Predictive Web Analytics solutions combine the foundational Web behavior data with predictive analytic application modules designed to quickly deliver online insight.
SPSS solutions make Predictive Web Analytics possible by providing the core capabilities needed to enable predictive analysis of Web data. By providing a highly scalable Web analytics platform, SPSS solutions make advanced analysis of large volumes of data feasible. Web Mining for Clementine enables Predictive Web Analytics with unrivaled enterprise scalability, accuracy, reliability and flexibility—while at the same time preserving visitors’ privacy preferences.
Predictive Web Analytics greatly simplifies the processing of Web data for predictive analysis using Web analytics technology proven over more than a decade—expertise unmatched by any vendor. SPSS technology gathers vast amounts of Web data, enabling you to efficiently utilize data from server-side and client-side collection—such as page dotting—as well as other online and offline applications.
SPSS Web mining technology efficiently scales to enterprise Web analysis demands by processing only the data needed to create an accurate view of online behavior. Accurate user identification, sessionizing of visits, and noise data filtering help ensure that decision makers draw reliable conclusions about current conditions and future events. Industry-leading user identification algorithms clearly identify customers as they transition from "anonymous" to "cookied" status during the course of their lifecycle. This accurate user identification also makes effective multi-channel analysis possible by correlating these online users with offline users. Multi-site, cross-site, and sub-site analytical capabilities enable companies with numerous Web properties to understand user behavior across their entire online business.
Online business event mapping, based on your specific online objectives, performs additional data transformations to prepare raw Web data for predictive analysis. Online business event data improves the integration of data from other channels—such as transactional data and textual data from call center notes—for 360 degree, multi-channel analysis.
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