Achieving deep integration

Now that we understand the benefits of fully integrated analytics solutions, some context around levels of integration is also helpful. There are essentially three levels on which analytics tools can be integrated with other web applications: the user interface level; the data and functionality level; and the content delivery level.

With deep integration, like that with the iAPPS Product Suite, your analytics software is interconnected with your other web applications at all three levels. Such an integrated product suite is both user-friendly and provides visitors with the relevant content that Gartner says they want and demand.

»» Level I: User Interface. In an integrated suite of web applications, all modules – analytics, content management, eCommerce, online marketing, – use the same graphical user interface (GUI). Screen layouts, drop-down menus, and icons share a common appearance in all applications.

As a result, the learning curve is shortened for the user – reducing training costs, lowering IT's support burden, and enabling rapid and widespread adoption of the system throughout the enterprise. A common GUI also makes the analytics package easier to use, enabling more rapid reaction in response to discovery on the analytics report of subpar web page performance.

»» Level II: Data Integration. With data level integration, all applications and modules share a common data set. Sharing of information between applications enhances decision-making and simplifies site maintenance and updating.

The page author can make changes for you to review in-line. The date of when the revised page goes live on the site is time-stamped in the analytics package, enabling you to compare page views before and after the revisions to see whether the edits are effective.

»» Level III: Content and Commerce Delivery Integration. At the deepest level, communication automatically takes place between analytics and other applications such as the content management system. Dynamic visitor segments and user profiling drive persuasive, personalized content to the right users at the right time. Result: enhanced user experiences through delivery of relevant, focused content and offers that result in higher conversion rates and revenues.