Eyes on The Prize

Integrating Web-generated data into your broader enterprise BI strategy is now a crucial factor in transforming information into competitive advantage

By Jack Hafeli

The evolution of new technology, particularly the Internet, has enabled new means of collecting customer-centric, relationship-based data. That data becomes information. The information becomes knowledge. Knowledge leads to competitive advantage, and competitive advantage translates into profits. And always, business analysis requirements should drive the process.

The Internet gives organizations of every size a network architecture that enables common connectivity, a standard browser interface, reduced training expenses, low cost of deployment, and virtually maintenance-free operation. Yet, as with each new generation of technology, all organizations must make the Web and all the information it contains an integral part of an overall business intelligence (BI) strategy.

However, in order for any Web-generated information to be valuable, it must fit into a context that is consistent with your organization's overall value proposition. If it has a solid BI foundation, your enterprise will have a customer-centric data warehousing strategy, a clear analytic application focus, and an understanding of the asset value of its information and how to use that asset to gain insight into your business. The introduction of new, Internet-based technology should not distract you into deploying that technology outside this context.

Regardless of whether they understand and accept it, all organizations -- dot-coms, manufacturers, retailers, distributors, or service organizations -- have become "information" companies. As businesses worldwide recognize the strategic value of information, particularly Web-based data, Web analytics -- the integration of Web-generated data and business analysis into a broader enterprise data warehousing and analytic application strategy -- will become crucial for translating information into competitive advantage. And, unlike products and services, pricing, and market positioning, all of which your competitors can openly view and learn from, Web analytics can capture and evaluate customer information that can be kept within the confines of your organization. There you can integrate it with existing internal information, such as purchasing and customer demographics, and apply it to knowledge-based decision making. For example, sales analysis, promotion analysis and planning, and customer and product profitability analyses can all be more robustly applied to business decisions if you integrate them with Web and other internal data.

As I explained earlier, a robust BI technology strategy tied into the overall business strategy is the most effective way to capture the value of Web analytics. Specifically, a Web-based data warehousing delivery strategy can further leverage all the information generated by and available to an organization, including insights gleaned from BI applications such as Web analytics. For any company that wants to leverage its investment in data warehouse and Web technologies, integrating Web-based data with a customer-centric data warehouse and Web analytics is crucial. Combined, these technologies can serve as powerful tools for affecting a faster return on equity and lower risk.

Web Analytics and Its Many Forms

"Web analytics" is a fairly generic term. Depending on organizational priorities, economics, vertical industry nuances, competition, corporate culture, and a host of other influences, Web analytics can take very different forms, including any or all of the following:

* Clickstream analysis, or analyzing the way visitors navigate or interact with your Web site. This type of basic analysis is typically intended to improve the visitor's experience -- to make interaction more intuitive, enjoyable, or valuable. This process can occur whether the Web site is purely informational, an active e-commerce site, or anything in between. Any organization with a Web site of any kind should be doing this kind of Web analytics.

* Analyzing e-commerce sales activities. This is the classic sales analysis every organization conducts with data from operational systems, including order entry, shipping and distribution, and accounts receivable. Frankly, every firm that has an e-commerce system in place should be performing this type of sales analysis. For companies that are new to e-commerce and have more traditional sales channels in place, system and data integration -- commonly known as "clicks and mortar" integration -- is critical for seeing the full business picture.

* Tracking your continuing relationships with Web site visitors. This fairly intuitive process occurs when your Web site serves as a means of acquiring new revenue-generating customers. If we are to apply the broadest definition of "customer," then even the most casual visitor to your site should be well treated. When you understand how users are navigating and interacting with your Web site -- using the clickstream analysis I previously described -- the next logical progression is to analyze and understand your ongoing interactions with these visitors as they become customers. This is the e-business component of a customer relationship management (CRM) strategy, regardless of whether your Web site can support e-commerce transactions.

Key Components

As an emerging technology with the potential to enhance competitive advantage for any company, Web analytics has gained momentum from two key technology trends: First, a growing number of companies now view information as a strategic component of their businesses. Second, using the Internet as a network platform is becoming much more common.

Fueled by these two trends, the Web has become a widely accepted source of customer information that you can tap for clues about how to conduct business and supplement intelligent decision-making. In fact, InformationWeek identified e-business intelligence as one of the key drivers behind the projected growth -- $150 billion in sales by the year 2003 -- of data warehousing.

The first step toward integrating Web analytics with your BI strategy is to recognize that information, in and of itself, can offer a strategic, competitive advantage to organizations that establish systems for sharing information across the enterprise. Organizations firmly subscribed to this view can make optimal use of Web analytics. It goes without saying that Web analytics should be tied into the organization's overall value proposition: Don't get caught up in implementing technology for technology's sake.

It's also critical to have a customer-centric data warehousing strategy in place, an architectural strategy that will let your enterprise leverage all information generated by and available to it for communicating with customers. When a data warehousing strategy is in place, you should build a customer-centric data warehouse system to ensure that all the information systems available to your organization -- Web servers, transaction and backroom processing systems, and BI and decision-support systems -- are integrated.

Such "closed-loop" integration is critical to any customer-focused BI strategy. For instance, a banking organization may interact with its customers via e-commerce, a traditional call center, and face-to-face customer activity. Without a truly customer-centric data warehouse in place, the bank's employees have no way of knowing the extent of business individual customers have with them. For example, does John Doe have CDs, a mortgage, auto loans, and a savings account? If transaction and other back-office systems are not tied to the front-office, customer-facing systems, system users lack a complete view of their customers and thus the ability to make knowledge-based business decisions that affect those customers. A closed-loop system facilitates best-customer response, as well as distribution and integration of all Web-based and operational information. It lets your organization take advantage of the Web as an additional source of new information about its customers.

With a closed-loop approach, the whole will clearly be greater than the sum of its parts, enabling your business to develop much richer relationships with customers. And while converting or building a customer-centric data warehouse may at first seem to be an enormous task, the effort can pay off handsomely in the long term by giving you a more complete view of your individual customers. With this knowledge in hand, your organization can interpret and act upon data to enhance customer interactions and relationships, and to support your overall business strategy.

When planning for the implementation, it's also important to take the time to fully understand the scope of the proposed BI application. Start simple and keep development of the system active and ongoing. Be prepared to make changes; accept the fact that your technology choices won't be ideal the first time out. Remember that the data will be useless if not tied to a business metric -- a data measure captured for its own sake with no analytic purpose -- and take steps to ensure that the source data will be clean and accurate.

It's also important during planning to take a stance in favor of those who will use the system. In other words, think like a customer -- whether that customer is an internal employee or an end customer. Be open-minded and creative about ways to use the information that's been collected: Be prepared to learn something new.

Furthermore, remember that Web analytics extend beyond analyzing clicks, to integrating information about online activity with internal customer intelligence, giving users a unified understanding of the customer. As a result, Web analytics can significantly contribute to the evolution of intelligent e-business by actually simplifying complexity and creating opportunities for proactive interaction with customers.

Getting More Customer Information

When you've designed a Web-based delivery strategy, you can direct it to benefit three key groups within the business: employees, supply-chain partners, and customers.

At first glance, for an organization's internal audience, Web analytics simply make traditional client/server-based analytic applications run over the Internet. In addition to having a new platform to run on, the Web gives employees a means to interact with customers, suppliers, investors, the media, and others.

However, when integrated with a data warehouse that is truly customer-centric, the Web acts as an added source of information about customers, giving users a whole new dimension of data they can use to personalize their customer-service efforts. For example, in the business-to-business realm, organizations can use Web analytics to identify most profitable customers and take steps to develop appropriate relationships with them.

The Web has also caused other, more dramatic shifts in the way employees analyze information to make business decisions. Instead of a handful of analysts who spend the majority of their time poring over data, Web-based data warehousing technology makes information affordable and readily available to many users across the enterprise. It lets them analyze data and generate reports to help facilitate day-to-day decision-making that is measurably more accurate and efficient. (For example, line managers could receive financial analysis capabilities over the Web.) In essence, Web access gives users the tools they need to perform necessary business functions accurately and efficiently.

STOKING THE FIRE

THE TOP FIVE TRENDS FUELING WEB ANALYTICS * The Internet has become a standard enterprise network platform. * Customer-centric analytic strategies are growing in popularity. * Information is now recognized as a strategic enterprise asset. * Organizations consider the Web a rich source of customer information and a viable platform for doing business. * Companies are busily integrating their information assets, inbound and outbound information flows, and enterprise value proposition.

Collaborating With Supply-Chain Partners

In addition to enhancing data warehouse applications within the enterprise, you can leverage Web analytics for better information collaboration and integration across the supply chain.

The growing field of collaborative planning, forecasting, and replenishment (CPFR) is one example of leveraging intelligent e-business. CPFR standards, created by the Voluntary Interindustry Commerce Standards (VICS) organization, let supply-chain partners work together to the benefit of all parties. A Web implementation of CPFR standards allows supplier-manufacturers and retailers, for instance, to compare and fine-tune product forecasts, thus improving forecast accuracy, reducing inventory levels and costs, improving or eliminating out-of-stocks, and increasing sales. In one pilot implementation by Syncra Systems Inc., supply-chain costs fell by 30 to 35 percent, and revenues for both the supplier and the retailer increased by 10 to 50 percent.

Similarly, in the automotive industry, Web exchanges let manufacturers find all pricing, inventory, and availability data about parts and materials. This capability gives manufacturers the flexibility to make just-in-time purchases of parts and materials, making business transactions much more efficient.

Technology-Enabled Customer Interaction

Online businesses need a more thorough understanding of what drives customer acquisition, conversion, and retention. Particularly in the area of customer relationship management (CRM), Web analytics signals the next generation of technology-enabled interaction. Information needs and capabilities become much more extensive than simply counting the number of visitors to a Web site when using Web analytics to reach customers. Understanding buyer behavior patterns on your site, the effectiveness of advertising and promotions, and how to best leverage cross-sell and up-sell opportunities are all critical components to driving online performance.

The delivery of analytic solutions can extend far beyond interaction with current customers. Using data stored in the warehouse, an organization can initiate proactive information exchanges with financial analysts, shareholders, and even the general public. Web analytics can provide a range of information, from very straightforward analysis to more sophisticated, intelligent e-business solutions that invoke a change of activity or prompt the user to provide more information, based on thresholds that have been incorporated into the system. In addition to driving online transactions, your business can leverage Web analytics to give customers the information they would otherwise have to seek elsewhere. For example, a manufacturer of food products could proactively provide information on complementary product offerings, grocery retailing trends, restaurant ratings, or other news related to its products and services. That's a value-added service that can build customer loyalty over time.

The Web lets organizations collect information from many new sources and use it in many new ways. Those companies that integrate all the data and use it most creatively -- incorporating it into every form of customer contact -- will reap the greatest benefits. By integrating Web-based customer data with mainframe data and backroom transaction processing, an organization can truly leverage the technology to generate new business. Ultimately, these personalized customer interactions can create opportunities for additional transactions, bringing in added revenues that would otherwise be impossible to realize.

Taking the technology one step further, data warehouses can include proactive analysis mechanisms that not only evaluate specific thresholds, but then actually make recommendations to the users, giving them immediate access to alternative solutions. In essence, the system prompts proactive interaction with its customers, creating opportunities for them to conduct additional transactions. The cost of the interaction is pennies. By comparison, the resulting return on the company's data warehousing investment is huge.

Facilitating Knowledge-Based Interaction

For organizations with a thorough BI strategy in place, Web analytics technology can benefit the extended enterprise, including internal audiences, supply-chain partners, and customers. It can arm many employees within an organization with the tools they need to become analysts. It can facilitate collaboration among multiple players in the supply chain, and it can create opportunities for additional transactions and proactive, personalized communication with a diverse group of customers. Ultimately, Web analytics can be the key to competitive advantage for any organization doing business in the rapidly changing landscape of the new, Internet-driven economy.

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Jack Hafeli (jhafeli@thinkfast.com) is director of consulting services, Midwest region, for ThinkFast Consulting Inc. (www.thinkfast.com). Hafeli has more than 20 years of experience in the consulting and software business, most of it involving the design, creation, and implementation of analytic business intelligence applications.