Research Publication Date: 18 January 2006
ID Number: G00132466
Magic Quadrant for Customer Data Mining, 1Q06 Gareth Herschel
SAS and SPSS are the leading vendors of data mining capability to support a CRM initiative. However, a large number of niche vendors offer complementary or better solutions for specific aspects of customer data mining.
© 2006 Gartner, Inc. and/or its Affiliates. All Rights Reserved. Reproduction of this publication in any form without prior written permission is forbidden. The information contained herein has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. Although Gartner's research may discuss legal issues related to the information technology business, Gartner does not provide legal advice or services and its research should not be construed or used as such. Gartner shall have no liability for errors, omissions or inadequacies in the information contained herein or for interpretations thereof. The opinions expressed herein are subject to change without notice.
WHAT YOU NEED TO KNOW Most enterprises rely on a combination of vendors to enable customer data mining. SAS and SPSS offer broad solutions that will serve most needs that enterprises may have in this market. Chordiant Software, Fair Isaac, Teradata and Unica have demonstrated synergy between their data mining solutions and their other applications. KXEN, Portrait Software/Quadstone and ThinkAnalytics can all be considered complementary to the larger vendors for enterprises willing to trade some analytical sophistication for faster model development.
MAGIC QUADRANT Figure 1. Magic Quadrant for Customer Data Mining, 1Q06
Source: Gartner (January 2006)
Publication Date: 18 January 2006/ID Number: G00132466 © 2006 Gartner, Inc. and/or its Affiliates. All Rights Reserved.
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Market Overview Client discussions indicate a high degree of uncertainty about the best approach to deploying data mining in support of CRM. Traditional approaches have emphasized analytical excellence and have been provided by vendors of best-of-breed data mining tools. Although this approach can work well in environments with a relatively small number of models or where taking the time to reach the right conclusion is feasible, they may not be the most suitable in the context of CRM. Many customer-related decisions must be made quickly (for example, assessing the likelihood of a customer to switch providers). In other cases, there are potentially thousands of models that could be built (for example, identifying the best target customer for thousands of products). Vendors are continually emerging with value propositions based on more than accuracy (for example, automated model building or real-time recommendations for customer interactions), offering the promise of a new source of competitive advantage, even for companies well-versed in data mining and CRM.
Market Definition/Description Customer data mining is the application of descriptive and predictive analytics (such as clustering, segmentation, estimation, prediction and affinity analysis) to support the marketing, sales and service functions. This analysis may occur as an integrated part of an operational application or as a stand-alone analytical application. The analysis of customer data in support of other business functions, such as credit risk analysis or fraud detection, is a related area but is not included within the definition of this market. Generic data mining tools can be used to support marketing, sales and service applications. However, the growing interest in deploying this capability beyond the traditional data mining team to organizations without an established background in data mining is attracting attention for packaged applications that provide more guidance and a process for users to perform CRM analysis.
Inclusion and Exclusion Criteria The focus of the Magic Quadrant for Customer Data Mining, 1Q06 is on vendors that offer the most-relevant and compelling solutions in the market. We used the following criteria to assess vendors for inclusion. As the market evolves, these criteria may be adjusted to reflect changing user requirements and vendor capabilities. Functionality Vendors in this market should provide: •
Packaged applications to support common CRM decisions, such as cross-sell or customer-churn prevention, with data-mining-driven insights.
•
A user interface suitable for business users — such as campaign, segment, product, sales or service managers — to perform analyses.
•
The capability to access data from heterogeneous sources, particularly those with information about customer interactions and transactions — such as customer data warehouses, call centers, e-commerce or Web site tracking systems, as well as thirdparty data providers that supply customer-related information, such as demographic or market spending information.
•
Robust data mining algorithms to provide reliable and scalable insights on different types and volumes of customer data.
Publication Date: 18 January 2006/ID Number: G00132466 © 2006 Gartner, Inc. and/or its Affiliates. All Rights Reserved.
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•
The capability to make the results of the analysis available to the appropriate decision makers — such as senior executives, functional managers, salespeople or call center agents.
Market Presence •
At least 15 referenceable customers using their data mining applications in support of CRM.
•
At least five new clients during the past 12 months.
Vendor Viability The vendor has at least enough cash to fund a year of operations at its current rate of cash depletion.
Added This is the initial Magic Quadrant for Customer Data Mining.
Evaluation Criteria Ability to Execute Of the seven possible criteria for assessing the vendor's Ability to Execute in this market, the vendor's product and market track record are the most important. Three other criteria (viability, marketing success and the customer experience) are of secondary importance, while sales execution and the vendor's operations are of low importance. Product/Service (High): The ability of the product to access customer data, guide the user to perform accurate analysis of typical business problems, and share the results of the analysis with relevant decision makers. Market Responsiveness and Track Record (High): An assessment of the vendor's success in creating and meeting consistent demand for its product, measured in new client wins and growing use in the installed base. Overall Viability (Business Unit, Financial, Strategy, Organization) (Standard): An assessment of the vendor's corporate viability, as well as its commitment to the ongoing development of its customer data mining product line and customer support. Marketing Execution (Standard): An assessment of the vendor's perceived presence in the market. Success in this market requires that the vendor establish credibility not only in the analytics or data mining market but also for CRM issues. Customer Experience (Standard): An assessment of the experience of being a customer of this vendor (separate from the user experience associated with the product). Successful vendors will ensure that their customers gain the full benefit of using the tool by providing appropriate consulting services, as well as enabling customers to learn from each other and to provide input about product direction. Sales Execution/Pricing (Low): An assessment of the efficiency and professionalism of the vendor's sales processes at selling into the multiple buying centers usually involved in customer data mining selections, and the appropriateness of the vendor's pricing model. Although aggressive sales tactics and price gouging can bring success in the near term, they are likely to alienate customers and prospects and jeopardize the vendor's ability to compete effectively in the market in the long term. Publication Date: 18 January 2006/ID Number: G00132466 © 2006 Gartner, Inc. and/or its Affiliates. All Rights Reserved.
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Operations (Low): An assessment of the internal processes and skills required to be a successful customer data mining vendor. This involves having and developing the appropriate mix of marketing, sales, management, development and support personnel, as well as supporting processes such as new product testing. Table 1. Ability to Execute Evaluation Criteria Evaluation Criteria
Weighting
Product/Service
high
Overall Viability (Business Unit, Financial, Strategy, Organization)
standard
Sales Execution/Pricing
low
Market Responsiveness and Track Record
high
Marketing Execution
standard
Customer Experience
standard
Operations
low
Source: Gartner
Completeness of Vision Of the eight possible criteria for assessing the completeness of the vendor's vision in this market, understanding the market and product strategy are the most important. Three other criteria are of standard or low relevance, and the remaining three are not currently relevant to the market or are covered within established criteria. Market Understanding (High): An assessment of how well the vendor understands the current and emerging needs of user organizations in this market. As more organizations apply customer data mining in more aspects of their daily operations, it becomes increasingly important for vendors to understand and communicate the importance of business users, the provision of business and analytic guidance, and the way customer data mining relates to other business processes. Offering (Product) Strategy (High): An assessment of the vendor's product portfolio and planned product enhancements to meet customers' current and future needs. Marketing Strategy (Standard): An assessment of the vendor's ability to establish a clear position in the market about what differentiates its application from other vendors, and to establish relevance for this uniqueness to target customers in CRM-related functions. Sales Strategy (Standard): An assessment of the vendor's strategy for using direct and partner channels. Vertical/Industry Strategy (Low): An assessment of the vendor's recognition that different industries have different customer data mining requirements, and the ability to build or customize solutions appropriate for specific industries. At the current stage of market maturity, organizations are willing to apply best practices from other industries. As the market matures and enterprises increasingly demand industry-specific solutions, the importance of this criterion is likely to rise. Business Model (No Rating): Vendors competing in this market are following the same general business model, so this is not an effective basis for differentiation. If vendors with a different business model enter the market, the importance of this criterion will increase.
Publication Date: 18 January 2006/ID Number: G00132466 © 2006 Gartner, Inc. and/or its Affiliates. All Rights Reserved.
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Innovation (No Rating): Innovation is included as a component in other categories for evaluation, particularly the offering (product) strategy criterion. Geographic Strategy (No Rating): Although regions are adopting customer data mining at different rates, we do not believe that geography will be a significant determinant in the overall evolution of the market or in establishing the selection criteria of user organizations. Table 2. Completeness of Vision Evaluation Criteria Evaluation Criteria
Weighting
Market Understanding
high
Marketing Strategy
standard
Sales Strategy
standard
Offering (Product) Strategy
high
Business Model
no rating
Vertical/Industry Strategy
low
Innovation
no rating
Geographic Strategy
no rating
Source: Gartner
Leaders Leaders are vendors whose performance excels in the customer data mining market segment. Not only are they suitable for the majority of enterprises to consider today, but they also have a significant impact on the direction and growth of the market.
Challengers Challengers are vendors that have entered the customer data mining market primarily to provide an offering complementary to their established business applications. In doing so, they expect to leverage their installed client bases. They typically offer a good breadth of functionality, but their solutions are primarily tied to their own applications.
Visionaries Visionaries are vendors that have a strong vision for the evolution of customer data mining. A visionary vendor is an influential innovator and demonstrates capabilities that mainstream vendors will eventually adopt. In the near term, the vendor may have to achieve sufficient scale, or there may be concerns about its ability to grow and provide consistent execution.
Niche Players Niche players are vendors that have targeted a specific segment of the market. They may be focused on a specific CRM function (for example, marketing), industry (for example, retail), geography (for example, Europe, the Middle East and Africa) or a business problem (for example, churn). Niche players are likely to lack depth or breadth of functionality relative to broader customer data mining requirements and may lack the ability to compete in all geographies or industries.
Publication Date: 18 January 2006/ID Number: G00132466 © 2006 Gartner, Inc. and/or its Affiliates. All Rights Reserved.
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Vendor Comments Chordiant Software Chordiant Software (www.chordiant.com) is a business process management vendor with an emphasis on consumer-facing processes in the financial services and telecommunications industries. Chordiant entered the customer data mining market with the acquisition of KiQ, a Dutch vendor of real-time recommendation solutions. Consider Chordiant's solution in three situations: first, when seeking a best-of-breed, real-time recommendation engine to provide insight about the next best action to take during a customer interaction; second, when selecting Chordiant Marketing Director and seeking a data mining solution; and third, when implementing Chordiant's broader Business Process Management vision and seeking a predictive analytic solution to drive more-insightful processes. For Chordiant to move beyond being a niche player, it must broaden its data mining capability to encompass a wider range of solutions (more visionary) or demonstrate significant traction in its installed base and with new accounts for its data mining solution (higher ability to execute).
Fair Isaac Fair Isaac (www.fairisaac.com) is pursuing a strategy of enabling enterprise decision automation. The combination of its Blaze rule engine and analytical modeling engine can be used to create extremely sophisticated and complex automated decision processes for any business function. To support specific aspects of customer data mining, Fair Isaac has also developed stand-alone analytical applications, such as the Peacock (Pairwise Co-occurrence Consistency) technology for market-basket-analysis-driven cross-sell recommendations. Although the Fair Isaac tools are robust, they have not yet developed broad traction (as data mining applications) in the context of CRM, and Fair Isaac has been slow to establish "mind share" in the customer data mining market beyond its reputation for credit scoring. The use of Fair Isaac for customer data mining is best considered as part of a broader engagement with the vendor for decision automation or when seeking a tool to be combined with a rule engine to integrate into complex rule management environments (for example, combining customer risk assessments with the likelihood of offer acceptance).
KXEN KXEN (www.kxen.com) was founded to automate the rapid creation of large numbers of models, and to build models in environments where there are thousands of potentially significant variables. Using patented technology, KXEN provides a broad set of analytic functions (regression, classification, variable importance, clustering, time series and association rules); but the offering is not an analytic workbench and does not provide a variety of "standard" algorithms, such as decision trees, that enterprises may expect. KXEN's product was conceived as a tool to be integrated into other applications rather than as a complete data mining environment; therefore, KXEN includes only limited functionality in areas such as extraction, transformation and loading or statistical analysis, which enterprises may consider integral to a complete data mining solution. Consider KXEN when creating large numbers of models rapidly in a mature data management environment. Enterprises seeking packaged applications or extensive domain expertise about the application of data mining to support CRM should consider one of KXEN's original equipment manufacturer (OEM) partners, such as Advizor Solutions, Alterian, ClarityBlue, Experian or smartFOCUS.
Portrait Software/Quadstone Portrait Software (www.portraitsoftware.com) offers an integrated data visualization tool and data mining workbench based on its acquisition of Quadstone on 2 December 2005. Quadstone had a
Publication Date: 18 January 2006/ID Number: G00132466 © 2006 Gartner, Inc. and/or its Affiliates. All Rights Reserved.
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track record of innovation in the customer data market, but is best considered as a tool to target specific business issues (particularly customer experience management and customer churn) from a combined service, visualization and data mining perspective. Quadstone recently released a new Web-based interface to its analytics tool, providing more-widespread user access to results, a self-service interface to data exploration and an intelligent search interface to structured data. Portrait Software/Quadstone can be used to enable collaboration between full-time analysts using data mining tools and business users seeking access to the data, and provides a specialized tool to optimize the response rates for campaign management. However, we recommend that clients wait until the implications of the acquisition have become clearer before investing in these applications (see "Portrait Software/Quadstone Deal Shows Mixed Promise")
SAS SAS (www.sas.com) is the largest vendor in the overall data mining market. With the mostcomplete set of data preparation and analytical tools in the market, there are few problems that cannot be solved using SAS technologies. SAS has transferred this credibility to the customer data mining space with an extensive track record of customer successes. However, the general perception of SAS is that its products are expensive and difficult to use. This may not be a significant limitation for dedicated data mining teams requiring a sophisticated tool to perform a range of corporate analysis. For the growing number of CRM-oriented deployments with a parttime-analyst user base and a business model based on a more-limited range of analysis, it can be difficult to justify using SAS rather than other tools in the market. Consider SAS as a best-ofbreed data mining tool to perform the most-complex or critical customer data mining tasks.
SPSS SPSS (www.spss.com) has aggressively pursued the customer data mining market. It has spent the past several years acquiring analytical applications in the predictive (Clementine for data mining and DataDistilleries for real-time predictions) and nonpredictive (NetGenesis for Web site analytics, Lexiquest for text mining and Dimensions for customer survey) markets. SPSS has combined these into a series of applications, such as PredictiveCallCenter (DataDistilleries and Clementine) and PredictiveWebSite (NetGenesis and Clementine). These applications have good market visibility and sales traction, and reflect a strong vision for the analytical side of CRM. Consider SPSS as a best-of-breed data mining vendor with a strong focus on CRM.
Teradata, a division of NCR Teradata, a division of NCR (www.teradata.com), has built its Teradata Warehouse Miner (TWM) application to use the underlying power of the Teradata Data Warehouse. Because its customers have enterprise analytic requirements, Teradata is optimizing not only TWM but also all data mining partner tools by focusing on its Analytic Data Set (ADS) Generator (an effective tool for performing data selection and transformation for subsequent use in any data mining tool, and enabling in-database scoring to provide high performing and scalable analytic models). In the customer data mining market, Teradata has partnerships with vendors such as Fair Isaac, KXEN, SAS and SPSS. Teradata customers should evaluate TWM as a solid generic data mining tool. For packaged customer data mining applications, consider combining the ADS Generator with an alternative customer data mining solution from one of Teradata's partners.
ThinkAnalytics ThinkAnalytics (www.thinkanalytics.com) was spun off from Gentia in late 2001 with a focus on embedded, real-time analytics in the telecommunications industry. ThinkAnalytics is based on an open platform with an open library of extensible components that can be combined to perform a variety of analyses. The models are deployed in the ThinkAnalytics Intelligent Enterprise Server,
Publication Date: 18 January 2006/ID Number: G00132466 © 2006 Gartner, Inc. and/or its Affiliates. All Rights Reserved.
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where they are available for any application (usually targeted at customer-facing applications, such as the call center or Web site) to query for an updated score. In addition to its open data mining platform, the company has added text mining capabilities and embedded a third-party business rule engine. ThinkAnalytics' relatively small size and telephone company/banking packaged applications for CRM, on top of its underlying data mining platform, positions the company as a niche player in the market today. Consider ThinkAnalytics if you are looking for real-time data mining, a strong model-building capability with rapid refresh, a strong orientation toward CRM, and the ability to design and embed your own data transformation or analytic components into a broader framework.
Unica Unica (www.unica.com) is an enterprise marketing management (EMM) vendor with modules for most elements of marketing functionality, including data mining (Affinium Model). Although Unica's origins are in data mining, its incremental development and sales effort has been in other areas of EMM. Affinium Model is well-regarded in the industry as a tool that enables rapid comparison of the predictive performance of algorithms. Unica's limited incremental development has been in ease-of-use areas, such as a Web-based user interface, data pre-processing wizards and new reports, rather than in the underlying analytical capability of the product (for example, for text mining). Unica has built some tailored applications on top of the underlying product to complement its core campaign management offering (such as Segmenter, Response Modeler and Cross Seller), but has strategically chosen not to expand beyond this target audience. Companies using or evaluating Unica for the other components of its marketing solution (particularly Affinium Campaign, which yields the greatest synergy with Affinium Model) should evaluate Affinium Model.
RECOMMENDED READING "Determine the Best Customer Predictive Analytics Approach" "Select Customer Data-Mining Vendors Based on Focus and Vision" "Criteria to Select a Data-Mining Vendor for CRM" "Magic Quadrant and MarketScopes: How Gartner Evaluates Vendors Within a Market"
Acronym Key and Glossary Terms ADS
Analytic Data Set
EMM
enterprise marketing management
OEM
original equipment manufacturer
RTD
Real-Time Decisions
TWM
Teradata Warehouse Miner
Note 1 Other Vendors Relevant to This Market Angoss Software (www.angoss.com) did not provide sufficient references to meet the criteria for formal evaluation in this Magic Quadrant. Angoss (KnowledgeSeeker and KnowledgeStudio) is a data mining workbench provider and a traditional competitor to SPSS' Clementine or SAS' Enterprise Miner. Angoss has developed packaged applications primarily targeting financial Publication Date: 18 January 2006/ID Number: G00132466 © 2006 Gartner, Inc. and/or its Affiliates. All Rights Reserved.
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services industry clients. The applications include FundGuard, a sales channel optimization system for mutual fund and annuity wholesalers; Claims & Payments Analysis, a claims analysis system for insurance claims auditors and investigators; and Credit Risk Analytics, a portfolio monitoring and strategy assessment solution for credit risk managers and analysts. Intelligent Results (www.intelligentresults.com) does not yet have sufficient market presence for formal evaluation in this Magic Quadrant. Intelligent Results was founded with a specific focus on the value of integrating text mining into the data mining process. It also has focused on the financial services industry with a variety of packaged applications targeting CRM and non-CRM aspects of the relationship, such as customer attrition and credit settlement/collections (see "Cool Vendors in Customer Relationship Management, 2005") Oracle (www.oracle.com) did not provide sufficient references to meet the criteria for formal evaluation in this Magic Quadrant. Oracle's history in this market dates to its acquisition of Darwin in June 1999. The Darwin application has been completely rewritten, and Oracle Data Miner is tightly integrated within the Oracle database, with the model building and scoring both carried out in SQL code within the database. In 10gR2, Oracle added support for decision trees, anomaly detection, automated data mining, fast SQL-apply scoring and a new wizard-driven graphical user interface. Enterprises considering Oracle will satisfy many of their data mining needs with Oracle Data Miner or the new Oracle Spreadsheet Add-In for Predictive Analytics, and can draw on Oracle's application group for easier-to-use, faster-to-deploy templates for specific CRM-centric analysis (for example, Oracle Marketing and Oracle Personalization). SAP (www.sap.com) did not provide sufficient references to meet the criteria for formal evaluation in this Magic Quadrant. SAP includes data mining capabilities as an embedded component of mySAP CRM. Many SAP customers are unaware that they already own the SAP customer data mining solution. It includes the most-common algorithms used in customer data mining analysis (association analysis, clustering, decision trees and regression, as well as ABC classification and weighted score tables). Because it is a single integrated solution, SAP customer data mining may result in significant implementation and software license savings. Siebel Systems (www.siebel.com) could not provide sufficient references to meet the criteria for evaluation due to the newness of the Siebel Real-Time Decisions (RTD) application. Embedded in RTD is a third-party data mining tool, which Gartner believes is from Sigma Dynamics. The integration with Siebel's call center application and domain expertise in the call center market make this a tool that Siebel customers investing in RTD capability must evaluate. Oracle/Siebel likely will continue the OEM partnership for RTD, but likely will rely on open connectors between Siebel Business Analytics and the underlying platform to leverage whichever data mining system the client wants. SSA Global (www.ssaglobal.com) entered the customer data mining market with the acquisition of Epiphany in September 2005. Epiphany's success in the customer data mining market came from its real-time recommendation engine, which SSA is continuing to make available as a standalone solution, as well as integrating it into its own CRM suite. The acquisition has reduced viability concerns with which Epiphany previously struggled. Since the acquisition, Epiphany has continued to win new deals.
Evaluation Criteria Definitions Ability to Execute Product/Service: Core goods and services offered by the vendor that compete in/serve the defined market. This includes current product/service capabilities, quality, feature sets, skills, etc.,
Publication Date: 18 January 2006/ID Number: G00132466 © 2006 Gartner, Inc. and/or its Affiliates. All Rights Reserved.
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whether offered natively or through OEM agreements/partnerships as defined in the market definition and detailed in the subcriteria. Overall Viability (Business Unit, Financial, Strategy, Organization): Viability includes an assessment of the overall organization's financial health, the financial and practical success of the business unit, and the likelihood of the individual business unit to continue investing in the product, to continue offering the product and to advance the state of the art within the organization's portfolio of products. Sales Execution/Pricing: The vendor’s capabilities in all pre-sales activities and the structure that supports them. This includes deal management, pricing and negotiation, pre-sales support and the overall effectiveness of the sales channel. Market Responsiveness and Track Record: Ability to respond, change direction, be flexible and achieve competitive success as opportunities develop, competitors act, customer needs evolve and market dynamics change. This criterion also considers the vendor's history of responsiveness. Marketing Execution: The clarity, quality, creativity and efficacy of programs designed to deliver the organization's message in order to influence the market, promote the brand and business, increase awareness of the products, and establish a positive identification with the product/brand and organization in the minds of buyers. This "mind share" can be driven by a combination of publicity, promotional, thought leadership, word-of-mouth and sales activities. Customer Experience: Relationships, products and services/programs that enable clients to be successful with the products evaluated. Specifically, this includes the ways customers receive technical support or account support. This can also include ancillary tools, customer support programs (and the quality thereof), availability of user groups, service-level agreements, etc. Operations: The ability of the organization to meet its goals and commitments. Factors include the quality of the organizational structure including skills, experiences, programs, systems and other vehicles that enable the organization to operate effectively and efficiently on an ongoing basis. Completeness of Vision Market Understanding: Ability of the vendor to understand buyers' wants and needs and to translate those into products and services. Vendors that show the highest degree of vision listen and understand buyers' wants and needs, and can shape or enhance those with their added vision. Marketing Strategy: A clear, differentiated set of messages consistently communicated throughout the organization and externalized through the Web site, advertising, customer programs and positioning statements. Sales Strategy: The strategy for selling product that uses the appropriate network of direct and indirect sales, marketing, service and communication affiliates that extend the scope and depth of market reach, skills, expertise, technologies, services and the customer base. Offering (Product) Strategy: The vendor's approach to product development and delivery that emphasizes differentiation, functionality, methodology and feature set as they map to current and future requirements. Business Model: The soundness and logic of the vendor's underlying business proposition. Vertical/Industry Strategy: The vendor's strategy to direct resources, skills and offerings to meet the specific needs of individual market segments, including verticals. Publication Date: 18 January 2006/ID Number: G00132466 © 2006 Gartner, Inc. and/or its Affiliates. All Rights Reserved.
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Innovation: Direct, related, complementary and synergistic layouts of resources, expertise or capital for investment, consolidation, defensive or pre-emptive purposes. Geographic Strategy: The vendor's strategy to direct resources, skills and offerings to meet the specific needs of geographies outside the "home" or native geography, either directly or through partners, channels and subsidiaries as appropriate for that geography and market.
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Publication Date: 18 January 2006/ID Number: G00132466 © 2006 Gartner, Inc. and/or its Affiliates. All Rights Reserved.
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