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Website Optimization by Andrew B. King
AltaVista, bounce rate, don't be evil, en.wikipedia.org, Firefox, In Cold Blood by Truman Capote, information retrieval, iterative process, Kickstarter, medical malpractice, Network effects, performance metric, search engine result page, second-price auction, second-price sealed-bid, semantic web, Silicon Valley, slashdot, social graph, Steve Jobs, web application
For reporting purposes, consider using simple engagement, the formula for which follows: Simple engagement = 1 - (single-access visits / total entries) Simple engagement is the reciprocated percentile created by subtracting the bounce rate from 1. In other words, it is an inversion of the "bounce rate" metric. It is a great metric for quickly determining whether visitors find content immediately relevant and engaging. It can point to major deficiencies in a page's design or content. You also can use it to measure the effectiveness of a new ad campaign. ora: Killer Keywords Bounce rate or simple engagement can give an analyst a quick means to identify fundamental issues with a page. Usually a very high bounce rate indicates that there is a loading problem with a server or script on a page, or a major keyword flaw.
Therefore, with the high bounce rate, we decided to flag family and murder as negative keywords, thus reducing the likelihood of getting inadvertent traffic. Using these negative keywords reduced our client's bounce rate on those pages, as well as their costs on those campaigns. Figure 10-9 illustrates the bounce rate per search engine referring visits to CableOrganizer.com during a given time period. Baidu and Yandex appear to give the highest bounce. This should not be surprising, as CableOrganizer.com provides no content in the dominant languages of those search engines. Figure 10-9. Bounce rate per search engine referring visits Google Analytics also provides pie charts, comparative charting, and trending to show metrics assigned to certain timelines and composition models.
Technical Blogging: Turn Your Expertise Into a Remarkable Online Presence by Antonio Cangiano
23andMe, Albert Einstein, anti-pattern, bitcoin, bounce rate, cloud computing, en.wikipedia.org, John Gruber, Kickstarter, Lean Startup, Network effects, revision control, Ruby on Rails, search engine result page, slashdot, software as a service, web application
Your blog will most likely be relatively popular and grow quickly, but you’ll also have relatively low average pageviews and time-on-site figures and a high bounce rate. (As we’ll see soon, Clicky addresses the issue of social media affecting bounce rate by redefining what a bounce is.) For example, ProgrammingZen.com’s global statistics for this month show 1.18 average pageviews, 36 seconds average time on site, and an 89.40 percent bounce rate. Filtering the statistics for search traffic only shows a much higher average pageviews value, triple the time on site, and a noticeably lower bounce rate. Conversely, the new visits percentage is an excellent 86 percent, regardless of traffic source.
The two concepts are not very different, except for the fact that an action such as downloading a file or clicking a link will be counted as an action but not as a pageview. The bounce rate is calculated in a drastically different way, however. Whereas Google might show me an 85 percent bounce rate, Clicky tells me that it’s 25 percent. The difference lies in the fact that the smart team behind Clicky has redefined the concept of bounce rate to better describe the behavior of the user. How Reliable Are Traffic Comparison Sites? As the owner of your blog, you’ll have exact, detailed statistics. However, unless you share these numbers, other people won’t know about them.
Translating these regular readers into dollars or into the other benefits you may be after is something that you can concern yourself with once your site is already established and has been running for a few months. In the beginning, your goal is to increase your subscriber count. Sure, other metrics such as visitors, pageviews, time on the site, and bounce rate are all interesting and important in their own way, but nothing beats subscribers as an indicator of growth (and that you are doing this whole blogging thing right). If your subscriber count isn’t growing, your blog is not living up to its full potential. By subscribers, I mean readers that follow your blog via feed or receive your posts via email.
The Art of SEO by Eric Enge, Stephan Spencer, Jessie Stricchiola, Rand Fishkin
AltaVista, barriers to entry, bounce rate, Build a better mousetrap, business intelligence, cloud computing, dark matter, en.wikipedia.org, Firefox, Google Chrome, Google Earth, hypertext link, index card, information retrieval, Internet Archive, Law of Accelerating Returns, linked data, mass immigration, Metcalfe’s law, Network effects, optical character recognition, PageRank, performance metric, risk tolerance, search engine result page, self-driving car, sentiment analysis, social web, sorting algorithm, speech recognition, Steven Levy, text mining, web application, wikimedia commons
At SMX Munich in April 2011, Bing’s Stefan Weitz and Google’s Maile Ohye both indicated that it was comparatively simple to find social media spam because the behavior pattern matching is more predictable on the social web than it is with the link graph. Similarly, user behavior on the Web provides many potential signals that search engines can use. Consider the example of bounce rate, which is a measurement of the percentage of visitors to a site that visit only one page. If one site has a 47% bounce rate, and another site that competes with it has a 60% bounce rate, you could consider the site with the 47% bounce rate a better page to show in response to a user’s search query. Search engines measure user interaction with the search results, and if someone clicks on a link, then returns to the results page a few seconds later and clicks a different link, this is a form of bounce that could indicate that the visited resource was of poor quality (i.e., the user did not find what he was looking for at that site).
“Search traffic” report from Google Analytics This type of data allows you to see which search engines are delivering the majority of the traffic to your site, and perhaps flag potential problems. Also, over on the right of Figure 4-16 you can see that this site has an unusually high bounce rate. The site owner may want to investigate this in more detail to find out whether the visitors to the site are getting what they are looking for. The next step would be to drill down into the bounce rate metric at the page level and see if there are specific pages that have problems that can be resolved. Yet another thing to look at is which pages are getting the most traffic. Figure 4-17 shows a sample report on that from Yahoo!
Clicking on other search results Once a user completes a search and visits a link, a common behavior indicating a problem with a result is that that user returns to the search results, often quite quickly, and then clicks on another result. This is often referred to as “comparison shopping.” Generating new searches Similarly, a user may look at a given search result, then come back to the search engine and modify his search query. Bounce rate Bounce rate is a measurement of the percentage of users who visit only one page on a website. Search engines extend that definition to take into account the interaction of the user with the search results. For example, if a user clicks on a search result, then returns to the SERPs and clicks on another result, that could be an indicator that the first result was not a good response for that search query.
Lifestyle Entrepreneur: Live Your Dreams, Ignite Your Passions and Run Your Business From Anywhere in the World by Jesse Krieger
Airbnb, always be closing, bounce rate, call centre, carbon footprint, commoditize, Deng Xiaoping, different worldview, financial independence, follow your passion, income inequality, independent contractor, iterative process, Ralph Waldo Emerson, search engine result page, Skype, software as a service, South China Sea, Steve Jobs
Here are some of the key metrics to focus on when using Google Analytics: Bounce Rate: This metric shows the percent of people who click into your home page and then hit the back button on their browser. It shows how relevant or compelling your homepage was with respect to what the visitor was searching for and expecting. If you just launched and are using AdWords only (as you work on your SEO, of course), a bounce rate of 50% isn’t bad, although ideally, you want it to be much lower. Remember though, you can have a 30% bounce rate with a fully executed SEO and CPC campaign strategy and still make a good profit. To lower your bounce rate, experiment with A/B testing for the home page to see what content visitors respond to best.
The Six-Figure Second Income: How to Start and Grow a Successful Online Business Without Quitting Your Day Job by David Lindahl, Jonathan Rozek
bounce rate, California gold rush, Charles Lindbergh, financial independence, Google Earth, new economy, speech recognition, There's no reason for any individual to have a computer in his home - Ken Olsen
If you would like more tips on how to care for your own Schnauzer, just visit her site at www.SchnauzerSecrets.com.” Here’s the point of Step Three—when visitors click on that link, make sure they immediately see something reinforcing that they’re in the right place. There’s a measurement tool called bounce rate, which means how many people arrive on your web page and never click any button before leaving. It’s not uncommon for sites to have a 60 to 80 percent bounce rate, or even higher. That means most of those people land on the page, take a glance, and decide, “That’s not what I expected.” Do not go to all the effort to get people to your web page and then have almost all of them bounce.
See also Marketing advertising for others pay-per-click promising instant results Advice, reliability/accuracy of Age, as false barrier to success Alcott.com Article marketing Audio products/services audio recordings for content creation CDs consulting hotlines free audio content FTP tool for downloading audio files MP3 audios teleseminars/webinars toll-free 24/7 recorded lines transcriptions of Backup systems Bank accounts Barriers to success false real BlendTec Blogs Blue Microphones Bonuses Books Boot camps Bounce rates Business certificates Buyers. See Customers Calendars Call to action Camtasia software CDs Checklists Checks/money orders Coaching Collectors Comfort zone, expanding Commuter newspapers Competition as false barrier to success guarantee as competitive advantage price-based uniqueness of product from Computers.
See Jargon Testimonials Testing, web site Time, as false barrier to success Toll-free 24/7 recorded lines Tracy, Brian Traffic analysis of quantity of targeted Transcriptions Trends Trial software T-shirts Twitter Uniqueness of products of situations unique selling proposition Upselling Variations on themes Videos DVDs free live event video capture technology YouTube Visualthesaurus.com Webinars Web site accepting money via altering to address nonbuyer issues analysis of traffic to bounce rates building blocks for collector information sites cost of dedicated IP hosting for design of directing prospects to specific pages of domain names for editing e-mail system for graphic design sites Joomla as tool for keywords/key phrases of lead generation using (See Lead generation) membership sites organic ranking of outsourcing work on product idea generator sites security issues for shopping carts on testing improvements to traffic to web forms on web hosting services for Wheel charts Wizard-based systems World Wide Web.
So Good They Can't Ignore You: Why Skills Trump Passion in the Quest for Work You Love by Cal Newport
Apple II, bounce rate, business cycle, Byte Shop, Cal Newport, capital controls, cleantech, Community Supported Agriculture, deliberate practice, financial independence, follow your passion, Frank Gehry, information asymmetry, job satisfaction, job-hopping, knowledge worker, Mason jar, medical residency, new economy, passive income, Paul Terrell, popular electronics, renewable energy credits, Results Only Work Environment, Richard Bolles, Richard Feynman, rolodex, Sand Hill Road, side project, Silicon Valley, Skype, Steve Jobs, Steve Wozniak, web application, winner-take-all economy
Here’s a typical e-mail from among the many I receive from people asking for advice on growing their own blog audience: “I’ve finished my first month of posting and am at about three thousand views. The bounce rate, however, is incredibly high, particularly through Digg and Reddit submissions, where it can get close to 90 percent. I’m wondering what next steps you think I should take to bring down the bounce rate?” This new blogger was viewing blogging as an auction market. In his conception, there are many different types of capital relevant to your blog—from its format, to its post frequency, to its search-engine optimization, to how easy it is to find it on social networks (this particular blogger invested serious time in submitting every post to as many social networking sites as possible).
The only capital that matters is whether or not your posts compel the reader. Some top blogs in this space have notoriously clunky designs, but they all accomplish the same baseline goal: They inspire their readers. When you correctly understand the market where blogging exists, you stop calculating your bounce rate and start focusing instead on saying something people really care about—which is where your energy should be if you want to succeed. Mike Jackson, by contrast, correctly identified that he was in an auction market. He wasn’t sure exactly what he wanted to do, but he knew it would involve the environment, so he set out to gain any capital relevant to this broad topic.
People Powered: How Communities Can Supercharge Your Business, Brand, and Teams by Jono Bacon
Airbnb, barriers to entry, blockchain, bounce rate, Cass Sunstein, Charles Lindbergh, Debian, Firefox, if you build it, they will come, IKEA effect, Internet Archive, Jono Bacon, Kickstarter, Kubernetes, lateral thinking, Mark Shuttleworth, Minecraft, minimum viable product, more computing power than Apollo, planetary scale, pull request, Richard Stallman, Richard Thaler, sexual politics, Silicon Valley, Travis Kalanick, Y Combinator
As with everything you do, measure the performance of that work, evaluate it, and try to spot patterns that either point to problems or potential. Example: Imagine you have published your content plan for a few months (focused on an Engineering persona), and you have noticed that shorter blog posts seem to get a higher rate of hits as well as a better bounce rate. Step 2. Develop a hypothesis. When you spot a pattern, develop a hypothesis that you would like to test. For example, if you notice an increase in traffic given certain conditions, is it worth testing those conditions? Are there types of content, engagement, or events that seem to perform better and are worth testing?
Example: To test the short-blog-post hypothesis, we will distribute six blog posts over the coming weeks, all technical in nature (so for the same Engineering persona). Two of these posts will be 150 words long, two will be 300 words long, and two will be 1000 words long. We will promote these equally and track the number of hits, the bounce rate, and the reader rating for each post after it has been live for two weeks. Step 4. Review the results. Review the data from your experiment. Did it provide any insight into whether your hypothesis was correct (or even had the opposite effect)? In some cases the data may be so jumbled that it does not provide concrete data either way.
In some cases the data may be so jumbled that it does not provide concrete data either way. If so, it might be worth trying a different experiment to test the same hypothesis. Example: When we look at the data from our blog-post-length experiment, we find that the shorter posts get on average 30 percent more reads and a 10 percent improvement in bounce rate. The longer posts performed the worst. This proves our hypothesis was true. Step 5. Determine next steps. Based on the results of the experiment, review and amend your strategy. Again, never test a hypothesis and then fail to make any strategic adjustments based on it. Otherwise, all of this work is a waste of time.
Google AdWords by Anastasia Holdren
Bid Simulator uses internal auction data, including Quality Score, to estimate where ads would have appeared and how frequently they would have been clicked with different bids. The simulator estimates click, cost, and impression data for Google Search and the Search Partners, not the Google Display Network. See Also Maximum Cost-Per-Click (Max CPC) Bounce Rate Bounce rate is the percentage of single-page visits to a website. Broad Match Keyword Describes the default AdWords keyword match type. A broad match keyword can trigger ads when a searcher’s query matches the keyword, includes the keyword, or is a variation of it. Keyword variations include synonyms, singulars and plurals, and variants.
The Internet Trap: How the Digital Economy Builds Monopolies and Undermines Democracy by Matthew Hindman
A Declaration of the Independence of Cyberspace, accounting loophole / creative accounting, activist fund / activist shareholder / activist investor, AltaVista, Amazon Web Services, barriers to entry, Benjamin Mako Hill, bounce rate, cloud computing, computer vision, creative destruction, crowdsourcing, David Ricardo: comparative advantage, death of newspapers, discovery of DNA, disinformation, Donald Trump, fault tolerance, Filter Bubble, Firefox, future of journalism, Ida Tarbell, informal economy, information retrieval, invention of the telescope, Jeff Bezos, John von Neumann, Joseph Schumpeter, lake wobegon effect, large denomination, longitudinal study, loose coupling, Marc Andreessen, Mark Zuckerberg, Metcalfe’s law, natural language processing, Netflix Prize, Network effects, New Economic Geography, New Journalism, pattern recognition, peer-to-peer, performance metric, price discrimination, recommendation engine, Robert Metcalfe, selection bias, Silicon Valley, Skype, speech recognition, Stewart Brand, surveillance capitalism, technoutopianism, Ted Nelson, The Chicago School, Thomas Malthus, web application, Whole Earth Catalog, Yochai Benkler
In fact, monthly audience reach is a much shallower statistic not remotely comparable to audited circulation numbers. The number of sites that a typical user will visit over the course of any thirty-day period is huge, and any individual visit means little. Those who visit a site once, spend less than thirty seconds, and then immediately click away still count as visitors. Most news sites have a high “bounce rate,” in which users visit a single page and then leave. A study of the twenty-five most popular national news Online Local News • 107 outlets by the Project for Excellence in Journalism highlighted this pattern. Most unique visitors to these top sites—77 percent on average—are “extremely casual users” who visit just once or twice a month.11 For many sites the portion of casual users exceeds 90 percent.
Seattle Times, 159, 190 security, 2, 42, 164, 175–78 server farms, 4, 15, 20, 28–29, 167 Shapiro, Carl, 30 Shaw, Aaron, 170 Sherman Antitrust Act, 175 shipping, 63, 66, 79, 81–82 Shirky, Clay, 12, 165–66 Shoenfeld, Zach, 145 Shop Direct, 26 Sifry, Micah, 7 Silicon Valley, 35, 84 Simon, Herbert, 4 238 • Index Sinclair Broadcasting, 131 singular value decomposition (SVD), 45, 58–59 skill-based habits of use, 34–35 slideshows, 108, 151, 160–61 smartphones, 2, 142–44, 165 Snowden, Edward, 176 Social Reader, 151 software: attention economy and, 2, 4; economic geography and, 65–66; nature of internet and, 164, 167, 176; news and, 105, 107, 110, 143, 155; personalization and, 54; tilted playing field and, 20–23, 26, 33–34, 36; traffic and, 87 Sotheby’s, 42 Soul of a New Machine, The (Kidder), 82 Spanner, 21, 23 speed: attention economy and, 1–2, 21–25, 30, 54, 81–82, 147–48, 166–67, 170, 190, 193n1, 193n2; Google and, 1–2, 21–25, 80, 144, 147, 176; Microsoft and, 24; news and, 146–47; performance dashboards and, 24; profit and, 198n41; stickiness and, 2, 146; traffic and, 1–2, 21–25, 30, 54, 81–82, 146–48, 152, 166–67, 170, 190 statistics: audience reach and, 68, 93, 106, 109, 111, 134, 159, 189; Box aphorism and, 64; Google and, 27, 68; linear models and, 44; Netflix Prize and, 44, 46–47; news and, 106, 109, 111, 115, 122–23, 127–28, 134, 155, 159, 187, 189; smaller sites and, 27; traffic and, 93, 106, 109, 111, 115, 122–23, 127–28, 134 Stecula, Dominik, 169 stickiness: architectural vs. economic power and, 171; attention economy and, 2, 11, 13; cooperation and, 158–59; costs and, 154–58; digital audience dynamics and, 135–37, 146–52; economic geography and, 74; economies of scale and, 16; false solutions and, 137–46; faster load times and, 146; favorable website traits and, 166; Google and, 2, 24, 156, 167, 171; government subsidies and, 133, 137, 140–42; infrastructure and, 13, 23, 152–54; journalism and, 132–37, 140–48, 152, 154, 157, 159–61; mobile devices and, 2–4, 13, 39, 69, 109, 137, 142–44, 147, 152, 160, 165, 167, 170, 179; myth of monetization and, 134–35, 140, 145; nature of internet and, 167, 170–71, 176, 180; networks and, 18; newspapers and, 11, 133, 135–36, 139–41, 146–49, 152–60, 167, 180; nonprofit journalism and, 118, 133, 137, 140–42, 146, 160; open web and, 140; paywalls and, 132, 137–40, 147, 160; personalization and, 48, 53; philanthropy and, 133, 137, 140–42; pivot to video and, 144–46, 202n31; recommendation systems and, 48–49; search results speed and, 2; tilted playing field and, 16, 18, 23, 36; traffic and, 2, 101 Stigler, George, 41–42 Stillwell, David, 59 stochastic dynamical systems (SDS), 85, 185 stock market, 9, 85–88, 92, 95, 100, 185, 199n15 storage, 21–23, 26, 34, 36 Stroud, Natalie, 32 StumbleUpon, 26 subscriptions: attention economy and, 4; economic geography and, 65, 67; methodology on, 181, 187, 190; news and, 138–39, 146–47, 151, 153, 157, 201n8; political economy and, 43–44, 48, 52, 54; revenue and, 4, 17, 43–44, 48, 52, 54, 65, 67, 138–39, 146–47, 151, 153, 157, 181, 187, 190, 201n8; tilted playing field and, 17 Sullivan, Andrew, 70 surveillance, 176–77 Sweet, Diana, 169 switching costs, 8, 34, 63, 72, 78–79, 164 tablets, 3, 39, 137, 142–44, 152, 165 telegraph, 12, 36, 174 telephones, 16–17, 132, 174 television: advertising and, 68; attention economy and, 11–12; cable, 12; economic geography and, 66, 70; innovation and, 12; methodology and, 187–88, 190–91; news and, 11, 104, 107, 110–14, 114, 121–31, 134–35; personalization and, 38, 42; regression analysis and, 190–92; satellite, 12 Tenenboim, Ori, 130 TensorFlow, 21 Tenzig, 27 Texas Tribune, 140 Thomas, Kristin Yates, 31 Thrall, Trevor, 169 threshold effects, 30, 88, 104, 114–15, 119–22, 129, 186–91 Index Thurman, Neil, 39 tilted playing field: advertising and, 15, 17, 25, 28–36, 30; Amazon and, 20, 22, 26, 28; Apple and, 15; apps and, 16, 18, 26, 28; architectural advantages and, 19–25; Bing and, 24, 28, 30–32; blogs and, 17, 25, 35; branding and, 28–32, 36, 86, 166; competition and, 16–17, 21–22, 26–37; concentration and, 19, 30, 32; consumption and, 22–23, 26, 29–34, 37; design advantages and, 25–28; economies of scale and, 7–8, 16–20, 24–25, 37; efficiency and, 20–23, 26, 37; email and, 34–35; experiments and, 24–26, 28, 31–32; Facebook and, 15–23, 26, 35–37; filters and, 19; Google and, 15–16, 18, 20–32, 36–37, 194n24, 195n63; investment and, 15, 19–23, 28–29, 33; journalism and, 35; lock-in and, 34–37, 61, 101, 173; markets and, 20, 24, 28–37; Microsoft and, 15, 20, 22, 24, 26–33, 195n63; models and, 22, 25; Netflix and, 26; networks and, 16–23, 28, 35–37, 193n5; news and, 18–19, 26–36; path dependence and, 35–37; personalization and, 23; quality and, 26, 30–33, 36; rankings and, 25, 31; revenue and, 20, 24, 26, 28–29, 31, 194n39; search engines and, 17, 24, 30–32; software and, 20–23, 26, 33–34, 36; stickiness and, 16, 18, 23, 36; subscriptions and, 17; traffic and, 19–32, 36–37, 194n39; user learning and, 33–34; video and, 22, 24; Yahoo! and, 26, 30–31 Time magazine, 178 Time Warner, 172 Ting, Wayne, 35 traffic: agglomeration and, 82–83; Amazon and, 87; attention economy and, 1, 3, 7–13; audience reach and, 83–96, 99–101, 104, 106–11, 114–18, 121, 129, 134, 169, 186–89; bounce rate and, 106; change and, 99–101; churn and, 9, 84–85, 88–95, 100–1, 163–64, 167; cities and, 82–83; click-through rates and, 56–57; competition and, 83, 86–87, 101; comScore and, 10, 87, 104–10, 113, 116, 119–22, 127, 128–29, 187–88, 199n19; concentration and, 7–8, 30, 32, 63, 83–88, 96, 99–101, 104, 122, 171, 199n15; consumer habit and, 86; distribution of, 84–85, 88–100; dynamics of, 82–101, 184–86; economic geography and, 63, 77–81; • 239 experiments and, 55, 100, 118, 130, 133, 160; Facebook and, 98, 100; favorable website traits and, 166; fluctuations in, 84–86, 93, 99; Google and, 87, 90, 98; growth in, 84, 88, 91, 95–96, 100; high-resolution data and, 87–88; Hitwise and, 84, 87–88, 89; innovation and, 100; investment and, 100; journalism and, 101; leakage and, 88–89, 90, 92; logarithms and, 88–96, 97, 100, 184–86; markets and, 84–90, 94, 95–100, 199n15, 200n18; methodology and, 181, 185, 188; metrics for, 11, 83, 87, 89, 101, 106–11, 115, 128–29, 133–34, 136, 148, 154–57, 160–61, 188; mobile devices and, 2–4, 13, 39, 69, 109, 137, 142–44, 147, 152, 160, 165, 167, 170, 179; models and, 82–84, 95, 99–100, 181–84, 199n15; monitoring software and, 87; multimedia content and, 151–52; nature of internet and, 164, 167, 171–72; net neutrality and, 64, 84, 131, 170–72, 175; networks and, 199n19 (see also networks); news and, 88–91, 96, 99–114, 118–22, 125, 130, 133–40, 143, 146–61; open web and, 132, 137, 140; overlap and, 67, 76–77, 108, 110; page views and, 24, 87, 106–18, 121, 125–29, 151, 157, 160–61, 188–89, 200n18; paywalls and, 138–39; personalization and, 40, 48, 53–56, 60; power laws and, 83, 86, 89, 93, 95–96, 184–85; randomness and, 85, 92, 95–96, 99, 121; rankings and, 7, 25, 31, 54, 84–96, 100, 110–12, 136, 157, 186; recommendation systems and, 39–40, 45, 48–49, 53, 59–61, 149; revenue and, 63, 65–68, 73–75, 79; search engines and, 101; shipping and, 63, 66, 79, 81–82; simulating, 93–99; speed and, 1–2, 21–25, 30, 54, 81–82, 146–48, 152, 166–67, 170, 190; stability and, 84–88, 91, 93, 99–101; statistics and, 93; stickiness and, 2, 101; as stock market, 85–87; surfing and, 77, 79, 107; tilted playing field and, 19–32, 36–37, 194n39; transportation and, 79, 82, 182; unique visitors and, 87–88, 106–11, 128, 134; volatility by, 91–93; Yahoo!
Growth Hacking Techniques, Disruptive Technology - How 40 Companies Made It BIG – Online Growth Hacker Marketing Strategy by Robert Peters
Airbnb, bounce rate, business climate, citizen journalism, crowdsourcing, digital map, Google Glasses, Jeff Bezos, Lean Startup, Menlo Park, Network effects, new economy, pull request, revision control, ride hailing / ride sharing, search engine result page, sharing economy, Skype, TaskRabbit, turn-by-turn navigation, ubercab
It is a software platform for inbound marketing that helps companies attract visitors, convert leads, and close on sales/deals. Users can manage all of their web content and social media accounts in one location, with tools in place to measure success rates by leads and customers. This is a more effective use of collected data than the traditional analytics of page views, time on page, and bounce rate among others. Hubspot began with 3 customers in 2006 and by 2013 had 10,595. The company follows a strategy of offering daily free content including its popular website grader, which analyzed more than 2 million websites in its first three years of operation. The HubSpot philosophy is that free content brings people to the company’s site thus generating quality leads at a lesser cost than could be achieved with traditional marketing techniques.
The Millionaire Fastlane: Crack the Code to Wealth and Live Rich for a Lifetime by Mj Demarco
8-hour work day, Albert Einstein, AltaVista, back-to-the-land, Bernie Madoff, bounce rate, business process, butterfly effect, buy and hold, cloud computing, commoditize, dark matter, delayed gratification, demand response, Donald Trump, fear of failure, financial independence, fixed income, housing crisis, Jeff Bezos, job-hopping, Lao Tzu, Mark Zuckerberg, passive income, passive investing, payday loans, Ponzi scheme, price anchoring, Ronald Reagan, upwardly mobile, wealth creators, white picket fence, World Values Survey, zero day
The Tribe Has Spoken My Web site needed a redesign, and I spent six weeks creating a new look. I was excited, and the world was going to love this design-it was clean, user friendly, and showcased my design prowess. And then I launched it. And the world hated it. Complaints poured in. My site's bounce rate (people who visit one page and immediately leave) skyrocketed. My conversion rate plummeted to virtually nothing. I went from 1,200 leads per day to barely 500. The tribe had spoken. Despite my investment in that redesign, I immediately reverted back to the old version and trashed six weeks of work.
In fact, every redesign I've ever done in 10-plus years was met with resistance. The question for critique was, how much was normal? And how much was legitimate? Complaints of change are the least informative and therefore are the ones most difficult to decipher. For my redesign failure, data confirmed that the complaints were substantial. Bounce rates tripled and my conversion ratio suffered. I had to suck up the failure, revert back, and start over. When you change, there will be complaints. Guaranteed. And yes, not all of them are actionable simply because human psychology is in play, not the integrity of your work. Complaints of Expectation Complaints of expectation occur when you negatively violate the expectation of your customer.
Understanding Sponsored Search: Core Elements of Keyword Advertising by Jim Jansen
AltaVista, barriers to entry, Black Swan, bounce rate, business intelligence, butterfly effect, call centre, Claude Shannon: information theory, complexity theory, correlation does not imply causation, en.wikipedia.org, first-price auction, information asymmetry, information retrieval, intangible asset, inventory management, life extension, linear programming, longitudinal study, megacity, Nash equilibrium, Network effects, PageRank, place-making, price mechanism, psychological pricing, random walk, Schrödinger's Cat, sealed-bid auction, search engine result page, second-price auction, second-price sealed-bid, sentiment analysis, social web, software as a service, stochastic process, telemarketer, the market place, The Present Situation in Quantum Mechanics, the scientific method, The Wisdom of Crowds, Vickrey auction, Vilfredo Pareto, yield management
Typically, a bot is endowed with the capability to react to different situations it may encounter. Two common types of bots are agents and spiders. Bots are used by companies like search engines to discover Web sites for indexing. Short for robot (Source: IAB) (see Chapter 2 model). Bounce: a visitor whose behaviors are classified within the bounce rate (see Chapter 7 analytics). Bounce rate: refers to the percentage of people that immediately exit or do not progress beyond the entry page within a certain time limit (Source: modified from Quirk and WebTrends) (see Chapter 7 analytics). Brand: distinctive name or trademark that identifies a product or manufacturer.
Lean Analytics: Use Data to Build a Better Startup Faster by Alistair Croll, Benjamin Yoskovitz
Airbnb, Amazon Mechanical Turk, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, barriers to entry, Bay Area Rapid Transit, Ben Horowitz, bounce rate, business intelligence, call centre, cloud computing, cognitive bias, commoditize, constrained optimization, en.wikipedia.org, Firefox, Frederick Winslow Taylor, frictionless, frictionless market, game design, Google X / Alphabet X, hockey-stick growth, Infrastructure as a Service, Internet of things, inventory management, Kickstarter, lateral thinking, Lean Startup, lifelogging, longitudinal study, Marshall McLuhan, minimum viable product, Network effects, pattern recognition, Paul Graham, performance metric, place-making, platform as a service, recommendation engine, ride hailing / ride sharing, rolodex, sentiment analysis, skunkworks, Skype, social graph, social software, software as a service, Steve Jobs, subscription business, telemarketer, transaction costs, two-sided market, Uber for X, web application, Y Combinator
The hypothesis was that the feature would be worth the first-time ordering pain, after which ordering would be much easier directly through Instagram. “Convenience was the hypothesis,” noted Massimo. But Massimo and his team were wrong. Not only were orders low, but page views started to drop on the landing page that promoted the feature, and bounce rate was high as well. It just wasn’t resonating. Two weeks after the feature was removed, the number of transactions doubled, and it continues to increase. The bounce rate on the new landing page improved while sign-in goal completions increased. So what did the Static Pixels team learn? “For starters, I think people didn’t transact through Instagram because it’s a very new and foreign process,” Massimo said.
Hello, Habits by Fumio Sasaki
And more than anything, the objective of yoga isn’t to strike poses. Once I got a little used to it, I rather enjoyed the fact that there were few guys around. Step 14: Realize that hurdles are more powerful than rewards Faced with massive amounts of information before our eyes, we’re getting more and more impatient. While the bounce rate (or the percentage of visitors who enter a website and then navigate—“bounce”—away without viewing the other pages) for sites that reload within a maximum of two seconds is around 9 percent, almost 40 percent quit looking at the site when the reload time is five seconds. In other words, regardless of how interesting the content on the site may be and no matter what fabulous products are being sold there, things that take time don’t get used.
Hacking Growth: How Today's Fastest-Growing Companies Drive Breakout Success by Sean Ellis, Morgan Brown
Airbnb, Amazon Web Services, barriers to entry, Ben Horowitz, bounce rate, business intelligence, business process, correlation does not imply causation, crowdsourcing, DevOps, disruptive innovation, Elon Musk, game design, Google Glasses, Internet of things, inventory management, iterative process, Jeff Bezos, Khan Academy, Kickstarter, Lean Startup, Lyft, Mark Zuckerberg, market design, minimum viable product, Network effects, Paul Graham, Peter Thiel, Ponzi scheme, recommendation engine, ride hailing / ride sharing, side project, Silicon Valley, Silicon Valley startup, Skype, Snapchat, software as a service, Steve Jobs, subscription business, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, working poor, Y Combinator, young professional
Then you need a data analyst who can mine those sources of data for patterns and rich insights that can lead to growth ideas to experiment with. These days most companies, even the most nascent, shoestring start-ups, are keeping close track of basic analytics for their websites and products, such as those captured by Google Analytics. But while metrics like page views, visits, and bounce rates are important to collect, they barely begin to tell the whole story about how customers interact with your product. That’s because these are very surface level metrics that don’t tend to reveal deeper insights into what customers truly value about what you are selling and whether you have achieved product/market fit.
Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel
Albert Einstein, algorithmic trading, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, backtesting, Black Swan, book scanning, bounce rate, business intelligence, business process, butter production in bangladesh, call centre, Charles Lindbergh, commoditize, computer age, conceptual framework, correlation does not imply causation, crowdsourcing, dark matter, data is the new oil, en.wikipedia.org, Erik Brynjolfsson, Everything should be made as simple as possible, experimental subject, Google Glasses, happiness index / gross national happiness, job satisfaction, Johann Wolfgang von Goethe, lifelogging, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, mass immigration, Moneyball by Michael Lewis explains big data, Nate Silver, natural language processing, Netflix Prize, Network effects, Norbert Wiener, personalized medicine, placebo effect, prediction markets, Ray Kurzweil, recommendation engine, risk-adjusted returns, Ronald Coase, Search for Extraterrestrial Intelligence, self-driving car, sentiment analysis, Shai Danziger, software as a service, speech recognition, statistical model, Steven Levy, text mining, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Davenport, Turing test, Watson beat the top human players on Jeopardy!, X Prize, Yogi Berra, zero-sum game
Peter van der Graff, “How Search Engines Use Machine Learning for Pattern Detection,” Search Engine Watch, December 1, 2011. http://searchenginewatch.com/article/2129359/How-Search-Engines-Use-Machine-Learning-for-Pattern-Detection. Education portal: “Case Study: How Predictive Analytics Generates $1 Million Increased Revenue,” case study provided by Prediction Impact, Inc. www.predictiveanalyticsworld.com/casestudy.php. Google: D. Sculley, Robert Malkin, Sugato Basu, and Roberto J. Bayardo, “Predicting Bounce Rates in Sponsored Search Advertisements,” Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2009. www.bayardo.org/ps/kdd2009.pdf. Sugato Basu, Ph.D., Google. “Lessons Learned in Predictive Modeling for Ad Targeting,” Predictive Analytics World San Francisco 2011 Conference, March 14, 2011, San Francisco, CA. www.predictiveanalyticsworld.com/sanfrancisco/2011/agenda.php#day1-7.
Bank 3.0: Why Banking Is No Longer Somewhere You Go but Something You Do by Brett King
3D printing, additive manufacturing, Airbus A320, Albert Einstein, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, asset-backed security, augmented reality, barriers to entry, bitcoin, bounce rate, business intelligence, business process, business process outsourcing, call centre, capital controls, citizen journalism, Clayton Christensen, cloud computing, credit crunch, crowdsourcing, disintermediation, en.wikipedia.org, fixed income, George Gilder, Google Glasses, high net worth, I think there is a world market for maybe five computers, Infrastructure as a Service, invention of the printing press, Jeff Bezos, jimmy wales, Kickstarter, London Interbank Offered Rate, M-Pesa, Mark Zuckerberg, mass affluent, Metcalfe’s law, microcredit, mobile money, more computing power than Apollo, Northern Rock, Occupy movement, optical character recognition, peer-to-peer, performance metric, Pingit, platform as a service, QR code, QWERTY keyboard, Ray Kurzweil, recommendation engine, RFID, risk tolerance, Robert Metcalfe, self-driving car, Skype, speech recognition, stem cell, telepresence, Tim Cook: Apple, transaction costs, underbanked, US Airways Flight 1549, web application
The homepage is a hotly contested property in most banks today, with every product team in the retail bank (and in some cases the whole bank) competing to get their hyperlink, product promotion, or anything else on the homepage. This is entirely counterproductive as it clutters the homepage and results in the risk of high bounce rates (we’ll talk more about this in later chapters). When we type in “Savings Account” or “Checking Account” into Google, we do get some optimised product selection experiences, but SEO (Search Engine Optimisation11) is still a challenge for many of these brands. Given the critical nature of online in brand selection, one would think that there would be millions of dollars a year spent on optimising the customer journey, but in most cases there have only been incremental improvements over the last five to six years.
How to Be a Liberal: The Story of Liberalism and the Fight for Its Life by Ian Dunt
4chan, Alfred Russel Wallace, bank run, battle of ideas, Bear Stearns, Bear Stearns, Big bang: deregulation of the City of London, Boris Johnson, bounce rate, British Empire, Brixton riot, Carmen Reinhart, centre right, David Ricardo: comparative advantage, disinformation, Dominic Cummings, Donald Trump, eurozone crisis, experimental subject, feminist movement, Francis Fukuyama: the end of history, full employment, Growth in a Time of Debt, illegal immigration, invisible hand, John Bercow, Kenneth Rogoff, liberal world order, Mark Zuckerberg, mass immigration, means of production, Mohammed Bouazizi, Northern Rock, old-boy network, Paul Samuelson, Peter Thiel, price mechanism, profit motive, quantitative easing, recommendation engine, road to serfdom, Ronald Reagan, Saturday Night Live, Scientific racism, Silicon Valley, Steve Bannon, The Wealth of Nations by Adam Smith, too big to fail, upwardly mobile, Winter of Discontent, working poor, zero-sum game
A powerful new infrastructure of analysis grew, using websites such as Google Analytics, Omniture and Coremetrics, to collect and evaluate user data. It had its own vocabulary to assess the most cherished behaviour of all: engagement. Measurement centred on the number of clicks, page impressions, time on site and bounce rate – the percentage of users who left after visiting just one page. This was the information and design system of advertising online. But increasingly it also became the status quo for non-advertising too. Social media companies could make more money on advertising when they captured the maximum amount of user time and attention possible.
Seeking SRE: Conversations About Running Production Systems at Scale by David N. Blank-Edelman
Affordable Care Act / Obamacare, algorithmic trading, Amazon Web Services, backpropagation, bounce rate, business continuity plan, business process, cloud computing, cognitive bias, cognitive dissonance, commoditize, continuous integration, crowdsourcing, dark matter, database schema, Debian, defense in depth, DevOps, domain-specific language, en.wikipedia.org, fault tolerance, fear of failure, friendly fire, game design, Grace Hopper, information retrieval, Infrastructure as a Service, Internet of things, invisible hand, iterative process, Kubernetes, loose coupling, Lyft, Marc Andreessen, microaggression, microservices, minimum viable product, MVC pattern, performance metric, platform as a service, pull request, RAND corporation, remote working, Richard Feynman, risk tolerance, Ruby on Rails, search engine result page, self-driving car, sentiment analysis, Silicon Valley, single page application, Snapchat, software as a service, software is eating the world, source of truth, the scientific method, Toyota Production System, web application, WebSocket, zero day