CRM in MARKETING

Making Customer Relationship Management Work  Published: July 04, 2001 in (Audio & Text)

Making Customer Relationship Management Work
Published: July 04, 2001 in Knowledge@Wharton
 

Go to a neighborhood restaurant every single Saturday night and spend big and you’ll get the deluxe treatment. You’ll be greeted by name, led to a good table right away and served a drink or two on the house. But if you take to demanding items not on the menu, sending plates back to the kitchen and arguing about the check, you’ll soon be lucky to get a glass of water -- at your
table by the restrooms.

Smart business owners quickly learn that the biggest profits can come from a small group of free-spending, easy-to-satisfy patrons, and that cheapskates who tie up the staff should not be
encouraged to return. But how can this knowledge be adapted to a big corporation that offers thousands of products to millions of customers who can come into contact with the company in
many different ways – in person, by phone or on the Internet?

To hear some proponents talk about it, all a company needs is to buy and install a Customer Relationship Management system, a sophisticated approach to tailoring service to individual customers – and to gathering valuable data at the same time. CRM has boomed over the past five years, thanks to computers and the Internet, and many experts expect sales of multi-million dollar CRM systems to soar at rates of 30% or more each year.

"Everybody is scrambling to integrate all their customer contact points," says Wharton marketing
professor George S. Day. At this early stage, much of the effort has gone into computers and related equipment, though many companies adopting the technology aren’t yet clear about what their systems will really have to do to build enduring and profitable relationshiphips with customers, he says.

"At their base, these are big, integrated infrastructure systems," says Noah F. Gans, a professor of operations and information management at Wharton. "They will collect data on every single customer action, anywhere that a customer might come into contact with the company… In each of these channels they will have some sort of hardware and software that is going to, at some level, manage the process of employees of the company interacting with the customers."

A recent report by Jupiter Media Metrix, the New York Internet tracking company, says 74% of the businesses polled expected to spend more on CRM equipment and software this year than they did in 2000, with most boosting spending 25% to 50%. Jupiter says this reflects a growing realization that, especially in a less-robust economy, it is cheaper to keep existing customers happy than to attract new ones.

While CRM can undoubtedly be valuable, says Peter S. Fader, a marketing professor at Wharton, it is also something of a fad. "Everyone is sort of flocking to it but not necessarily getting anything out of it," he notes. Many companies, he predicts, will fail to make the cultural and organizational changes needed to make CRM work, or will use the resulting data unwisely. Distinguishing profitable customers from unprofitable ones seems appealing, for instance, but it can be counterproductive if the company uses the knowledge to drive away small customers who might have become big ones in the future.

"Focusing too closely at the individual level is a mistake," Fader says. The trick, which not many companies have yet mastered, "is to find the right level of aggregation" – to categorize customers in groups that are neither too big nor too small.

A large corporation may spend tens of millions of dollars on a CRM system. Among the big CRM suppliers are Oracle, Siebel Systems and IBM, and dozens of other companies specialize in components such as telephone call center technology, database software and Internet systems. Because the whole idea is to customize each system to a specific company’s needs, there is no universal definition of CRM, which has both business-to-business and business-to-consumer applications.
 

Call your local bank about your checking account and you may discover the person on the phone is looking at a screen that summarizes your previous calls and displays information about your mortgage and credit card as well. That’s CRM. Log on to Amazon.com and you may find a personalized list of suggested books that have appealed to readers with buying habits like yours. CRM again.

Currently, the financial services industry has the best CRM efforts, with companies like Capital One, Fidelity and Vanguard Group among the best examples, Day says. Lands’ End and many other catalogue companies also are among the best CRM implementers, since data mining has long been at the heart of their business, adds Fader. Traditional bricks-and-mortar retailers are less successful, since they have little tradition of gathering information during customer transactions, he says.

Generally, CRM is seen as a system for funneling to one place information that otherwise would be dispersed in a big company, where one hand may not know what the other 10 hands are doing. This means collecting information from phone centers and Internet sites, from contacts by sales people or the customers’ visits to various retail and wholesale operations – from any "touch-point."
 

Ideally, the information is analyzed to gain insight into each customer’s needs and behavior, and then it is used to improve the customer’s dealings with the company. This can be as simple as freeing the customer from having to repeat his mailing address every time he places an order, to something like being able to instantly tell the customer the status of a shipment. The analysis might guide sales efforts, so that the customer receives mailings, calls, e-mails or Website advertising tailored to his likes.
 

Using the data collected during the customer’s various contacts, the company "will try to make
inferences about what you want," Gans says. The bank that holds your mortgage and checking account may learn at some point that you have children and may then try to sell you a college savings product.
 

Customers are also analyzed in aggregate to get a clearer picture of the market for the company’s products or services. The most profitable customers may receive first class treatment, while others ride coach. As a preferred customer, you may quickly get a human being when you phone, while the less-desired customer must wrestle with a phone tree.

A bank customer with only $100 on deposit who habitually phones during the bank employee’s busiest time, might be deemed too costly, Gans says. But the same customer making just as many calls during slow hours might be worth keeping. A good CRM system can differentiate between the two, but only if it has data on employees’ workloads and the cost of providing various services.

Gans is looking at how companies can use CRM to allocate resources such as Internet servers. If a company has a mixture of fast and slow servers, it would be best to route preferred customers to the fast ones, since there’s more value in keeping these people satisfied, he points out.

For a company to implement a CRM program successfully, it must have more than hardware and
software – it must have a corporate culture that emphasizes customer satisfaction, Day explains.
Typically, a successful company searches for the long-term value in each customer rather than simply tallying one-time transactions, he says.

A company installing a CRM system must have the capability of collecting and pulling together vast amounts of information about its customers and their transactions. Many companies find this the most difficult part of the program, he says. Sales people, for instance, have traditionally guarded their turf, refusing to share information on customers they have cultivated.

Finally, successful companies must have organizational structures and incentive plans that serve the CRM effort rather than undermining it. Pay and bonuses, for example, should be tied to customer satisfaction rather than mere sales quotas, Day says. The company must have a way of measuring customer satisfaction. That can be done directly with surveys, or indirectly with proxy measures, such as the rate of on-time deliveries. "If your incentives are really oriented toward retaining customers as opposed to capturing them, then you have a very different culture," Day points out.

Among the toughest challenges for companies turning to CRM is figuring how customers will change over time, says Fader. A company may invest heavily in satisfying a big, profitable customer, but other factors could cause the customer’s needs to change and his purchases to decline nonetheless.
 

Many companies, he cautions, are embracing the idea of "firing customers", or getting rid of the least profitable ones. But typically, most customers are only marginally profitable at any one time. Yet they provide the pool from which the most profitable customers emerge, though often only temporarily. Shrinking the pool can rob the company of future business.
 

Fader is also concerned that many companies install CRM systems and think that’s it. But to make them work, the systems require constant tinkering and experimentation. "Most companies are not experimenting on a systematic basis," he says.
 

For any company, the goal is to have a CRM system that makes customers feel the service is better than the competitors,’ Day says. As many companies become aware of this, installing CRM systems becomes something of an arms race. "The technology is diffusing pretty rapidly," he says. "It’s getting a lot easier to move data around. And yet, what I foresee is that a very few companies will gain an advantage from it. The rest will get stuck in the Red Queen syndrome – you run faster and faster just to stay in place."

Winning the Competition for Customer Relationships By Professor George Day

 
The market-driven approach that characterizes relationship leaders gives them an advantage that is difficult to copy. Their rivals will have to think long and hard about whether to also strive for leadership. But at a minimum they need to avoid being at a disadvantage. Meanwhile the leaders can’t relax; they need to understand why they are ahead, and how to stay ahead. (Please see Winning the Competition for Customer Relationships By Professor George Day  Our Server

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Advanced Marketing Automation
Maximize returns on customer communication strategies
through intelligent, integrated marketing processes

Table of Contents

Executive summary ....................................................................................................... 1
Marketing challenges of the new millennium ............................................................. 2
The evolution to unified marketing automation ......................................................... 4
Four phases of intelligence-based marketing automation........................................ 6
The critical importance of a cross-functional framework ......................................... 7
The technology enablers of fourth-generation marketing automation.................... 9
     Enterprise architecture ................................................................................................. 9
     Industry-leading analytics........................................................................................... 10
     Capabilities that give more control to business users................................................ 11
     The ability to extend into other areas of marketing.................................................... 12
          Event-driven marketing in real time, at the right time............................................. 12
          Mathematical, constraint-based marketing optimization ........................................ 13
Summary....................................................................................................................... 14

Executive summary
How can you consistently beat your profitability goals — and your competitors? On the surface,
it’s not that complicated. Just understand your customers better and faster than anyone else, and use that knowledge to target them more effectively than anyone else.

If only it were that simple. Unfortunately, while information about customers is plentiful, actionable
customer intelligence often remains elusive. Customer data pours in from every conceivable
channel. Assembling a coherent picture of customers from all those puzzle pieces — a picture on which you can confidently build a profitable marketing strategy — can be a formidable challenge.

To tackle this challenge, many companies are turning to marketing automation for improved
efficiency and effectiveness of marketing activities. These companies often find, however, that this technology isn’t sophisticated enough to operate at the speed of business today.

To provide a comprehensive solution for current marketing challenges, marketing automation
solutions must offer three key functions:

• Campaign and customer analysis. A comprehensive marketing automation solution
provides quantitative tools to analyze customers and prospects and to help marketers
craft the right offers. Advanced systems also provide statistical analysis and predictive
modeling to tightly define target markets, forecast campaign effectiveness and
continuously improve through “closed-loop” marketing, in which the system self-learns
from information gleaned from prior campaigns.

• Campaign management. At the heart of any marketing automation solution is the
capability to effectively automate essential campaign processes, including managing all
communication with customers across multiple channels, tracking responses, and
consolidating and reporting results.

• Centralized management and control of disparate systems. These campaign
analysis and automation functions can draw on a customer-centric data warehouse that
pulls customer data from all appropriate back office systems, channels and third-party
data. Advanced marketing automation systems should also allow business users to
incorporate data mapped from other existing sources into the campaign planning and
executing process. These capabilities support a customer-oriented, cross-functional view
needed for creating truly effective campaigns. In addition, the solution should provide
centralized management of existing application systems, to ensure that IT resources can
support marketing as efficiently as possible.
 

The most advanced generation of marketing automation technology seamlessly combines these
functions to produce a centralized, fully integrated environment for total marketing performance.
Marketers can leverage the breadth of this functionality to maximize campaign returns through the essential phases of a disciplined marketing process: plan, target, act and learn.

Marketing challenges of the new millennium
In the days of the community general store, shopkeepers enjoyed a very favorable offer-to response ratio because they knew their customers personally. They could tailor their offerings to
create the most compelling offer at the right price, at the right time. They could also consider
complementary purchases, based on the shopkeeper’s personal knowledge of a customer’s
likelihood to need and buy.

That customer-centric view became logistically unfeasible or impossible in the era of global mass marketing and particularly difficult for marketers who reach customers through remote channels.

Nonetheless, customers still expect to be treated personally, immediately and consistently. With
the proliferation of choices made possible by remote and online marketing techniques (catalog,
direct mail, Web, etc.), customers are more empowered and less loyal than ever. If their
expectations are not met, they can click to the competitor with ease, or place a toll-free call to the marketer whose new catalog arrived in their mailbox this week.

This scenario alludes to some emerging marketing challenges:

• Proliferation of customer touch points. Years ago, marketers interacted with
customers primarily through three channels: call centers, direct mail and face-to-face.
Today, even small to mid-sized retailers reach customers through dozens of channels: email,
fax, pagers, Internet, trade shows, value-added resellers, distributors and more.
 

How can marketers gather a consistent view of the customer that crosses all those diverse touch points, while still personalizing the view of each individual customer?

• Heightened expectations for marketing campaigns. It’s not uncommon for Fortune
500 companies to plan as many as 3,000 campaigns in a single year, clearly a significant
endeavor. Even the largest companies can’t afford to paper the world with their glossy
catalogs if they’re not reaching prospects likely to buy. Nor can they afford to send direct
mail to huge, undifferentiated databases. The frequency and turnaround of campaigns is
higher than ever, and so is the expectation for return on investment.

How can marketers be sure they’re accurately targeting the right audience with the right offer at the right time?

• Lack of cross-functional cooperation. The marketing process is shaped by different
groups of users with widely differing requirements. Narrow technology that focuses on
only a few small pieces of campaign implementation makes it extremely difficult for key
players on the marketing team — including business analysts, database marketers,
quantitative analysts and IT— to effectively leverage each other’s contributions and
collaborate on a comprehensive, repeatable marketing process.

How can you implement a technology framework that supports the entire marketing team and the entire process, from setting strategy, to targeting opportunities, implementing customer communication initiatives and measuring results?

• Rapid growth in organizational data. Discrete enterprise systems churn out gigabytes
of data about customers and campaigns — both online and offline — yet few enterprises  are in a position to assemble that information into a coherent picture that can support informed, intelligent decision making. Intuition still guides many marketing decisions in an environment that really calls for a structured, predictive framework of rigorous analysis.

How can marketers access, consolidate and clean all available customer data to create a
comprehensive foundation for deriving the best customer intelligence?

• New regulatory challenges. Antispam legislation, the Do-Not-Call Registry and other
regulatory initiatives are forcing marketing departments to rethink their communication strategies. Blind delivery of unsolicited offers is now illegal in many cases, making it more important than ever to implement a reliable method for controlling customer contacts.

How can you consistently enforce a customer contact policy and ensure that different business units aren’t sending multiple or conflicting offers to the same customers?

• The need to respond more quickly and effectively to customer behavior. The interaction between business and customer is best understood as a two-way communication. Customers often don’t communicate with vendors directly, however. Instead they respond to offers through various behaviors: purchasing a new product immediately or failing to purchase anything for a period of time. Even when a customer purchases a different type of product than usual, that behavior can be a significant input to use when evaluating future interactions with that customer.

How can companies most effectively keep up with the listening (event-driven) end of the customer dialogue and translate that information into more profitable, timely customer interactions?

• Resource constraints that limit possibilities. Even with the volume of campaigns that large companies run in a given year, the reality is that marketing resources are not unlimited. Every marketer knows the pressure of budget constraints, but how do channel constraints, such as call center capacity or revenue goals affect the offers that a company presents to its customers?

How can a marketing organization determine the best possible set of offers to present, to which customers, within the bounds of resource constraints, available offers and marketing goals?

With increased customer expectations and demand for an exact fit to requirements, it is
increasingly important to not only provide accurate insights about the customer, but to put that
information within reach of all contributors to the marketing process.

The evolution to unified marketing automation

Marketers recognized long ago that they could leverage computer technology to face these
challenges and do a better job with marketing campaigns.

In the 1960s, computers kicked mass marketing into high gear with zip-code segmentation,
merging and purging of files, computer-generated letters and direct marketing techniques. In the
1970s, statisticians began applying analytical applications such as list testing and further
segmentation. The 1980s brought improved database marketing with targeted campaigns driven
by population analytics and relational databases. The 1990s heralded the era of relationship
marketing (also called one-to-one marketing) based on the premise that customer relationships
can be formed and profits increased by delivering information and products based on individual
needs.

In four decades, then, we have witnessed a shift from mass marketing — push as much product
as possible to the world — to a targeted customer focus — identify unique customer niches and
cater to their needs.

Marketing automation systems are struggling to make the corresponding transition. As the
discipline of marketing has evolved, the implementation of marketing automation has evolved
through several distinct generations.

The first generation of marketing automation, originating in the 1960s but not seeing
widespread acceptance until the late 1980s and early ‘90s, leveraged computer technology to
automate the operational marketing tasks mentioned above. These products enabled marketers
to segment, target and reach customers more efficiently.

This generation of operational point solutions, usually based on proprietary databases and
standalone systems, improved the effectiveness of simple campaigns with turnaround times of
several months.

The second generation of marketing automation took a more holistic, cross-functional focus,
considering campaign management in context with overall business processes. Software
solutions shifted from proprietary databases to open systems, with emphasis on scalability,
enhanced automation of product-oriented campaign processes for efficiency and more timely
reporting.

This generation of cross-functional solutions reduced the marketing department’s reliance on IT,
supported faster campaign turnaround cycles and made progress in integrating sales and service channels across all touch points. First- and second-generation marketing automation systems predominate today, even as the changing marketplace demands more than these task-oriented systems can provide.

The third generation of marketing automation takes data integration a step further and:

• Supports a customer-centric view that provides a consistent, coherent view of the
customer across multiple touch points.

• Integrates sales force automation, call center systems and electronic channels.

• Feeds campaign performance results back into the system to support continuously
improving, closed-loop marketing.

The fourth generation of marketing automation is the critical underpinning for today’s
merchandising environment, with higher expectations, pressure for faster turnaround at lower
costs and narrower windows of opportunity. This most advanced generation of marketing
automation solution:

• Introduces advanced analytics to turn business data into customer intelligence, at the
right time.

• Provides powerful capabilities to serve the diverse needs of all marketing team members
in the most appropriate way, from business users to quantitative analysts to IT.

• Optimizes each customer contact by tailoring promotions and contact channels to best
suit the customer’s expectations.

• Enables more opportunistic marketing than ever by responding to triggers that indicate a
change in a customer’s state, as derived by demographics or analytics. Did the customer
just move to a different climate? Purchase baby items for the first time? Make a
purchase without add-on options? Buy two items that indicate a potential need for a
third?
• Is built on a platform that enables centralized data management and security, as well as
the exchange of information between applications. This centralized control smoothes the
way for IT to incorporate current and future intelligence applications into the company’s
IT infrastructure.

Investments in fourth generation marketing automation solutions that can create in-depth
customer intelligence pay off for marketers by:

• Restoring the personal-service value that remote channels and mass marketing
removed.

• Fostering greater long-term loyalty through relationship building.

• Maximizing lifetime value of each customer through cross-selling and up-selling.

• Increasing the rate of return on marketing initiatives by targeting the right customer with
the right message, at the right time and via the right media.

Four phases of intelligence-based marketing automation

Given that large organizations commonly plan hundreds or thousands of different campaigns in a
single year, marketers have to maximize and optimize their performance results at every stage of the process. Systematic and profitable marketing incorporates four key phases:

• Plan the most effective marketing campaign offers and strategies.

• Target campaign activities to tightly defined market segments with high propensities
to buy.

• Act on those plans with automated campaign management tools, such as modules to
pull lists, generate customized e-mail and direct mail materials, and track results.

• Learn from campaign experience by measuring campaign results and automatically
feeding that intelligence back into the system to fine tune future campaigns.

Fourth-generation marketing automation addresses each stage of the marketing process, while
recognizing that all stages are interdependent and involve the contributions of many different
types of contributors.

The payoff from investments in advanced marketing automation is significant — shorter marketing cycle times, better odds of getting your message out to customers ahead of the competition, cost savings realized by replacing scattershot campaigns with truly targeted ones and rising return on investment as the results of each campaign are immediately applied to the next.

The critical importance of a cross-functional framework

The Plan-Target-Act-Learn marketing process relies on input and participation from at least five
very different user groups:

• Executive management who focus on strategy and performance.

• Business analysts who understand customers and plan communication strategies.

• Campaign managers who construct complex, multistage, analytics-based campaigns.

• Quantitative analysts who build marketing models and perform sophisticated data
analysis.

• IT professionals who develop and maintain the marketing automation infrastructure.

Each user group has its specific needs for software functions and interfaces. For example,
executives might require a customizable, overarching interface allowing them to view specific
reports or drill down into more specific functionality when the need arises. Quantitative analysts
might prefer the ability to delve behind the scenes to manage intricacies of modeling processes
rather than just picking and choosing from a predefined model. IT professionals are closely
focused on the integrity and accessibility of marketing data.

The reporting requirements of each group will also vary tremendously — from strategic-level
budgets and plans for executives, to summary and detail views of campaign activities and results for business users to information about metadata manipulations and import/export functions for IT professionals.

The following chart  highlights some of these interdependencies in a typical marketing
organization. The dilemma for marketers is that typical marketing automation systems have not
offered a “one size fits all” proposition that recognizes this interdependent framework.

Fourth-generation marketing automation addresses this critical issue by rallying all users under
one unified system that provides the user-to-system and system-to-system interfaces — along
with tools and functions — appropriate to each of their needs. Executives can manage all
marketing activities from a single dashboard. Quantitative analysts can take advantage of the
database marketer’s interface to create custom models and reports and fine tune parameters of
system performance. IT professionals have tools and reporting capabilities that give them control over how data elements are captured, validated, stored, accessed and updated — as well as how the end-to-end infrastructure should perform.

The technology enablers of fourth-generation marketing
automation

The essential stages of marketing automation described earlier — plan, target, act and learn —
demand more than first- and second-generation software solutions can provide. Third-generation
solutions start to fill critical gaps by automating functions across multiple business units and
customer contact channels, and by providing some self-learning capability. Fourth-generation
solutions, such as SAS Marketing Automation, integrate powerful campaign management
functionality with:

• An enterprise architecture that provides centralized control and management of application systems and can pull data from virtually any source to meet intelligence and performance requirements within the current IT environment.

• Industry-leading analytics to derive and apply true customer intelligence.

• Capabilities that give more control to business users while supporting cross functional
collaboration.

• The ability to extend into other areas of marketing, such as real-time, event-driven marketing and mathematical marketing optimization.

________________________________________________________________
Enterprise architecture

The need for companies to embrace a customer-centric vision has been well documented in
recent years. From an organizational standpoint, this means aligning sales and service behaviors around customer relationships instead of around specific organizational structures or products.

In a marketing automation solution based in customer intelligence, companies integrate customer information from across the entire organization, as well as from partners and other external sources, to develop one comprehensive view of customer behavior. Only with a unified view can you accurately identify and differentiate customer needs, define marketing campaigns based on those needs and thereby maximize return on investment from marketing initiatives.

SAS Marketing Automation includes a data warehouse that provides a panoramic view of the
customer and includes legacy data, transaction data and preference information. This data
warehouse assembles the customer view spanning all touch points and systems. Business data
and key operational metrics from diverse departments are aligned, shared and integrated in a
common repository. Information about customers, which may currently exist in various databases across the enterprise, is combined and made compatible to support meaningful analysis.

As part of its global metadata approach, SAS Marketing Automation also allows companies to
translate warehouse and data structures into business terms, allowing business users to query
data without assistance from IT. This capability ensures the consistency of reports and
information by capturing business rules that can be used across departments and by establishing allowable usage information.

Companies need centralized control of application systems to help IT support marketing more
efficiently. With so many application systems spread throughout the company, IT is often bogged down by ad hoc requests. Centralized management helps reduce that demand by making information systems more efficient and productive.

At the center of SAS Marketing Automation is an enterprise platform that allows companies to
meet intelligence and performance requirements within the current IT environment by providing a
central point of control for disparate application systems. This means that the same marketing
automation applications can be deployed with no modification across various back-end systems
throughout the organization. And IT users who are not SAS experts have the ability to easily
administer the SAS environment.

The architecture of SAS Marketing Automation allows for:

• Full use of hardware throughout the organization, ensuring maximum performance and
efficiency of marketing automation applications.

• A reduced need for specialized developers and system knowledge, which frees
developers for more important tasks.

• Intelligence software that meets both IT and business needs by delivering full support for
open standards in application development.

____________________________________________________________________

Industry-leading analytics

To increase the rate of return on marketing campaigns, marketing strategies must be based on an accurate and comprehensive understanding of customers across all functional areas and contact channels. The model of campaign management based on customer intelligence calls for creating intelligent campaigns that are tightly targeted to the highest-value customers, for the most relevant opportunity, through the most effective channel, at the most appropriate time.

In many marketing organizations, the business analyst — the person usually held accountable for the success or failure of a marketing campaign — faces significant obstacles in focusing analytic efforts on the right questions and effectively integrating analytic results into marketing processes. SAS Marketing Automation breaks down these barriers by empowering business analysts — with or without statistical backgrounds — to surface the results of in-depth analyses and behavioral models within the context of a particular business problem.

Advanced analytic techniques available in SAS Marketing Automation enable business analysts to better understand and anticipate customer behavior and thereby build relationship value. Here are some representative analytics that are available or can be embedded in SAS Marketing Automation to create effective marketing campaigns:

• Market basket analysis — Analyze the mix of products that a given customer purchases, with a view to understanding what other products to sell them.

• Segmentation analysis — Identify the most valuable and profitable customers to help define appropriate target marketing programs.

• Cross-selling predictions — Identify the right time to make an offer to an existing customer, and determine the optimal content and contact channel.

• Customer channel analysis — Analyze and predict the most suitable and efficient channels for initial contact, up-selling and cross-selling activities.

• What-if analysis — Change key campaign variables and determine how they affect the
outcome.

• Customer value modeling — Calculate the total value of keeping customers throughout the lifetime of the relationship.

• Customer risk analysis — Calculate the risks associated with a given customer, including credit risk, likelihood of defection to a competitor and so on.

Advanced analytics enable you to “mine” the customer data to transform masses of data into
meaningful market segments on a formal or ad hoc basis. Armed with this information, you can
create highly tailored marketing campaigns and identify high-value individuals, instead of deluging customers with irrelevant offers.

SAS Marketing Automation offers the ability to visually track and view migration of customers
among segments over time to see how marketing efforts positively or negatively affect customer
behaviors. Rather than merely looking at a snapshot of the customer profile, marketers can better track customer behavior across the life of their relationship with the company.

_____________________________________________________________

Capabilities that give more control to business users

As was discussed earlier, an effective marketing process relies on the contributions of very
different types of users, from strategic-level to infrastructure level, from business perspective to
number-crunching perspectives. With SAS Marketing Automation, all your business units will have access to SAS’ powerful data management and analytic capabilities — in a way that directly supports their role in the organization. This application integration broadens the potential user base and empowers specialists and generalists to work together more efficiently.

SAS Marketing Automation offers a variety of capabilities specifically for business users,
including:

• A powerful interface that gives users the flexibility to go behind the scenes to define and
perform in-depth analysis and campaign definitions. A portal-driven dashboard, for instance, gives marketers one central point from which to manage all marketing activities. The solution also lets users define visual, process-driven campaign flows. Advanced clustering analysis also helps marketers generate target lists and visually track the ways clusters relate to each other. Quantitative analysts can define analytic processes in SAS Enterprise Miner and “register” their models to be accessible within SAS Marketing Automation. By embedding analytics in the process, business users can easily access scores generated in SAS Enterprise Miner for use at any point while generating a campaign list.

• Campaign execution capabilities, such as campaign process activity breakdown. This activity breakdown ensures that every campaign has an audit trail for regulatory inspection and review. Improved scheduling features help business users schedule and execute campaigns more efficiently. A multithreaded scheduler also supports multiple, multistage campaigns simultaneously, enabling users to schedule a large number of campaigns within a short period of time. This capability is becoming critical as enterprises initiate more sophisticated and frequent campaigns.

• The ability to translate complex data structures into useful business terms for more rapid,
customized reporting. With SAS Marketing Automation, IT can provide common sets of
information, called information maps, in terms that are understood by business users. Business users can then use the information maps to create queries and build the reports they need without IT intervention and without having to know anything about the way data is organized throughout the organization.

• Data warehousing capabilities that enable business users with minimal training or programming skills to access the information they need. SAS data warehousing technology also ensures the accuracy and timeliness of the data used by business groups.

• Robust Web reporting also makes developing and distributing reports very much a business user activity, freeing this burden from IT.

By giving business users the ability to perform complicated tasks in a straightforward way, SAS
Marketing Automation effectively frees IT from one-time reporting requests, meaning that fewer
specialists are required and less time needs to be spent training marketing users about physical data stores or query tools. IT can also manage and move the physical locations of data stores without affecting existing reports.

___________________________________________________________

The ability to extend into other areas of marketing

SAS Marketing Automation, part of the SAS Customer Intelligence solutions family, can be
extended through integration with other SAS solutions, providing even greater benefit for
marketing organizations through the broadest, most capable marketing solution available.

Event-driven marketing in real time, at the right time
In addition to outbound channels like direct mail and catalogs, companies are now coordinating
inbound, outbound and event- and behavior-based communications. This means tracking and
responding to customers across all touch points and providing a consistent face regardless of the communication channel.

SAS Interaction Management is a solution that enables companies to take the campaign
management capabilities of SAS Marketing Automation to the next level of real-time marketing. It
uses a patented approach to event-driven marketing to track individual customer behavior and
alert businesses to real-time opportunities for delivering timely, effective communications.

A well-planned offer delivered too late is just as bad as a poorly targeted offer delivered in real
time. SAS Interaction Management helps you get closer to the goal of meaningful, one-to-one
customer communications by enabling you to deliver precisely targeted messages at just the right moment.

• Tailor interactions in real time.

• Receive early warnings of new opportunities.

• Set unique criteria for triggers based on time, events and behavior.

• Personalize dialogs with one-to-one granularity.

• Fuel front-office systems with intelligence.
 

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Mathematical, constraint-based marketing optimization

While the need to communicate more effectively with customers continues to grow, marketing
budgets and other resources often do not, which limits the number of offers that can be extended. What’s more, marketing departments face increasing pressure to demonstrate a quantifiable contribution to the organization’s performance and growth.

Through SAS Marketing Optimization, SAS provides the mathematical capability of allocating
finite marketing resources across multiple channels, business constraints and marketing
scenarios in order to target the right customer with the right communication through the right
channel.

SAS Marketing Optimization offers:

• Recommended offer assignments and channel allocation for maximizing profitability.

• True mathematical, constraint-based optimization.

• An easy-to-use interface designed for business users.

• Analytic insight into how marketing constraints affect profitability (what-if analysis).

• User-defined constraints and optimization objectives.

While there are vendors that focus solely on marketing optimization, SAS is the only company that can provide an integrated solution to address marketing automation and optimization.

Summary

The term marketing automation only alludes to one small part of the total equation. Advanced marketing automation solutions such as SAS Marketing Automation address far more than just automating the functions associated with planning and carrying out a campaign. First- and second-generation marketing automation solutions have been limited by offering only superficial analytic capabilities that are poorly integrated with customer communication processes, or simply can’t keep up with the need for frequent, multilayered campaigns.

To truly maximize the profitability of every customer relationship, you need a marketing
automation solution that supports your entire marketing team and provides improved efficiency and effectiveness at every stage of the marketing process — from setting strategy to targeting opportunities, implementing customer communication initiatives, measuring results and feeding that information back into planning for future campaigns.

Advanced marketing automation builds business value by unifying multiple internal systems, organizational silos, marketing team members and customer channels into an enterprise wide customer intelligence strategy. SAS Marketing Automation provides a unique, integrated approach to help you understand your customers better than anyone else, and use that knowledge to target them more effectively than anyone else.

In one integrated system, SAS Marketing Automation brings together campaign planning and budgeting, customer segmentation and profiling, campaign management, and campaign and customer analysis. It is the only solution that combines award-winning data warehousing and data mining with state-of-the-art campaign management tools — analysis and operational processes combined in one integrated environment for total, closed-loop marketing automation.

Advanced Marketing Automation
for Banking
Maximizing Campaign Returns through
Customer Intelligence

Table of Contents
Executive Summary .......................................................................................................1
Marketing Challenges of the New Millennium.............................................................2
The Evolution to Analytics-Based Marketing Automation.........................................3
Four Phases of Intelligence-based Marketing Automation .......................................5
   Plan the Most Effective Marketing Initiatives................................................................6
   Target Campaign Activities to Precisely Defined Customer Segments .......................7
   Act on Marketing Plans with Maximum Operational Effectiveness ..............................8
   Learn from Campaign Experience..............................................................................10
The Critical Technology Enablers of Marketing Automation ..................................11
   Centralized Data Warehouse to Support a Customer-Centric View ..........................12
   Industry-Leading Analytics to Derive and Apply True Customer Intelligence ............13
Summary.......................................................................................................................14

Executive Summary
How can you consistently beat your profitability goals — and your competitors? On the surface,
it’s not that complicated. Just understand your customers better and faster than anyone else, and use that knowledge to target them and meet their needs more effectively than anyone else.

If only it were that simple. Unfortunately, while information about customers is plentiful, actionable
customer intelligence often remains elusive. Customer data pours in from every conceivable
channel. Assembling a coherent picture of customers from all those puzzle pieces — a picture on which you can confidently build a profitable marketing strategy for your bank — can be a
formidable challenge.

To tackle this challenge, marketing automation solutions must provide three key functions:

• Campaign and customer analysis. A comprehensive marketing automation solution
provides quantitative tools to analyze customers and prospects to help craft the right
message and product/service offers. Advanced systems also provide statistical analysis and
modeling to tightly define target markets and continuously improve through “closed-loop”
marketing, in which the system self-learns from information gleaned from prior campaigns.

• Campaign management. At the heart of any marketing automation solution is the capability
to effectively automate essential campaign processes, including managing all communication
with customers across multiple channels, tracking responses, and consolidating and reporting
results.

• Consolidated view of the customer through data warehousing. These campaign analysis
and automation functions draw on a customer-centric data warehouse that pulls customer
data from all appropriate back-office and front-office systems, channels and third-party data.
This data warehouse supports a customer-oriented, cross-functional, cross-product view
needed for creating truly effective campaigns.

The most advanced generation of marketing automation technology seamlessly combines these
functions to produce a centralized, fully integrated environment for total marketing performance.
Banks can leverage the breadth of this functionality to maximize campaign returns through the
four essential phases of a disciplined marketing process:

• Plan the most effective marketing campaign offers with a top-down strategic focus.

• Target campaign activities to tightly defined customer segments, and manage each segment
in a way that fosters improved response.

• Act on those plans in a way that increases campaign velocity, flexibility and return on
investment (ROI).

• Learn by measuring campaign results and integrating new knowledge into refined strategies
and future campaigns.

Marketing Challenges of the New Millennium
In simpler days, banks enjoyed high customer loyalty and a very favorable offer-to-response ratio because they knew their customers personally and had a relationship based on history and
mutual understanding. They could tailor their products and services to offer the right product to
the right customers at the right time. They could also present the most logical cross-sell and up sell offers to their customers, based on their knowledge of the customers’ life-stage, personal
preferences and needs.

Deregulation, technology, globalization, increased competition and increased customer
expectations have irrevocably changed the face of the banking industry. Growth of the Internet
and changing regulatory policies have lowered the entry barriers, increasing cross-border and
cross-sector competition in the industry. The ease of switching banks and the commoditized
nature of most products and services have lowered customer loyalty, making the banking industry more competitive and complex. Today, banks are converging, consolidating and globalizing to survive, and the quaint image of a personal neighborhood bank is becoming nothing more than a fading memory.

Today’s national and multinational service providers are interacting with millions of customers
through multiple channels, making it logistically unfeasible to maintain personalized customer
interactions and an enterprise-wide, customer-centric view. Nonetheless, customers still expect to be treated personally, immediately and consistently. The proliferation of choices made possible by remote and online marketing techniques (online banking, call centers, kiosks, ATMs and direct mail) has empowered customers and made them less loyal. If their expectations are not met, they can easily switch to a competitor with a single click, or place a toll-free call to the bank whose new low-interest credit card offer arrived in their mailbox this week.

This scenario alludes to some emerging challenges facing banks:

• Proliferation of customer touch points. Five years ago, banks interacted with customers
primarily through three channels: call centers, direct mail and retail branches. Today, even
small to mid-sized banks reach customers through dozens of channels: e-mail, fax, VRU,
Internet, ATMs, brokers and more.

How can banks gather a consistent view of the customer that crosses all those diverse touch
points, while personalizing the view to the customer as well?

• Heightened expectations for marketing campaigns. It’s not uncommon for Fortune 500
banks to plan as many as 3,000 campaigns in a single year, clearly a significant endeavor.
Even the largest banks can’t afford to paper the world with their offers if they’re not reaching
prospects likely to buy. Nor can they afford to send direct mail to huge, undifferentiated
databases. The frequency and turnaround of campaigns is higher than ever, and so is the
expectation for return on investment.

How can banks be sure they’re accurately targeting the right audience with the right offer at
the right time?

• Speed and immediacy demands of the Web. “E-business, with its characteristic
transactional volume and speed, demands no less than the automation of the entire spectrum
of interactions,” says Quaero Research in its report, “Campaign Management Marketplace”
(2001). “With access to a wide range of information on the Web, the customer who sees an ad
can ask for details, move on to something else, or check out the competition in a single click.“

How can banks interact more effectively with customers over the Web in real time?

• Rapid growth in organizational data. Discrete enterprise systems churn out gigabytes of
data about customers and campaigns — both online and offline — yet few enterprises are in
a position to assemble that information into a coherent picture that can support informed,
intelligent decision-making. Intuition still guides many marketing decisions in an environment
that really calls for a structured, predictive framework of rigorous analysis.

How can banks access, consolidate and clean all available customer data to create a
comprehensive foundation for deriving the best customer intelligence?

The Evolution to Analytics-Based Marketing Automation (Please see above and return)

First- and second-generation
marketing automation systems
predominate today, even as the
changing marketplace
demands more than these task oriented
systems can provide.

Four Phases of Intelligence-based Marketing Automation   (Please see above and return)
______________________________________________________________

Plan the Most Effective Marketing Initiatives

The marketer’s first task is to plan maximally effective marketing campaign offers and strategies,
in alignment with overall corporate goals. To do that, you need a clear, top-down picture of the
business issues at play. What is the immediate and long-term value of each customer/segment?
From an enterprisewide perspective, what is the best way to increase customer retention, brand
and product awareness and demand?

The planning stage is also where business strategy merges with marketing content. What product
offers should be included in the campaign? How should the offers be conveyed? What
communication methods will work best for this campaign? At what cost? What are the program
steps and sequence? Expected results?

This planning process must be framed within a company-wide strategic vision. It’s not enough to
manage functional units toward individual successes and expect their merits to trickle up through
the organization. Management should establish organization-wide objectives, align all functional
units toward that bigger picture of success and reward units based on organization-wide metrics.

Fourth-generation marketing automation supports that holistic perspective, enabling you to plan
complex campaign strategies and operations within the context of corporate-level objectives. A
critical component in generating a corporate-level view is to have direct access to a central data
repository that holds all validated, up-to-date campaign and customer information. A
fourth-generation marketing automation system incorporates this knowledge to make campaigns
more personal, relevant and effective, and integrates reference data from previous campaigns to help gauge costs and anticipate results.
__________________________________________________

Case study — SAS Marketing Automation in Action

Plan

A leading U.S. bank with approximately $20 billion in managed assets has chosen SAS Marketing Automation to plan marketing strategies that will enable it to effectively attract and retain high value customers. The bank’s goal is to better understand its customers and their needs, so it can extend the right offers at the right time, through the right promotional vehicle.

Unlike many other banks whose branch, call center and online efforts operate as independent
business entities, this bank will integrate customer and sales data from these three channels into
a central data warehouse. This data management strategy provides two key benefits for planning:
(1) provides a unified view of the customer across all channels, and (2) enables an enterprise wide context for developing campaigns that benefit the entire organization, not just one product
line or business unit.

The bank’s marketing department sits on a gold mine of information accumulated from the
transactions of millions of customers. In addition to analyzing customer behavior, the marketing
group uses SAS analytics to predict which new product/service bundle will succeed with which
customer segments via which channels.

Armed with consolidated, valid, up-to-the-minute data about customer behavior and
corporate-level strategic vision, the bank can effectively plan multiple, highly tailored marketing
campaigns, rather than sending out volumes of direct mail and e-mail to an undifferentiated
mailing list. As a result, the bank’s campaign initiatives reach more interested customers and
result in more cross-sell/up-sell opportunities, bringing higher profitability and ROI.

________________________________________________________

Target Campaign Activities to Precisely Defined Customer Segments
Targeting is crucial to effective customer relationship management, not only in improving your
chances of reaching high-value customers, but in ensuring that you don’t waste scarce resources on attempting to sell to the wrong people. To anticipate customer needs, improve customer retention and identify opportunities to cross-sell and up-sell, marketers have to understand the unique characteristics of each customer segment in an increasingly fragmented marketplace.

The targeting phase asks:

• How should we define our customer segments?

• How are customers moving between segments over time?

• Which customers are most likely to leave?

• Which customers are good candidates for cross-selling or up-selling?

• Which communication channel should we use?

• What are the characteristics of a good customer?

• Are we recruiting high-value customers or low-value customers?

Effective targeting allows you to:

• Increase customer retention by identifying “at risk” customers and implementing targeted
loyalty programs.

• Refine marketing campaigns to target those most likely to buy.

• Quantify shifts in behavior, predict long-term value and identify prime cross-sell and up-sell
opportunities.

A prerequisite to effective targeting is a more complete understanding of your customers, which
can be obtained through techniques such as customer profiling, customer profitability analysis,
churn/retention analysis and behavior analysis. Fourth generation marketing automation
dynamically integrates sophisticated data mining and analysis capabilities into the targeting
function. Data mining returns tremendous bottom-line impact as it turns data into predictive
information, information into knowledge and knowledge into greater business value. With
forward-looking analytics, you can better segment customers for more targeted campaigns.

_______________________________________________

Case study — SAS Marketing Automation in Action

Target
 

A multi-billion dollar U.S.-based regional bank competing in a market dominated by large national players wanted to improve its campaign effectiveness by better understanding and targeting its customers. The bank had traditionally mailed out its campaigns to random portions of its client base, relying mainly on intuition rather than science. The result was a poor response rate and high campaign costs.

Using SAS Marketing Automation’s statistical modeling and data mining capabilities, the bank was able to analyze its customers’ demographic, transactional and behavioral data to better segment its customers. It then used the SAS solution to send out the same campaign material to a SAS-determined target audience. The result was a 400% improvement in the response rate.
 

The bank also uses SAS Marketing Automation to model and execute event-based campaigns.
Through a single view of customers across the enterprise and more intelligent segmentation, the
bank is targeting the right customers, with the right product/service offerings, via the right channel.
_______________________________________________

Act on Marketing Plans with Maximum Operational Effectiveness

Automated campaign management tools streamline the customer contact processes of a
campaign, including pulling lists, establishing control groups, scheduling campaign activities and tracking results. Even second-generation marketing automation systems handle these tasks. Fourth-generation marketing automation dramatically improves operational effectiveness by introducing an extra layer of intelligence to the essential tasks of campaign management,
communications and reporting.

For example, the campaign management component of SAS Marketing Automation provides:

• Integrated prioritization and scheduling for complex, multi-channel, multi-stage campaigns.

• Efficient selection, screening and filtering of internal and purchased contact lists to produce
clean, non-duplicated target lists, without reliance on the IT group.

• Coordination and optimization of outbound and inbound communications over multiple
channels for hundreds of thousands or hundreds of millions of customers.

• The ability to create, deliver and track high-volume, opt-in, personalized email marketing
campaigns based on a thorough understanding of the customer.

• Dynamic response handling to automatically update customer contact history, response
tracking and analytical processes.

• Tracking of “hard” responses (purchase decisions) and “soft” responses (subtle changes or
trends in user behavior), recorded through conventional channels or e-media.

• Automatic updates to the central customer data warehouse of customer contact history,
response history and analytical results.

__________________________________________________
Case study — SAS Marketing Automation in Action

Act

Operating in more than 30 countries with two dozen subsidiaries, a large consumer finance
institution needed an automated and systematic way to analyze customer behavior and
implement smarter, more efficient campaigns. In an environment of intense competition, the
company needed up-to-date market intelligence to acquire and cross-sell to customers — and
they needed to be able to act on it before competitors did. Already using SAS extensively
throughout the world, the company turned to SAS Marketing Automation to complete its global
customer relationship management (CRM) solution.

Rather than sending direct mail to inefficient, clumsily targeted mailing lists, the company now
applies intelligent rules to identify the right households, and even the right person in each
household, to receive specific offers. Rather than initiating campaigns on arbitrary or calendar based schedules, the SAS system enables them to schedule key campaign activities and regular communications in ways that create the greatest opportunity. They are also able to update models automatically for any changes to customer records, ensuring that predicted outcomes always reflect the latest information.

Overall, SAS Marketing Automation has helped the company reduce the time-to-implementation
for their campaigns. In addition, unlike many competitors who rely heavily on acquiring new
customers to expand revenue — difficult in an economic slowdown — the company is leveraging SAS Marketing Automation to increase revenues from existing customers. By effectively cross-selling and up-selling products and keeping profitable customers happy, business units increase the profitability of their client bases while contributing to overall corporate goals.

_____________________________________________________

Learn from Campaign Experience

Obtaining detailed customer knowledge is one thing; effectively integrating it into future marketing campaigns is another. You should be able to measure the effectiveness of a campaign against the goals established in the plan phase and then use that information to improve future campaigns.

Did the customers respond, and if so, how did they respond? Did we achieve our objectives? This information is critical to capture, monitor and incorporate back into the customer data warehouse. Through this ongoing self-learning process, you gain an ever more accurate picture of customers’ wants and needs, leading to more effective campaigns over time.

Advanced marketing automation solutions let you track all customer responses via a central
database, enabling you to measure the response to each marketing campaign and improve on
that performance next time around. You can also create multiple control groups to provide
baselines against which to measure response rates. These test cells allow you to field-test
campaign features, such as different modeling algorithms, creative treatments or channel options.

Ideally, you could import responses directly and automatically from inbound communication
channels into a response table, such as auto-recording all the “click-to-buy” responses to an email offer. Or you could use a calculated rule linking a response to a campaign or communication, even if the respond channel isn’t the same as the outbound channel. For example, if the customer receives a letter and responds to it via the Web or phone, the link can easily be established and recorded.

Not all communications produce, or even demand, a direct response. For example, a campaign
that aims to alter customers’ patterns of channel usage may not require any inbound
communications from the customer and no explicit purchase decision. The campaign’s success
might be measured not in phone calls or cards returned, but in changes in transaction patterns
among the target group. By tracking such inferred responses, fourth generation marketing
automation solutions can help you identify subtle trends that are easy to miss when there is no
direct feedback to measure.

The learning capability allows you to reach far beyond customer reactions to specific campaigns. With the right technology, you can analyze historical customer data, purchased customer data, and customer transaction data and sales data from every channel. You can use this information to better understand drivers of customer profitability, build accurate predictive models of customer behavior, and implement a more targeted — and more profitable — campaign the next time.

With that kind of customer knowledge in your arsenal, you are in a position to develop more
effective marketing strategies and redirect costly marketing resources toward the most profitable
customer segments.

______________________________________________

Case study — SAS Marketing Automation in Action
Learn

The U.S. bank in the second case study relies on SAS to evaluate both the return on investment
and sales success of every major campaign. The results of these measurements provide
marketers with the quantitative evidence they need to make smart, cost-effective decisions about future campaigns. The result is a self-learning, closed-loop cycle in which the marketing phases are constantly being improved and refined. This has allowed the bank’s marketing division to keep a step ahead of the constantly changing market, and has produced consistently high return on investment for all promotional activities.

_______________________________________________
Each of these four stages — plan, target, act and learn — is integral to the total marketing
automation value chain.

⇒ Once you understand the customer base, you can segment those customers into groups to
which you can target with tailored service and marketing activities

.
⇒ Using analytics, you can quantify shifts in behavior, predict long-term value, and identify
prime cross-sell and up-sell opportunities.

⇒ This customer intelligence forms a basis for highly targeted market campaigns and offers.

⇒ Automate and streamline implementation for complex, multi-channel, multi-stage campaigns.

⇒ Glean responses and trends from marketing campaigns and then cycle them back into the system to fine-tune its effectiveness.

The payoff from these technology investments is significant — shorter marketing cycle times,
better odds of getting your message out to customers ahead of the competition, reduced costs by replacing scattershot campaigns with truly targeted ones, and rising return on investment as the results of each campaign are immediately applied to the next.

The Critical Technology Enablers of Marketing Automation

The essential stages of marketing automation described earlier — plan, target, act and learn —
demand more than first- and second-generation software solutions can provide. Third-generation
solutions start to fill critical gaps by automating functions across multiple business units and
customer contact channels, and providing some self-learning capability.

Fourth-generation solutions, such as SAS Marketing Automation, integrate powerful campaign
management functionality with:

• A centralized data warehouse to support a customer-centric view.
• Industry-leading analytics to derive and apply true customer intelligence.
 

Centralized Data Warehouse to Support a Customer-Centric View
No matter how large the target market, it is composed of individuals, with individual characteristics and predilections. Therefore, the key to effective mass marketing is not to treat your market like a mass. The more in-depth your intelligence about individual customers, the greater the effectiveness of your marketing efforts.

But what if you need to interact with millions of customers? What if you’re dealing with lean profit
margins that require high-volume economies of scale? How do you restore personal service —
and the sales value it creates — when you’re marketing on a regional, national or global scale?
How do you provide that value-added, personalized service without eroding profit margins?

The answer is to embrace an enterprisewide, customer-centric vision. From an organizational
standpoint, that means you should align sales and service behaviors around customer
relationships instead of around specific organizational structures or products.

In a marketing automation solution based in customer intelligence, you integrate customer
information from across the entire organization, as well as from partners and other external
sources, to develop one comprehensive view of customer behavior. Only with a unified view can you accurately identify and differentiate customer needs, define marketing campaigns based on those needs and thereby maximize return on investment from marketing initiatives.

At the center of SAS Marketing Automation is a multi-dimensional data warehouse, based on a
banking specific data model, that serves as the central collective memory of the organization’s
customers. Using award-winning data warehousing technology and best practices gathered from
25 years of banking industry experience, SAS provides a panoramic view of the customer that
incorporates legacy data, transaction data, preference information and data from any source that
helps describe customers and their attributes.

The SAS data warehouse:

• Uses logical and physical data models specific to the banking industry to improve “time to
intelligence” and reduce project risk and deployment time.
• Provides an open structure that works with any existing database environment to maximize
flexibility and reduce cost.
• Integrates input from multiple contact point systems, such as clickstream data from Web
commerce, retail branches, ATMs and call centers.

• Integrates with back-office systems, such as core transaction processing systems, CIFs and
MCIFs.
• Integrates third-party data, such as geo-demographic, socio-economic data from third-party
application data vendors, prospect lists and credit bureau data.
• Performs data cleansing, validation, deduplication, merge-‘n-purge and update functions to
maintain data integrity.
• Enables a comprehensive, 360-degree view of customers across touch points, products and
functional areas.
• Supports meaningful analysis to turn this data into intelligence you can act on.

In short, the SAS data warehouse assembles a single, enterprisewide view of the customer,
spanning all touch points and systems. Business data and key operational metrics from diverse
departments are aligned, shared and integrated in a common repository. Information about
customers, which may currently exist in various databases across the enterprise, is combined and made compatible, to support meaningful analysis.

Industry-Leading Analytics to Derive and Apply True Customer Intelligence
To increase the rate of return on marketing campaigns, marketing strategies must be based on an accurate and comprehensive understanding of customers across all functional areas and contact channels. The model of campaign management based on customer intelligence calls for creating intelligent campaigns that are tightly targeted to the highest-value customers, for the most relevant opportunity, through the most effective channel, at the most appropriate time.

Advanced analytic techniques enable analysts — with or without statistical backgrounds — to
better understand and anticipate customer behavior and thereby build relationship value. Here are some representative analytics available in SAS Marketing Automation to create optimally effective marketing campaigns.

• Customer profitability analysis. Calculate the current and potential profitability of a customer
throughout the lifetime of the relationship.
• Credit scoring analysis. Calculate the credit risk associated with a given customer.
• Customer attrition analysis. Predict which of your customers are most likely to leave.
• Cross-sell/up-sell analysis. Analyze the mix of products that a given customer has, with a
view to understanding what other products to sell to that customer. Also identify the right time
to make an offer to an existing customer, and determine the optimal content and contact
channel for the offer.
• Segmentation analysis. Identify your most valuable and profitable customers to help define
appropriate target marketing programs.

• Channel optimization analysis. Analyze and predict the most suitable and efficient channels
for initial contact, up-selling and cross-selling activities.
• What-if analysis. Change key campaign variables and determine how they affect the
outcome.

Advanced analytics enable you to “mine” the data warehouse to transform masses of data into
meaningful market segments on a formal or ad hoc basis. Armed with this information, you can
create highly tailored marketing campaigns and identify high-value individuals, instead of deluging customers with irrelevant offers.
 

Summary

The term marketing automation only alludes to one small part of the total equation. Advanced
marketing automation solutions such as SAS Marketing Automation address far more than just
automation. They support comprehensive operational and analytic processes that build business value by unifying multiple internal systems, organizational silos and customer channels into an enterprise wide customer intelligence strategy. Because it helps you better understand customer needs, SAS Marketing Automation — and the customer intelligence it delivers — let you optimize customer satisfaction, revenue and profits, and increase value for all stakeholders.

SAS Marketing Automation provides a unique, integrated approach to help you understand your
customers better than anyone else, and use that knowledge to target them more effectively than
anyone else. In one integrated system, one easy-to-use graphical environment, SAS Marketing
Automation brings together campaign management, and campaign and customer analysis. It is
the only solution that combines award-winning data warehousing and data mining with state-ofthe-
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Marketing Optimization — An Introduction

Table of Contents
What is optimization?.................................................................................................... 1
Prioritization, rules and optimization — a comparison of methods......................... 1
     Prioritization ................................................................................................................. 2
     Rules ............................................................................................................................ 3
     Optimization ................................................................................................................. 4
The SAS approach to marketing optimization............................................................ 4
Organizational considerations ..................................................................................... 6
Standard reports and sensitivity analysis .................................................................. 6
Extending optimization with business intelligence ................................................... 7
    Balancing suppression rules and constraints............................................................... 7
Success with SAS® Marketing Optimization............................................................... 7
Summary........................................................................................................................ 8
About SAS ...................................................................................................................... 8

What is optimization?
The complexity of direct marketing has expanded rapidly in recent years, particularly with the
growth of electronic marketing channels. Companies today have to make difficult decisions about targeting the right customers with the right offers while staying within budget and channel
capacities, all without cannibalizing future sales or saturating customers with too many messages. That is a lot to manage, particularly when multiple campaigns from one company might also be competing for customers’ attention.
 

Optimization is a process that resolves these complex issues by looking at problems in a holistic fashion that balances the constraints of an organization with the need to improve key metrics. Unlike traditional business-rule methods for allocating campaigns to customers, optimization allows marketers to gain critical knowledge about factors that affect the success of marketing campaigns, such as the impact of adding a new channel, the probable results of reducing a budget or the consequences of instituting a strategic contact policy.
 

The best way to explain the differences between traditional approaches and optimization is
through example. This paper will provide an example to show the value associated with this new
approach to direct marketing, to discuss organizational challenges common when implementing
optimization and to detail the SAS approach to marketing optimization.
 

Prioritization, rules and optimization — a comparison of methods
The following example attempts to illustrate problems that arise when companies execute
customer-based campaigns where there are limits on which customers are eligible to receive
offers. In cases where one customer only qualifies for one offer, the problem is simple — the
customer gets that offer. The problem becomes more challenging, however, when there is a
group of customers that qualifies for more than one offer. Figure 1 shows this situation.
Overlapping sections in the diagram represent customers who qualify for multiple offers. If
optimizing across time periods, the overlap can increase exponentially. What makes offer
allocation decisions even more important is that customers who qualify for more than one offer
are often the most valuable customers. Poor decisions about campaign allocation could
jeopardize that value.

Companies approach this problem in different ways. In the following example, three approaches
will be compared: prioritization, rules-based and optimization. The first thing many companies do when attempting to make a decision about offer allocation is to develop model scores that reflect the probability of response for given customers and given campaigns. These model scores, in addition to other values such as the expected revenue from a response, make up an expected value. Table 1 shows the expected values for each customer-campaign combination. Execution of this campaign also has two constraints:

• Each campaign can be sent, at most, to three customers in the list.
• Each customer can receive only one campaign.
 

Prioritization
Prioritization is the most common approach database marketers take to solve this problem. Put
simply, prioritization assigns an order of priority for each campaign being considered within the
same time period. For example, it may have been determined that Campaign A is the best
performing campaign available. Therefore, it will get its first choice of customers and will choose
customers 1, 7 and 9 because they offer the highest expected values available. Campaign B will get the best customers remaining, and Campaign C will get the rest. Table 1 shows the results of the prioritization method. Shaded cells mark the customers chosen to receive each campaign. Using this approach, the company can expect $655 in profit for the three campaigns.
By looking carefully at the customers chosen for each campaign, there is clearly room for
improvement. Specifically, it is logical to think that Customer 1 should have received Campaign B, which would have resulted in an improvement of $20. Campaign selection based on this type of reasoning is described below.

Table 1: Results of the prioritization method.
 

Rules
Based on what we learned about prioritization, the logical question becomes: Why not give each customer the offer that will result in the most revenue? This question describes the rules-based approach. This approach establishes rules that look at each customer in order to determine the appropriate campaign for that customer.

In our example, Customer 1 will get Campaign B, Customer 2 will get Campaign C and so on.
This seems like a major improvement over prioritization, and in some cases it is. However, the
drawback of this approach is that if revenue opportunities exist further down the list of customers, the marketer may not be able to target them because of constraints. Remember that each campaign can go to a maximum of three customers. Because of this constraint, Customer 9 cannot get Campaign B, even though it would be a better choice. The rules-based approach
would result in a $715 profit for this organization.

Table 2: Results of the rules-based approach.

Optimization

The use of operations research techniques enables the best allocation of customers to
campaigns. This method takes opportunity cost into account with the knowledge that extending an offer to any particular customer could prevent a better offer from being presented. Evaluating all combinations simultaneously will result in the best possible solution. In this case, a profit of $745 was achieved using the same customers and the same campaigns. This represents an
improvement of more than 13 percent over the prioritization method.
 

Table 3: Results of mathematical optimization.

While a detailed look at the mathematical methods for optimization is not within the scope of this
paper, it is important to note two things. First, this simple example does not reflect the enormity of typical marketing optimization problems. Many companies face similar situations with millions of customers, dozens of campaigns, complex constraints and sophisticated contact policies. When the scale of the problem increases, so does the opportunity for improvement. Many large
organizations have seen improvements of greater than 25 percent.

Second, the computational power necessary to solve such complex problems traditionally has
been a bottleneck. Intensive research by a team of operations research scientists and domain
experts has yielded a breakthrough algorithm that solves large-scale problems efficiently. Due to these innovative approaches, SAS allows marketers to solve these problems in a timeframe that is reasonable and flexible enough to fit the objective.
 

The SAS approach to marketing optimization
As mentioned above, any optimization exercise will consist of an objective, a set of constraints
and a contact policy. SAS® Marketing Optimization allows marketers who know nothing about
optimization techniques to construct a scenario with these three components and then optimize
campaigns for execution.

Objective — The objective for a marketing optimization problem can be defined in many ways,
depending to the overall goals of the campaign. If the overall goal is to increase profitability, the
marketer can choose profit as the metric to be maximized. SAS provides flexibility in the goals of the campaigns so that the optimized value can be the result of an equation of two or more
metrics. In other cases, the marketer might set an objective to minimize, such as risk or cost.

Constraints — Constraints enable marketers to specify key marketing limits such as minimums
or maximums for spending. Constraints can also be set at the customer segment level. Such
constraints can involve:
     • Budget. Set the budget constraints for any or all campaigns. In addition, budget constraints
can be created at the individual communication level.
    • Cell size. Very often campaigns need to be a certain size to be worth executing. Marketers
can create constraints that reflect the real nature of the direct marketing world through minimum or maximum cell sizes.
    • Channel capacity. Outbound and inbound channels often have limits, whether in terms of
the total hours a call center can handle or the number of pieces a mail house can send out.
    • Custom. Constraints can be constructed such that they enforce a variety of specific limitations. For example, geographic constraints may dictate that a certain number of customers are contacted within a certain region. There may be additional constraints that ensure a proper ratio of high value to low value customers are contacted across campaigns.
    • ROI. All campaigns can have an additional constraint that drives toward a threshold so that a
certain ROI is targeted across the campaigns.
 

Contact policy — Contact policies are important for planning the number of allowable touches that the overall campaigns or brand can have on each individual customer. These can be set in a variety of ways:
       • Maximum contacts. A limit can be placed on the number of touches per customer for the
overall cycle. For example, an organization might say that each customer can be contacted only twice per cycle. This can be maintained at the overall level or the individual customer level.
       • Group/subgroup. Contact policies can be constructed so that they allow certain types of
communication more leeway. A credit card company may want to limit the amount of a certain expensive offer, for example.
       • Time period. It is important also to optimize across time. A contact policy can be constructed that limits the number of offers in any given time period. So, a customer could be restricted to three communications in January and two in February. A rolling time period can limit that same customer to, for example, four communications over any two-month period.
 

As marketing organizations mature, they may start with a simplistic contact policy, such as an
overall limit on all customer contacts, and then graduate to a more sophisticated strategy. It is
critical to consider capabilities that will allow the most flexibility. In addition, customer-level contact policies, when applied, add more complexity to the underlying algorithm, making it critical to have an optimization engine that can handle this load.

Organizational considerations
Despite powerful technology for solving complex marketing optimization problems, sometimes the hardest part is overcoming the organizational challenges associated with implementing optimization techniques. There are some difficult questions to be asked. Product or campaign managers are often rewarded for the performance of their product or campaign rather than the performance of the entire organization. So, in the example used above, Campaign A has a higher profit using prioritization than using optimization. If the campaign manager for Campaign A is rewarded based on the performance of only that campaign, there will be resistance to change. The overall profitability of marketing activities needs to be aligned and communicated effectively for an optimization process to be successful.
 

Another advantage of using optimization in marketing is that it can serve as an impassionate
arbitrator among campaigns. Optimization doesn’t play favorites when deciding which campaigns will get the best customers, but the organization needs to be committed to letting the numbers speak for themselves. This approach is consistent with the overall trend toward more analytic methods in marketing.
 

SAS can help in this collaborative process through the use of an information delivery portal. As
optimization scenarios are run, the results can be viewed through this Web-based portal. In fact,
as a best practice it is valuable to explore many different scenarios before putting the results of
the optimization into the finished campaign. The portal summarizes and aggregates results by
campaign and communication to ensure that key objectives are being met and that key
stakeholders are aware of the potential impact of campaigns.
 

Standard reports and sensitivity analysis
Another important aspect of using optimization is the ability to gain insight into each constraint’s
impact. Upon running an optimization scenario, SAS Marketing Optimization generates a set of
reports that includes an objective summary report, campaign/communication summary reports
and graphs, a constraint summary, and a sensitivity analysis. With the constraint summary, the
user can identify which constraints are limiting the overall objective and by how much. An
opportunity cost of five dollars for budget constraint, for example, would tell the user that
increasing the budget by one dollar would increase the overall objective by five dollars. Once this sort of information is available, the marketer then needs to determine how much to increase the budget. Sensitivity analysis helps with this determination, since it can show the appropriate range for which constraint summary information is valid. So, for example, if the budget was $100,000, the marketer may be able to increase the budget to $125,000 before the incremental benefit becomes negligible. Again, there is tremendous value associated with creating multiple scenarios and experimenting with the outcomes of different configurations of budgets, constraints and contact policies.

Extending optimization with business intelligence
In addition to these standard reports, SAS Marketing Optimization can take advantage of the
enterprise reporting capabilities of the SAS®9 platform. These include such capabilities as ad hoc reports, Web-based reports and an information delivery portal to distribute reports to
stakeholders. SAS also recognizes that Microsoft Excel is the de facto standard for many
marketing analysts and has built a seamless integration between SAS and Excel, so those users can stay in the environment most comfortable for them.
 

Balancing suppression rules and constraints
Given the enormous value that optimization provides, should organizations be optimizing every
offer? At one extreme, the organization would let optimization decide all offers; all eligibility and
contact policy rules would be left completely up to mathematics. At the other extreme would be to let all decisions be made arbitrarily, based on gut feel or business rules. The ideal situation, of course, lies somewhere in the middle of these extremes. The exact balance depends on the
organization. There will always be occasions for which the predictive model was not designed
(optimization would not work in those cases), and there will always be value that can be added
with more embedded analytics. An intelligent integration between SAS Marketing Optimization
and the predictive modeling, campaign scheduling and campaign management capabilities of
solutions such as SAS Marketing Automation can help achieve this balance.
 

Success with SAS® Marketing Optimization
SAS has experience using marketing optimization to solve the unique business problems in a
number of different industries. For example:

• A North American catalogue retailer wanted to focus on being smarter about how it
managed the cost structure of its different channels. Having multiple call centers, direct mail
and e-mail channels available, the retailer did not know how to spread offers, or combinations
of offers, across these various channels. By leveraging an existing modeling effort using
SAS, the company was able to exploit the knowledge it had derived about these different
channels for significant campaign performance improvements.

• A North American financial services institution wanted to move beyond standard
solutions for database marketing to lift returns from marketing campaigns. This company has
worked with SAS to combine predictive modeling with SAS Marketing Optimization to create
the best multichannel offer selection and targeting solution in the industry. Using SAS the
company increased expected ROI for a recent campaign by 50 percent and has analyzed
more than 70 offers all at once for a variety of products and more than three million
customers.

• A European telecommunications company had established complex business rules for
prioritizing cross-sell offers. This process of prioritization was largely inefficient and led to a
suboptimal offer allocation. By combining business rules and constraint-based optimization,
this organization has dramatically improved the prioritization process.

Summary
 

SAS Marketing Optimization can efficiently help marketers determine who to contact with which
campaigns in a complex marketing environment where customers could qualify for multiple or
competing offers. Through the use of advanced analytics, SAS solves this problem in a manner
that is superior to traditional prioritization or rule-based systems. An interface designed for
marketers makes it easy for users to enter objectives, constraints and contact policies. The
resulting information is readily available for what-if analysis and can be executed seamlessly
when integrated with a campaign management application such as SAS Marketing Automation.
 

About SAS
 

SAS is the market leader in providing a new generation of business intelligence software and
services that create true enterprise intelligence. SAS solutions are used at more than 40,000 sites — including 96 of the top 100 companies on the FORTUNE Global 500® — to develop more profitable relationships with customers and suppliers; to enable better, more accurate and
informed decisions; and to drive organizations forward. SAS is the only vendor that completely
integrates leading data warehousing, analytics and traditional BI applications to create intelligence from massive amounts of data. For nearly three decades, SAS has been giving customers around the world The Power to Know®.

Ensure Success with SAS^® for Insurance

Insurance is all about providing peace of mind for policyholders. But peace of mind is something that many insurers themselves lack, as uncertainty looms over the issues they face:

Are we over-exposed to catastrophe risk? Will competitors steal the customers we’ve worked so hard – and spent so much – to acquire? How can we tell which customers are profitable and which ones aren’t? Will our agents who drive revenues defect to the competition? All this uncertainty is compounded by the macroeconomic underwriting cycle of alternating hard and soft markets. In addition, insurers must comply with ever-changing regulations and increasing demands from rating bureaus, consumers and investors. Failure to address any of these issues can spell disaster. Delivering peace of mind to insurers SAS can help ease the uncertainty facing the insurance industry. We tackle insurers' top-of-mind issues head-on with proven, industry-specific solutions and a robust foundation technology that enable you to: Build innovative pricing models using the most advanced analytic techniques available. Accurately forecast business trends using our high-performance forecasting server software. Make access to information simple and painless for all users with our business intelligence and advanced analytics platforms. Respond quickly and thoroughly to regulatory and rating bureau demands using transparent reporting applications. Detect and prevent fraudulent activity by mounting a multifaceted defense against would-be fraudsters and organized fraud rings. Effectively manage all aspects of risk – operational, market or credit risk. Determine customer lifetime value and predict behaviors such as attrition and cross-sell response with considerable accuracy and ease. Monitor all these initiatives with easy-to-use, industry-specific scorecards and dashboards. SAS delivers peace of mind for insurers based on a solid foundation for success that includes: An end-to-end platform for data integration, data storage, business intelligence and analytics – all tied together with open metadata. An insurance-specific data model that reduces implementation time for major projects significantly. Our powerful, fourth-generation language, which has been under constant development for more than three decades. Integrated, industry-specific SAS Insurance Intelligence Solutions, a family of flexible, extensible solutions that include prebuilt data and analytic models as well as streamlined processes and techniques that speed up both implementation and results, giving you a fast track to significant ROI. Benefits Manage risk. The ability to assess and manage risk more effectively than the competition is a key differentiator for insurance companies. SAS offers a variety of solutions to support the successful management of all relevant risk types: SAS Risk Management for Insurance provides a consistent, coherent approach to managing risk throughout the enterprise. SAS Financial Management Solutions enhance the transparency and clarity of your enterprise financial information, helping you to fully comply with changing financial reporting regulations and reduce audit risks. Increase customer profitability. We combined our unmatched analytic power with our knowledge of insurance-specific CRM challenges in solutions that empower you to execute a comprehensive CRM strategy: Gain essential knowledge and predictive capabilities for determining customer behavior with SAS Cross-Sell and Up-Sell for Insurance. Determine the likelihood of policy lapses and customer attrition, as well as which customers are worth targeting for retention campaigns, with SAS Customer Retention for Insurance. Use customer data from all touch points to create accurate segments for successful marketing strategies with SAS Customer Segmentation for Insurance. Drive more effective, efficient marketing campaigns with SAS Marketing Automation for Insurance, which combines SAS' advanced analytics with powerful campaign management functionality. Reduce the time and effort needed to produce rate revisions using SAS Ratemaking for Insurance, which facilitates increased pricing granularity and innovation. Give marketers the ability to identify their most- and least-profitable customers over the course of many years, incorporating such factors as cross-sell, claims and retention probabilities, with SAS Customer Lifetime Value for Insurance. Improve operational efficiency. SAS also offers solutions to help you efficiently manage your key internal processes:   Gain insights that enable you to plan and implement effective human capital strategies to derive the most value from employees and intermediaries with SAS Human Capital Management. Go beyond traditional IT performance management and leverage the full potential of every IT resource across the enterprise using SAS IT Management Solutions. Improve financial decision making and optimize financial performance in every corner of your organization using the industry-leading budgeting, planning, consolidation and reporting capabilities of SAS Financial Management Solutions. SAS has served the insurance industry since 1976, and we will continue to develop industry-specific solutions tailored to meet your precise needs and give you The Power to Know®.

Looking for more information on SAS solutions for insurance? Watch the on-demand Webcast "What Insurers Need to Know About Service Oriented Architecture." Download the special sascom supplement on maximizing customer lifetime value. Read related success stories.

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mySAP Customer Relationship Management: Features & Functions

mySAP Customer Relationship Management (mySAP CRM) includes features and functions to support core business processes in the following areas:

Features & Functions of mySAP CRM: Marketing

mySAP Customer Relationship Management (mySAP CRM) enables you to maximize the efficiencies of marketing resources and empower marketers to acquire and develop long-term customer relationships. Marketers can analyze, plan, execute, and measure all marketing activities. With mySAP CRM, you gain a flexible application to power marketing success.

mySAP CRM supports critical marketing processes, including:

• Marketing resource management -- Analyze, plan, develop, implement, and measure all marketing activities to maximize the efficiencies of your available resources and gain visibility and control into your marketing processes. mySAP CRM helps you control and manage your budget and marketing spend. The application also allows you to facilitate collaboration among team members and coordinate marketing activities across the enterprise, increasing the speed and effectiveness of your marketing processes.

• Segment and list management -- Manage enterprise customer and prospect data without the need for IT support. With mySAP CRM, you can create and capture customer profile data to better target and personalize marketing messages, and you can view all relevant enterprise customer information from a central point. Using an interactive, drag-and-drop interface, your marketers can perform ad hoc, high-speed customer segmentation and segment analysis -- and quickly identify opportunities and gain insights into customer segments with data visualization features.

• Campaign management -- Analyze, plan, execute, and measure marketing activities through all inbound and outbound interaction channels to build long-term profitable relationships. With mySAP CRM, you can make the most of dialog marketing by implementing inbound and outbound campaigns that are both multichannel and multiwave. You can develop and execute the best marketing strategy, using constraint-based optimization techniques to determine the optimum marketing mix.

• Trade promotion management -- Effectively manage trade promotions that increase brand equity and achieve sales objectives. With the SAP Trade Promotion Management application, you can gain complete visibility into trade programs at each stage of their life cycles -- to reduce error, improve efficiency, and control trade spend.

• Lead management -- Generate highly qualified, prioritized leads and automate your lead distribution process to handle leads faster. mySAP CRM enables you to align marketing and sales organizations -- and extend your lead management process to partner organizations -- to increase conversion rates. The application provides full visibility into the lead management process, enabling you to optimize all activities.

• Marketing analytics -- Leverage a wide range of analytics, such as customer values, churn scores, and satisfaction scores, to make profitable decisions. Insights gained from mySAP CRM help you understand why marketing activities did or did not work. The application also helps you identify business challenges and opportunities -- and predict customer behaviors, anticipate their needs, and create more relevant, targeted messages.

SAP Trade Promotion Management: Enabling an Integrated, Closed-Loop Promotion Process

In the consumer products industry, trade promotions can account for up to one-fifth of a company's profit or loss. To lower costs, you require functionality for managing promotion processes and budgets, bringing together all involved parties -- inside and outside your organization.

With SAP Trade Promotion Management, you get an application that gives you complete visibility into trade programs at each stage of their life cycles. So you can effectively manage trade promotions that increase brand equity and achieve sales objectives.

SAP Trade Promotion Management delivers powerful connectivity. The application enables a closed-loop process that adds value to each of the five major steps in the trade promotion process: headquarter planning, field accounts planning, sell-in and negotiation, retail execution and validation, and pre- and post-event evaluation and analysis.

At each process step, your entire organization has a single-system, real-time view of all relevant information that allows facts-based decision-making and collaboration. So you can reduce error, improve efficiency, and control trade spend.

Features & Functions of mySAP CRM: Channel Management

mySAP CRM provides an Internet-based solution to manage partner relationships and enable channel partners to sell more effectively. Personalized portals help brand owners manage their partner relationships, collaborate with channel partners, and optimize channel operations. Plus, you can provide channel partners with portal-based access to all the information they need to sell to and interact with end customers.

With mySAP CRM, you can optimize these key channel management processes:

• Partner management -- Manage channel partner relationships throughout the partner life cycle. mySAP CRM enables you to plan and forecast channel sales and revenues, segment your partner base for more effective partner programs and management, and track partner training and certifications.

• Channel marketing -- Motivate partners to sell your products and services rather than competitive offerings. With mySAP CRM, you can provide relevant information to partners, maintain consistent branding, and manage partner incentives. Functionality to manage content, catalogs, collateral, campaigns, and leads -- as well as personalization features and a partner locator -- help you drive demand for your products through channel partners.

• Channel sales -- Give your partners and direct sales force the same knowledge, tools, and expert advice -- and gain insight into demand across all selling channels to effectively forecast future business. mySAP CRM enables a full range of channel sales processes, including account and contact management, activity management, opportunity management, interactive selling and configuration, quotation and order management, multi-tier sales tracking and forecasting, and partner compensation management.

• Channel service -- Ensure consistent and timely service to end customers by providing your partners with the tools and expertise to manage problem resolution and ongoing service relationships. mySAP CRM enables a range of business processes, including partner knowledge management, request management, real-time partner support, installed-base management, and complaints and returns management.

• Channel commerce -- Include partners in collaborative selling across organizational boundaries, and enable end customers to order products and services across your demand network. With mySAP CRM, you can create a collaborative showroom environment and manage distributed catalogs and content. The application also supports distributed and hosted order management.

• Partner and channel analytics -- Get a broad range of standard reports and analyses to determine partner coverage and gaps, partner and channel performance, revenue and sales statistics, the return on your partner investments, your gross margins with partners, and partner utilization. Provide channel partners with reports and analyses relevant to their business.

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