Web Analytics Overview
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Web Analytics Overview

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Slides used at the USC Annenberg Journalism Director's Forum, Oct. 13, 2009

Slides used at the USC Annenberg Journalism Director's Forum, Oct. 13, 2009

See the YouTube video at http://www.newsnumbers.com/web-analytics-overview-video.html

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Web Analytics Overview Web Analytics Overview Presentation Transcript

  • Finding Meaning in the Metrics October 2009 Dana Chinn
  • Web analytics essentials • Why measuring audiences is different for online • Behavioral vs. attitudinal • Basic site metrics Counting vs. calculating engagement • Social media metrics Understanding followers, analyzing content • Attitudinal research Finding out the “why” of current, new, potential audiences 2
  • Traditional ad-supported business model Newspapers Magazines Radio TV Direct mail ...subsidized audiences Yellow Pages defined by Outdoor demographics, geography HIGH BARRIERS ...few competitors TO ...everyone in its place ENTRY ...can only measure mass e.g., paid circulation3
  • Online ad-supported business model Online Newspapers Direct mail Magazines Yellow Pages Radio Outdoor TV Online-only ...(highly) subsidized audiences defined by individual behavior, attitudes ...few barriers to entry ...change in behavior, business ...little geographic focus ...everyone’s online, competing with each other ...can measure anything (niches, engagement) 4
  • Two ways to understand online audiences Behavioral research: What people did when they visited a site Attitudinal research: What people said they did, and why they go or don’t go to a site 5
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  • Journalism Online projects it will have 100,000,000+ monthly unique visitors “Journalism Online Says Letters of Intent Now Cover More Than 1,000 Media Outlets,” paidcontent.org, Sept. 14, 2009 8
  • Who: Nikki Finke Content: 24/7 unique info about The Industry UVs: “a few” 100,000 Industry execs who visit 10x/day Value: $10 million “Call Me,” by Tad Friend, The New Yorker, Oct. 12, 2009 9
  • What really matters in online? What people do... ...who they are, and what they think. 10
  • Unique visitors visit websites, generate page views. 11
  • A “unique visitor” is actually a “unique computer” 12
  • Unique visitors may be over- or undercounted Work =33 unique visitors = unique visitors Hotel Home = 1 unique visitor Work 13
  • The no. of unique visitors is based on the time period you specify. S M T W Th F S 1 July 6-12 July 13-19 July 20-26 31 The number of unique visitors... ...on July 1 is six; July 31, two. “Daily unique visitors” ...for the week of July 13 is five. “Weekly unique visitors” ...for the month of July is seven. “Monthly unique visitors” 14
  • The math of visits A visit is a period of activity separated by at least 30 minutes of inactivity. A visitor clicks into your site at 1 p.m., surfs for 20 minutes, then clicks into CNN.com. One visit A visitor clicks into your site at 1 p.m., surfs for 45 minutes, talks on the phone for 30 minutes without touching the keyboard, then hangs up and goes back to your site for 20 minutes before clicking into CNN.com. Two visits A visitor clicks into your site at 1 p.m., surfs for an hour, leaves his computer for 29 minutes, and then comes back and surfs for another hour before clicking into CNN.com. One visit 15
  • Calculating engagement Two ratios visits per unique visitor page views per visit One the bounce rate proportion of the page where people enter your Example: 50% site most often 16
  • Visits per weekly unique visitor Example 2.5 visits per week Are visitors coming to your site with the frequency you need to build loyal, satisfied audiences ? If you update your site 24/7, is your content engaging enough to compel someone to visit more than two or three times a week? 17
  • Page views per visit, by week Example 3.6 page views per visit When visitors do come to your site, are they engaging with its content? Does a high number suggest visitors can’t find what they want? 18
  • Bounce rate of top entry pages One visit with one page view to the home page = 1 bounce No. of bounces + No. of visits that started with the home page and had 2+ page views = 100% of visits 19
  • Example Home page bounce rate = over 50% Over half of the visits to the CNN.com home page left CNN.com without clicking into any other pages Best (?) cases: Came only to get the headlines Home page has dynamic content not captured with page views (check your business model) Worst cases: Couldn’t find what they wanted Didn’t like what they saw Source: “Can CNN, the Go-To Site, Get You to Stay?” by Brian Stetler, New York Times, Jan. 17, 2009 20
  • Newsroom numbers vs. advertising numbers Newsroom Advertising • Census data • Panel data 100% of all visitors, visits, Activity from a sample of self- page views for all sections selected people. Only total site data for a limited number of sites. • Internal data • External data Confidential Used to compare sites • Omniture • comScore Google Analytics Nielsen WebTrends Compete etc. etc. • Web Analytics • Interactive Association Advertising Bureau 21
  • Types of social media channels Sharing Networking News Bookmarking Reviews From “Five essentials for social media marketing,” by Lisa Wehr, CEO/Oneupweb, iMedia Connection, July 17, 2009 22
  • Social media: a constant stream of calls to action For consumers the true value of a network is measured by the frequency of engagement of the participants. -- Interactive Advertising Bureau Social Media Ad Metrics Definitions, May 2009 23
  • Understand Twitter’s simple complexity, understand how social media is measured Content Followers 24
  • The perfect (measurable) Tweet • A call to action to participate, engage with you Look at this. Go here. What do you think? • A link To get news, information Tweets are now a primary news source, the new home page To respond to the call to action • A #hashtag and/or keywords • A comment “Commenting9/21/09 http://mashable.com/2009/09/20/commenting-on-retweets/ Pete Cashmore, Mashable, is important, even essential.” 25
  • “Perfect” tweets are less than 120 characters RT/via @handle + call to action/comment + link + #hashtag 100 characters 111 characters Watch handle, hashtag sizes Lost the link Note: Twitter will be changing its RT and comment functions 26
  • Analyzing content Review hashtags, keywords, sentiment See a list of Twitter tools at http://www.newsnumbers.com/socialmedia.html 27
  • Is your news org part of the conversation in real-time web signaling events? “When a burst of tweets citing a particular subject or URL emerges, it’s a signaling event.” --Rishab Ghosh, co-founder of Topsy, a search engine for tweets, in “Live in the Moment,” by Clive Thompson, Wired magazine, October 2009 28
  • Analyzing followers Look for influencers. Review reach, following/follower ratio See a list of Twitter tools at http://www.newsnumbers.com/ socialmedia.html 29
  • Analyze your follower profiles to assess their likelihood of engagement Do your followers identify with your keywords? See a list of Twitter tools at http://www.newsnumbers.com/socialmedia.html 30
  • Attitudinal research Do you know the people behind the clicks? 1. What was the purpose of your visit today? 2. Were you able to complete your task today? 3. If not, why not? 4. If you did complete your task, what did you enjoy most about our site? Caution: Pop-up survey data is a truth but not the complete truth. Pop-ups are only completed by those who feel like it...it’s not a representative sample. 31
  • Do you know who’s not coming to your site, and why? • Start with focus groups, usability studies, etc. (not thinking about you) • Follow with surveys that reach a representative sample of the target audience Measure niche audiences, not “all people who could possibly be interested in coming to our site at any time for whatever reason.” 32
  • Define success by who your audiences are and what they’re doing, thinking Universal Studios Hollywood ad, 2007 33
  • Dana Chinn Lecturer USC Annenberg School of Journalism E-mail: chinn@usc.edu Phone: 213-821-6259 www.newsnumbers.com Blog on web analytics for newsrooms Delicious bookmarks Basic metrics; video metrics Social media metrics methodology Twitter Tools list 34