Enterprise Decision Management - a Weblog

(By guest Blogger, Gib Bassett)

The title of this post includes a quote from the film, “The Wizard of Oz,” when Dorothy’s dog Toto draws back a curtain revealing the “real” wizard (a man) pulling levers and pushing buttons to illuminate a frightening hologram of a smoky and not too nice false wizard. The jig is up, and the wizard is exposed for what he is, just a man. If only the same could be said of the experts driving data mining and predictive analytic software in today’s leading companies.

While not exactly wizards in the Harry Potter sense, many of these folks have advanced degrees in statistics and mathematics, and thus are able to help their employers comb through mountains of data to identify actionable insights for improving business performance. For executives, it may as well be smoke in mirrors, such is often the complexity of these analyses.

Some software vendors would have you believe otherwise, but in reality the tools which enable predictive analysis are most often designed for an analyst first, to make him or her more productive. There has yet to be a software application into which you can speak, “give me a list of the customers I should retain over the next 12 months to optimize my profit given x, y and z” that doesn’t require a “wizard” of sorts performing the analysis in the background for you. And there may never be.

Having said (or written) that, it’s easy to understand the conclusions reached by Stephen Swoyer in his November 7 column on The Data Warehousing Institute (TDWI) website titled, “Predictive Analytics: Slow Adoption Despite Big Benefits.” Swoyer observes that adoption of traditional rearward looking BI has been much stronger than predictive analytics � not surprising when one considers a traditional BI solution is architected with a defined target database that is fed information from a consistent source, and from which reports and other analysis are generated. The “mystery” of data collection and storage has largely become a repeatable science, yet data preparation remains the single largest time and money component in data mining (predictive analysis) projects. The reason this remains the case is because it typically takes someone with a good deal of analytical talent to identify and massage source data such that meaningful predictive analysis can occur; it is as much art as it is science.

Further recent evidence of this can be found in the FinTech 100 report from American Banker and Financial Insights magazines. This annual ranking of top vendors serving the financial services industry includes an article titled, “Software Playing Catch-Up with the Promise of Data Analytics,” by Jeanne Capachin, a research vp with Financial Insights. Capachin observes that “Many of the big failed CRM projects of the late 1990s and the early part of this decade were failures as the analytic solutions were put ahead of strong information management.” She uses “information management” to broadly apply to both data warehouses at one extreme and source data for predictive analytics/data mining at the other, but in both cases the implication is there is little turnkey about predictive analytic software. Yet despite these hurdles, ” ...almost 80% of the institutions surveyed plan to increase spending on business intelligence and analytic applications over the next 12 months” -- so attractive are the benefits reported by successful companies.

Capachin’s conclusions parallel those in my upcoming December 3 DM Review article, “Decision Services: Pragmatic Real-Time Analytics.” What you can infer from Capachin’s comment is that early CRM solutions were not just immature, but over hyped with respect to their analytical components. While these have improved, gains have been made mostly in the tools used by expert users. Decision Services are an SOA (Services Oriented Architecture) concept designed to encapsulate the rules and/or models to be executed by operational systems and therefore offer a foundation for predictive analytics, at a pace appropriate for an organization given its business, technical and analytical maturity.

For example, before moving to predict and act upon customer behavior via interaction channels like your website or call center, does it not first make sense to automate the decisions you must now take with your customers via these channels? For example, the things you know to be self evident, such as whether or not you wish to grant a loan to someone with a given credit score? Or a particular pattern of fraud that has been flagged for investigation repeatedly? Capturing and automating decisions such as these with a solution grounded in Enterprise Decision Management (EDM) principles sets the stage for successful deployment of predictive analytics, at a time when an organization is ready.

Which next raises the issue of where to begin, an important adoption issue Swoyer’s article points out via a quote by TDWI Director of Research Wayne Eckerson:

Most (business managers) have only a vague notion about the business areas or applications that can benefit from predictive analytics, he writes. [M]ost don’t know how to get started: whom to hire, how to organize the product, or how to architect the environment.

Decision Yield is a methodology which pulls back the curtain of a company’s operations, identifying the decisions most likely to benefit from an EDM solution. The result can serve as a map of sorts toward reaping the benefits of predictive analytics, and it doesn’t take a degree in wizardry to understand.

(Posted by guest blogger, James Taylor)

One of the most fun things writing this blog over the last 2 years has been watching the growing number of subscribers. Today I see we are over 1,000 for the first time. A real milestone. Thank you all for reading.

Now all I need to do is get the Smart (Enough) Systems Blog(RSS) to do the same....

Visit my Smart (Enough) Systems Blog(RSS) or my ebizQ blog (RSS). Buy the bookor visit the companion wiki.

(Posted by guest blogger, James Taylor)

One of the most common reasons for discussing enterprise decision management, and one of the most common ways in which people want to make their systems smarter, is in personalizing them. Making a system respond in a reasonable yet personal way to a consumer or other customer is widely, and correctly, seen as a way to bring better service to bear in a scalable way. When I saw this post on Personalization…New buzzwords, same business value I was reminded of this fact. The post started by reiterating that personalization has come up before and had its moments of popularity. It also pointed out some synonyms that have become popular like "behavioral targeting, precision marketing, and micro segmentation". So what is it that has made personalization come around again and why might this time be the charm?

The post identifies a number of reasons. Firstly there are now "practical ways to implement and manage dynamic sites that 'personalize' the experience, segment their sites and improve the quality of their recommendations". This comes in two areas. The sites themselves are more dynamic and more likely to be built dynamically from content stored in a content management systems. It is much easier to inject personalization into the decision as to what content to retrieve and display if the content is being assembled dynamically than if the page is fundamentally a static one. The technology for making the personalization work has also improved. Business rules management systems are more scalable and easier to integrate, SOA means that many more technologies can be easily made to "play nice" and the sophistication of analytic models has improved so that the actual analysis of data results in better rules and predictions as to what a customer or prospect might want.

It is also true, as the post notes, that "business tools that give marketing managers and merchandisers the ability to easily define online segments, tag content (products, reviews, articles, etc.) and create rules to fully-automate real-time intelligent targeting". This ability to bring business users more fully into the picture by giving them viable control over the rules being used by the personalization is key. While there are some difficulties to be overcome, the ability of the business to be and feel in control really matters. Marketers don't like to give up control to a black-box, so giving them control helps with adoption and, while analytics are very powerful, many personalization decisions remain judgmental until data can be collected making it important to engage the experts.

Like the post I think that there is a also a general trend to people liking personalization more. They are more comfortable with personalized offers and responses. Inpart this is thanks to marketers asking them questions - what are their preferences, what are they interested in and so on -and in part it is simply a comfort level arising from growing use of self-service and web-based systems. Balancing offers with questions to elicit more information is what is known as "Best Next Action" where a decision as to the right action for this customer is taken and then the resulting question or offer or action is delivered through the customers choice of channel. Personalization in this context feels more likely to deliver value and so is more tolerated by the customer.

In the end personalization must deliver value not simply more junk mail. As companies figure out how to do this, customers are responding. Adopting enterprise decision management to automate and improve your customer treatment decisions by, among other things, personalizing them is the most effective way to do this. Not only does it separate decision making from the channel, ensuring cross-channel consistency, it also mixes analytic insight with business control for maximum results. Add in adaptive control to constantly challenge your approach and try new ways to personalize and you should be set. For more on this check out these other posts I have written on the topic:

• Using decision management to take marketing to the next level
• Personalization, targeting, segmentation, customer states
• Personalization (again)
• 1:1 communication with scale
• Secrets of business user rule maintenance
• Best Next Action

Visit my Smart (Enough) Systems Blog(RSS) or my ebizQ blog (RSS). Buy the bookor visit the companion wiki.

Technorati Tags: 1:1, analytics, business rules, EDM, enterprise decision management, marketing, personalization, predictive analytics, segmentation, adaptive control

(Posted by guest blogger, James Taylor)

One of the most common reasons for discussing enterprise decision management, and one of the most common ways in which people want to make their systems smarter, is in personalizing them. Making a system respond in a reasonable yet personal way to a consumer or other customer is widely, and correctly, seen as a way to bring better service to bear in a scalable way. When I saw this post on Personalization…New buzzwords, same business value I was reminded of this fact. The post started by reiterating that personalization has come up before and had its moments of popularity. It also pointed out some synonyms that have become popular like "behavioral targeting, precision marketing, and micro segmentation". So what is it that has made personalization come around again and why might this time be the charm?

The post identifies a number of reasons. Firstly there are now "practical ways to implement and manage dynamic sites that 'personalize' the experience, segment their sites and improve the quality of their recommendations". This comes in two areas. The sites themselves are more dynamic and more likely to be built dynamically from content stored in a content management systems. It is much easier to inject personalization into the decision as to what content to retrieve and display if the content is being assembled dynamically than if the page is fundamentally a static one. The technology for making the personalization work has also improved. Business rules management systems are more scalable and easier to integrate, SOA means that many more technologies can be easily made to "play nice" and the sophistication of analytic models has improved so that the actual analysis of data results in better rules and predictions as to what a customer or prospect might want.

It is also true, as the post notes, that "business tools that give marketing managers and merchandisers the ability to easily define online segments, tag content (products, reviews, articles, etc.) and create rules to fully-automate real-time intelligent targeting". This ability to bring business users more fully into the picture by giving them viable control over the rules being used by the personalization is key. While there are some difficulties to be overcome, the ability of the business to be and feel in control really matters. Marketers don't like to give up control to a black-box, so giving them control helps with adoption and, while analytics are very powerful, many personalization decisions remain judgmental until data can be collected making it important to engage the experts.

Like the post I think that there is a also a general trend to people liking personalization more. They are more comfortable with personalized offers and responses. Inpart this is thanks to marketers asking them questions - what are their preferences, what are they interested in and so on -and in part it is simply a comfort level arising from growing use of self-service and web-based systems. Balancing offers with questions to elicit more information is what is known as "Best Next Action" where a decision as to the right action for this customer is taken and then the resulting question or offer or action is delivered through the customers choice of channel. Personalization in this context feels more likely to deliver value and so is more tolerated by the customer.

In the end personalization must deliver value not simply more junk mail. As companies figure out how to do this, customers are responding. Adopting enterprise decision management to automate and improve your customer treatment decisions by, among other things, personalizing them is the most effective way to do this. Not only does it separate decision making from the channel, ensuring cross-channel consistency, it also mixes analytic insight with business control for maximum results. Add in adaptive control to constantly challenge your approach and try new ways to personalize and you should be set. For more on this check out these other posts I have written on the topic:

• Using decision management to take marketing to the next level
• Personalization, targeting, segmentation, customer states
• Personalization (again)
• 1:1 communication with scale
• Secrets of business user rule maintenance
• Best Next Action

Visit my Smart (Enough) Systems Blog(RSS) or my ebizQ blog (RSS). Buy the bookor visit the companion wiki.

Technorati Tags: 1:1, analytics, business rules, EDM, enterprise decision management, marketing, personalization, predictive analytics, segmentation, adaptive control

(Posted by guest blogger, James Taylor)

One of the most common reasons for discussing enterprise decision management, and one of the most common ways in which people want to make their systems smarter, is in personalizing them. Making a system respond in a reasonable yet personal way to a consumer or other customer is widely, and correctly, seen as a way to bring better service to bear in a scalable way. When I saw this post on Personalization…New buzzwords, same business value I was reminded of this fact. The post started by reiterating that personalization has come up before and had its moments of popularity. It also pointed out some synonyms that have become popular like "behavioral targeting, precision marketing, and micro segmentation". So what is it that has made personalization come around again and why might this time be the charm?

The post identifies a number of reasons. Firstly there are now "practical ways to implement and manage dynamic sites that 'personalize' the experience, segment their sites and improve the quality of their recommendations". This comes in two areas. The sites themselves are more dynamic and more likely to be built dynamically from content stored in a content management systems. It is much easier to inject personalization into the decision as to what content to retrieve and display if the content is being assembled dynamically than if the page is fundamentally a static one. The technology for making the personalization work has also improved. Business rules management systems are more scalable and easier to integrate, SOA means that many more technologies can be easily made to "play nice" and the sophistication of analytic models has improved so that the actual analysis of data results in better rules and predictions as to what a customer or prospect might want.

It is also true, as the post notes, that "business tools that give marketing managers and merchandisers the ability to easily define online segments, tag content (products, reviews, articles, etc.) and create rules to fully-automate real-time intelligent targeting". This ability to bring business users more fully into the picture by giving them viable control over the rules being used by the personalization is key. While there are some difficulties to be overcome, the ability of the business to be and feel in control really matters. Marketers don't like to give up control to a black-box, so giving them control helps with adoption and, while analytics are very powerful, many personalization decisions remain judgmental until data can be collected making it important to engage the experts.

Like the post I think that there is a also a general trend to people liking personalization more. They are more comfortable with personalized offers and responses. Inpart this is thanks to marketers asking them questions - what are their preferences, what are they interested in and so on -and in part it is simply a comfort level arising from growing use of self-service and web-based systems. Balancing offers with questions to elicit more information is what is known as "Best Next Action" where a decision as to the right action for this customer is taken and then the resulting question or offer or action is delivered through the customers choice of channel. Personalization in this context feels more likely to deliver value and so is more tolerated by the customer.

In the end personalization must deliver value not simply more junk mail. As companies figure out how to do this, customers are responding. Adopting enterprise decision management to automate and improve your customer treatment decisions by, among other things, personalizing them is the most effective way to do this. Not only does it separate decision making from the channel, ensuring cross-channel consistency, it also mixes analytic insight with business control for maximum results. Add in adaptive control to constantly challenge your approach and try new ways to personalize and you should be set. For more on this check out these other posts I have written on the topic:

• Using decision management to take marketing to the next level
• Personalization, targeting, segmentation, customer states
• Personalization (again)
• 1:1 communication with scale
• Secrets of business user rule maintenance
• Best Next Action

Visit my Smart (Enough) Systems Blog(RSS) or my ebizQ blog (RSS). Buy the bookor visit the companion wiki.

Technorati Tags: 1:1, analytics, business rules, EDM, enterprise decision management, marketing, personalization, predictive analytics, segmentation, adaptive control

(Posted by guest blogger, James Taylor)

One of the most common reasons for discussing enterprise decision management, and one of the most common ways in which people want to make their systems smarter, is in personalizing them. Making a system respond in a reasonable yet personal way to a consumer or other customer is widely, and correctly, seen as a way to bring better service to bear in a scalable way. When I saw this post on Personalization…New buzzwords, same business value I was reminded of this fact. The post started by reiterating that personalization has come up before and had its moments of popularity. It also pointed out some synonyms that have become popular like "behavioral targeting, precision marketing, and micro segmentation". So what is it that has made personalization come around again and why might this time be the charm?

The post identifies a number of reasons. Firstly there are now "practical ways to implement and manage dynamic sites that 'personalize' the experience, segment their sites and improve the quality of their recommendations". This comes in two areas. The sites themselves are more dynamic and more likely to be built dynamically from content stored in a content management systems. It is much easier to inject personalization into the decision as to what content to retrieve and display if the content is being assembled dynamically than if the page is fundamentally a static one. The technology for making the personalization work has also improved. Business rules management systems are more scalable and easier to integrate, SOA means that many more technologies can be easily made to "play nice" and the sophistication of analytic models has improved so that the actual analysis of data results in better rules and predictions as to what a customer or prospect might want.

It is also true, as the post notes, that "business tools that give marketing managers and merchandisers the ability to easily define online segments, tag content (products, reviews, articles, etc.) and create rules to fully-automate real-time intelligent targeting". This ability to bring business users more fully into the picture by giving them viable control over the rules being used by the personalization is key. While there are some difficulties to be overcome, the ability of the business to be and feel in control really matters. Marketers don't like to give up control to a black-box, so giving them control helps with adoption and, while analytics are very powerful, many personalization decisions remain judgmental until data can be collected making it important to engage the experts.

Like the post I think that there is a also a general trend to people liking personalization more. They are more comfortable with personalized offers and responses. Inpart this is thanks to marketers asking them questions - what are their preferences, what are they interested in and so on -and in part it is simply a comfort level arising from growing use of self-service and web-based systems. Balancing offers with questions to elicit more information is what is known as "Best Next Action" where a decision as to the right action for this customer is taken and then the resulting question or offer or action is delivered through the customers choice of channel. Personalization in this context feels more likely to deliver value and so is more tolerated by the customer.

In the end personalization must deliver value not simply more junk mail. As companies figure out how to do this, customers are responding. Adopting enterprise decision management to automate and improve your customer treatment decisions by, among other things, personalizing them is the most effective way to do this. Not only does it separate decision making from the channel, ensuring cross-channel consistency, it also mixes analytic insight with business control for maximum results. Add in adaptive control to constantly challenge your approach and try new ways to personalize and you should be set. For more on this check out these other posts I have written on the topic:

• Using decision management to take marketing to the next level
• Personalization, targeting, segmentation, customer states
• Personalization (again)
• 1:1 communication with scale
• Secrets of business user rule maintenance
• Best Next Action

Visit my Smart (Enough) Systems Blog(RSS) or my ebizQ blog (RSS). Buy the bookor visit the companion wiki.

Technorati Tags: 1:1, analytics, business rules, EDM, enterprise decision management, marketing, personalization, predictive analytics, segmentation, adaptive control

(Posted by guest blogger, James Taylor)

One of the most common reasons for discussing enterprise decision management, and one of the most common ways in which people want to make their systems smarter, is in personalizing them. Making a system respond in a reasonable yet personal way to a consumer or other customer is widely, and correctly, seen as a way to bring better service to bear in a scalable way. When I saw this post on Personalization…New buzzwords, same business value I was reminded of this fact. The post started by reiterating that personalization has come up before and had its moments of popularity. It also pointed out some synonyms that have become popular like "behavioral targeting, precision marketing, and micro segmentation". So what is it that has made personalization come around again and why might this time be the charm?

The post identifies a number of reasons. Firstly there are now "practical ways to implement and manage dynamic sites that 'personalize' the experience, segment their sites and improve the quality of their recommendations". This comes in two areas. The sites themselves are more dynamic and more likely to be built dynamically from content stored in a content management systems. It is much easier to inject personalization into the decision as to what content to retrieve and display if the content is being assembled dynamically than if the page is fundamentally a static one. The technology for making the personalization work has also improved. Business rules management systems are more scalable and easier to integrate, SOA means that many more technologies can be easily made to "play nice" and the sophistication of analytic models has improved so that the actual analysis of data results in better rules and predictions as to what a customer or prospect might want.

It is also true, as the post notes, that "business tools that give marketing managers and merchandisers the ability to easily define online segments, tag content (products, reviews, articles, etc.) and create rules to fully-automate real-time intelligent targeting". This ability to bring business users more fully into the picture by giving them viable control over the rules being used by the personalization is key. While there are some difficulties to be overcome, the ability of the business to be and feel in control really matters. Marketers don't like to give up control to a black-box, so giving them control helps with adoption and, while analytics are very powerful, many personalization decisions remain judgmental until data can be collected making it important to engage the experts.

Like the post I think that there is a also a general trend to people liking personalization more. They are more comfortable with personalized offers and responses. Inpart this is thanks to marketers asking them questions - what are their preferences, what are they interested in and so on -and in part it is simply a comfort level arising from growing use of self-service and web-based systems. Balancing offers with questions to elicit more information is what is known as "Best Next Action" where a decision as to the right action for this customer is taken and then the resulting question or offer or action is delivered through the customers choice of channel. Personalization in this context feels more likely to deliver value and so is more tolerated by the customer.

In the end personalization must deliver value not simply more junk mail. As companies figure out how to do this, customers are responding. Adopting enterprise decision management to automate and improve your customer treatment decisions by, among other things, personalizing them is the most effective way to do this. Not only does it separate decision making from the channel, ensuring cross-channel consistency, it also mixes analytic insight with business control for maximum results. Add in adaptive control to constantly challenge your approach and try new ways to personalize and you should be set. For more on this check out these other posts I have written on the topic:

• Using decision management to take marketing to the next level
• Personalization, targeting, segmentation, customer states
• Personalization (again)
• 1:1 communication with scale
• Secrets of business user rule maintenance
• Best Next Action

Visit my Smart (Enough) Systems Blog(RSS) or my ebizQ blog (RSS). Buy the bookor visit the companion wiki.

Technorati Tags: 1:1, analytics, business rules, EDM, enterprise decision management, marketing, personalization, predictive analytics, segmentation, adaptive control

(Posted by guest blogger, James Taylor)

One of the most common reasons for discussing enterprise decision management, and one of the most common ways in which people want to make their systems smarter, is in personalizing them. Making a system respond in a reasonable yet personal way to a consumer or other customer is widely, and correctly, seen as a way to bring better service to bear in a scalable way. When I saw this post on Personalization…New buzzwords, same business value I was reminded of this fact. The post started by reiterating that personalization has come up before and had its moments of popularity. It also pointed out some synonyms that have become popular like "behavioral targeting, precision marketing, and micro segmentation". So what is it that has made personalization come around again and why might this time be the charm?

The post identifies a number of reasons. Firstly there are now "practical ways to implement and manage dynamic sites that 'personalize' the experience, segment their sites and improve the quality of their recommendations". This comes in two areas. The sites themselves are more dynamic and more likely to be built dynamically from content stored in a content management systems. It is much easier to inject personalization into the decision as to what content to retrieve and display if the content is being assembled dynamically than if the page is fundamentally a static one. The technology for making the personalization work has also improved. Business rules management systems are more scalable and easier to integrate, SOA means that many more technologies can be easily made to "play nice" and the sophistication of analytic models has improved so that the actual analysis of data results in better rules and predictions as to what a customer or prospect might want.

It is also true, as the post notes, that "business tools that give marketing managers and merchandisers the ability to easily define online segments, tag content (products, reviews, articles, etc.) and create rules to fully-automate real-time intelligent targeting". This ability to bring business users more fully into the picture by giving them viable control over the rules being used by the personalization is key. While there are some difficulties to be overcome, the ability of the business to be and feel in control really matters. Marketers don't like to give up control to a black-box, so giving them control helps with adoption and, while analytics are very powerful, many personalization decisions remain judgmental until data can be collected making it important to engage the experts.

Like the post I think that there is a also a general trend to people liking personalization more. They are more comfortable with personalized offers and responses. Inpart this is thanks to marketers asking them questions - what are their preferences, what are they interested in and so on -and in part it is simply a comfort level arising from growing use of self-service and web-based systems. Balancing offers with questions to elicit more information is what is known as "Best Next Action" where a decision as to the right action for this customer is taken and then the resulting question or offer or action is delivered through the customers choice of channel. Personalization in this context feels more likely to deliver value and so is more tolerated by the customer.

In the end personalization must deliver value not simply more junk mail. As companies figure out how to do this, customers are responding. Adopting enterprise decision management to automate and improve your customer treatment decisions by, among other things, personalizing them is the most effective way to do this. Not only does it separate decision making from the channel, ensuring cross-channel consistency, it also mixes analytic insight with business control for maximum results. Add in adaptive control to constantly challenge your approach and try new ways to personalize and you should be set. For more on this check out these other posts I have written on the topic:

• Using decision management to take marketing to the next level
• Personalization, targeting, segmentation, customer states
• Personalization (again)
• 1:1 communication with scale
• Secrets of business user rule maintenance
• Best Next Action

Visit my Smart (Enough) Systems Blog(RSS) or my ebizQ blog (RSS). Buy the bookor visit the companion wiki.

Technorati Tags: 1:1, analytics, business rules, EDM, enterprise decision management, marketing, personalization, predictive analytics, segmentation, adaptive control

(Posted by guest blogger, James Taylor)

One of the most common reasons for discussing enterprise decision management, and one of the most common ways in which people want to make their systems smarter, is in personalizing them. Making a system respond in a reasonable yet personal way to a consumer or other customer is widely, and correctly, seen as a way to bring better service to bear in a scalable way. When I saw this post on Personalization…New buzzwords, same business value I was reminded of this fact. The post started by reiterating that personalization has come up before and had its moments of popularity. It also pointed out some synonyms that have become popular like "behavioral targeting, precision marketing, and micro segmentation". So what is it that has made personalization come around again and why might this time be the charm?

The post identifies a number of reasons. Firstly there are now "practical ways to implement and manage dynamic sites that 'personalize' the experience, segment their sites and improve the quality of their recommendations". This comes in two areas. The sites themselves are more dynamic and more likely to be built dynamically from content stored in a content management systems. It is much easier to inject personalization into the decision as to what content to retrieve and display if the content is being assembled dynamically than if the page is fundamentally a static one. The technology for making the personalization work has also improved. Business rules management systems are more scalable and easier to integrate, SOA means that many more technologies can be easily made to "play nice" and the sophistication of analytic models has improved so that the actual analysis of data results in better rules and predictions as to what a customer or prospect might want.

It is also true, as the post notes, that "business tools that give marketing managers and merchandisers the ability to easily define online segments, tag content (products, reviews, articles, etc.) and create rules to fully-automate real-time intelligent targeting". This ability to bring business users more fully into the picture by giving them viable control over the rules being used by the personalization is key. While there are some difficulties to be overcome, the ability of the business to be and feel in control really matters. Marketers don't like to give up control to a black-box, so giving them control helps with adoption and, while analytics are very powerful, many personalization decisions remain judgmental until data can be collected making it important to engage the experts.

Like the post I think that there is a also a general trend to people liking personalization more. They are more comfortable with personalized offers and responses. Inpart this is thanks to marketers asking them questions - what are their preferences, what are they interested in and so on -and in part it is simply a comfort level arising from growing use of self-service and web-based systems. Balancing offers with questions to elicit more information is what is known as "Best Next Action" where a decision as to the right action for this customer is taken and then the resulting question or offer or action is delivered through the customers choice of channel. Personalization in this context feels more likely to deliver value and so is more tolerated by the customer.

In the end personalization must deliver value not simply more junk mail. As companies figure out how to do this, customers are responding. Adopting enterprise decision management to automate and improve your customer treatment decisions by, among other things, personalizing them is the most effective way to do this. Not only does it separate decision making from the channel, ensuring cross-channel consistency, it also mixes analytic insight with business control for maximum results. Add in adaptive control to constantly challenge your approach and try new ways to personalize and you should be set. For more on this check out these other posts I have written on the topic:

• Using decision management to take marketing to the next level
• Personalization, targeting, segmentation, customer states
• Personalization (again)
• 1:1 communication with scale
• Secrets of business user rule maintenance
• Best Next Action

Visit my Smart (Enough) Systems Blog(RSS) or my ebizQ blog (RSS). Buy the bookor visit the companion wiki.

Technorati Tags: 1:1, analytics, business rules, EDM, enterprise decision management, marketing, personalization, predictive analytics, segmentation, adaptive control

(Posted by guest blogger, James Taylor)

One of the most common reasons for discussing enterprise decision management, and one of the most common ways in which people want to make their systems smarter, is in personalizing them. Making a system respond in a reasonable yet personal way to a consumer or other customer is widely, and correctly, seen as a way to bring better service to bear in a scalable way. When I saw this post on Personalization…New buzzwords, same business value I was reminded of this fact. The post started by reiterating that personalization has come up before and had its moments of popularity. It also pointed out some synonyms that have become popular like "behavioral targeting, precision marketing, and micro segmentation". So what is it that has made personalization come around again and why might this time be the charm?

The post identifies a number of reasons. Firstly there are now "practical ways to implement and manage dynamic sites that 'personalize' the experience, segment their sites and improve the quality of their recommendations". This comes in two areas. The sites themselves are more dynamic and more likely to be built dynamically from content stored in a content management systems. It is much easier to inject personalization into the decision as to what content to retrieve and display if the content is being assembled dynamically than if the page is fundamentally a static one. The technology for making the personalization work has also improved. Business rules management systems are more scalable and easier to integrate, SOA means that many more technologies can be easily made to "play nice" and the sophistication of analytic models has improved so that the actual analysis of data results in better rules and predictions as to what a customer or prospect might want.

It is also true, as the post notes, that "business tools that give marketing managers and merchandisers the ability to easily define online segments, tag content (products, reviews, articles, etc.) and create rules to fully-automate real-time intelligent targeting". This ability to bring business users more fully into the picture by giving them viable control over the rules being used by the personalization is key. While there are some difficulties to be overcome, the ability of the business to be and feel in control really matters. Marketers don't like to give up control to a black-box, so giving them control helps with adoption and, while analytics are very powerful, many personalization decisions remain judgmental until data can be collected making it important to engage the experts.

Like the post I think that there is a also a general trend to people liking personalization more. They are more comfortable with personalized offers and responses. Inpart this is thanks to marketers asking them questions - what are their preferences, what are they interested in and so on -and in part it is simply a comfort level arising from growing use of self-service and web-based systems. Balancing offers with questions to elicit more information is what is known as "Best Next Action" where a decision as to the right action for this customer is taken and then the resulting question or offer or action is delivered through the customers choice of channel. Personalization in this context feels more likely to deliver value and so is more tolerated by the customer.

In the end personalization must deliver value not simply more junk mail. As companies figure out how to do this, customers are responding. Adopting enterprise decision management to automate and improve your customer treatment decisions by, among other things, personalizing them is the most effective way to do this. Not only does it separate decision making from the channel, ensuring cross-channel consistency, it also mixes analytic insight with business control for maximum results. Add in adaptive control to constantly challenge your approach and try new ways to personalize and you should be set. For more on this check out these other posts I have written on the topic:

• Using decision management to take marketing to the next level
• Personalization, targeting, segmentation, customer states
• Personalization (again)
• 1:1 communication with scale
• Secrets of business user rule maintenance
• Best Next Action

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