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This document discusses using web data to predict trends and identify early adopters. It notes that the adoption of new technologies follows an S-curve over time. However, with Web 2.0, the adoption curve is compressed, making it important to use timely metrics to find the tipping point and identify early adopters in order to filter for emerging trends.

Predictive Power of Web 2.0 Data Hitwise High Order Bit Bill Tancer GM, Global Research, Hitwise

Hyper-innovation Requires More Timely and Complete Metrics for Actionable Insight

Roger’s Adoption Curve Speed of Adoption is function of: p = initial speed of adoption q = speed of later growth

Bill Tancer General Manager, Global Research 415 597 4201 [email_address] Find out more: - Our Blog: www.ilovedata.com - Science of Search on TIME.com

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Wb7_tancer_bill

1. Predictive Power of Web 2.0 Data Hitwise High Order Bit Bill Tancer GM, Global Research, Hitwise

2. Hyper-innovation Requires More Timely and Complete Metrics for Actionable Insight

3. Roger’s Adoption Curve Speed of Adoption is function of: p = initial speed of adoption q = speed of later growth

4. 2.0 Adoption Compression

5. Finding the Tipping-Point

6. Identifying the Early Adopter

7. Filtering for Trends

8. Bill Tancer General Manager, Global Research 415 597 4201 [email_address] Find out more: - Our Blog: www.ilovedata.com - Science of Search on TIME.com

Wb7_tancer_bill

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