Web Analytics Maturity Model
Throughout this book, we’re going to look at a maturity model for web visibility. The first of these models is web analytics, shown in Table 5-3. It borrows heavily from work by Bill Gassman of Gartner and Stephane Hamel of Immeria, and shows how companies progress through various levels of maturity with their web analytics.
Table 5-3. The Web Analytics Maturity Model (adapted from Stephane Hamel and Bill Gassman)
Maturity level | Level 1 | Level 2 | Level 3 | Level 4 | Level 5 |
---|---|---|---|---|---|
Focus? | Technology: make sure things are alive | Local site: make sure people on my site do what I want them to | Visitor acquisition: make sure the Internet sends people to my site | Systematic engagement: Make sure my relationship with my visitors and the Internet continues to grow | Web strategy: Make sure my business is aligned with the Internet age |
Who? | Operations | Merchandising manager | Campaign manager/SEO | Product manager | CEO/GM |
Analytics | Page views, visits, visitors, top ten lists, demographics, technographics | Path analysis, funnel reports, A/B testing, KPIs, dashboards | Merchandising, segmentation, SEO, community referrals, campaign optimization, personas, KPI alerts | Multichannel aggregation, cost-shifting analysis, lifetime visitor value, personalization, dynamic content serving | Multichannel sales reporting, activity-based costing, balanced scorecards, strategic planning, predictive analytics, integrated user experience |
Most organizations begin by looking only at traffic. They then turn their efforts ...
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