E-intelligence describes a group of applications that marry e-commerce and business intelligence technologies. E-intelligence is the missing ingredient in most e-businesses today. It provides the information companies require to acquire, cross-sell, up-sell and retain more customers than their competitors as well as continually refine their e-business strategies and increase ROI.

Even though companies deliver products and services, it's the information about those things that makes the sale. Moreover, information is the glue that binds customers and sellers in long-term relationships. According to John McKean in his book, Information Masters: Secrets of the Customer Race, 70 percent of customer value comes during interactions with the seller over time, and these interactions are information intensive.

New dot-com companies are using information as a lethal weapon in their quest to establish brand while acquiring, up-selling and retaining customers in the hyper-competitive e-business marketplace. Other firms are integrating customer information culled from multiple systems inside and outside the company to provide customers with personalized sales, marketing and support. Still others are aggregating point-of-sale and inventory data so that suppliers can better forecast manufacturing demand and manage logistics operations as well as benchmark their performances against competitors and customers' expectations.

Types of E-Intelligence

Patricia Seybold Group uses the term "e-intelligence" to refer to analytic applications that help companies harness information to improve e-customer relationships. There are two types of e-intelligence applications: reflective and proactive.

Reflective E-Intelligence

Reflective e- intelligence applications analyze the effectiveness of Web site designs, e- commerce storefronts and marketing campaigns by measuring customers' Web site behaviors. Most of the source data for these applications comes from Web logs. But full-featured e-intelligence applications also draw from order entry systems, point-of-sale transactions, call center trouble tickets and other operational applications. The categories of reflective e-intelligence applications are:

E-Traffic Analysis. E-traffic analysis applications answer the question, "What's happening on my Web site?" These tools collect and summarize Web logs without throwing away useful detail. These tools can measure:

  • Web site stickiness
  • Most popular pages
  • Most common paths through the site
  • Most common exit pages
  • Average session times
  • Ratio of new to registered users
  • Most common URLs and IP addresses

Armed with this information, companies can continually improve their Web site designs to make it easier for customers and partners to do business with them.
E- Commerce Analysis. These applications are an extension of the traffic analysis programs just mentioned but focus specifically on customer transactions and support requests. These applications answer the tough questions that can spell the difference between success and failure in an e- business. They can measure:

  • Look-to-book ratios (or the percentage of people who buy a product after looking at it on a Web site)
  • Abandoned shopping carts
  • Average selling price per transaction
  • Number of items per transaction
  • Average number of queries or clicks to find items in a catalog
  • Degree of channel cross-fertilization (i.e., customers who browse the Web but purchase at retail stores and vice versa)
  • Degree of Web cannibalization (whether Web sales cause a decline in sales via traditional channels)

E- commerce analysis applications walk companies through the process of redesigning customers' shopping experiences to optimize revenues and customer satisfaction.
E-Marketing Analysis. These applications evaluate the effectiveness of marketing campaigns executed via the Web, e-mail or other electronic media. These applications often measure the relationship of page views to clickthroughs to actual purchases, by product category, customer segment or other variable. In general, these tools measure the effectiveness of:

  • Product promotions
  • Interaction rules governing each campaign
  • Banner ads and other advertising campaigns
  • Affiliate programs
  • Loyalty programs
  • Pricing assumptions
  • Cross-channel marketing programs

E-marketing analysis applications naturally feed data and insights into proactive e- intelligence applications that are designed to optimize customer interactions, maximize the returns on marketing campaigns and enhance customer service.

Proactive E-Intelligence

Proactive e-intelligence applications use a broad range of customer information in real time or near real time to better acquire, cross-sell/up-sell, retain and support customers. The categories of proactive e-intelligence applications are:

E- Personalization. These real-time and near real-time applications are the workhorses of e-businesses. They collect, integrate and mine customer information, profiles and preferences for use in marketing campaigns.

  • Real-Time Personalization. Real-time personalization applications dynamically generate offers, ads and page views to Web site visitors. These applications apply campaign rules to customer information in real time and dynamically generate Web pages to optimize customer interactions. The best of these tools can apply news rules and generate new pages on the fly based on new information gained about the customer at the Web site or call center.
  • Near Real-Time Personalization. Near real-time personalization applications apply rules to customer databases in batch. These applications may broadcast personalized views of syndicated information (i.e., news feeds, weather, sports or financial information) or other types of relevant information (i.e., stock portfolios, events, offers or newsletters).

The purpose of near real-time applications is to cement customer relationships by keeping individuals informed of things they've expressed an interest in hearing about. They can also be used to deliver personalized offers based on a customer's profile or target market segment.
E-Self Service. These applications are designed to give customers and suppliers quick access to account information and other information about the company that is relevant to their tasks at hand. E-self-service applications are also known as extranets or premier pages.

For example, a company might establish an e-self-service application that gives customers and suppliers access to:

  • An ERP application to check account status
  • A data warehouse to run canned and custom reports about historical account activity
  • A product catalog that provides customers with a customized view of products and prices based on pre-negotiated terms and conditions
  • A help-desk application designed to answer frequently asked questions
  • A performance-measurement application to give customers a view into the level of service they are receiving from a vendor
  • Company contact information
  • Collaborative applications, such as calendars, project management applications, group folders and discussion threads to facilitate cross-departmental and cross-company teams.

E-Benchmarks. These applications are supported by a data warehouse of historical information, usually point-of-sale data, but also on-time shipments and deliveries and quality ratings. These extranet data warehouses can be used by suppliers to manage their inventories, improve demand-planning processes and gauge their performances against peers and competitors.

Once companies lay down their basic e-business infrastructure, a competitive differentiator will be how well companies understand and act on the unique needs and desires of their customers. To do this, companies need to deploy e-intelligence technologies and practices to track, analyze and refine their e-business strategies. This will help them keep up with today's fickle customers and stay ahead of the competition.

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