© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Internet Marketing & e-Commerce Ward Hanson Kirthi Kalyanam Requests for permission to copy any part of the material should be addressed to: PERMISSIONS DEPARTMENT THOMSON BUSINESS and ECONOMICS 5109 Natorp Boulevard Mason, OH Phone: (800)

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Part Three: Chapter 16 Online Research “The first problem of our business is to win an audience, hold an audience, interest an audience.” William Paley, Radio as a Cultural Force

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Running a Survey As research tools move online, the political landscape offers lessons Famously, the polling-based prediction of “Dewey Defeats Truman” in 1948 In 1936, a survey based on telephone and auto ownership predicted that Alfred Landon would beat Franklin D. Roosevelt in the presidential race

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Running a Survey SOURCE: National Atlas of the United States What happened instead: Roosevelt swept the election – poll problems stemmed from asking wrong questions or wrong people

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Types of Online Surveys Convenience surveys useful for exploratory research, but no control for sample bias or project sample estimates to full population

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Types of Online Surveys Examples of convenience surveys –Entertainment surveys provide interactive content, track fan base, brand allegiances –Unrestricted self-selected surveys offer early insights, but complicated by coverage bias from repeat responders –Volunteer option panels allow operator to control for repeat responders, use weighting schemes

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Types of Online Surveys Probability surveys require sampling frame to provide accurate projection to relevant population

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Types of Online Surveys Examples of probability surveys –Intercept surveys catch shoppers, voters at the point of action –List-based surveys create sample frame from registered user base –Mixed modes, pre-recruited panels and full population probability samples

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Measuring Survey Quality Coverage dependant on Internet penetration and technology issues Self-selection bias can skew representation of population Response rate can be improved through language, incentives, follow up Measurement error from confusing wording, incomplete alternatives, design and narration considerations

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Finding the Right Audience Choosing between panel and log file measurements –Tracking web traffic in log files relays broad patterns but requires adjustments for problems of failed responses, system crashes, estimating unique visitors –Tracking panels of households allows tracking of all sites visited by household, audience duplication, and demographics

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Finding the Right Audience SOURCE: Adapted by authors from Yahoo!Research Panel versus log file measurements

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Finding the Right Audience Tracking through domain structure –Understanding the hierarchy: properties, media titles, channels, groups –Crucial site metrics can vary across hierarchical classifications

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Finding the Right Audience SOURCE: Data Source comScore Media Metrix, figure by authors Hierarchical classification structure used for tracking media entities

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Finding the Right Audience Recognizing audience patterns and duplication at web sites –Some overlap can be useful, but too much wastes resources and user time –Server log files can provide details on surfing patterns within sites

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Finding the Right Audience SOURCE: Raw data from comScore Media Metrix, figure by authors Visitor overlap across sports sites, April 2005

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Finding the right audience Source and loss analysis offers context for online visits –Web logs capture referring URL (the source), panel-tracking services can show a site user’s next destination (where lost) –Useful for audience building and competitive analysis

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Finding the right audience SOURCE: Raw data from comScore Media Metrix, figure by authors Source loss analysis for Bebe.com, April 2005

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Finding the Right Audience Demographic and behavioral consumption patterns –Building user profiles based on race, gender, age, household size, income –Behavioral data more actionable, information on products of direct interest –Composition index measures proportion of the traffic at a web site that consist of visitor matching a certain profile

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Finding the Right Audience Reach, frequency and cost per thousand impressions (CPM) –Reaching a specific number of users with the right frequency and context at lowest CMP crucial to targeting right audience

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Congestion and Delay The impact of delay changes based on expectations, the activity affected, and perceptions of the cause and control Sources of delay: –Network outages –Server lags –Transmission lags –Access lags

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Congestion and Delay The full Internet lag experienced by users

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Congestion and Delay Monitoring is the most basic step in understanding, managing delays –Data monitoring tools typically only track server lag –Internet companies monitor total lag with synthetic monitoring/sampling approach

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Congestion and Delay Managing perceptions of delay –Duration or countdown information to manage perceived wait time –Anchor and adjustment model holds that first few pages on a site influence user’s perception of site performance –Important for initial pages to load quickly

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Congestion and Delay

© Copyright 2006, Thomson South-Western, a division of the Thomson Corporation Congestion and Delay SOURCE: Weinberg, Berger, and Hanna, “A Brief Updating Process for Minimizing Waiting Time in Multiple Waiting Time Events: Application to Website Design.” Journal of Interactive Marketing 17, no 4 (2003): 24-37