All businesses recognize that great value exists within their customer-related data. They understand that by integrating, organizing, and analyzing this data they can drive actionable business intelligence to improve their marketing, sales, and customer service operations. As the intelligence behind a company's overall CRM efforts, CRM analytics help companies answer questions such as:

• Who are our most valuable customers?

• Which marketing campaigns are delivering our best customers?

• How do we maximize the opportunity to sell other products to our existing customers?

• Who are our "at-risk" customers, and how can we improve their satisfaction and loyalty?

BancBoston Robertson Stephens describes the benefits of obtaining CRM analytics capabilities:

"We believe two abilities have become crucial to success: the ability to analyze and understand the data about the customer base through sophisticated, easy-to-use reporting tools; and to act on that knowledge to customize products, services, and all touch points (sales, call center, marketing) to fulfill customer need in the right way, at the right time, and through the right channels."¹

Effective data collection (warehousing) and analysis (data mining and analytic reporting) are key tools to improve CRM effectiveness for all companies. Companies that have done so have reported improvements in marketing campaign effectiveness, higher sales conversion rates, as well as significant decreases in customer acquisition costs and improvements in customer loyalty. Simply put, CRM analytics fuels a more profitable business.

More companies are beginning to invest in the strategic advantage that CRM analytics offers them. The demand for data warehousing and data mining services is enormous. In 1999, 83 percent of U.S. companies reported efforts or commitments to develop data warehousing facilities. The major portion of growth in the industry has occurred in the last decade – 72 percent of the companies deploying data warehousing have done so since 1995.² Currently, analysts estimate the data warehousing and data mining market to total $20 billion, with CAGR estimated to be 47 percent through 2005.³

Current Options for Deploying CRM Analytics Infrastructure: Build, Buy, or Outsource

The following are core CRM analytics functions:

• Data integration and management (data warehousing)

• Customer segmentation and behavior analysis

• Marketing campaign analysis (analytics and data mining)

• Personalization and recommendation models for targeted marketing, sales, and service applications (predictive data mining)

When a business determines it needs data warehousing, data mining, and analytic reporting capabilities for CRM, it is presented with three approaches; build (in-house development, usually with external consulting help); buy (purchasing off-the-shelf licensed software, often with consulting, as well); or outsource to a managed service.

Build (In-House Development)

In-house development is usually the most expensive option, as the enterprise has to define all of its requirements, pay for software development by expensive experts, and bear all the R&D costs itself.

Building and managing data warehousing solutions in-house is time-consuming and costly. Typical time commitment is one to two years. Often, systems integrators, whether working on billable hours or at a fixed price, build a solution and then exit, leaving the enterprise to maintain, operate, and improve the system. Companies choosing this route must invest heavily in storage and application software and hardware. And the initial hardware and software expenses constitute only a small portion of the total cost, which is largely shaped by maintenance demands, especially those arising from changing requirements.⁴

Many companies that deploy homegrown solutions find themselves frustrated by the cost and complexity of running these systems, even with the help of expensive consultants. Collecting data, managing related systems, and driving value from data is not a core competence of most businesses. They are simply not set up for, nor can they afford to attract and retain the right talent for, solving data warehousing and analysis challenges.

Building and maintaining data warehousing and data mining facilities in-house is just too costly in terms of time and money, assuming a business can even find staff with the rare skills required. A vast majority of data warehousing projects end in failure (85 percent), often after millions have been spent. Forty percent don't even get off the ground.⁵ When data mining applications are added, such as customer segmentation or predictive modeling, these issues are exacerbated as the complexity is greater and the number of experts with the domain knowledge to implement data mining applications is more limited.

Buy (Licensed Software)

The next most expensive route is "buying" licensed software and systems. Not only are the initial fees high, but also an annual "percentage is often charged to renew the license each year. In addition, maintenance fees are required over the life of the software, which can be more than double the initial expense. The current statistic is for every $1 spent initially, $5 more is spent in maintenance. If customization is required, the enterprise will likely pay consulting wages for this additional service. On top of this, the "Buy" approach still means, as with the "Build" option, that companies must buy, configure, and operate large complex systems on their own or with the help of expensive consultants.

Firms that chose to buy licensed software need extensive IT resources and must be prepared to:

• Develop and support the IT infrastructure for the applications.

• Make a large capital investment in acquiring and installing the software. (This makes the software difficult to trial.)

• Develop considerable internal expertise with the software to gain its full utility.

• Cope with regular software upgrades, additional modules and bug fixes.

Outsource to Managed Service

In contrast to the previous two options, it is more effective and economic for companies to outsource to a company that provides data warehousing and data mining as managed services – for example, via hosted applications delivered securely over the Internet, otherwise known as the application service provider (ASP) model.

In this option, a service provider takes on the hardware, software, and personnel costs in exchange for a recurring (usually monthly) fee. Both the enterprise and the service provider win; the enterprise avoids the high in-house infrastructure and personnel costs, while the service provider earns regular revenues, as well as economies of scale that individual enterprises can rarely attain.

Managed CRM analytics services provide a turnkey solution, rapid ramp-up, flexibility, deep expertise, scalability, easy upgrades, and dramatically reduced complexities and costs, all with minimal impact on the enterprise's human resources.

Many companies have identified the benefits of outsourcing. In 1990, U.S. businesses spent $7.2 billion on outsourcing computer operations.⁶ Just eight years later, International Data Corporation (IDC) reported that outsourced IT process spending worldwide was close to $100 billion, and is expected to surge to over $151 billions by 2003.⁷ Jupiter Strategic Planning found that 65 percent of Web companies said they currently outsource analysis or would consider doing so.⁸ IDC goes on to say that marketing applications, specifically customer management software, is the highest growth segment (44 percent versus 15 percent for all applications). Marketing applications are predicted to grow at 50 percent through 2004.⁹

Benefits of the Managed Service Model for CRM Analytics

"Successful outsourcing enables organizations to focus on what they do best – accomplish their mission."¹⁰

The benefits of the managed model for CRM analytics are:

• Lower upfront costs and lower overall risk

• Accelerated implementation

• Low total cost of ownership (TCO)

• Usability, continued improvements and pain-free upgrades

• Outstanding return on investment (ROI)

Lower Upfront Costs and Lower Overall Risk

digiMine has an excellent strategy of providing data warehousing and data mining as an affordable service. There is a good market potential for a service that can provide in-depth business intelligence without the in-house effort normally associated with building and maintaining a data warehouse.

– Dan Vesset, Senior Research Analyst, IDC

Virtually Zero Equipment Costs

In a Forrester study of 40 Fortune 500 companies,¹¹ 95 percent believed the cost to implement a customer data management system would be more than $500,000. Hiring a data warehousing/data mining services company means the enterprise avoids the upfront expenses of software licenses and hardware systems. digiMine, for example, owns and operates the entire CRM analytics infrastructure, including storage, data warehouse systems, analytical and mining software applications, application servers, and software.

Minimal Personnel Costs

Finding data warehousing and mining expertise at a reasonable cost is extremely difficult, as simultaneous capabilities in data aggregation and management, software, database marketing, statistics, and mathematics are required. Seventy-five percent of all companies report they consider 15 percent or less of their IT personnel well-trained or experienced in data warehousing.¹² Due to the shortage of data warehousing and data mining skills, many companies hire outside consultants to train IT personnel. Assuming a company could build the staff in-house, it always runs the risk of losing this expertise to another company once after investing the resources to develop it.

The managed service model enables companies to access talented warehousing and analytics experts without the typical time and expense of building the team internally. Hiring a service company instead of creating a team in-house transfers the costs of recruiting, training, and retaining expertise to the service provider, allowing companies to focus their staff on more essential functions.

Lower Overall Risk, Guaranteed Success

All the way around, because of the lower equipment and personnel costs, faster implementation times (see below), and expertise of a managed service provider, an enterprise that hires a service provider for CRM analytics is taking a much smaller risk than if they purchase and/or develop their own system. In-house projects often cost too much and take too long, usually producing an inferior product at the end. A study by Earl Hadden and Associates found that 85 percent of data warehouse projects fail to meet their intended objectives, and 40 percent don't even get off the ground. By contrast, service solutions are usually guaranteed to deliver results. And if clients are dissatisfied, they can abandon a service provider much more quickly, with much less investment lost.

Accelerated Implementation

We needed a high-powered analytics and data mining solution very quickly. It was apparent that digiMine's approach was the right fit for us, based on their service model for taking on the data management infrastructure and delivering powerful, intuitive analytics that would help us make the right decisions for Xbox.com. It was impressive to see digiMine produce what we needed in such short order.

– Don Hall, director of Xbox.com.

In Forrester's study of 40 Fortune 500 companies,¹³ almost a third believed that implementing a customer data management system on their own would take more than a year. Managed service providers can reduce this time to deployment significantly, because the infrastructure and applications are already built, tested and in operation. digiMine's services, for example, require only six to eight weeks for implementation. Unlike systems integrators who are motivated to extend the length of a project, managed service providers are motivated to get a client's services up and running quickly to initiate service and fees. As a result, "customers begin realizing the benefits of CRM analytics much faster than with solutions deployed in-house.

Low Total Cost of Ownership

At the very least, the [managed solution] approach improves IT overhead by eliminating database administrators, dedicated on-site hardware, and the developers needed to write the data mining algorithms.

–Peter Urban, senior analyst, AMR Research Inc.¹⁴

Lower Ongoing Operating Costs

In a study by Benchmark Research, more than 50 percent of "private and 83 percent of public organizations found that outsourcing cut costs. At the same time, these organizations reported an increase in the quality of the IT services.¹⁵ The Congressional Budget Office estimated that cost savings from 20 to 40 percent could be achieved through outsourcing.¹⁶

Outsourced CRM analytics services, like those offered by digiMine, drastically reduce ongoing budget requirements. As described above, outsourced service providers minimize initial equipment and personnel costs. These savings are realized "continually over the duration of a service agreement.

Pay as You Go

Managed service providers offer monthly pricing that allow clients to amortize costs and pay as they realize the solution's benefits. This is much more cost-effective than enormous upfront expenditures prior to implementation.

Usage-Based Pricing

Rather than paying a one-size-fits-all licensing fee, service provider prices are usually based on data volume and the complexities of analytics to be deployed. Customer costs vary as their business and analytic needs grow and fluctuate. This is a boon for companies that may have inconsistent data volumes or intermittent analysis projects, as well as for small and medium-sized companies whose needs are not as extensive.

Usability, Continued Improvements, and Pain-Free Upgrades

We selected digiMine because they offer powerful, easy-to-use business analytics through a cost-efficient service model. We were especially impressed by digiMine's ability to apply their solutions to our particular objectives and needs.

–Darren Huston, Senior VP, New Ventures, Starbucks

Usable Reporting and Applications

Timely, intuitive reports that business managers can rely on for strategic decision support are the core value of any CRM analytics solution. Development and delivery of powerful but usable analytic reports are often failing points for companies attempting to develop their own CRM analytics solutions. Along with data warehousing and mining infrastructure, managed service providers relieve their clients of this difficult, complex effort.

digiMine provides customized, Web-based reporting on a daily basis. Analytic reports are designed with the business user in mind and are easy to manipulate and interpret – the business user need not be a statistician or rely on one to use the reports. Reports empower analysis of product performance, merchandising, customer behavior, user segmentation and affinities, "geographic distribution, Web site traffic, marketing campaign effectiveness and more. digiMine also provides ready-built "predictive data mining models that can be applied to client CRM and marketing systems for multichannel cross-sell/upsell "recommendations, or personalized marketing campaigns.

A Continually Improving Service

Due to a managed service vendor's need to attract and retain customers, it is more likely to continually innovate features and functions that increase the value of CRM analytics top clients. A managed service evolves and improves more frequently and reliably than both solutions developed in-house and licensed systems. digiMine clients, for example, reap the benefits of its ongoing development without added investment of time, personnel or budget.

Simplified Upgrades and Customization

As a service provider improves and expands its services, new features and benefits are delivered to clients with minimal effort. The service provider manages software development, hardware upgrades, testing and deployment on its own infrastructure. Upgrades, service improvements, new applications and fixes are delivered to the client company seamlessly.

In the same vein, with a managed provider's service commitment and focus on CRM analytics applications, clients can initiate and complete custom analysis requirements and special projects much faster than in-house efforts or with licensed systems.

Economies of Scale

With multiple clients, the CRM analytics service provider gains economies of scale in equipment, service, and expertise that individual companies cannot attain. In the course of delivering its solutions, the service provider develops new skills and capabilities at an accelerated rate. These innovations and efficiencies are passed on to customers in lower prices and better application performance

The Bottom Line: ROI

digiMine's continued success is a clear indication that the hosted services model for data warehousing and analytical services is finding an audience.

–Andrew Braunberg, Analyst, Current Analysis

Improved Business Performance + Low TCO = ROI

As described previously, CRM analytics enhance a company's ability to acquire new customers, sell more to existing customers, and improve customer loyalty. The managed service model maximizes these benefits through fast deployment and improved usability and flexibility to help meet business objectives. In addition, the service model represents lower capital expense, in terms of both initial and ongoing costs, all with lower risk of failure than in-house solutions or licensed systems. The result for companies is a higher return on their investment in CRM analytics.

Conclusion

For companies investigating how to most effectively implement CRM analytics, the best decision is to hire a managed service provider. Through the managed model, they will most effectively reap the benefits of true customer intelligence, which will improve marketing effectiveness, increase revenue and profit margin, and grow customer loyalty. Companies that choose managed CRM analytics service solutions will avoid prohibitively high system and staffing costs and enjoy fast deployment, all at lower risk. Businesses will also realize greater flexibility and usability of the applications, so their CRM analytics applications more easily address their specific needs and objectives. Most importantly, companies choosing the managed service model for CRM analytics will see a superior return on their investment. And common concerns or perceived risks about the managed service model are typically allayed through deeper investigation. Overall, by outsourcing the heavy lifting of CRM analytics infrastructure to a service provider, companies are able to concentrate on what they do best: optimize customer relationships and build their businesses.

About digiMine

digiMine is setting new standards for the delivery of powerful data mining and analytics. digiMine managed service solutions transform raw data into actionable business intelligence for more profitable marketing campaigns, sales interactions, and customer relationships. The company's solutions are powered by a managed data warehouse and delivered via the Internet, providing fast deployment, a low total cost of ownership, and outstanding return on investment. For additional information about digiMine call 425.460.5000 or visit the company Web site at www.digiMine.com.

End Notes

¹ Marshall Senk, Manager Director and Senior Research Analyst, BancBoston Robertson Stephens, November, 1999.

²"Data Warehousing for Business Intelligence," Curt Hall, Cutter Information Corp., 1999.

³ "Data Mining Digs In," Jennifer Lach, American Demographics, July 1999; "A Data Miner Goes for Gold on the Web," Business Week Online, Sept. 7, 2000.

⁴ Gartner Group, 2000.

⁵ "Data Warehouse Technical Guide," Thomas Flanagan and Elias Safdie, The Cordis Group, Inc., 2000; study by Earl Hadden and Associates.

⁶ Kirkpatrick, David, "Technology: Why not farm out your computing?" Fortune, September 23, 1991.

⁷ International Data Corporation, July 8, 1999.

⁸ Jupiter Communications "Usage Analysis – Refining and Managing User Data." March 13, 2000.

⁹ International Data Corporation, "Customer Relationship Management Applications."

¹⁰ "Outsourcing Information Technology," February, 1998, General Services Admin., Wash. DC.

¹² "Data Warehousing for Business Intelligence," Curt Hall, Cutter Information Corp., 1999 Forrester, 2000.

¹³ Forrester, 2000.

¹⁴ Computerworld, April 2000.

¹⁵ Pritchard, Stephen "Outsourcing – the Insider Guide," Independent, August 1998.

¹⁶ Gabig, Jerome S., Jr., "Privatization: A Coming Wave for Federal Information technology requirements," National Contract Journal, Volume 27, Issue 1,1996.