also will include the next release of Microsoft Business Scorecard Manager, company officials said on June 6. Microsoft also will be updating the analytics and visualization technologies it acquired when it announced its intentions to purchase Boise, Idaho-based ProClarity in April 2006. Microsoft officials said on June 6 that Microsoft had completed its ProClarity acquisition.

In March of this year, Ajenstat described the list of future OBA applications as including "business scorecards, budgeting and planning apps, consolidation and financial reporting apps."

Doug Burgum, Senior Vice President of Microsoft Business Solutions (MBS), said his division was working hand-in-hand with the OBA team. On June 6, Microsoft revealed that Microsoft's Dynamics ERP and financial applications will integrate with PerformancePoint.

"Part of the long-term vision is for us to take advantage of OBA stuff that's appropriate," Burgum told Microsoft Watch. "We want to make that part of the solutions we sell.

"The concept on Biz# is that it was to achieve BI in a user interface, connecting to lots of different ERP systems. Companies would be allowed to choose," said Burgum.

Oracle Buys Demantra

2006-06-11T12:18:00.000-07:00

Latest News about Oracle said it is buying Demantra, a software maker of tools for managing sales and inventory. Financial terms weren't disclosed.

The acquisition, expected to be completed later this month, continues an Oracle shopping spree that began three years ago when the Redwood Shores, Calif.-based company launched a hostile takeover bid for rival PeopleSoft.

The battle lasted 18 months before Oracle finally sealed the US$11.1 billion deal.

Since then, Oracle has spent more than $8 billion buying a variety of other companies, including Siebel Systems Latest News about Siebel in a $6.1 billion purchase that closed four months ago.

Demantra provides Demand-Driven Planning solutions that enable marketing, sales, and supply chain departments to create and execute to a one–number plan. The Demantra Spectrum Suite includes solutions for Trade Promotion Management & Optimization, Real-Time Sales & Operations Planning, Demand Management, and Retail Planning & Store Replenishment. These solutions manage the rapid creation, planning, and fulfillment of demand from promotion management to store replenishment, resulting in improved demand visibility, more profitable promotions, optimized service levels, increased customer responsiveness, lower operational costs, and increased sales and profits.

Demantra has over 140 customers, spanning a range of industries, including: Consumer Goods, Media & Entertainment, Industrial Manufacturing, and Quick Service Restaurants. Demantra has provided proven results — 100 to 500 percent ROI — to global organizations including: Unilever, Johnson & Johnson, Welch's, Reckitt Benckiser, McCain Foods, Hunter Douglas, Baxter Healthcare, Wendy's International, Applica, and VTech.

Founded in 1996, Demantra is headquartered in Waltham, Massachusetts and has regional headquarters in Rotterdam, Sydney, and Ramat Gan, Israel.

SAS Campaign Management Module

2006-06-08T10:28:00.000-07:00

SAS is one of the best statistical packages that's available. They have also advanced their capabilities in database management. Now SAS is trying to claim leadership in the world of campaign management. So what differentites their solution? These are the strengths according to SAS:

Maintain an integrated customer view. SAS provides a unified view of customers across your enterprise that incorporates information from all touch points and channels, ensuring that customer information is consistent, secure, accurate and comprehensible to users.
Manage customer life cycles. Customer segmentation and profiling capabilities consolidate insight at a customer level to build and monitor critical strategic segments over time.
Improve effectiveness through better targeting, measurements and analytics. Through advanced analytic techniques such as data mining, market basket analysis, link analysis, forecasting and optimization, as well as segmentation, profiling and behavior analysis, SAS Marketing Automation helps you understand customers' past behavior and predict future opportunities.
Drive complex communication strategies. Through an intuitive graphical interface and in-depth campaign management functions, business users can easily deploy the results of advanced analytics and drive multichannel, multistage communications using reliable customer intelligence.
Understand the results of marketing activities. SAS Marketing Automation allows users to fully understand campaign responses, whether those responses involve direct communication or subtle changes in behavior. Reports on campaign effectiveness combine this response analysis with budget expectations to deliver a full picture of the financial return achieved by each marketing initiative.
Provide integrated support for all business units. SAS Marketing Automation fully supports the activities of your key marketing campaign participants, including business users, database marketers, quantitative analysts and IT.
Manage your IT infrastructure. Allowing companies to take advantage of their existing IT infrastructure, SAS Marketing Automation is built on technology that can be deployed across the enterprise in a scalable, multitier architecture.

Company Profile: Arbitrel

2006-06-06T20:28:00.000-07:00

Arbitrel, Inc. is an eCRM (Customer Relationship Management) software company that helps companies improve the effectiveness of their customer, prospect and partner relationships. Arbitrel is dedicated to building and delivering intelligent software solutions that enable business professionals to better leverage the Internet for marketing, sales and commerce. Whether the need for our clients is effective email marketing campaigns, or extending it to include online commerce, Arbitrel's suite of products can meet those needs.

Arbitrel was established with the goal of providing enterprise-class business software for the mid-market. The company's goal is to provide mid-market businesses similar capabilities of the solutions that world's largest corporations (Fortune 1000) use, yet offering them at prices that mid-market customers can afford.

For more information on Arbitrel's news and events, please click here.

eCampaign Overview

Arbitrel eCampaign is an intelligent eMessaging and eMarketing system that offers extensive tools to Create, Send, Track, and Target email/newsletter campaigns.

Identify and reach your target customers by targeting your prospects and customers through eCampaign's powerful response tracking technology.
Personalize messages based on your existing customer data creating true one-to-one relationships with your targeted audience, increasing message relevance and email impact. It's a one-to-one messaging system.
Create professional messages by easily downloading and editing HTML content from the web or existing images without any technical expertise.
Conduct multi-staged marketing campaigns based on individual customer responses to previous campaigns driving higher conversion and ROI. Refine your messages and your targets with "point-to-click" functionality based on actual customer actions and interest levels.
Build greater customer loyalty by keeping your customers aware of new products, providing personalized services, and communicating valuable information.

With Arbitrel eCampaign, you can proactively manage your customer relationships

You can "push" your company brand out instead of trying to pull prospects in.
Rekindle your customer relationships and boost traffic to your site.
Improve customer retention and loyalty with frequent business/product updates.

eCampaign is easy to use, most business users can learn to operate it in a few hours, and the typical deployment takes only two days. The system has a powerful and scalable architecture. Behind the scenes, Arbitrel eCampaign consists of several servers including: the Advanced Response Tracking Server, Return Mail Server, Load Balancing Server, and Advanced Mail Delivery Server capable of delivering emails approximately 50 times faster than a conventional server. It is written in pure JAVA enabling communication with any of the JAVA-enabled platforms and Enterprise databases (MS SQL, Oracle, etc.), while the client application is written in Visual Basic, making it a business user-friendly interface.

Company Profile: YellowBrick Solutions

2006-06-06T20:08:00.000-07:00

YellowBrick Solutions specializes in marketing automation software and services that can help you more effectively and efficiently manage marketing programs. Let YellowBrick Solutions show you how to start simply and cost-effectively, deploy quickly, and evolve seamlessly to multi-channel, real-time customer communications.

YellowBrick Solutions is your partner whether your direct marketing efforts are focused on one channel or multiple channels. Capabilities offered in the YellowBrick Marketing Automation Suite include data readiness and analysis, campaign design and execution, and reporting.

YellowBrick Solutions contributes to the profitability of marketing programs through:

Increasing Revenues

Deliver personalized, relevant, and timely communications to targeted segments to greatly increase response rates and ultimately increase sales.
Increase customer loyalty by providing ongoing and relevant communications that promote brand awareness and provide new up-selling or cross-selling opportunities.
Monitor campaign performance and make real-time adjustments to campaigns that are under-performing to ensure that response and revenue targets are achieved.

Increasing Marketing Campaign Efficiency and Effectiveness

Perform faster customer segmentation and analysis through direct access to customer data.
Shorten campaign planning and execution cycles with easy-to-use graphical interfaces and reusable campaign elements.
Maintain consistency of messaging across channels.
Increase relevancy of messages based on profiles and interactions.
Optimize marketing resources through ongoing campaign monitoring and reporting capabilities.

Simplified Deployment for Lower Cost-of-Ownership

Reduce deployment times
Start simple, add more functions as business needs change.
Integrate out-of-the-box with existing databases, data cleansing and analysis packages, and channel-specific fulfillment tools.
Reduce demand for IT resources.

Company Profile: AIMS Software = smartFOCUS

2006-06-05T13:49:00.000-07:00

AIMS develops CRM software and focuses mostly on clients from Europe. Their software package includes: smartSERVER, smartANALYZER, smartCAMPAIGNER, smartMODELER and smartREPORTER. Given all the "smarts" another name for the company is "smartFOCUS".

smartFOCUS develops, deploys and supports a portfolio of leading data integration, descriptive and predictive analysis, campaign planning and management and reporting solutions that integrate to deliver Intelligent Marketing. Intelligent Marketing enables marketers to acquire, retain and grow more profitable customer relationships and increase return on marketing investment.

Details on the programs of the package are as follows:

smartSERVER, the single marketing platform delivers an environment for very fast, high volume data management and storage and underpins the front office applications smartANALYZER, smartMODELER, smartCAMPAIGNER and smartREPORTER. smartSERVER is developed on a column based data storage model that optimizes data for marketing. The massive capacity of the smartSERVER ensures that customer, product and transaction data is easily integrated to deliver a complete and single view of the customer with results being delivered to the desktop immediately.

smartANALYZER is the intuitive and highly vizual descriptive analysis application that enables marketers to deliver 'train of thought' analysis at their desktops on billions of rows of data whilst maintaining the ability to view the data down to record level. The smartANALYZER solution has an intuitive drag & drop user interface that empowers marketers with the ability to create and vizualise the results of complex analysis and queries without the need for programming or statistical skills.

smartMODELER is an intuitive, powerful and vizual data modeling application designed to enhance productivity for analysts and marketers. It utilizes the data available within the smartSERVER to create sophisticated models through a step by step, wizard driven interface. Heavy duty mathematical processing is undertaken by the smartSERVER to optimise speed of model creation and the use of server processing power.

smartCAMPAIGNER offers an affordable technology answer to marketing campaign management requirements providing all the functionality required for executing and automating multiple campaigns through multiple channels. By exploiting the speed and flexibility of the smartSERVER, campaigns can be set up quickly and easily using the same intuitive user interface.

smartREPORTER provides a cost effective answer to marketing KPI reporting. It delivers all the functionality required for creating persistent reports, within the widely adopted MS Excel environment, that are easily deployed across the business. By exploiting the power, speed and flexibility of the smartSERVER and the familiarity of MS Excel, templates can be easily designed and scheduled.

smartFOCUS has developed a range of commercial programs to enable our business partners to leverage the benefits that our marketing analysis and automation technology can bring to their organisation. Partners may sign up to multiple programs should they wish. smartFOCUS has three programs designed to offer flexible benefits to our partners and their customers:-

Partneship with AIMS Sofware (smartFOCUS):

Bureau Partner
Bureau Partners are organisations who within their operational processes take client data, for example through hosting clients marketing databases or building data driven marketing projects such as segmentation, profiling or modeling. They will use smartFOCUS technology within their business to drive significant productivity gains around engineering, manipulating and understanding data on behalf of their clients, thus reducing internal costs, increasing margins and shortening delivery times.

Application Service Provider
ASP partners are typically Bureau Partners wishing to add new capability to their existing services whereby clients can now access their data, hosted at the partner, via the web through a standard browser. smartFOCUS applications provide a highly graphical, easy to use, easy to manage environment with a flexible commercial model that enables your customers to get instant access to the valuable data resources you hold.

Value Added Reseller
VAR partners re-sell smartFOCUS applications to their clients. smartFOCUS provides as little or as much assistance in the sales; implementation and support processes as the partner requires.

VAR partners are typically organisations who already offer system integration services. They may already be providing marketing solutions around modeling, campaign management or customer service and see the innovation smartFOCUS analysis and marketing automation solutions as a unique differentiator in their marketplace.

Their client list includes: AAA, EuroRSCG, Avis, P&G, QVC and Sympatico.

SAS vs. R

2006-06-01T15:13:00.000-07:00

Many of my friends tell me there's been an uptick lately in new books that focus primarily on R. It also sounds like non-academic statisticians are accelerating their switch to R (mostly from SAS).

It feels like SAS has become really focused on the enterprise-side and not doing the cutting-edge statistical computing work anymore. In contrast R package has some interesting statistical work.
Statisticians (especially in academics) are becoming mmore and more savvy programmers with every generation. Statisticians who have also done work in C, Java, or scripting languages can appreciate the flexibility in data structures that R offers.

SAS has really become like an enterprise database with advanced mathematical/statistical functionality. Most people simply don't need all of the enterprise functionality (or the pricing) it offers and are better off with the combination of R and flat files or an open source DB like MySQL.
However as long as there are enterprises doing statistics, SAS will exist. Many of the employers I know of run SAS shops. However, R is a favorite among biostatisticians, it's becoming better documented, and it's FREE. All good reasons for academic use.

Part of the reason that enterprises prefer SAS is the support- the really fabulous documentation and tech support. With R, you have the R mailing list. You also have to study the R FAQ really well.

Also, in ceratin industries, SAS seems to have reached some sort of "trusted" status.

I think that if R truly wanted to compete in that space it would need to improve the database support and some of the memory requirements (which have been improving or at least changing recently) along with maybe some sort of Red Hat-like company to provide the documentation and support (and, if the licensing could be worked out, an "Enterprise-level" user interface, that likely means point-n-click access to certain modules). For addressing SAS's "trusted" status you could go with something like the OpenBSD auditing projects---since the code is totally open you can actually do things like peer review audits. SAS also has pretty extensive reporting facilities, but I think that R's Sweave like tools will be better in the long run (for those who don't know about it, very handy. It lets you do things like include the commands for generating figures in the LaTeX document itself s.t. processing the LaTeX document automagically generates the figures, tables, etc and inserts the appropriate LaTeX code that gets passed on to the LaTeX toolchain to generate the DVI, PDF, etc).

R encourages the good software development practices, especially
the use of test cases and documentation. There is no SAS equivalent to
R CMD check. This is extremely important. You are ensuring that your code
does what you think it does, both today and in the future..

R's graphics are superior to SAS.

Via Sweave, xtable and friends, R makes it very easy to practice
literate programming.

Oracle vs SAP

2006-05-28T19:51:00.000-07:00

It used to be that the ERP market had an 800-lb gorilla, SAP, and a number of smaller competitors. Then Oracle went on a shopping spree, gobbling up companies like J.D. Edwards, PeopleSoft, Siebel, Retek and others. Suddenly, there are two gorillas in the market, along with a whole bunch of customers who now find themselves under the Oracle umbrella. Is this a good thing or a bad thing? So far, customers have been courted by sales reps from both sides and often benefited from having aggressive reps compete over who can offer up the sweetest deal for going all-SAP or all-Oracle.

But the larger issue is: what does the future hold for the ERP market? What good is a bargain today if you have to jump ship again in a few years? More specifically, is Oracle's vision of Project Fusion a pie in sky dream that will only lead to disaster for customers? Or perhaps SAP should be more concerned about issues like TCO and flexibility than they appear to be?

SAP Point of View:

NetWeaver Vs. Fusion: Survival of fittest favors the fit

The NetWeaver vs. Fusion competition looks more and more like a Darwinian race for survival, with two distinct but similar species competing for resources in the same biological niche. That niche, of course, is your IT budget, and the race for survival is manifesting itself in briefings and sales presentations across the globe.

The natural world has several strategies for how such a race is run – and won – and each provides some insight into what the eventual outcome of the NetWeaver vs. Fusion struggle will be. One such strategy is competitive coexistence, though at the price of constant conflict. Another biological model is parasitism. A third, the least likely, is symbiosis. But the most probable outcome, the one that everyone at SAP and Oracle would prefer over any other, is the one that nature seems to favor more often than not: total dominance. And, based on what we now know about the two companies' strategies, given such an outcome, NetWeaver would be the winner, hands down.

Why I believe NetWeaver would win out is based on no small amount of digging into the two companies' plans. SAP has been plugging away at its NetWeaver strategy for several years now, while Oracle recently updated analysts, the press, and some customers at a conference in San Francisco. And while there are details and plans galore on both sides (ad infinitum, if not ad nauseam), there are three irrefutable facts that give NetWeaver a serious edge over Fusion.

Better roadmap

The first is that I believe SAP has done a better job of both articulating its roadmap for NetWeaver and delivering on it. To be fair, that is in part because they have been at it longer than Oracle. Remember, Fusion is barely a year old, whereas NetWeaver has been bandied about as a concept for almost three years. But I also believe that SAP's advantage in building out its own applications – as opposed Oracle's strategy of acquiring or partnering to build its applications portfolio – has allowed the market to see more clearly where SAP is going and what functionality will be available once the full force of NetWeaver's service architecture can be brought to bear on the market. Oracle's Fusion Middleware strategy is relatively well thought-out and well-defined, but the roadmap for Fusion Applications still has a lot of blank space in it – placeholders for as-yet unannounced acquisitions and partnerships.

Vertical functionality

This brings me to my second point. In my opinion, vertical industry-specific functionality is where the rubber hits the road as the future of enterprise applications unfolds. Indeed, all that trouble to build and implement service architectures like NetWeaver and Fusion would largely be for naught if all they did was enable more monolithic, general-purpose enterprise software. The real value-add for service architectures comes from their ability to take individual services and build them, Lego-like, into applications that are essentially mass-customized for individual business in individual industries.

This means that, in addition to a strong services infrastructure, a vendor needs a large portfolio of services to assemble – the more the merrier. This is where SAP's next advantage comes into play. SAP's has experience in 28 verticals, and the software functionality to prove it. As NetWeaver unfolds, one of SAP's tasks will be to service-orient all that functionality and make it available as building blocks for the future. That's a non-trivial task, but one that, once done, provides SAP customers with an exceptionally large palette of vertical industry functionality on which to build their service-oriented future.

Oracle, on the other hand, has always lagged in providing deep vertical functionality, a fact acknowledged by the vertical focus of their acquisition and partnering strategy. While there is some deep vertical functionality now in the Fusion playbook – Retek in retail was a major coup, and Siebel can provide some CRM-specific vertical functionality in the industries that it targeted – the scope of this functionality still lags behind that of SAP. And while Oracle is now vowing to fill in the blanks with more partner products, until we can evaluate exactly what those products can do and how many vertical industries they allow Oracle to compete in, SAP still has the vertical industry advantage.

The Fusion timeline

Finally, I have trouble with Oracle's very ambitious timeline for its Fusion Applications. Oracle argues that they are "halfway to Fusion", largely on the strength of their work on Fusion Middleware. I'll grant them that. But halfway to Fusion Applications – particular a suite of highly verticalized service-oriented applications based on least six different code bases (if you count the pieces of software that make up its Oracle, PeopleSoft, J.D. Edwards, Siebel, Retek, and ProfitLogic product lines) – I'm having trouble with the scope of that task. Bear in mind, Fusion Applications are slated to come out in 2008, after Oracle releases updates to its eBusiness Suite, PeopleSoft, and J.D. Edwards lines. That is, to use a technical term, a boatload of application development work.

Sure Oracle is big, sure they're full of some of the smartest minds in the industry… so is Microsoft, whose ambitious plans to develop its own next-generation version of its enterprise software suite – Project Green – foundered and has been radically redrawn and retimed. (Not to mention Microsoft's plans for its operating system, middleware, and a fair amount of the rest of its offerings.) In other words, history tells us that that huge software projects at a minimum tend to miss their deadlines, if not fail hugely. And while I don't think Oracle will fail – Fusion Applications will some day see the light of day – I don't believe that day will dawn in 2008.

Again, to be fair, SAP also has a monumental development task – but it's from a single code-base of software that the company has spent 20-plus years developing. NetWeaver's timetable benefits greatly from its status as a next-generation project based on internally developed software, and not on a massive blending and rewriting of a half-dozen different applications and code-bases.

In the end, software evolution plays by different rules than biological evolution, and Fusion's prospects could change quickly in the next year or so. But, as things stand today, Fusion looks like a candidate for endangered species protection, even before it actually enters the race for survival. If biology defines software destiny, Fusion's destiny looks perilous at best.

Oracle Point of View
Why select Oracle Applications for your organization's ERP system?

What do Ingersoll Rand, Starbucks Coffee Company, General Dynamics and Harvard University have in common? They use Oracle Applications 11i to automate their operations.

Set aside all the sales and political machinations that can, and do, occur in the executive offices when an organization decides to purchase an ERP system. Let's ask the question: What are the compelling attributes of Oracle Applications? Does Oracle really have a better offering than SAP? This article takes a brief look at Oracle Applications' strengths -- the product's extensibility, its technology stack, ease of implementation and the total cost of ownership -- and what they mean for companies that are selecting an ERP system.

Extensibility

While no "out-of-the-box" ERP system can meet the needs of every customer, Oracle Applications' flexibility is an attribute that has drawn many companies into its fold. Oracle's offering also shines in several areas with regard to extensibility -- Web applications, workflow and reporting.

Oracle's approach to Web applications is so flexible that an organization's IT department can personalize a Web application, such as iProcurement, so that employees logging in from Bangkok see relevant information for that region, and employees logging in from Dallas, Texas, access information that is appropriate to their region. iExpense is another example of the incredible configurability of Oracle's Web applications. Many companies have used this portion of Oracle Applications to streamline their business processes associated with employee expense reimbursements. Robb Robison, Purchasing Manager at a Bay Area software company, is a fan. "I worked with SAP at my previous employer. I'm working with Oracle now. It's just more flexible. For example, iExpense is simpler and easier to work with than anything SAP has. And it's in English!"

Oracle's workflow and business event system allows companies to configure business processes in a variety of ways, with the capability of sending e-mail notifications and alerts to practically anyone associated with the organization. SAP does not offer anything that is equally configurable or flexible.

One of the common complaints of SAP customers relates to the difficulty associated with getting actionable information out of SAP. A senior manager at a utility and SAP customer bemoaned the fact that he needed additional headcount for business system analysts to produce reports and access needed financial information. In contrast, Oracle reporting is so easy and accessible that any user with the proper privileges can produce a report. Further, with Oracle's addition of Daily Business Intelligence, retrieving actionable data from the applications has become a matter of reading a dashboard and drilling into the necessary data.

Technology

Oracle's technology stack for its Applications makes the flexibility and configurability possible. It is true that better "best of breed" solutions exist in the market. Still Oracle embraced the middleware market early on when it began talking about using its middleware as the cornerstone for a "service oriented architecture" in 1999 (see Note 1).

Consequently, the company has a strong middleware product. Further, Oracle Corporation has worked on simplifying and opening its Applications architecture. The benefit to Oracle's customers is a product that is easier to install, maintain and use productively. Finally, the company's efforts toward creating a unified data model are paying off. With Oracle Applications' unified data model, organizations have one source of record. There is no more jockeying between departments -- sales and accounting, for example -- about which numbers are valid. SAP still makes its customers work with five different data models. If a company wants a single source of truth with SAP, it must build a data warehouse. Oracle's Daily Business Intelligence product makes a data warehouse optional for many of its customers. The result is faster access to actionable information at less expense.

Implementation challenges

ERP systems are complex. An ERP implementation is such a major undertaking for any organization that poor planning, misaligned scope or mediocre execution can result in bringing the company's operations to a complete halt. Over the years, news reports have described the more egregious implementation failures -- Irish Health Services, Hewlett Packard, Hershey Foods, Whirlpool and King County, Washington. Whether these failures were the principal responsibility of the customer or the vendor does not change the reality of increased challenges that any company faces when it attempts to implement SAP's software. According to Nucleus Research, companies that it interviewed encountered a couple of daunting issues implementing SAP -- customization and integration. These two challenges led to additional, equally serious problems confronting SAP customers, increased duration and internal costs for deployment. SAP requires on average four times more internal resources, and companies spend almost twice as much for SAP training (see Note 2). Further, the SAP customization and integration issues can increase consulting costs substantially.

A company can install Oracle Applications and begin conducting its operations successfully in six months. Oracle Applications was installed and deployed at Brocade Communications in San Jose, California, in six months, as well as at OpenWave in Cupertino, California. American Tower in Boston, Massachusetts, completed its implementation in eight months. Toni & Guy USA based in Carrollton, Texas, assisted by BearingPoint's R2i methodology, completed its Oracle Applications deployment in five months! How many companies have been able to implement and be productive on SAP in eight months or less? As of January 2006, the answer is none that this author is aware of.

SAP has been successful with its pitch to CEOs and CFOs regarding the benefits and features of its products. However, in speaking with the very people who will actually deploy, maintain and use the ERP system -- system analysts, business analysts, subject matter experts and end users -- they maintain that Oracle Applications, even with its warts, is easier, more user-friendly and less time-consuming than SAP.

Total cost of ownership

All roads -- extensibility, technology and implementation -- lead to total cost of ownership (TCO) and ROI. Which is better, Oracle's or SAP's? Oracle Applications' extensibility and flexibility alleviate the need for customization. With less customization come faster deployments, lower consulting costs and internal resources that return to business operations quicker. The effect of all these attributes is a lower cost of ownership. In fact, not only are Oracle's costs lower than SAP's, but Oracle's average three-year TCO is 48% lower than SAP's (see Note 3). With a difference that substantial, why select SAP?

Conclusion

If an organization is looking to sustain its competitive advantage and become a market leader in its industry, this means constant organizational change through streamlining business processes, reorganization and restructuring, and so forth. As economic history confirms, these activities are demanding in and of themselves. They become nearly impossible with an ERP system that is inflexible, difficult to implement and maintain, hard to use and unnecessarily costly. Oracle Applications, on the other hand, can be successfully deployed in a short time frame. It is flexible and highly configurable. It has a lower TCO than SAP. Working with Oracle Applications is easier than SAP, according to users who have seen both. Does Oracle really have a better offering than SAP? The answer is a resounding "Yes!"

CRM Software: Campaign Management

2006-05-28T12:53:00.000-07:00

Affinium Campaign (Unica)- This product is a campaign management system, which supports multi-wave, event-driven, scheduled, repeat, one-off, multi-stage, multi-channel, and longitudinal (relationship) campaign programs, as well as other campaign scenarios.

For more information regarding Unica please see:
Company Profile: Unica
Web Analytics from Unica

AIMS (AIMS Software)- This product provides the marketing division with powerful tools to manage all marketing campaigns, whether centrally issued and/or locally handled, through any combination of distribution channels.

Amyyon Marketing (Amyyon)- Amyyon Marketing allows companies to manage their marketing and promotional campaigns more effectively.

Annuncio Live (Annuncio)- This product is a complete internet marketing automation solution that enables marketing professionals to define, automate, track and analyze internet and integrated marketing campaigns.

AppropriAd (Data4s Future Technologies)- This product is an on-line campaigning solution based on behavioural user profiles. It allows advertisers and marketers to precisely detect and reach their audience for advertising initiatives.

Arbitrel eCampaign (Arbitrel)- This product provides an user interface designed to allow users with no programming experience to create effective e-Marketing campaigns, track receiver responses, view campaign reports and perform statistical analysis. With its advanced tracking capabilities, it records response rates down to who opened emails, how long they were open, which links were clicked, and information on return mail handling. It also maintains a record of customer interactions with emails sent through the program.

Austin Logistics Inc. (Austin Logistics Inc.)- Develops software solutions and services for B2C relationships. Offers CallTech, award-winning call center management software, and ResponseTech, a direct marketing/campaign management solution.

Caspian Marketing (Caspian)- This product is for managing any type and size of campaign with lead management and segmentation and drill down options.

DataLodgics (Matrix Technology Group, Inc.)- This product integrates customer data from multiple sources to leverage customer knowledge into targeted, automated, market-driven executions. It provides the marketer with information to accurately target the intended audience for a product.

E.6 System (E.piphany, Inc.)- This integrated, next-generation solution merges analytical and operational CRM capabilities to drive intelligent, effective, and personalized interactions with customers on any touch point.

eMeasure (MarketSoft)- This product measures and optimizes marketing ROI. It allows companies to track every customer communication and sales lead, close the loop with SFA and ERP systems, and measure the overall effectiveness of marketing activities.

FIND (Ardexus)- This product helps companies attract and grow a larger customer base through the creation of a sophisticated, multi-tiered Marketing Plan.

ForeSight (Advanced Software Applications)- This campaign management solution is an integrated system combining data analysis and mining with campaign process development, execution, and tracking.

Gemplus P-CRM Suite (Gemplus)- This product takes information telecom operators gather about their customers and transforms it into predictive knowledge. Then the knowledge can be leveraged through optimised and personalized customer interactions across many channels. It automates and industrializes the P-CRM business process enterprise-wide, from data refresh and analyses, to predictive modelling, campaign design and optimisation, campaign launch and reporting.

GoldMine (FrontRange Solutions Inc.)- This product's tools manage the facets of prospect/client information. It blends Internet functionality, opportunity management, day and time scheduling, telemarketing scripting, mail/fax merge, sales management and reporting/analysis to effectively manage any team.

Intrinsic7 (Intrinsic)- This product, together with Expertise, allow users to target, measure, and report against many different media campaigns.

Leads Management (Peregrine Systems, Inc.)- Remedy Leads Management software is a comprehensive contact and opportunity management system that automates telesales and marketing processes to shorten the sales cycle, increase sales productivity, and increase the success of marketing programs.

MarketFirst (MarketFirst)- This company is one of the industry leaders in interactive marketing automation and direct response. It is available in both a license format as well as a hosted model.

Marketic One (Marketic)- This product enables the optimization of marketing automation throughout the company (Central/Network marketing campaigns). Profitability is increased by sending the right message to the right customer at the right time through the right channel.

MyMarketingMachine (Zoomio, Inc.)- A hosted marketing automation platform that enables companies to build and execute multi-channel marketing campaigns that are completely trackable – combining email, telemarketing, the Web, wireless and off-line tools.

OpenBOX Marketing Campaign Management (OpenBOX Technologies)- Web-based solution that fully automates and monitors and measures ROI of multi-stage, multi-channel campaigns.

Prime@Vantage (PrimeResponse)- This product suite is for sophisticated campaigns that span all traditional and e-marketing channels to increase response rates and ensure the best-possible customer experience. This automated, business-to-consumer marketing solution integrates your customer communications across all traditional marketing channels (direct mail, call center and advertising).

Propulsion (Propulsion)- This company is a 2 year old ASP for Campaign Management services. Their service consists of an ASP Campaign Management platform and c0-management for "push" campaigns. They are based in Europe.

Protagona Ensemble (Protagona Worldwide)- This integrated marketing solution is a suite of software products that empowers clients worldwide to execute effective marketing campaigns across all channels-including the Web, call centers, direct sales, and traditional direct marketing.

SpinnakerPro (Narragansett Technologies, Inc.)- This product is a Campaign Management tool built on Microsoft .NET. It offers full HTML design, a central content manager, analytics, web page and microsite creation functionality.

Talisma Campaign (Talisma Corporation)- This product enables marketing professionals to generate targeted customer lists, dynamically personalize the messages in either HTML or Plain Text, and scale to millions of e-mail messages a day.

Xchange Dialogue (Xchange Applications)- This product is a marketing automation suite that manages, delivers and measures on-line and off-line campaigns, centrally and locally.

YellowBrick Experience Manager (YellowBrick Solutions)- This product is a comprehensive marketing automation solution that facilitates data analysis, segmentation, and profiling; multi-channel campaign planning and execution; and campaign analytics.

Customer Segmetation: Definitions and Concepts

2006-05-26T10:10:00.000-07:00

What Does Customer Segmentation Mean?
Very broadly, the goal of customer segmentation is to know your customers better, and to use that knowledge to enhance corporate profitability. Effective segmentation drives revenue growth through increased ability to meet customers' demands. Segmentation's greatest impact is on the top line, growing the number of customers, the amount of sales per customer, and the lifetime value of the customer. But it can also have a hand in the cost side, in aligning costs -- to more economically serve each customer segment. In short, segmentation impacts customer profitability, which impacts corporate profitability. Companies paying attention to customer segmentation are reaping rewards.

Customer Segmentation is the subdivision of a market into discrete customer groups that share similar characteristics. Customer Segmentation can be a powerful means to identify unmet customer needs. Companies that identify underserved segments can then outperform the competition by developing uniquely appealing products and services. Customer Segmentation is most effective when a company tailors offerings to segments that are the most profitable and serves them with distinct competitive advantages. This prioritization can help companies develop marketing campaigns and pricing strategies to extract maximum value from both high- and low-profit customers. A company can use Customer Segmentation as the principal basis for allocating resources to product development, marketing, service and delivery programs.

Customer segmentation is the practice of dividing a customer base into groups of individuals that are similar in specific ways relevant to marketing, such as age, gender, interests, spending habits, and so on. Using segmentation allows companies to target groups effectively, and allocate marketing resources to best effect. According to an article by Jill Griffin for Cisco Systems, traditional segmentation focuses on identifying customer groups based on demographics and attributes such as attitude and psychological profiles. Value-based segmentation, on the other hand, looks at groups of customers in terms of the revenue they generate and the costs of establishing and maintaining relationships with them. Customer segmentation procedures include: deciding what data will be collected and how it will be gathered; collecting data and integrating data from various sources; developing methods of data analysis for segmentation; establishing effective communication among relevant business units (such as marketing and customer service) about the segmentation; and implementing applications to effectively deal with the data and respond to the information it provides.

Methodology

Customer Segmentation requires managers to:

Divide the market into meaningful and measurable segments according to customers’ needs, their past behaviors or their demographic profiles;
Determine the profit potential of each segment by analyzing the revenue and cost impacts of serving each segment;
Target segments according to their profit potential and the company’s ability to serve them in a proprietary way;
Invest resources to tailor product, service, marketing and distribution programs to match the needs of each target segment;
Measure performance of each segment and adjust the segmentation approach over time as market conditions change decision making throughout the organization.

Common Uses

Companies can use Customer Segmentation to:

Prioritize new product development efforts;
Develop customized marketing programs;
Choose specific product features;
Establish appropriate service options;
Design an optimal distribution strategy;
Determine appropriate product pricing.

Analysis

Companies in general are embracing the benefits of segmentation. It is both insightful and exciting to see the quantitative and qualitative benefits companies are realizing from actively pursuing multidimensional, dynamic segmentation: double- digit million dollar revenue growth, 30 to 50 percent increases in customer asset retention, shifts of organizational structures to segment alignment, and expansions and changes to corporate strategy, to name a few.¹

As you can imagine, there are opportunities for companies to learn from these results and to improve not only marketing performance (customer acquisition, retention, migration to higher value) but also to make knowing the customer a way of life in their organizations -- using segmentation across functions and levels for multiple purposes. Paying attention to time-based characteristics, appending attitudes to understand why customers buy, and actively watching how customers change over time are opportunities not fully being taken advantage of by all companies today.

Interestingly, despite all the latest advances in technology, sophisticated algorithms and customer relationship management (CRM) capabilities available to companies, segmentation still requires thorough business analysis and interpretation to be truly viable and have impact. A focus on the key building blocks of segmentation -- segment characteristics, time and profitability -- will bode well for any company embarking on or improving upon segmentation.

However, exactly which segment characteristics are most relevant -- and when -- must be figured out by each company. Common methods for determining this are sophisticated means such as factor analysis and statistical models, as well as tried-and-true, trial-and-error methods. Segmentation choice is based on a host of drivers, including purpose of segmentation (for example, strategic versus tactical, company-wide versus initiative-based, one-on-one versus portfolio level), type of product versus service, and company and industry specifications.

In the following pages, we evaluate how successful companies are not only using segmentation to better reach profitable customers, but also how they are making segmentation a way of life in their companies, weaving it into all areas of the organization to improve business performance, top line and bottom line. As a result of this, opportunities have been identified which virtually all companies can apply and from which they have the potential to derive benefits.

Customer Segmentation utilizing Canonical Discriminant Analysis

2006-05-22T13:40:00.000-07:00

There are several different methods that can be applied to customer segmentation. Canonical Analysis is yet another way of tackling this task.

Canonical Correlation is an additional procedure for assessing the relationship between variables. Specifically, this analysis allows us to investigate the relationship between two sets of variables. For example, an educational researcher may want to compute the (simultaneous) relationship between three measures of scholastic ability with five measures of success in school. A sociologist may want to investigate the relationship between two predictors of social mobility based on interviews, with actual subsequent social mobility as measured by four different indicators. A medical researcher may want to study the relationship of various risk factors to the development of a group of symptoms. In all of these cases, the researcher is interested in the relationship between two sets of variables, and Canonical Correlation would be the appropriate method of analysis.

Computational Methods and Results

Some of the computational issues involved in canonical correlation and the major results that are commonly reported will now be reviewed.

Eigenvalues. When extracting the canonical roots, you will compute the eigenvalues. These can be interpreted as the proportion of variance accounted for by the correlation between the respective canonical variates. Note that the proportion here is computed relative to the variance of the canonical variates, that is, of the weighted sum scores of the two sets of variables; the eigenvalues do not tell how much variability is explained in either set of variables. You will compute as many eigenvalues as there are canonical roots, that is, as many as the minimum number of variables in either of the two sets.

Successive eigenvalues will be of smaller and smaller size. First, compute the weights that maximize the correlation of the two sum scores. After this first root has been extracted, you will find the weights that produce the second largest correlation between sum scores, subject to the constraint that the next set of sum scores does not correlate with the previous one, and so on.

Canonical correlations. If the square root of the eigenvalues is taken, then the resulting numbers can be interpreted as correlation coefficients. Because the correlations pertain to the canonical variates, they are called canonical correlations. Like the eigenvalues, the correlations between successively extracted canonical variates are smaller and smaller. Therefore, as an overall index of the canonical correlation between two sets of variables, it is customary to report the largest correlation, that is, the one for the first root. However, the other canonical variates can also be correlated in a meaningful and interpretable manner (see below).

Significance of Roots. The significance test of the canonical correlations is straightforward in principle. Simply stated, the different canonical correlations are tested, one by one, beginning with the largest one. Only those roots that are statistically significant are then retained for subsequent interpretation. Actually, the nature of the significance test is somewhat different. First, evaluate the significance of all roots combined, then of the roots remaining after removing the first root, the second root, etc.

Some authors have criticized this sequential testing procedure for the significance of canonical roots (e.g., Harris, 1976). However, this procedure was "rehabilitated" in a subsequent Monte Carlo study by Mendoza, Markos, and Gonter (1978).

In short, the results of that study showed that this testing procedure will detect strong canonical correlations most of the time, even with samples of relatively small size (e.g., n = 50). Weaker canonical correlations (e.g., R = .3) require larger sample sizes (n > 200) to be detected at least 50% of the time. Note that canonical correlations of small magnitude are often of little practical value, as they account for very little actual variability in the data. This issue, as well as the sample size issue, will be discussed shortly.

Canonical weights. After determining the number of significant canonical roots, the question arises as to how to interpret each (significant) root. Remember that each root actually represents two weighted sums, one for each set of variables. One way to interpret the "meaning" of each canonical root would be to look at the weights for each set. These weights are called the canonical weights .

In general, the larger the weight (i.e., the absolute value of the weight), the greater is the respective variable's unique positive or negative contribution to the sum. To facilitate comparisons between weights, the canonical weights are usually reported for the standardized variables, that is, for the z transformed variables with a mean of 0 and a standard deviation of 1.

If you are familiar with multiple regression, you may interpret the canonical weights in the same manner as you would interpret the beta weights in a multiple regression equation. In a sense, they represent the partial correlations of the variables with the respective canonical root. If you are familiar with factor analysis, you may interpret the canonical weights in the same manner as you would interpret the factor score coefficients. To summarize, the canonical weights allow the user to understand the "make-up" of each canonical root, that is, it lets the user see how each variable in each set uniquely contributes to the respective weighted sum (canonical variate).

Canonical Scores. Canonical weights can also be used to compute actual values of the canonical variates; that is, you can simply use the weights to compute the respective sums. Again, remember that the canonical weights are customarily reported for the standardized (z transformed) variables.

Factor structure. Another way of interpreting the canonical roots is to look at the simple correlations between the canonical variates (or factors) and the variables in each set. These correlations are also called canonical factor loadings. The logic here is that variables that are highly correlated with a canonical variate have more in common with it. Therefore, you should weigh them more heavily when deriving a meaningful interpretation of the respective canonical variate. This method of interpreting canonical variates is identical to the manner in which factors are interpreted in factor analysis.

Factor structure versus canonical weights. Sometimes, the canonical weights for a variable are nearly zero, but the respective loading for the variable is very high. The opposite pattern of results may also occur. At first, such a finding may seem contradictory; however, remember that the canonical weights pertain to the unique contribution of each variable, while the canonical factor loadings represent simple overall correlations. For example, suppose you included in your satisfaction survey two items which measured basically the same thing, namely: (1) "Are you satisfied with your supervisors?" and (2) "Are you satisfied with your bosses?" Obviously, these items are very redundant. When the program computes the weights for the weighted sums (canonical variates) in each set so that they correlate maximally, it only "needs" to include one of the items to capture the essence of what they measure. Once a large weight is assigned to the first item, the contribution of the second item is redundant; consequently, it will receive a zero or negligibly small canonical weight. Nevertheless, if you then look at the simple correlations between the respective sum score with the two items (i.e., the factor loadings), those may be substantial for both. To reiterate, the canonical weights pertain to the unique contributions of the respective variables with a particular weighted sum or canonical variate; the canonical factor loadings pertain to the overall correlation of the respective variables with the canonical variate.

Variance extracted. As discussed earlier, the canonical correlation coefficient refers to the correlation between the weighted sums of the two sets of variables. It tells nothing about how much variability (variance) each canonical root explains in the variables. However, you can infer the proportion of variance extracted from each set of variables by a particular root by looking at the canonical factor loadings. Remember that those loadings represent correlations between the canonical variates and the variables in the respective set. If you square those correlations, the resulting numbers reflect the proportion of variance accounted for in each variable. For each root, you can take the average of those proportions across variables to get an indication of how much variability is explained, on the average, by the respective canonical variate in that set of variables. Put another way, you can compute in this manner the average proportion of variance extracted by each root.

Redundancy. The canonical correlations can be squared to compute the proportion of variance shared by the sum scores (canonical variates) in each set. If you multiply this proportion by the proportion of variance extracted, you arrive at a measure of redundancy, that is, of how redundant one set of variables is, given the other set of variables. In equation form, you may express the redundancy as:

Redundancy_left = [(loadings_left²)/p]*R_c²
Redundancy_right = [(loadings_right²)/q]*R_c²

In these equations, p denotes the number of variables in the first (left) set of variables, and q denotes the number of variables in the second (right) set of variables; R_c² is the respective squared canonical correlation.

Note that you can compute the redundancy of the first (left) set of variables given the second (right) set, and the redundancy of the second (right) set of variables, given the first (left) set. Because successively extracted canonical roots are uncorrelated, you could sum up the redundancies across all (or only the first significant) roots to arrive at a single index of redundancy (as proposed by Stewart and Love, 1968).

Practical significance. The measure of redundancy is also useful for assessing the practical significance of canonical roots. With large sample sizes (see below), canonical correlations of magnitude R = .30 may become statistically significant (see above). If you square this coefficient (R-square = .09) and use it in the redundancy formula shown above, it becomes clear that such canonical roots account for only very little variability in the variables. Of course, the final assessment of what does and does not constitute a finding of practical significance is subjective by nature. However, to maintain a realistic appraisal of how much actual variance (in the variables) is accounted for by a canonical root, it is important to always keep in mind the redundancy measure, that is, how much of the actual variability in one set of variables is explained by the other.

Assumptions

The following discussion provides only a list of the most important assumptions of canonical correlation analysis, and the major threats to the reliability and validity of results. Distributions. The tests of significance of the canonical correlations is based on the assumption that the distributions of the variables in the population (from which the sample was drawn) are multivariate normal. Little is known about the effects of violations of the multivariate normality assumption. However, with a sufficiently large sample size (see below) the results from canonical correlation analysis are usually quite robust.

Sample sizes. Stevens (1986) provides a very thorough discussion of the sample sizes that should be used in order to obtain reliable results. As mentioned earlier, if there are strong canonical correlations in the data (e.g., R > .7), then even relatively small samples (e.g., n = 50) will detect them most of the time. However, in order to arrive at reliable estimates of the canonical factor loadings (for interpretation), Stevens recommends that there should be at least 20 times as many cases as variables in the analysis, if one wants to interpret the most significant canonical root only. To arrive at reliable estimates for two canonical roots, Barcikowski and Stevens (1975) recommend, based on a Monte Carlo study, to include 40 to 60 times as many cases as variables.

Outliers. Outliers can greatly affect the magnitudes of correlation coefficients. Since canonical correlation analysis is based on (computed from) correlation coefficients, they can also seriously affect the canonical correlations. Of course, the larger the sample size, the smaller is the impact of one or two outliers. However, it is a good idea to examine various scatterplots to detect possible outliers (as shown in the example animation below).

Market Basket Analysis

2006-05-18T19:08:00.000-07:00

What is Market Basket Analysis?

Market Basket Analysis is a modelling technique based upon the theory that if you buy a certain group of items, you are more (or less) likely to buy another group of items. It is also often defined as: an algorithm that examines a long list of transactions in order to determine which items are most frequently purchased together.

As you may have already guessed its name comes from the idea of a person in a supermarket throwing all of their items into a shopping cart (or a "market basket"). The results can be useful to any company that sells products, whether it's in a store, a catalog, or directly to the customer.

Significant increases in cross-sell revenues can be achieved by using knowledge of customer purchasing habits such as:

Which product combinations are bought
When they are purchased; and in
What sequence

Developing this understanding enables businesses to promote their most profitable products and encourage customers to buy items that might have otherwise been overlooked or missed.

Obvious examples of this are supermarkets who store huge volumes of consumer sales, each basket being tracked by individual loyalty cards.

Microsoft CRM Gets Cisco Support

2006-05-17T12:46:00.000-07:00

Cisco recently released CRM Connector 3.0, a customer relationship management (CRM) application integrated with Microsoft Dynamics CRM 3.0 (see Screen Shot on the left).

The product is billed by Cisco officials as helping small and medium-sized businesses (SMBs) gain access to customer information on inbound and outbound calls, “increasing operational efficiency and providing an improved customer experience.”

In collaboration, the Cisco and Microsoft have developed a channel and partner self-service Website to support the delivery of combined products to small and medium-sized organizations.

The Cisco Unified CRM Connector 3.0 helps to provide a complete view of the customer, including current and past purchases, sales information, order status, account relationships, and billing information, company officials say.

When a call is received by the Cisco Unified CallManager or Cisco Unified CallManager Express, the Cisco Unified CRM Connector 3.0 links to the Microsoft Dynamics CRM system and provides onscreen pop-up windows of the customer contact record and phone call activity so that the service agent can track the call. The same information and capabilities are also accessible remotely. New customer data or phone call information is uploaded back into the system, so the next interaction picks up where the last one left off.

Features in the Cisco Unified CRM Connector 3.0 include an Internet Protocol phone service that pushes complete customer information to Cisco Unified IP phones from inbound calls that match a customer record. The IP phone lookup service allows users to view customer contact information from any Cisco XML extensible markup language display-capable Unified IP phone.
Additional features include fast and easy click-to-dial functionality for accessing CRM contact records, call-duration tracking, and detailed call-information capture.

SAS Tutorials and Resources (Online Courses)

2006-05-17T11:52:00.000-07:00

SAS Institute

Support and Services

Publications

Publications Catalog

Technical Support

Technical Notes

Frequently asked questions (searchable database)

FTP site: general download , download stats utilities and macros

SAS Tutorials by O. Schabenberger

Introduction to Data Manipulation in SAS

Some Common Tasks with The SAS System (descr. stats, hypothesis tests, etc.)

Intro to Publication Quality Graphs with The SAS System

Intro to Slicing of Interactions with PROC GLM and PROC MIXED

SAS Code for Experimental Designs (JAVA or HTML )

What To Do about Significant Interactions (Guide to Slicing)

Generating Experimental Plans in SAS

SAS Tutorials and Manuals By Others

Univ. of Wisconsin

Rice University

Cornell University

York University

Virginia Tech (SAS Intro and manual on gopher)

Thomas Jefferson University

UCF Computer Services I& R Support 03/09/94 (General SAS manuals)

SAS help (University of Michigan Consulting Center)

University of Southern California: SAS FAQ

University of Southern California: Searchable documentation database

SAS User Group gopher

SAS.Masses

SAS Internet Groups

SAS-L (monthly gopher archive of mailing list)

SAS.Masses SAS-L FAQ (frequently asked questions on the SAS-L mailing list)

SPSS Tutorials

2006-05-13T08:41:00.000-07:00

I've compiled a list of SPSS tutorial pages available on the web. They are very helpful and self explanatory and you can access them very easily. Most of these tutorials are hosted by colleges and Universities so they are pretty good and free to access. Please leave comment if you have trouble with any of these tutorials and I will fix the link, etc. Enjoy:

SPSS On-Line Training Workshop by Dr.Carl Lee, Dr Felix Famoye and Joyce Sharp from Central Michigan University. This is a very comprehensive tutorial which assumes no prior knowledge of SPSS. About 40 Quick Time movies are used to cover most SPSS topics. A fast internet connection is recommended.

Resources to Help you Learn and Use SPSS by UCLA's Academic Technology Services This is another great site to learn how to use SPSS's menus and syntax. Sections include:

Class Notes,
Learning Modules
Fundamentals of Using SPSS,
Reading Raw Data,
Basic Data Management
Intermediate Data Management
FAQ,
Textbook Examples,
Regressions with SPSS.

Statnotes: An Online Textbook

many topics

Key Concepts and Terms

Assumptions

FAQ

Bibliography

SPSS Course Content by Lee A. Becker, University of Colorado, Colorado Springs

Data Definition,
Descriptive Statistics,
Statistical notes on Scales of measurement and Confidence Intervals
Data and File transformations
Crosstabulations and Measure of Associations
Differences between two groups (t-test and NPAR test)
ANOVA: between Subjects (1-way, 2-way, 3-way, SME and unequal ns)
ANOVA: Repeated Measures (1-way, 1-way and 1-between, 2-way and 1-between

The World of Visual Statistics by Dr.David J. Kraus. This is very complete!
This site contains examples using SPSS as well as theoretical and practical information on a wide variety of statistical subjects such as:

Introduction to Matrix Algebra
Matrix Algebra Operations
Elements of Statistics in Matrix Algebra Notation
Linear Multiple Regression Analysis
Hierarchical Multiple Regression Analysis
Coded Multiple Regression Analysis
Multiple Regression within the Repeated Measures Design
Analysis of Variance Using Matrix Algebra
Analysis of Covariance
Factorial Analysis of Variance
Principal Components Analysis
Factor Analysis
Canonical Analysis
Discriminant Analysis

Psychology Statistics and Methods by Jan Frijters, University of Guelph . Do a statistics self-assesment quiz and Download assignments description and related data files in for Course 6060 and Course 6380

SPSS Tutorials by Michael Speed, Texas A&M University (requires Media Player)
Very good site covering a wide cross section of topics such as:
Installing and Using SPSS
Data Manipulation
Basic Data Analysis and Graphs
Regression Analysis (eg Constrained Regression, All Possible Subsets)
Advance Topics in Regression
Analysis of Variance

Web Analytics from Unica

2006-05-13T07:24:00.000-07:00

"Affinium NetInsight" is Unica's Web-analytics solution. It is part of the Enterprise Marketing Management (EMM) Affinium suite. According to Unica Affinium NetInsight will be available this summer (2006) either as software or as an on-demand model. The good news is it can be sold separately (or of course as a part of Unica's Affinium suite).

This is another effort by a software vendor to integrate customer data across the enterprise. In this case NetInsight, in conjunction with other Affinium suite modules, will enable marketers to integrate Web analytics with other customer level data.

This is what Unica executives said about the solution:
Marketers will be able to automate marketing based on their Web and cross-channel knowledge to "close the loop across customer touch points," says Andrew Hally, senior director of segment management at Unica. For example, Hally says marketers can automate the end-to-end process for lead generation from pay-per-click advertising to lead capture and distribution. Or, they can tie offline purchases to search engine marketing to improve measurement and incorporate Web behavior into customer segmentation and profiles for improved targeting.

As one can easily imagine this product was cased off of technology from Web-analytics provider Sane Solutions (which Unica acquired in February 2006). The new product will be using an open and scalable Web data warehouse. The open architecture will let end-users integrate NetInsight with traditional Business Intelligence applications (Business Objects, SAS, etc).

My Analysis:
There is no need to point out that the Internet is playing an increasingly vital role from a marketing perspective. It is especially influential in the decision making process. Majority of the marketers had trouble combining demographic and transactional customer data with Web based behavior level data. The main reasonto this is different types of data are usually siloed within the organization. In other words customer data should be synchronized across all channels.Any product trying to address this need has a reason to exist.

Based on the quick turn around for this product launch (literally 3 months: Unica acquired Sane Solutions in Feb. 2006 and launched the integrated product in May 2006) I am expecting upgrades from the orginial launch. As end-users get involved and start running the integrated solutions Unica should be leveraging their feedback for improved integration (and user experience) with the next versions.

SAS vs. SPSS

2006-05-12T11:09:00.000-07:00

I have tried to summarize my thoughts regarding the 2 very popular statistical computing / data mining software available in the market place. I have 10+ years of experience with both SAS and SPSS. Still I would only call myself a power user.

Please feel free to leave your comments after reading my post.
I really would love to hear your thoughts regarding this issue since I believe every user brings another perspective to the discussion.

Anyways. Below are my thoughts:

Functionality:
From a functionality percperive, there is a lot of overlap between SAS and SPSS. From a statistical point of view they should be comparable, that is, the numerical results of statistical analysis of course must be the same. They offer very similar statistical procedures.

Of course there are some exceptions. For example SAS offers PROC MIXED, which do not have an equivalent in SPSS. SPSS includes some routines aimed at things like reliability and multiple response processing which have no equivalent in SAS. In general, SAS provides better access to
specialized and multivariate procedures, with the exception of SPSS's wonderful curve fitting routine.

There is some difference in approaching specific programming problems; for example:
FORMATS vs. VALUE LABELS. Both have their advantages, and I would like SAS to support both! Because of some different and sometimes easier programming syntax (e.g. RECODE), you would have to get used to thinking somewhat differently about a problem.

Missing values (any values or range declared missing) in SPSS are interpreted as such during
data manipulations (as far as I remember correctly), while in a SAS DATA step you have to account for missing values yourself.

SAS compiles programming code before running, while SPSS doesn't. Which means SPSS is an interpreter . In my opinion SPSS runs much slower than SAS, probably because of that.

Platforms:
SPSS has copncentrated on windows over the last several years. The user interface for that version seems easier to use for those who already work in Win/NT. The version for MVS has not been updated for 8+ years. The version for UNIX is several releases behind, as well. SPSS has committed to bringing out more current versions for Unix and the Macintosh. SAS is very up to date for UNIX. I think this is their strongest platform.

SAS has more programming power in its base language. SPSS for windows provides a powerful, and unrelaated, scripting language. SAS can be used across platforms (Connect & Share).
I do not think SPSS can provide this. SAS seems to have better data base connectivity. Both offer warehousing products. The product from SAS is award winning.

Company Profile: Unica

2006-04-21T11:43:00.000-07:00

One of the things we would like to do on this blog is to provide information on important solution providers in the marketing and technology world. Our first article is featuring Unica, a provider of "Enterprise Marketing Management (EMM) solutions".

First things first; Unica is a public company - had their IPO in the second half of 2005. There's plenty of financial information (regarding Unica) available in Google Finance and Yahoo Finance. There's also some information available on Forbes.com.

Unica -like many other technology companies in the Massachusetts area- is a MIT start-up. All three founders of the company have their roots at this educational institution:

Yuchun Lee, Co-Founder and CEO (only active founder in senior management), holds Bachelors and Masters degrees in Electrical Engineering and Computer Science from MIT. He also worked at MIT's Lincoln and Media Labs.

Ruby Kennedy, holds BS and MS degrees in Computer Science from MIT and is co-author of Solving Data Mining Problems Through Pattern Recognition, (Prentice-Hall, 1995-1997).

David Cheung, holds a BS degree in Electrical Engineering from MIT and is the core software architect of Unica's Affinium.

According to Gartner; Unica (together with SAS and Teradata) is a leading vendor in campaign management (as listed in Magic Quadrant for Multichannel Campaign Management).

Post Siebel Sweep: What's Oracle Up To?

2006-04-19T09:00:00.000-07:00

On January 31st (of 2006) Oracle Corp. Announced "the completion of its acquisition of Siebel Systems, Inc.". This was an important event for the marketing software industry. Specifically for the Customer Relationship Management software vertical.

Larry Ellison (the CEO of Oracle said this meant "... Undisputed leader(ship) in Customer Relationship Management software". Further elaborated:

"Oracle's focus on modern, standards-based applications and middleware is moving us into a leadership position in applications and on-demand services. Siebel accelerates that move..... Siebel's expertise with industry-specific customer-facing applications combined with rich analytics will not only serve as the centerpiece of our CRM strategy for Oracle Fusion Applications, but can also be used to extend our current customers investments today..."

So what does it all mean? It actually has implications at many different levels. It has implications at the end-user level. It has implications at the organizational level - not to mention the ones in the world of marketers and IT professionals. But most important, this acquisition has implications on the competitive landscape of marketing software. Here are my thoughts:

1) Oracle is extending it's monopoly status vertically. They are not happy to run the show only in one single piece of the software world (meaning data storage environments). They would like to grow vertically but want areas that they can cross-sell their core competencies to.

2) Siebel was in a very competitive space. New comers like Unica have started threatening Siebel for a while now. From a 'shareholder' perspective; I believe this was the right-time to cash in. Nothing wrong with that.

3) It's a mystery to me how the organizational cultures will crash (or have already started crashing). It's always hard when you have a take-over like this; especially for the company that's being taken over (Siebel in this case). Wall Street likes to see improved financials (which usually translates to "reduction-in-force" - not healthy for the company culture).

4) The end-users may be happy to get one integrated solution for their CRM needs - that's if Oracle manages to integrate platforms properly (knowing Oracle - they probably will be successful). There's no way of telling what's going to happen in the long term.

I will continue posting about this topic in the future.

What Does Data Mining Mean?

2006-03-13T09:09:00.000-08:00

Data Mining can be defined as "The nontrivial extraction of implicit, previously unknown, and potentially useful information from data" and "The science of extracting useful information from large data sets or databases". Although it is usually used in relation to analysis of data, data mining, like artificial intelligence, is an umbrella term and is used with varied meaning in a wide range of contexts. It is usually associated with a business or other organization's need to identify trends. Data mining involves the process of analysing data to show patterns or relationships Sorting through large amounts of data and picking out pieces of relative information or patterns that occur E.g. picking out statistical information from some data

A simple example of data mining is its use in a retail sales department. If a store tracks the purchases of a customer and notices that a customer buys a lot of silk shirts, the data mining system will make a correlation between that customer and silk shirts. The sales department will look at that information and may begin direct mail marketing of silk shirts to that customer, or it may alternatively attempt to get the customer to buy a wider range of products. In this case, the data mining system used by the retail store discovered new information about the customer that was previously unknown to the company. Another widely used (though hypothetical) example is that of a very large North American chain of supermarkets. Through intensive analysis of the transactions and the goods bought over a period of time, analysts found that beers and diapers were often bought together. Though explaining this interrelation might be difficult, taking advantage of it, on the other hand, should not be hard (e.g. placing the high-profit diapers next to the high-profit beers). This technique is often referred to as Market Basket Analysis.

In statistical analyses, in which there is no underlying theoretical model, data mining is often approximated via stepwise regression methods wherein the space of 2^k possible relationships between a single outcome variable and k potential explanatory variables is smartly searched. With the advent of parallel computing, it became possible (when k is less than approximately 40) to examine all 2^k models. This procedure is called all subsets or exhaustive regression. Some of the first applications of exhaustive regression involved the study of plant data.

Essential Marketing Information

2006-03-12T11:48:00.000-08:00

Journals and Conferences:

AMA Home Page JM and JMR past tables of contents and searches.
AMA Conferences An updated conference listing
Marketing Research On-Line An on-line journal for publishing marketing research.

Links to marketing departments at universities:
List of B-Schools Servers - via Dartmouth U. (Links to all business schools)
Institute for the Study of Business Markets - Penn State University
Tilburg University - Links to web sites of interest to marketing academics
Marketing Science Centre, University of South Australia. An R&D resource for marketing.

Links to companies, business offers, and marketing efforts:
MouseTracks - Marketing Resource Center
NerdWorld Commercial Marketing Site Internet advertising and marketing resources.

Marketing research information sources:
U.S. Department of Commerce - National Trade DataBase
Patent Information- Patent searches, classifications, laws, and more.
The Federal Government - The White House, Agencies and more (via the University of Michigan)
AMA Home Page - Conferences, Journal Info, etc.

Marketing teaching tools:
Harvard Publishing - Order cases, books, etc. on-line.
The Syllabus Center
Syllabus for an interactive WWW Marketing Course

Links to Marketing Specializations:
General Marketing
Consumer-Packaged Goods
Global Business Management
High Tech Marketing
Market-based Consulting

Bookmark the Marketing and Technology Blog

2006-01-29T13:40:00.000-08:00