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IndexNote to the Reader: Throughout this index boldfaced page numbers indicate pri-mary discussions of a topic. Italicized page numbers indicate illustrations.

AA/B tests

in behavior targeting, 302as first test, 81, 209overview, 197, 197pros and cons, 198

Abandonment Rate metric, 55benchmarks, 218importance, 73, 152

Absolute Unique Visitors metric, 39–43accuracy vs. precision, 284–285action dashboards, 288

benchmarks and segments, 291–292consolidated, 290–291critical few metrics, 292–293elements, 288–290, 289evolving, 294guidelines, 291insights in, 289, 293single-page rule, 293–294

Actionable Web Analytics (Atchison and Burby), 437

actionsactionable insights, 4–5, 422actionable testing ideas, 202–204actionable vs. knowable in surveys,

184, 184metrics for, 36

Actions/Steps quadrant in action dashboards, 290

Activity metric for Twitter, 272Ad Planner tool, 4, 214

demographic segmentation analysis, 236–237, 237

psychographic segmentation analysis, 238, 238

search behavior, 239self-reported data, 219, 220

ad position in PPC, 113–114, 113–114Adblade ad provider, 236Aden, Timo, 400administration costs, vendor questions

about, 23–24Adobe AIR technology, 248–249ads, number and layout, 203AdSense for blog ads, 264, 395AdWords Keyword tool

campaign tracking, 309competitive intelligence, 217integration with, 26keyword expansion analysis,

234, 235paid clicks, 110

Affinium netInsightcookies, 129SeO analysis, 102tags, 140in three-bucket strategy, 29

aggregate data vs. customer behavior, 93–94, 93–94

AIR technology, 248–249Alexa toolbar, 214All Visits metric, 103, 103, 108Alltop site, 244Also Visited reports,

223–224, 224Amazon, video use by, 273Amethon company, 251

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analysesaction-driving, 412–415, 413in tool selection strategy, 17–19vendor questions about, 24

analytics managers and directors hiring guidelines, 403–406

Analytics Talk blog, 400Android-based phones, 250annual support costs, vendor questions

about, 23applications

analyzing, 248–249, 248data limitations, 139

areas of caution in lab usability studies, 174–175

artificially intelligent visual heat maps, 192–193, 193

Atchison, Shane, 437Atlas Solutions, 236Attention Tracking reports, 276, 276attributes

of analytics managers, 404metrics, 59–62, 61

attribution in multitouch campaigns, 358

alternatives, 366–368, 366challenges, 364–365issues, 359–361, 360models, 361–365, 361overview, 358–359summary, 368

Audience Attention reports, 276, 276audience growth in blogs, 258–260, 259audience identification in competitive

intelligence, 235–240, 236–238, 240

Audience Science company, 299auditing data, 287author contributions to blogs,

257–258, 258Authority metric, 262, 262authorized consultants, vendor

questions about, 24

automated modeling engines in behavior targeting, 300, 300

availability factorsin SLAs, 32–33tool selection strategy, 18

Average Order Value metric, 109, 109, 153–154, 154

Average Position reports, 113Average Revenue per email Sent

metric, 122Average Shared Links Click-Through

Rate (CTR) metric, 268–269, 269Average Time on Site metric, 165Average Time to This Page metric, 83Average Value metric, 269average Visits per visitor metric,

162–164, 163averages, 330

distributions, 331, 331segmentations, 330–331, 330

Avg. Time on Site metric, 77, 114, 114

BB&H Photo Video site, 224–225, 225B2B (business-to-business) websites,

166–168Bachman, Jess, 398–399bad exit tracking, 55, 151barriers to web measurement, 432–433

budget and resources, 433–434data excess, 435–436data reconciliation, 436–437IT blockages, 437–438, 437–438misunderstandings, 435senior management buy-in, 436siloed organizations, 434–435staff competency, 439strategy vacuums, 434tools and technology, 433, 439–440trust, 439

baseline performance metrics, 275, 275basic statistics skills for web analytics,

396–397

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behavior targeting (BT), 298challenges, 299–301, 300prerequisites, 301–302promises, 299testing in, 302

benchmarksaction dashboards, 291–292competitive studies, 190–191for context, 319–320, 319–320inaccurate, 425online survey providers, 188for pressure on management,

430–431from vendors, 218–219, 218

Bennett, Steve, 63best friend metrics, 318biased video segments, 279Blog Metrics plug-in, 261blogs, 257

audience growth, 258–260, 259birth of, 243–244Bounce Rate, 53citations and ripple index,

262–263, 262costs, 263raw author contributions,

257–258, 258ROI, 263–265, 265on web analytics, 400–401

Bango Analytics company, 251, 253, 255

bossesdata-driven, 426–429pressure on, 429–432receptive, 420–421

Bounce Rate metricA/B testing, 197attributes, 62benchmarks, 218direct Traffic, 118email campaigns, 121exceptions and excuses, 53importance, 77

levels, 93mobile customer experiences, 254organic search traffic reports, 103overview, 51–52, 51–52site overlay reports for, 83site searches, 97, 97Top entry Pages with, 202Twitter, 269visitor acquisition reports, 80

brainpower factor in tool selection strategy, 18

Brand evangelists Index, 415alternate calculation, 418–419, 419case and analysis, 415–416, 416outcome, 418problem, 416–417results, 417–418, 417solutions, 417summary, 419

brand termslong-tail strategy, 341–342, 342paid search impact on, 205–207,

205–206branding campaigns, 328broad match types, 354–356, 356Browse Rate metric, 69browsers

embedded in phones, 250tracking, 128

budget as barrier to web measurement, 433–434

Burby, Jason, 437business individual contributors,

388–390business outcomes in email campaigns,

121–122business team leaders, 391–392business-to-business (B2B) websites,

166–168

Ccalculated metrics, 336–337Call Avoidance metric, 158

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campaignsemail, 119–122multitouch. See multitouch campaign

attribution analysisparameter configuration, 142–143tag-based solutions, 251tracking, 251, 309–310Twitter, 269

cannibalization, 205–207, 205–206card-sorting studies, 191–192careers in web analytics, 385–386

activities distribution for, 401–403, 402

business individual contributors, 388–390

business team leaders, 391–392hiring guidelines, 403–406options, salary prospects, and

growth, 386–387skills for, 393

blogs for, 400–401data visualization and

presentation, 398–399detective, 396education, 394–396free webinars for, 399–400practical experience, 393questioning, 397statistics, 396–397tools experience, 393–394from working with business

teams, 398technical individual contributors, 388technical team leaders, 390–391

Cart Abandonment metricbenchmarks, 218importance, 152–153

category terms in long-tail strategy, 341–342, 342

centralized models, 440–442change handling skills for analytics

managers, 404changes, data decay from, 134–135

chat tracking, 378–379Checkout Abandonment metric,

152–153Checkout page testing, 202churn

in action dashboards, 294Twitter metric, 266

citationsblogs, 262–263, 262social webs, 246

clean data collection, 286click density analysis

importance, 73overview, 81–83, 81–82

click-through rate (CTR) metricPPC, 112Twitter, 268–269, 269

click-to-open rate (CTOR) metric, 120Clickequations blog, 401Clickequations tool

COGS data, 356even-click credit, 362impression share, 351–352, 352multivariate testing, 204pay-per-click analysis, 348–349, 349

clickstream dataintegration with, 189–190internal site search analysis, 95–100,

95–100tools, 12, 12Web Analytics 1.0, 5, 5Web Analytics 2.0, 6–7, 6–7

ClickTale company, 136–138ClickTracks tools, 3

cookies, 129data sampling, 132, 132site overlay reports, 82in three-bucket strategy, 29videos, 279, 280visits metric, 37–38What’s Changed reports, 61, 61, 325,

325Code Green data sampling, 131–133

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Code Orange data sampling, 131–133Code Red data sampling, 131–133COGS (cost of goods sold) metric,

112, 356communicating test results, 212communication factors in SLAs, 33company cultures

tool selection strategy, 18transforming, 408–412

comparative value in blogs, 264comparisons

key metrics and segments against site average, 316–318, 316–318

key metrics performance over time, 314–315, 314–315, 321–324, 321–324

long-term traffic, 222–223, 222–223vendors, 28–34

Compete tool, 214hybrid data, 221keywords performance, 226long-term traffic trends comparisons,

222, 223Share of Search analysis, 150share-of-shelf analysis, 231, 232

competitive intelligence (CI) analysis, 6, 6–7, 213–214

audience identification and segmentation, 235–240, 236–238, 240

benchmarking studies, 190–191benchmarks from vendors,

218–219, 218benefits, 9–10context in, 319–320, 319–320data sources, types, and secrets,

214–215hybrid data, 220–221network data, 217panel data, 216–217for pressure on management, 431search and keyword analysis,

217–218, 225–235, 226–235

self-reported data, 219–220, 220toolbar data, 215tools, 12, 12traffic analysis, 221–225, 222–225

completing task questions in surveys, 186–187

complexity of metrics, 60compound metrics, 336–337computation changes, data decay

from, 134comScore panel, 214, 216conferences, internal, 411consolidated dashboards, 290–291consultants

dashboards by, 288for pressure on management, 432vendor questions about, 24

content analysis in direct Traffic, 119Content Consumption metric, 158Content created metric, 258content democracy evolution, 243–246,

244–247content grouping in pilot tests, 31contests, 410–411context, 314

in action dashboards, 290, 292engagement, 56industry benchmarks and

competitive data, 319–320, 319–320

key metrics and segments against site average comparisons, 316–318, 316–318

key metrics performance for different time periods comparisons, 314–315, 314–315

lonely metrics, 318–319, 318for ratios, 335, 335segmenting for, 315–316, 316tribal knowledge, 320–321

contextless video, 136contextual influence in videos,

279–280, 280

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controlled experiments, 205challenges and benefits, 208examples, 207–208offline impact of online

campaigns, 382online impact of offline campaigns,

374–376, 375paid search impact, 205–207,

205–206Conversation Rate metric

blogs, 260–261, 261social webs, 245Twitter, 270, 271

Conversion Rate metric, 438vs. Average Order Value,

153–154, 154benchmarks, 218cookieless data, 130diagnosing, 64–66, 64–65email campaigns, 121–122Outcomes by All Traffic Sources

reports, 87overview, 55–56segmenting, 100, 100Twitter, 269–270, 270videos, 279

conversionslatent, 329Macro and Micro, 156–160,

156–159cookies. See tracking cookiesCoradiant tool, 13–14Coremetrics tools

competitive intelligence, 218, 218

even-click credit, 362industry benchmarks, 319, 320Margin metric, 112mobile customer experiences, 252in three-bucket strategy, 28–29

correlations vs. causality, 154cost of goods sold (COGS) metric,

112, 356

cost per acquisition in media mix modeling, 366

costsblogs, 263PPC, 112vendor questions about, 23–24in video playback, 137

Cotlar, daniel, 148coupons, 370–371, 371, 379–380courtship model, 346Crawl Stats report, 104, 104Crazy egg tools, 3Creese, Guy, 11critical metrics, 36–37, 63

action dashboards, 288–289, 292–293

Bounce Rate, 51–53, 51–52Conversion Rate, 55–56engagement, 56–59, 57exit Rate, 53–55, 54importance, 436success measures, 147–149, 149time, 44–51, 44–50visits, 37–44, 37, 39–43

critical questions in tool selection strategy, 17–21

critical thinking skills, 404–406CRM Metrix surveys, 381CTOR (click-to-open rate) metric, 120CTR (click-through rate) metric

PPC, 112Twitter, 268–269, 269

culturefor testing, 209–212tool selection strategy, 18transforming, 408–412

curiosity in analytics managers, 404current performance of direct Traffic,

117–118, 117custom credit model, 363–364custom reporting

for context, 335, 335leveraging, 66–69, 66–69

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custom tags, 310customer behavior

vs. aggregate data, 93–94, 93–94illogical, 425PPC, 114–116, 115videos, 281

customer-centric strategy, surveys for, 187

customer experience, video playback of, 136–138

customer listening posts in behavior targeting, 301–302

Cutroni, Justin, 400

Ddaily stuff in pilot tests, 32daily Unique Visitors metric, 39–43, 41danuloff, Craig, 401dashboards. See action dashboardsdata analysis

lab usability studies, 173in testing, 212

data collectionmobile customer experiences,

250–253vendor questions about, 22–23videos, 273–274, 273–274

data decay, 134–136data-driven culture development,

407–408barriers to web measurement,

432–440, 437–438confidence in data, 420–426,

422, 424data-driven bosses, 426–429management pressure, 429–432metric definition changes, 415–419,

416–417, 419reports and analyses driving action,

412–415, 413transforming company culture,

408–412

data excess as barrier to web measurement, 435–436

data overloadas barrier to web measurement,

435–436in behavior targeting, 300

data quality, six-step process for, 286–287, 286

data reconciliation, 138, 139as barrier to web measurement,

436–437campaign parameter configuration,

142–143first-party cookies vs. third-party

cookies, 139–140key metrics definitions, 140–141pilot tests, 32sampling, 143sessionization, 141tag order, 143tagging precision, 140URL parameter configuration,

141–142web log data vs. JavaScript tags, 139

data sampling, 130in pilot tests, 31for reconciliation, 143scenarios, 131–133, 132–133

data sources in competitive intelligence, 214–215

data visualization skills, 398–399days to Purchase metric

importance, 84, 153PPC analysis, 114–115, 115

de Valk, Joost, 258death & Taxes visualization

(Bachman), 398–399, 399decay, data, 134–136decay model, 364decentralized models

vs. centralized, 440–442as tool selection factor, 18

decision matrices for blogs, 265, 265

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deep device-specific information, 255degree of engagement, 57deletion rates for cookies, 129delivery rate metric, 120demand metric in Twitter, 272demographic segmentation analysis,

236–237, 236–238depth of Visit metric

direct Traffic, 119for engagement, 57, 57non-ecommerce websites, 165–166

desired outcomes in Twitter, 266destinations in competitive intelligence,

224–225, 225detailed trends, 77diagnosing conversion rates, 64–66,

64–65different time periods, comparisons for,

314–315, 314–315digsby application, 247dimensional metrics in Twitter, 271diminishing marginal returns,

424, 424direct Traffic metric

benefits, 86capturing, 117content analysis, 119current performance, 117–118, 117for days to Purchase, 115, 115–116for educating management, 118, 118importance, 116–117purchase behavior, 119segmenting, 119trends, 324, 324in visitor acquisition reports, 78

direct value of blogs, 264distributions, 331, 331diversity in behavior targeting, 300doctors Without Borders, 265donde esta Avinash cuando se le

necesita? blog, 400doubleClick tool, 236dVd covers testing, 204

Eeconomic value, quantifying, 159–162education

about direct Traffic, 118, 118about imperfect data, 421for web analytics, 394–396webinars, 399–400

ego positions, 114eisenberg, Bryan, 401email campaigns, 119–120

business outcomes, 121–122responses, 120–121website behavior, 121

email providers, cookies with, 128embarrassing management strategies,

429–432emotional filters, 57empty containers, 123, 249end-to-end PPC view, 111–112, 111–112engagement metrics

overview, 56–59, 57Twitter, 271videos, 276–277, 277

enhanced Google Analytics plug-in, 326enterprise-class web analytics, 27–28entity Association tool, 218environment changes in predictive

analytics, 306ethnio company, 176–178, 177evangelism

brand. See Brand evangelists Indexfor testing, 212

even-click credit method, 362event Tracking model

empty containers, 249overview, 123–126, 123–125social webs, 246videos, 273–274, 274

exact match types, 354–356, 356exit Rate metric

exceptions, 55overview, 53–55, 54site overlay reports for, 83

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% exits metric, 83expansion, keyword, 234, 235experience requirements for analytics

managers, 405experimentation and Testing, 6, 6–7,

195–196A/B testing, 197–198, 197actionable testing ideas,

202–204in behavior targeting, 302benefits, 8–9controlled, 205–208, 205–206culture for, 209–212expertise for, 212first tests, 81multivariate testing, 198–201pilot tests, 30–32for pressure on management,

429–430tools, 12, 12

exporting data, vendor questions about, 25

eye-tracking studies, 192

FFacebook, 166, 242failures

costs, 9key points of, 79–80quick and cheap, 425–426

fairness in pilot tests, 31faith-based initiatives

blogs, 265causes, 408, 420videos, 273

fake page views, 123fastest-rising search terms, 230–231,

230–231Feed Subscribers metric,

150–151feedback. See surveysFeedburner tool, 246Feng-GUI program, 192

filtersemotional, 57filtering robots, 139unboring, 413–414

fingerprint algorithms, 255Firebug tool, 140Fireclick tool, 218, 218first-click credit method, 362first-party cookies

overview, 127–128vs. third-party, 139–140for unique visitors, 39

Fivesecondtest company, 191Flash

data limitations, 139tracking, 3, 122, 311

Flex tracking, 122, 139flow of attention, 192fluid web concept, 311Flurry company, 253flushing cookies, 139focus

critical few metrics for, 148on outcomes, 412on what’s changed, 350–351, 351

Followers metric, 266, 271follow-up in lab usability studies, 173Fotonatura website, 158foundation metrics, 76–774Q survey, 4

description, 187for videos, 281for visitor source, 372, 372

fractional factorial multivariate testing, 200

free traffic, 79free webinars, 399–400Fresh egg, 379friendly websites for pressure on

management, 431–432Frontline series, 273–274, 273–274full factorial multivariate testing,

200–201

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functionality in pilot tests, 30funnels

keywords, 346–348, 346–347precision in, 423videos, 279, 280

Futurenow’s Marketing Optimization blog, 401

GG1 phone, 256, 256garbage in, garbage out principle in

behavior targeting, 301geographic interests, search terms for,

227–230, 228–239Gerea, Carmen, 418Goal Conversion metrics

clickstream data, 97Google Analytics, 67, 67organic traffic correlation, 109segmenting, 100, 100SeO analysis, 103Twitter, 269

goalsconfiguring, 308–309mobile customer experiences,

253–254Outcomes by All Traffic Sources

reports, 87SeO, 108–109, 108–109as test criteria, 210–211

Godin, Seth, 160, 259, 264, 400Gold, Stuart, 63golden rules for ratios, 335good enough metrics

accepting, 287, 426–427educating leadership about, 421vs. perfect, 63

good exits, tracking, 151Google Ad Planner tool, 4, 214

demographic segmentation analysis, 236–237, 237

psychographic segmentation analysis, 238, 238

search behavior, 239self-reported data, 219, 220

Google AdWords toolcampaign tracking, 309competitive intelligence, 217integration with, 26keyword expansion analysis,

234, 235paid clicks, 110

Google Analytics toolAbsolute Unique Visitors, 44blog, 401campaign tracking, 309competitive intelligence, 218, 218,

320, 320context in, 317, 317custom reports, 67, 68data sampling, 132, 133direct Traffic, 117–118, 117Goal Conversion report, 67, 67impact, 3industry benchmarks, 319, 319integration with, 26# Landing Pages for Organic Traffic

report, 105, 105mobile customer experiences,

252–254, 254Outcomes by All Traffic Sources

report, 85, 85paid clicks, 110Search Keyword report,

66, 66segmentation, 92–93, 92site overlay reports, 81, 81social webs, 246tags, 140in three-bucket strategy, 29

Google Insights tool, 150Google Trends for Websites

Also Visited reports, 223–224, 224

long-term traffic trends comparisons, 222, 222

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Google Website Optimizer, 8integration with, 26MVT testing, 199starting with, 81

googlebot, 344grabbed widgets, 126Greatest Survey Questions ever,

185–187, 186Gross Margin per Visitor metric,

148–149, 149growth

blogs, 258–260, 259web analytics careers, 386–387

guiding principles, 313–314context, 314–321, 314–320inactionable KPI measurements.

See inactionable KPI measurement techniques

KPI trend comparisons over time, 321–324, 321–324

latent conversions, 329latent visitor behavior, 327–329,

328–329long-tail strategy, 338–345, 338–339,

341–343, 345PPC analyses, 348–356, 349–356upper funnel keywords, 346–348,

346–347what’s changed reports, 324–326,

325, 327

HHawthorne effect, 175head and heart strategy, 10head count requirements, vendor

questions about, 24head data and keywords

actionable, 422–423, 422in search, 338–340, 338–339, 341

health of metrics, action dashboards for, 289

heat maps, 192–193, 193heroes, creating, 410

HiPPOs (Highest Paid Person’s Opinion), 8

hiring guidelines for analytics managers and directors, 403–406

historical data, 133, 135–136history factor in tool selection

strategy, 18hits metric limitations, 36Hitwise ISP, 214Hitwise tool

competitive intelligence, 217demographic segmentation analysis,

236, 236geographic data, 229, 229keywords performance, 226psychographic segmentation

analysis, 238Share of Search, 150top searches data, 230–231, 231

home pages, limited importance of, 72“how much” question, 6–8HTC G1 phone, 256, 256Hughes, david, 295, 400hybrid data in competitive intelligence,

220–221hypotheses in testing, 210

Iideas democracies, 196IeWatch Professional tool, 140illogical customer behavior, 425image tags, 251–253Impact on Company quadrant in action

dashboards, 290impacts

action dashboards for, 289emphasis on, 409–410site search, 99–100, 99–100

imperfect dataaccepting, 287, 426–427educating leadership about, 421vs. perfect, 63

imprecise tagging, 140

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impression virgins, 342–343, 346impressions

PPC, 112, 351–353, 352vs. traffic, 106–107, 106–107

imputed value of actions, 160inaccurate benchmarks, 425inactionable KPI measurement

techniques, 330averages, 330–332, 330–331compound and calculated metrics,

336–337percentages, 332–334, 333–334ratios, 334–335, 335

incomplete dataaccepting, 287, 426–427educating leadership about, 421vs. perfect, 63

incremental costs, vendor questions about, 23

indexed scores, 419indexing

search engines, 103–106, 104–105Twitter performance, 266

IndexTools, 3, 423indices from online survey

providers, 188industry benchmarks, 319–320,

319–320inline segmentation, 99insights

action dashboards for, 289, 293actionable, 4–5, 222connecting with data, 414importance of, 422macro, 70–73

Insights for Search toolcompetitive intelligence, 214, 218keywords performance, 226search terms, 227–229

instantly useful metrics, 61–62integrating data

by online survey providers, 189–190vendor questions about, 26

intelligent analytics evolution, 306–307

campaign/acquisition tracking, 309–310

revenue and uber-intelligence, 310rich-media tracking, 311tags, 307–308tools settings, 308–309

intent, visitor, 73, 79–80, 86, 95Interaction Time metric, 126internal conferences, 411internal site search analysis, 95–100,

95–100interpretation

dashboard data, 288video playback, 136

iPerceptions online surveys, 4customer-centric strategy, 187for offline impact predictions, 381for Voice of Customer, 430

iPhone phones, 250ISP data for competitive

intelligence, 217issues and obstacles in web analytics,

283–284accuracy vs. precision, 284–285action dashboards, 288–294, 289,

291–292behavior targeting, 298–302, 300intelligent analytics evolution, 306–

311, 307multichannel analytics,

296–298, 297nonline marketing models, 294–296,

295–296online data mining and predictive

analytics, 302–306quality, 286–287, 286

IT blockages as barrier to web measurement, 437–438, 437–438

IT factor in tool selection strategy, 19

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JJavaScript tags

mobile customer experiences, 251–253

vs. web log data, 139JimmyR site, 244Joel, Mitch, 266Juice Analytics, 326Junk Charts blog, 400

KKaiser blog, 400Kaizen Analytics blog, 400Kampyle surveys, 181, 281, 415Kaplan company, 233–234, 233Kefta behavior targeting, 299Kenshoo tool, 348key metrics

definitions reconciliation, 140–141different time period comparisons,

314–315, 314–315site average comparisons, 316–318,

316–318key performance indicators (KPIs)

actionable, 149–151description, 37guidelines, 419inactionable. See inactionable KPI

measurement techniquestrend comparisons over time,

321–324, 321–324key points of failure, 79–80Key Trends & Insights quadrant in

action dashboards, 290keys

multichannel analytics, 296–298, 297

predictive analytics, 305tags for, 310vanity URLs for, 369

Keyword discovery tool, 234

Keyword Forecast tool, 218Keyword Group detection tool, 218Keyword Positions reports, 113–114,

113–114Keyword Tool, 217keywords

Bounce Rate metric, 52in competitive intelligence, 217,

225–235, 226–235expansion analysis, 234, 235Google Analytics reports, 66, 66, 71mobile customer experiences, 255in search engine results, 106–108,

106–107site overlay reports, 83visitor acquisition reports, 80

KeywordSpy tool, 234kinds of engagement, 57Klout tool, 271, 272knowable vs. actionable in surveys,

184, 184knowledge factor in tool selection

strategy, 18Kogi BBQ, 266KPIs (key performance indicators)

actionable, 149–151description, 37guidelines, 419inactionable. See inactionable KPI

measurement techniquestrend comparisons over time,

321–324, 321–324

Llab usability studies, 170–171

areas of caution, 174–175benefits, 174best practices, 174conducting, 172data analysis, 173post-implementation, 173preparation stage, 171–172

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landing pagessegmenting, 92testing, 202Yahoo! Web Analytics, 69, 69

# Landing Pages for Organic Traffic report, 105–106, 105

large and huge businesses, Multiplicity elements in, 13

last-click credit method, 362last page, time on, 49latent conversions, 329latent visitor behavior, 327–329,

328–329layout of ads, 203Lead Submission pages testing, 202leaders

data-driven, 426–429pressure on, 429–432receptive, 420–421

leakageBounce Rate for, 54exit Rate for, 54

Length of Visit metricemail campaigns, 121non-ecommerce websites, 165, 165

lifecycle process metrics, 63–64, 63Likelihood to Recommend

metric, 159line of sight metrics, 149Link Popularity Check report, 105listening posts in behavior targeting,

301–302live chat tracking, 378–379live pilot tests, 30live recruiting, 176–178, 177LivePerson, 379living pages, 245local feedback, page-level surveys

for, 181Localytics company, 253Locations metric, 275, 275logs-based solutions, 250–251lonely metrics, 318–319, 318

long-tail strategy, 338–339, 338brand and category terms,

341–342, 342head and tail computation,

339–340, 339optimal, 344–345, 345search engine marketing,

342–344, 343long-term traffic trend comparisons,

222–223, 222–223lost clients, vendor questions about, 27lost revenue in PPC analyses,

351–353, 353Loyalty metrics. See Visitor

Loyalty metric

Mmachine-language algorithms in

behavior targeting, 300Macro Conversions, 156–160,

156–159, 436macro insights, 70–73management

as barrier to web measurement, 436data-driven, 426–429pressure on, 429–432receptive, 420–421

Map Overlay metric, 255maps

heat, 192–193, 193search terms, 227

Margin metric, 112marginal attribution analysis, 367–368marginal returns, diminishing,

424, 424Marin tools, 348market experimentation. See

experimentation and TestingMarket Motive organization, 309, 400market research, 372, 372marketers, analysts as, 427–428Marketing Productivity blog, 401Marketing Profs organization, 400

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Marketleap reports, 105Marshall, John, 61Mason, neil, 64match types in PPC analyses, 354–356,

355–356math skills for web analytics, 396–397mathematical rigor by online survey

providers, 188Maxamine tool, 13MeasureMap tool, 246Medcraft, Steve, 30, 32media

mix models, 366–367, 366rich-media tracking, 311

medium-sized businesses, Multiplicity elements in, 13

mental flexibility skills for analytics managers, 404

message amplification in Twitter, 267–268, 268

@Messages metric, 271metrics overview, 35–36

attributes, 59–62, 61changing definitions, 415–419,

416–417, 419compound and calculated,

336–337critical. See critical metricscustom reporting, 66–69, 66–69lifecycle process, 63–64, 63macro insights, 70–73perfect vs. good enough, 63strategic tactics, 64–73, 64–70

Meyers, Rachel, 414micro-blogging sites, 266Micro Conversions, 156–160,

156–159, 436micro-ecosystem reports, 69–70, 70mind-sets, 428–429Mint tool, 3missing data in predictive analytics, 305misunderstandings as barrier to web

measurement, 435

mobile customer experiences, 250data collection, 250–253reporting and analysis, 253–257,

254–256Mobilytics company, 251, 253MochiBot tool, 3moderators for lab usability studies, 171Mongoose Metrics, 379Monthly Unique Visitors metric, 39–43Mortensen, dennis, 401Most Significant Falls reports, 326Most Significant Rises reports, 326move fast, think smart philosophy, 287multichannel analytics, 368–369

offline impact of online campaigns, 376–383, 377, 380–381

online impact of offline campaigns, 369–376, 370–373, 375

overview, 296–298, 297Multiple Outcomes Analysis,

6–8, 6–7tests and measurements, 211tools, 12, 12

multiple primary purposes in predictive analytics, 304

multiple visit behaviors in predictive analytics, 305

Multiplicity conceptin data reconciliation, 436overview, 11–13, 12vendor questions about, 22–23

multipurpose ecommerce websites, 159

multitouch campaign attribution analysis, 358

alternatives, 366–368, 366challenges, 364–365issues, 359–361, 360models, 361–365, 361overview, 358–359summary, 368

multitouch conversions, 358multivariate regression models, 397

29393bindex.indd 463 9/16/09 8:29:34 PM

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 ■   

multivariate testing (MVT)in behavior targeting, 302common techniques, 200–201overview, 198–200, 198–200pros and cons, 201

MySpace, 242

Nname-value pairs, 249nedstat tools

Absolute Unique Visitors, 44mobile customer experiences, 255in three-bucket strategy, 29

negotiating SLAs, 32–34net detractors, 430net promoters, 430net Promoters metric, 159netbooks, 239netInsight tool

cookies, 129SeO analysis, 102tags, 140in three-bucket strategy, 29

netmining company, 299network data in competitive

intelligence, 217network strength metric, 272new and Returning Visitors

metric, 130new elements, vendor questions

about, 26–27new Visitors metric, 53% new Visits metric, 77new York Times

Times Reader, 248–249, 248Visualization Lab, 398

newbies for pilot tests, 31non-ecommerce website success

measures, 162–166, 163–165non-Line Blogging blog, 400non-Paid Traffic metric, 103, 103noncampaign, nonsearch, nonlinked

traffic. See direct Traffic metric

nonline marketing models, 294–296, 295–296

nontraditional value in blogs, 264normalizing tabbed browsing, 50, 50notte, Michael, 400novo, Jim, 207, 401number completed videos watched

metric, 167number of free samples ordered

metric, 167

OObservePoint tool, 13off-site content, 151, 245–246offer codes

offline impact of online campaigns, 379–380

online impact of offline campaigns, 370–371, 371

Offermatica tool, 81office hours, holding, 411–412offline campaigns

online impact on, 369–376, 370–373, 375

online impacted by, 376–383, 377, 380–381

offline customer experiences, 248–249, 248

Omniture tool, 3behavior targeting, 299blog, 401cookies, 127–129Margin metric, 112mobile customer experiences, 252paid clicks, 110SeO, 102tags, 140in three-bucket strategy, 28–29unique visitors metric, 39webinars by, 399

on-the-fly segmentation capabilities, 188

one-night stand mentality, 346

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465

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Ind

ex

online activitiescard-sorting studies, 191–192data mining, 302–306education for, 395–396failure costs, 9surveys. See surveystesting, 204

online campaignsoffline impact on, 376–383, 377,

380–381offline impacted by, 369–376,

370–373, 375open-ended questions in surveys, 187Open rate metric, 120open-text customer responses, 189opportunity analysis, 227–230,

228–239opportunity costs of blogs, 263opportunity pies, 155, 155OptimalSort company, 191Optimost tool, 8, 81order of tags, 143Order Size metric, 122organic searches

controlled experiments, 205–207, 206

traffic reports, 102–103, 102–103Ortega, Fernando, 158Otamendi, Rene dechamps, 379Other bucket in visitor acquisition

reports, 78–79outbound link tracking, 151outbound marketing effort

optimization, 204outcome-based metrics, 36outcomes

email campaigns, 121–122emphasis on, 409–410focus on, 412importance, 8Multiple Outcomes Analysis, 6–8,

6–7, 12, 12, 211SeO, 108–109, 108–109Twitter, 266

Outcomes by All Traffic Sources reports, 85–87, 85

outsiders, dashboards by, 288outsourced online usability,

178–179overlap in competitive sites,

223–224, 224Overture Keyword Tool, 234ownership of data, vendor questions

about, 25

Ppacket-sniffing-based solutions, 251Page depth metric, 91page-driven data collection

mechanisms, 123page-level surveys, 180–181, 180page view costs, vendor questions

about, 23Page Views metric

benchmarks, 218data sampling, 130description, 77limitations, 36, 126mobile customer experiences,

254–255rich experiences, 122–123segmentation analysis, 239site overlay reports, 83

Page Views per Visit metric, 334pageless experiences, 123pages

data sampling, 131–132exit Rate metric, 53–55, 54

Pages/Visit metricdescription, 77direct Traffic, 118mobile customer experiences, 254

paid search. See also pay-per-click (PPC) analyses

impact on brand keywords and cannibalization, 205–207, 205–206

29393bindex.indd 465 9/16/09 8:29:34 PM

466

ind

ex

 ■   

site search analysis, 110–116, 111–115sponsored links, 101traffic from, 111

Paid Traffic metric, 103, 103Paine, K. d., 36PALM (People Against Lonely

Metrics), 318pan-session metrics, 130pan-session purchase behavior, 84panel data

for competitive intelligence, 216–217for unique visitors, 39

Panos company, 379–380, 380Papadakis, Theo, 57paper printouts, 170paradox of data, 2partial factorial multivariate

testing, 200path analysis in multitouch campaign

attribution, 364–365pay-per-click (PPC) analyses, 348–349

ad position, 113–114, 113–114customer behavior, 114–116, 115end-to-end view, 111–112, 111–112impression share and lost revenue,

351–353, 352–353keyword arbitrage opportunities,

349–350, 349–350long-tail strategy, 343–344ROI distribution reports,

353–354, 354site search analysis, 110–116,

111–115user search query and match types,

354–356, 355–356what’s changed focus, 350–351, 351

pay per page views in data sampling, 130

People Against Lonely Metrics (PALM), 318

people changes, data decay from, 135Percent Mobile company, 251, 253Percent of new Visits metric, 218

Percentage of selection and solution guide downloads metric, 167

Percentage of solutions by the same member Id metric, 167

Percentage of Visits that viewed the Product Folder directories metric, 167

percentages, 332, 333raw numbers, 333, 334segmenting, 333, 334statistical significance, 334

perfect metricseducating leadership about, 421vs. good enough, 63

permission-based surveys, 182, 183persistent cookies, 127phone calls, tracking, 378–379photo-publishing websites, 158, 158phrase match types, 354–356, 356pilots surveys, 190Pinch Media company, 253Piwik tool, 3pollutants, isolating, 382Pols, Aurelie, 379pop-up and pop-under surveys,

182, 182post-implementation of lab usability

studies, 173postclick marketing, 299postfacto segmentation, vendor

questions about, 25Posts per month metric, 258PPC. See pay-per-click (PPC) analysesprecision

vs. accuracy, 284–285in funnels, 423for quality, 287

preclick marketing, 299predictive analytics, 302–303

data types, 303–304missing primary keys and data

sets, 305multiple primary purposes, 304

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Ind

ex

multiple visit behaviors, 305pace of change issues, 305–306variables, 304

presentation skills for web analytics, 398–399

prices, testing, 203–204primary keys

multichannel analytics, 296–298, 297

predictive analytics, 305tags for, 310vanity URLs for, 369

primary purposespredictive analytics, 304of visits, 154–156, 155

primary research, 382–383primitive indicators, 76–77, 76PRIZM segments and groups, 238problems, testing for, 211–212Products Sold metric, 109, 109professional services costs, vendor

questions about, 23Profitability metric, 122prospects, 71prototypes, 170–171psychographic segmentation analysis,

238–239, 238purchase behavior in direct Traffic, 119purpose of visit in surveys, 186

QQooqle site, 244qualitative data, 169–170

lab usability studies, 170–175outsourced online usability, 178–179remote research, 175–178, 177surveys. See surveysweb-enabled research, 190–193

qualitysite search, 97–99, 97–99six-step process for, 286–287, 286

Quantcast tool, 214, 219, 220questioning skills for web analytics, 397

questionssurveys, 185–187, 186tool selection strategy, 17–21for vendors, 21–27

Rrapid usability tests, 191–192ratios, 334

context for, 335, 335golden rules for, 335

Raw Author Contributions metric, 257–258, 258

raw numbers with percentages, 333, 334Reach metric

blogs, 260Twitter, 271

real time metrics, 61really simple syndication (RSS),

150–151blogs, 259–261, 260–261social webs, 246

Recency metric, 94, 328, 328importance, 150overview, 164–165, 164

reconciling data. See data reconciliationredeemable coupons, 370–371, 371,

379–380redirects, 369–370, 370referral strings in paid search, 110referrals in competitive intelligence,

224–225, 225Referring Sites reports, 78, 326Referring URLs reports, 71Referring Websites (URLs) metric, 130Registration pages, 202regression models, 397related search terms, 230–231, 230–231relevant metrics, 60, 62relevant people in Twitter, 266remote research, 175–178, 177Repeat Visitors metric, 128Replies Received Per day metric, 270Replies Sent Per day metric, 270

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ex

 ■   

reportsaction-driving, 412–415, 413configuring, 308custom, 66–69, 66–69mobile customer experiences,

253–257, 254–256Outcomes by All Traffic Sources,

85–87, 85site overlay, 81–83, 81–82as tool selection factor, 17–19visitor acquisition, 78–81, 78–80Visits to Purchase, 83–85, 84

requests, session, 38resources as barrier to web

measurement, 433–434response rate in Twitter, 268responses

email campaigns, 120–121pilot tests, 30surveys. See surveys

Results Page Views/Search metric, 97, 98

retention rate in email campaigns, 120–121

retesting lab usability studies, 173Returning Visitors metric, 94Retweetist tool, 268Retweetrank tool, 268retweets, 267–268, 268revenue

cookieless data, 130email campaigns, 122SeO, 108–109, 108–109and uber intelligence, 310

revenue per click (RPC) metric, 112rich Internet applications (RIAs), 134rich-media, tracking, 122–126, 123–

125, 139, 311ripple index for blogs, 262–263, 262risk factor in tool selection, 18RobotReplay company, 136–137robots

B2B website visits, 166filtering, 139

ROI metricblogs, 263–265, 265PPC, 112, 353–354, 354SeO, 108–109, 108–109

role models, 410root causes for trends, 290RPC (revenue per click) metric, 112RSS/Feed Subscribers metric, 150–151RSS feeds, 150–151

blogs, 259–261, 260–261social webs, 246

run time sampling, 143

Ssalary prospects in web analytics,

386–387Sales metric, 159sample bias in panel data, 216sampling, 130

in pilot tests, 31for reconciliation, 143scenarios, 131–133, 132–133

SAS (software-as-a-service) model, 201satisfaction computation, 416Save Your Itinerary feature, 116saving data, 135–136SbKT (Search-based Keyword Tool),

344–345, 345scalable listening. See surveysscale

in behavior targeting, 299video playback, 136

scale filters, 414scorecards in Klout, 271Screen Resolution metric, 254–255screen-sharing applications, 178search analysis, 95

audience segmentation, 239–240, 240competitive intelligence, 217–218,

225–235, 226–235direct Traffic, 116–119, 117–118email campaigns, 119–122keywords. See keywords

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long-tail strategy, 338–345, 338–339, 341–343, 345

pay-per-click/paid search, 110–116, 111–115, 348–356, 349–356

pilot tests, 31quality, 97–99, 97–99related terms, 230–231, 230–231rich media, 122–126, 123–125segmentation and impact, 99–100,

99–100SeO. See Search engine Optimization

(SeO) analysisupper funnel keywords, 346–348,

346–347usage, 95–96, 95–96

Search-based Keyword Tool (SbKT), 344–345, 345

Search depth metric, 98Search engine Keywords metric, 130search engine marketing (SeM),

342–344, 343Search engine Optimization (SeO)

analysis, 101–102, 101keyword performance, 106–108,

106–107organic search traffic reports,

102–103, 102–103outcomes, 108–109, 108–109search engine indexing, 103–106,

104–105Search engine Saturation report, 105search engines

Bounce Rate, 52indexing by, 103–106, 104–105in visitor acquisition

reports, 78–79% Search exits metric, 97, 97Search Funnels tool, 218% Search Query Refinements metric,

98–99, 98–99secrets in competitive intelligence,

214–215security factors in SLAs, 33

segmentation, 88–89, 88action dashboards, 291–292average data, 330–331, 330benefits, 89–90, 89–90Bounce Rate, 53competitive intelligence, 235–240,

236–238, 240for context, 315–316, 316creating and applying, 90–93, 91–92demographic, 236–237, 236–238direct Traffic, 119online survey provider

capabilities, 188percentages, 333, 334in pilot tests, 31psychographic, 238–239, 238search behavior in, 239–240, 240site average comparisons, 316–318,

316–318site search, 99–100, 99–100in trend analysis, 323–324, 323–324vendor questions about, 25videos, 278

selectivity in data collection, 286–287self-publishing platforms, 243self-reflection, 17self-reported data for competitive

intelligence, 219–220, 220selling tactics testing, 203–204SeM (search engine marketing),

342–344, 343SeMPO webinars, 399senior management buy-in as barrier to

web measurement, 436SeO (Search engine Optimization)

analysis, 101–102, 101keyword performance, 106–108,

106–107organic search traffic reports,

102–103, 102–103outcomes, 108–109, 108–109search engine indexing, 103–106,

104–105

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 ■   

service-level agreements (SLAs), 32–34session cookies, 127session Ids, 38sessionization, 141Share of Search metric, 150share-of-shelf analysis, 231–232, 232share of voice concept, 351sharing websites, 158, 158Short Visits metric, 80siloed organizations as barrier to web

measurement, 434–435single-page rule for action dashboards,

293–294single-page view sessions, 48–49, 48site average comparisons, 316–318,

316–318Site Catalyst tool, 3Site Content topic, 281site-level surveys, 182–184, 182–183site overlay reports, 73, 81–83, 81–82site search analysis. See search analysisSite Usage metrics, 254SiteCatalyst tool, 3SiteSpect tool, 8, 81Six Sigma/Process excellence, 148six-step data quality process,

286–287, 286SKU mix, 203SLAs (service-level agreements), 32–34small businesses, Multiplicity elements

in, 13small sites, problems in, 424–425Smile Train, 265, 273Social engagement reports,

276–277, 277social web, 241–242

blogs, 257–265, 258–262, 265content democracy evolution,

243–246, 244–247data challenges, 242, 243education for, 395–396mobile customer experiences,

250–257, 254–256

offline customer experiences, 248–249, 248

Twitter, 247–248, 266–272, 267–272videos, 273–281, 273–278, 280

software-as-a-service (SAS) model, 201software versions, vendor questions

about, 22Song, Sidney, 400sources of traffic, 86Spaz application, 247split credit model, 363–364sponsored links, 101stability in predictive analytics, 306staff competency as barrier to web

measurement, 439standard metrics. See critical metricsStatCounter visits metric, 37, 37statistical significance of

percentages, 334statistics skills for web analytics,

396–397strategic imperative, 10, 11strategic tactics, 64–73, 64–70strategy vacuums as barrier to web

measurement, 434structured experiences, 55Subscriber retention rate in email

campaigns, 120–121Subscribers metric for blogs,

259–260, 260success measures, 145–147, 146

Average Order Value, 153–154, 154B2B websites, 166–168cart and checkout abandonment

metrics, 152–153critical few metrics, 147–149, 149days to Purchase and Visits to

Purchase, 153economic value, 159–162KPIs, 149–151lab usability studies, 173Macro and Micro conversions,

156–160, 156–159

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non-ecommerce websites, 162–166, 163–165

primary purpose of visits, 154–156, 155

support costs, vendor questions about, 24

support factors in SLAs, 33support quality in pilot tests, 31–32surveys, 179–180

mistakes, 184–185, 184–185offline impact of online campaigns,

380–381, 381online impact of offline campaigns,

372, 372online survey providers, 188–190questions, 185–187, 186types, 180–184, 180, 182–183for videos, 281

system parameters in data reconciliation, 142

systems changes, data decay from, 134

Ttabbed browsing, 49–51, 49–50tactical shift, 11–13, 12tags

campaigns, 309–310custom, 310email campaigns, 120importance, 307–308imprecise, 140mobile customer experiences, 251–253order, 143vs. web log data, 139

tail keywords, 338–340, 338–339, 341Tan, Shirley, 230Task Completion Rate metric

importance, 149Macro Conversions, 158in surveys, 186, 186

TCO (total cost of ownership)in pilot tests, 30–31vendor questions about, 23–24

Tealeaf company, 136technical areas in pilot tests, 30technical individual contributors, 388technical support websites,

158–159, 159technical team leaders, 390–391technology

as barrier to web measurement, 433, 439–440

blog costs, 263Technorati, 262–263, 26210/90 rule, 16–17, 24test box layouts, 204Test&Target tool, 3, 8testing. See experimentation

and TestingTexas Instruments website, 167Thayer, Shelby, 400third-generation tools in PPC analyses,

348–349third-party cookies

vs. first-party, 139–140overview, 127–128for unique visitors, 39

three-bucket strategy, 28–29Ticket Opened metric, 158TigTags tool, 255–256, 255Time After Search metric, 98time costs of blogs, 263time metrics, 44–51, 44–50Time on Page metric, 44–47,

45–46, 83Time on Site metric, 44–47, 45, 47

benchmarks, 218direct Traffic, 118in engagement, 58mobile customer experiences, 254Twitter, 269

time requirements for pilot tests, 31Time to the Page metric, 83timely metrics, 60–62Times Reader, 248–249, 248tool/consultant hype, 209–210tool pilots, 29–32

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ex

 ■   

tool selection strategy10/90 rule, 16–17critical questions, 17–21important, 16vendor comparisons, 28–34vendor questions, 21–27

toolbars, 215tools

B2B website visits, 168as barrier to web measurement, 433,

439–440configuring, 308–309limiting, 423–424

Top 10 Referrers metric, 135Top entry Pages metric

importance, 72report, 52, 52testing, 202in visitor acquisition reports, 80

Top Landing Pages reports, 52, 197top referrers, Bounce Rate for, 52top viewed pages, 73Top Visited Pages metric, 130total cost of ownership (TCO)

in pilot tests, 30–31vendor questions about, 23–24

Total Visits metric, 38touches, 358tracking

email campaigns, 120mobile applications, 253

tracking cookies, 126–127choice and data storage, 128–129deletion rates, 129first-party and third-party, 127–128,

139–140mobile customer experiences, 255as online survey provider

requirement, 189transient and persistent, 127for unique visitors, 38–39working without, 129–130

tracking parameters, 142

traffic analysiscompetitive intelligence, 221–225,

222–225online impact of offline campaigns,

372–374, 373organic search, 102–103, 102–103paid search, 111

transforming company culture, 408–412

transient cookies, 127Trending Upward blog, 400trends

action dashboards for, 289–290comparing over time, 321–324,

321–324root causes for, 290

Trends for Websites toolAlso Visited reports, 223–224, 224hybrid data, 221long-term comparisons, 222–223,

222–223tribal knowledge

for context, 320–321in tool selection strategy, 18in trend analysis, 322–323, 322

Trinity strategy, 4trust as barrier to web

measurement, 439TubeMogul tool, 273Turner, Stephen, 61Tweet Citations metric, 262, 262Tweetdeck application, 247Tweetmeme tool, 262–263Twitter, 242, 246, 247, 266

Click-Through Rate, 268–269, 269Conversation Rate, 270, 271Conversion Rate, 269–270, 270growth, 266, 267measuring, 247–248, 248message amplification, 267–268, 268metrics, 271–272, 272

Twittercounter tool, 266, 267TwitterFriends tool, 270, 271

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473

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ex

Uuber-intelligence, 310UCd (user-centric design)

methodologies, 170, 173UGC (user-generated content), 243unboring filters, 413–414uncomplex metrics, 60, 62Unica tool, 246unique browsers, tracking, 128unique value propositions (UVPs), 415Unique Visitors metric

blogs, 259–260, 259in Conversion Rate, 55–56cookies for, 126–128data sampling, 132mobile customer experiences, 255overview, 38–39, 39saving, 135videos, 275, 275working with, 39–44, 39–43

universal searches, 106, 277unquantifiable value for blogs, 265, 265up-front testing decisions, 210–211Updates metric, 271upper funnel keywords, 346–348,

346–347Urchin, 129URL Builder tool, 110URLs

parameter configuration, 141–142vanity, 369–370, 370

usability in pilot tests, 30usability labs, 171Usability Sciences surveys, 381usability tests, 191–192user-centric design (UCd)

methodologies, 170, 173user cookies, 127user-generated content (UGC), 243user research

lab usability studies, 170–175outsourced, 178–179remote, 175–178, 177

surveys. See surveysweb-enabled options, 190–193

user search queries in PPC analyses, 354–356, 355–356

UserTesting.com company, 178UserVoice surveys, 181UserZoom company, 191UVPs (unique value propositions), 415

V% of Valuable exits metric, 151vanity URLs, 369–370, 370variables in predictive analytics, 304Velocity metric, 271vendors

comparing, 28–34competitor benchmarks from,

218–219, 218enterprise-class, 27–28online survey providers, 188–190questions for, 21–27

Vera, Gemma Munoz, 400video playback of customer experience,

136–138videos

advanced analysis, 278–279contextual influence, 279–280, 280customer behavior measures, 281data collection, 273–274,

273–274data limitations, 122–126,

123–125, 139metrics and analysis, 274–278,

275–278segmentation, 278Social engagement report,

276–277, 277viralness, 277, 277Voice of Customer data, 281

Views metric for videos, 275, 275Viral distribution and detail report,

277, 277viralness, 126, 277, 277

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 ■   

virtuous data quality cycle, 286–287, 286

Visible Measures tool, 273Visitor Loyalty metric, 94

direct Traffic, 119importance, 150latent visitor behavior, 328, 329overview, 162–164, 163

Visitor Recency metric, 94importance, 150latent visitor behavior, 328, 329overview, 164–165, 164

visitorsacquisition reports, 78–81, 78–80in predictive analytics, 305tracking cookies, 126–130

Visitors metricmacro insights, 71–73saving, 135

Visits metricbenchmarks, 218blogs, 259–260, 259in Conversion Rate, 55–56mobile customer experiences, 252move to, 36overview, 37–38segmentation, 91Twitter, 269Unique Visitors, 38–39, 39working with, 39–44, 39–43

Visits to Purchase metriccookieless data, 130importance, 153reports, 83–85, 84, 359, 360

visual heat maps, 192–193, 193visual impressions, 351–353, 352Visual Revenue blog, 401Visualization Lab, 398Voice of Customer (VOC), 6, 6–7, 9

for pressure on management, 430questions in surveys, 187tools, 12, 12videos, 276, 281

WWAA webinars, 399WASP tool, 140Web Analytics 2.0 overview, 4–6, 5–7

bonus analytics, 13–14Clickstream, 7Competitive Intelligence, 9–10experimentation and Testing, 8–9Multiple Outcomes Analysis, 7–8strategic imperative, 10–11tactical shift, 11–13, 12Voice of Customer, 9

Web Analytics Career Introspection Guide, 387

Web Analytics in China blog, 400Web Analytics Inside blog, 400Web Analytics Vendors & Challenges

video, 29Web Bug tool, 140Web developer Toolkit tool, 140web-enabled emerging user research

options, 190–193Web Link Validator tool, 140web log data vs. JavaScript tags, 139webinars, 399–400Webmaster Tools

Crawl Stats report, 104, 104keywords report, 106, 106SeO, 101

website behavior in email campaigns, 121

website changes, data decay from, 134–135

WebSort company, 191Webtrends tool, 3

cookies, 128Margin metric, 112reports, 7–8SeO, 102tags, 140in three-bucket strategy, 28–29unique visitors metric, 39

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Weekly Trends metric, 135Weekly Unique Visitors metric, 39–43weighted means, 418–419, 419“what question”, 6“what else” question, 6, 9–10What’s Changed reports, 61, 61

overview, 324–326, 325, 327PPC analyses, 350–351, 351

“What’s your point?” filters, 412“why” question, 6, 8–9widgets, 122, 126wireframes prototypes, 170–171WordPress metrics, 258Wordtracker tool

competitive intelligence, 214keyword expansion analysis, 234

XxiTi, 3

Absolute Unique Visitors, 44Bounce Rate, 51, 51cookies, 129direct Traffic, 117, 117

Most Significant Falls reports and Most Significant Rises reports, 326

in three-bucket strategy, 29

YYahoo! for audience identification, 236Yahoo! Site explorer, 104, 104Yahoo! Web Analytics

cookies, 129description, 2Landing Pages report, 69, 69release, 3segmentation, 91, 91, 93in three-bucket strategy, 29Top entry Pages report, 52, 52unique visitors metric, 39

Yellow Pages websites, 53YouTube, 242, 274–275

ZZappos company, 207

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