LIVErtising 2015 5 advertising goes digital slideshare
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LIVErtising 2015 5 advertising goes digital slideshare
- 5. LIVErtising.NET IHECS 2014-2015 Mobile-ready company websites in Wallonia 5 68% 30% 5%
- 12. LIVErtising.NET IHECS 2014-201512 total digital = 47%
- 14. BUT…
- 24. COOKIES…?
- 25. LIVErtising.NET IHECS 2014-2015 Are cookies dead? 25 02 03 01 limited REACH poor CROSS- DEVICE tracking PRIVACY concerns limited REACH poor CROSS- DEVICE tracking
- 27. LIVErtising.NET IHECS 2014-201527 If you continue to use this site without changing the settings, you consent to the use of the cookies.
- 28. LIVErtising.NET IHECS 2014-2015 So, what now? 28 02 03 01 STABLE identifiers STATISTICAL identifiers KNOWN identifiers STABLE identifiers STATISTICAL identifiers
- 30. BLOWING A FEW MISTAKES
- 31. #1
- 32. LIVErtising.NET IHECS 2014-2015 Blowing a few myths 32
- 35. 1 2 3 Benchmark?
- 36. LIVErtising.NET IHECS 2014-2015 example de silo en digital 36
- 37. LIVErtising.NET IHECS 2014-201537 S i l o s
- 39. #2
- 52. #2
- 53. #3
- 73. LIVErtising.NET IHECS 2014-201573 • CTA: wording, size, colour, location... • Headline (id.) • Copy: Product/service description • Design: style, colours, background, size, position • Visuals: position, size, people/abstract, gender, … • Forms: length, type of fields, place, CTA… • Pricing, promotional offers...
- 74. #3
- 78. #4
- 79. LIVErtising.NET IHECS 2014-2015 Blowing a few myths 79
- 80. LIVErtising.NET IHECS 2014-201580 AmplifyInteractBuild Launch your page Respond to fans Get shares, RTs, … Build a fan base Publish to fans Listen to fans
Notes de l'éditeur
- 68% of cies in Wallonie have a website, only 5 % are mobile ready http://www.eteamsys.com/conference/google/files/CONF-ETEAMSYS-GOOGLE-MIKE-BRX231014%20V3.pdf
- http://www.digimedia.be/whos-who-company-list.php?lng=fr&rubric=whos-who-digital-media
- http://www.marketingcharts.com/wp/wp-content/uploads/2013/09/MarketingCharts-Top-5-Charts-of-Aug-2013.pdf
- http://www.marketingcharts.com/online/2015-marketing-budget-trends-by-channel-49517/ 2015 Marketing Budget Trends, by Channel December 16, 2014 - by MarketingCharts staff StrongView-2015-Marketing-Budget-Plans-by-Program-Dec2014Business leaders are generally optimistic about the direction their marketing budgets will take next year, according to a StrongView survey [pdf]. Indeed, 54% expect their budgets to grow next year (up from 46% in last year’s survey), with one-third of those forecasting budget growth of at least 10%. So which channels are slated for increases – and which will see budget cuts? The findings strike a familiar tone with respect to the online-offline divide. In other words, digital marketing channels are those topping the list of planned budget increases, while traditional channels head the list of those set for budget reductions. Within the US, this shift has been in the works for quite some time, even though survey data suggests that traditional media advertising continues to perform very well relative to online advertising. In any case, email marketing is the program for which the largest share (60.7%) of respondents plan budget increases, a finding that makes sense given email’s consistently highly-rated ROI. Of note, despite difficulties measuring its ROI, social follows email, with almost half of respondents planning an increase in 2015. (Maybe marketers should pay more attention to email than social – or Facebook, at least? According to Forrester Research, “If you have to choose between adding a subscriber to your email list or gaining a new Facebook fan, go for email every time.”) Rounding out the top 5 programs (of 10 identified) tabbed for budget increases next year are mobile marketing (40.2%), search (38.3%) and display (37.4%). Clearly, digital is where the action is. Traditional media, meanwhile, continues to suffer from planned decreases. Print advertising remains most susceptible to cuts, with almost one-third of respondents expecting a decrease in funding. Direct mail (22.3%) and TV/radio advertising (17.8%) are also under the gun, with more respondents planning to decrease than increase their budgets. 2015 and 2014 Budget Trends Compared Looking at how responses to this year’s survey compare with last year’s, a few notable points emerge: There is more interest in mobile budgets this year, with the 40% predicting an increase representing significant growth from last year’s 32%; Similarly, the proportion of respondents predicting an email marketing budget hike has grown from last year; and Consistent with last year’s results, planned budget increases for trade shows and events and public relations outpace planned spending decreases, although the gap is narrowing for trade shows. Honing in on email marketing programs, the survey indicates that: Triggered/transactional programs (42.2%) and lifecycle programs (41.4%) top the list of planned spending hikes, unlike last year, when social media channel growth was on top; and Loyalty (45.2%) and welcome (35.9%) are the lifecycle email marketing programs that most plan to increase spending on, much as they were last year. About the Data: The StrongView industry survey was conducted with SENSORPRO from November 21 to December 5, 2014, among 377 business leaders. Some 33.5% of respondents come from organizations with 1-50 employees, while 28.2% come from organizations with more than 1,000 employees. Almost three-quarters (73.4%) are with companies headquartered in North America. Respondents represent companies in a range of industries, with marketing/advertising (16.4%), technology/internet (14.3%) and retail (10.5%) most heavily represented.
- Online advertising continues to remain concentrated with the 10 leading ad-selling companies, which accounted for 71% of total revenues in Q4 2013, down slightly from the 72% reported in Q4 2012. Companies ranked 11th to 25th accounted for 10% of revenues in Q4 2013, consistent with the 10% reported in Q4 2012. Despite the emergence of a few heavyweights in internet advertising publishing, the concentration of top-10 revenue has remained relatively unchanged over the past ten years, fluctuating between 69% and 74%.
- “Internet” is an empty word until you specify what it is; contrary to TV advertising, radio, and so on, which are immediately specific: 30’ commercial, …
- https://gigaom.com/2014/03/29/as-advertisers-phase-out-cookies-whats-the-alternative/ As advertisers phase out cookies, what’s the alternative? Nima Wedlake, Thomvest Ventures Mar. 29, 2014 - 12:00 PM PDT 10 Comments Credit: Flickr/soosay A A What will become of the humble cookie? The tiny data files sent from websites to browsers have come under much scrutiny recently, particularly from privacy advocates and policy makers. Even advertisers agree that the web needs a viable alternative that balances privacy concerns with marketers’ desire to target users effectively. As investors focused on the advertising technology space, we’ve paid close attention to the discussions surrounding cookies and other tracking mechanisms, given their importance to the ad ecosystem. In this post, we’ll summarize these discussions and touch on emerging tracking technologies that may ultimately replace cookies. Is the cookie crumbling? Third-party cookies (i.e., cookies set by someone other than the website being visited) have enabled digital advertising to flourish into the multi-billion dollar industry it is today. They are used to run retargeting campaigns, enable real-time bidding exchanges, and reconcile user-specific demographic data across multiple sources. And they’re everywhere–nearly 85 percent of the top 1,000 sites have cookies set by a third party, according to a study by the UC Berkeley Center for Law and Technology. Yet many industry leaders have grimly declared “the death of the cookie” sometime within the next few years. What’s the cause of their cynicism? Here are some of the most common critiques: Privacy concerns: Critics argue that third-parties collect and store excessive data on consumers, often without their knowledge. Consumers agree–57 percent of Internet users are either “concerned” or “very concerned” about their online privacy, according to a recent study by analytics firm Annalect. Law makers are concerned as well, and have floated potential legislation to limit the scope of tracking by third-party advertisers. They’ve tasked industry and consumer groups with defining a browser-based “Do Not Track” standard that would allow users to easily opt out of tracking. Limited reach: Cookies aren’t effective in mobile environments (third-party cookies are blocked by default on iOS devices, for instance). This can be limiting for advertisers, given that we spend more time on mobile devices than we do laptops and PCs. Additionally, many desktop browsers including Firefox, Safari and Internet Explorer have chosen to preemptively opt users out of accepting third-party cookies. Poor cross-device tracking: Cookies can’t provide cross-device targeting capabilities (i.e. targeting the same user across mobile and desktop devices). As consumer attention continues to bifurcate across devices, the value of desktop-only cookies starts to decline. So what’s next? What’s the magic bullet that balances privacy considerations with sophisticated cross-device tracking capabilities? Some interesting cookie alternatives have emerged, each with their own benefits and drawbacks. We can classify these identifiers into three buckets: known, stable and statistical. Known identifiers are typically associated with some form of personal information, such as a name or email address. Large consumer internet companies have access to millions of known IDs, across both desktop and mobile. These IDs have some important advantages over third-party cookies: Known IDs are highly accurate given that we typically pass highly accurate demographic and interest data to social media companies like Facebook and Twitter. Known IDs have large mobile and cross-device reach (persistent login across desktop and mobile devices) Privacy concerns may be mitigated by giving users ample control over the how/when the ID is passed to advertisers Both Facebook and Twitter are expected to begin allowing advertisers to use their known IDs outside of their “walled gardens” (Twitter’s acquisition of MoPub has many industry observers predicting that this will happen on mobile in the near future). Stable identifiers are typically associated with a specific device or browser. Apple’s IDFA (“identifierForAdvertising”) used on iOS devices is a good example of a stable ID. These IDs are typically persistent (don’t expire or erase), anonymous and allow for user opt-out. Most notably, Google is rumored to be developing a stable ID system, known as AdID. The AdID would be a unique identifier associated with the Chrome browser and Android devices that persistently identifies users. It would be anonymously passed to advertisers approved by Google, while giving users greater control over how they are tracked online (such as the ability to opt-out or block specific advertisers). The AdID could also include “known” data for users logged in to Google products like Gmail and Google. Details on AdID are sparse, but its implications are vast given Google’s massive reach and scale. See Ari Paparo’s excellent post for some predictions on how the AdID may be designed. Finally, statistical IDs attempt to bypass cookies entirely by using other attributes to identify users, such as IP address, device type, and browsing patterns. Using these attributes, companies like Drawbridge, TapAd and AdTheorent can probabilistically determine whether two devices are connected (for instance, your phone and PC). The resulting statistical ID can then be used for ad targeting. Here’s a more detailed description of the technology. Although promising, the technology is still in its early days; most statistical IDs are typically only 60 to 70 percent accurate. Nonetheless, many within the industry are optimistic about the potential of statistical IDs because they allow for cross-device targeting, are anonymous (quelling some privacy concerns) and aren’t owned by a single large player like Google or Facebook. Nima Wedlake is an analyst at Thomvest Ventures, focusing on advertising technology. Follow him on Twitter @nimajw.
- https://gigaom.com/2014/03/29/as-advertisers-phase-out-cookies-whats-the-alternative/ As advertisers phase out cookies, what’s the alternative? Nima Wedlake, Thomvest Ventures Mar. 29, 2014 - 12:00 PM PDT 10 Comments Credit: Flickr/soosay A A What will become of the humble cookie? The tiny data files sent from websites to browsers have come under much scrutiny recently, particularly from privacy advocates and policy makers. Even advertisers agree that the web needs a viable alternative that balances privacy concerns with marketers’ desire to target users effectively. As investors focused on the advertising technology space, we’ve paid close attention to the discussions surrounding cookies and other tracking mechanisms, given their importance to the ad ecosystem. In this post, we’ll summarize these discussions and touch on emerging tracking technologies that may ultimately replace cookies. Is the cookie crumbling? Third-party cookies (i.e., cookies set by someone other than the website being visited) have enabled digital advertising to flourish into the multi-billion dollar industry it is today. They are used to run retargeting campaigns, enable real-time bidding exchanges, and reconcile user-specific demographic data across multiple sources. And they’re everywhere–nearly 85 percent of the top 1,000 sites have cookies set by a third party, according to a study by the UC Berkeley Center for Law and Technology. Yet many industry leaders have grimly declared “the death of the cookie” sometime within the next few years. What’s the cause of their cynicism? Here are some of the most common critiques: Get all the news you need about Media with the Gigaom newsletter Subscribe Privacy concerns: Critics argue that third-parties collect and store excessive data on consumers, often without their knowledge. Consumers agree–57 percent of Internet users are either “concerned” or “very concerned” about their online privacy, according to a recent study by analytics firm Annalect. Law makers are concerned as well, and have floated potential legislation to limit the scope of tracking by third-party advertisers. They’ve tasked industry and consumer groups with defining a browser-based “Do Not Track” standard that would allow users to easily opt out of tracking. Limited reach: Cookies aren’t effective in mobile environments (third-party cookies are blocked by default on iOS devices, for instance). This can be limiting for advertisers, given that we spend more time on mobile devices than we do laptops and PCs. Additionally, many desktop browsers including Firefox, Safari and Internet Explorer have chosen to preemptively opt users out of accepting third-party cookies. Poor cross-device tracking: Cookies can’t provide cross-device targeting capabilities (i.e. targeting the same user across mobile and desktop devices). As consumer attention continues to bifurcate across devices, the value of desktop-only cookies starts to decline. Photo from Thinkstock/bestdesigns Photo from Thinkstock/bestdesigns Stacking up the alternatives So what’s next? What’s the magic bullet that balances privacy considerations with sophisticated cross-device tracking capabilities? Some interesting cookie alternatives have emerged, each with their own benefits and drawbacks. We can classify these identifiers into three buckets: known, stable and statistical. Known identifiers are typically associated with some form of personal information, such as a name or email address. Large consumer internet companies have access to millions of known IDs, across both desktop and mobile. These IDs have some important advantages over third-party cookies: Known IDs are highly accurate given that we typically pass highly accurate demographic and interest data to social media companies like Facebook and Twitter. Known IDs have large mobile and cross-device reach (persistent login across desktop and mobile devices) Privacy concerns may be mitigated by giving users ample control over the how/when the ID is passed to advertisers Both Facebook and Twitter are expected to begin allowing advertisers to use their known IDs outside of their “walled gardens” (Twitter’s acquisition of MoPub has many industry observers predicting that this will happen on mobile in the near future). Stable identifiers are typically associated with a specific device or browser. Apple’s IDFA (“identifierForAdvertising”) used on iOS devices is a good example of a stable ID. These IDs are typically persistent (don’t expire or erase), anonymous and allow for user opt-out. Most notably, Google is rumored to be developing a stable ID system, known as AdID. The AdID would be a unique identifier associated with the Chrome browser and Android devices that persistently identifies users. It would be anonymously passed to advertisers approved by Google, while giving users greater control over how they are tracked online (such as the ability to opt-out or block specific advertisers). The AdID could also include “known” data for users logged in to Google products like Gmail and Google. Details on AdID are sparse, but its implications are vast given Google’s massive reach and scale. See Ari Paparo’s excellent post for some predictions on how the AdID may be designed. Finally, statistical IDs attempt to bypass cookies entirely by using other attributes to identify users, such as IP address, device type, and browsing patterns. Using these attributes, companies like Drawbridge, TapAd and AdTheorent can probabilistically determine whether two devices are connected (for instance, your phone and PC). The resulting statistical ID can then be used for ad targeting. Here’s a more detailed description of the technology. Although promising, the technology is still in its early days; most statistical IDs are typically only 60 to 70 percent accurate. Nonetheless, many within the industry are optimistic about the potential of statistical IDs because they allow for cross-device targeting, are anonymous (quelling some privacy concerns) and aren’t owned by a single large player like Google or Facebook. Nima Wedlake is an analyst at Thomvest Ventures, focusing on advertising technology. Follow him on Twitter @nimajw.
- Online vs Offline = Either / Or - Agencies / campaigns / advertisers Digital = separate world from offline – No: SMARTphones, SMARTcars, SMARTobject: ON & OFF convert Need to decline the BRAND in an INTEGRATED MULTICHANNEL mode ----------- OOH Advertising Reach Said Outpacing Other Media May 8, 2012 inShare 1 Adding out-of-home (OOH) advertising formats to other media can significantly boost a campaign’s reach, says the Outdoor Advertising Association of America (OAAA) in a May 2012 report conducted by the Media Behavior Institute. The study tabbed the reach of billboards highest among outdoor formats, at 83% of adults aged 18-64, with alternative (42%), street furniture (28%), and transit (11%) following. Comparing these formats to the reach of other media, the report suggests that coupling billboards with mobile advertising can increase mobile’s reach by more than 300%, while billboards and the internet together can more than double the internet’s reach in the afternoon. Other results indicate that combining street furniture with social networking can increase the latter’s reach by up to 66%. OOH Audiences Feel More Positive Data from the “USA TouchPoints” study indicates that consumers feel more positive when exposed to OOH advertising, when compared to other media such as live TV. For example, on an emotional index, a higher proportion of the billboard audience than live TV audience feels confident and excited, while 40% less feel bored (9% vs. 15%). This pattern extends to other media, too: billboard audiences are slightly more likely than radio audiences to say they are happy (72% vs. 68%), while alternative audiences are much less likely than live TV audiences to be bored (5% vs. 15%). Similarly, radio listeners are twice as likely to feel frustrated as alternative audiences (16% vs. 8%), and live TV audiences are 40% more likely than transit audiences to be frustrated (14% vs. 10%). The study used data from 1,000 smartphones diaries to capture data every 30 minutes over 10 days, tracking details such as activities, emotion, location, media use, and social setting. One reason why OOH ads might be received positively by their audiences is that they provide a welcome distraction from daily life, particularly while traveling, which accounts for 62% of away-from-home time. Indeed, results from a CBS Outdoor survey released in March 2012 indicate that two-thirds of the European adults surveyed agreed that outdoor advertising is a welcome distraction while traveling, a proportion that rose to 72% among 18-34-year-old smartphone and tablet owners. OOH Audiences Highly Engaged in Other Activities The study also finds a significant proportion of OOH audiences are also using other media. For example, 63% of billboard’s audience uses radio in the same half-hour, a proportion that drops to 56% among 18-34-year-olds, but rises to 71% among those with $75k or more in annual household income. Similarly, 21% of transit’s audience also text, use an application or browse the internet on mobile in the same half-hour, rising to 31% among 18-34-year-olds. Other Findings: The overall reach of transit ads is smaller on the weekend than during the week (8% vs. 12%), as it is for billboards (79% vs. 84%). Reach is the same during the week and the weekend for street furniture (28%), while it rises on the weekend for alternative (44% vs. 41%). Only 6% of street furniture audiences are bored. 7% of the alternative audience aged 18-34, and 14% of the transit audience in that age group use social networking sites in the same half-hour.
- Re-imagining Google Analytics to support the versatile usage patterns of today's users Monday, October 29, 2012 | 9:30 AM Labels: Announcements A typical consumer today uses multiple devices to surf the web and interact in many ways with your business. For most large businesses, already swimming in many sources of hashed data, it’s an enormous challenge, but also an incredible opportunity. Measurement today is evolving from technology that counts site traffic into a broader system that measures your effectiveness in advertising, sales, product usage, support, and retention. Ultimately, this sort of integrated measurement can help you deliver the best service, products, and experiences for your customers. We’ve been developing solutions, like Google Analytics Premium and Mobile App Analytics to advance this vision. For large enterprises, such as Premium customers and those who want to work with APIs, we're now starting to offer “Universal Analytics.” This will help these customers tailor Google Analytics to their needs, integrate their own datasets and ultimately get a more complete vision of the entire marketing funnel. The new tools offered by Universal Analytics via the new Measurement Protocol (an API that enables you to send your data to Google Analytics) can help you measure the how people actually become and remain loyal customers: Consumers use multiple devices. Mastering data on your website is no longer sufficient - larger clients are increasingly asking for a cross platform view of their data in Analytics. The tools from the Measurement Protocol allow you to seamlessly send your own data about your customers and business (from any digital device that you are measuring) to your Analytics account. This can help you see how users interact with your brand from multiple touchpoints - phones, tablets, laptops or more - in one place. The world is mobile. We announced Mobile App Analytics at I/O in 2012 as a beta. It’s been delivering great results for clients. Universal Analytics now enables you to measure your marketing more holistically by integrating this data with your Google Analytics account. Cross-channel measurement is essential. Cross-channel information is more important and more diverse than ever before. Universal Analytics, via the Measurement Protocol, lets you sync your own data from across various marketing channels, so you can discover relationships between the channels that drive conversions. Your business is unique. Not every campaign (or app, or website!) is the same, and sometimes, depending on your business and goals, you want to learn more about a particular aspect of the way visitors interact with your business. With Universal Analytics, you can integrate your own data and can customize the metrics that matter to you - beyond website visits. Google Analytics can deliver the custom metrics you want, in the same report you’re used to, based on the customized data you provide. As a Google Analytics user, Universal Analytics won’t mean any changes in your account. But if you’re a large enterprise that is interested in exploring the integration options, you can learn about getting started in our help center.
- https://support.google.com/analytics/?hl=en?utm_medium=email&utm_source=newsletter&utm_campaign=novemberlapse&utm_content=en_us
- http://www.experian.com/assets/marketing-services/2014_digital_marketer_benchmark_and_trend_report/index.html
- http://www.digimedia.be/News/fr/13662/carrefour-crase-la-p-dale-du-marketing-digital.html
- http://www.slideshare.net/DDBHealthBE/ddb-health-is-turning-10-digital-transformation-jo-caudron?qid=ecc39f8a-2241-4139-ae4c-5f71a0c20986&v=qf1&b=&from_search=2
- Destination -> HUB Web = CONTENT – LINKS – REPUTATION Positioning Visibility Reputation
- http://www.slideshare.net/webdirections/javascript-apis-and-mashups
- https://blog.bufferapp.com/the-science-of-colors-in-marketing-why-is-facebook-blue In another amazing experiment Performable (now HubSpot) wanted to find out whether simply changing the color of a button would make a difference to conversion rates. They started out with the simple hypothesis of choosing between 2 colors (green and red) and trying guess what would happen. For green, their intuition was this: “Green connotes ideas like “natural” and “environment,” and given its wide use in traffic lights, suggests the idea of “Go” or forward movement.” For red, their thinking went like this: “The color red, on the other hand, is often thought to communicate excitement, passion, blood, and warning. It is also used as the color for stopping at traffic lights. Red is also known to be eye-catching.”So, clearly an A/B test between green and red would result in green, the more friendly color to win. At least that was their guess. Here is how their experiment looked like: the science of colors in marketing performable So how did that experiment turn out? The answer was more surprising than I had expected: The red button outperformed the green button by 21% What’s most important to consider is that nothing else was changed at all: 21% more people clicked on the red button than on the green button. Everything else on the pages was the same, so it was only the button color that made this difference.
- https://blog.bufferapp.com/the-science-of-colors-in-marketing-why-is-facebook-blue In another amazing experiment Performable (now HubSpot) wanted to find out whether simply changing the color of a button would make a difference to conversion rates. They started out with the simple hypothesis of choosing between 2 colors (green and red) and trying guess what would happen. For green, their intuition was this: “Green connotes ideas like “natural” and “environment,” and given its wide use in traffic lights, suggests the idea of “Go” or forward movement.” For red, their thinking went like this: “The color red, on the other hand, is often thought to communicate excitement, passion, blood, and warning. It is also used as the color for stopping at traffic lights. Red is also known to be eye-catching.”So, clearly an A/B test between green and red would result in green, the more friendly color to win. At least that was their guess. Here is how their experiment looked like: the science of colors in marketing performable So how did that experiment turn out? The answer was more surprising than I had expected: The red button outperformed the green button by 21% What’s most important to consider is that nothing else was changed at all: 21% more people clicked on the red button than on the green button. Everything else on the pages was the same, so it was only the button color that made this difference.
- Using wp plugins for A/B testing
- http://www.quicksprout.com/2014/11/05/ab-testing-for-beginners-70-resources-to-get-you-started/?utm_content=buffer1dca5&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer#.
- http://images.textmaster.com/20TOOLS_CLEVERMARKETERS_EN.pdf AB Tasty allows you to test your web pages to see which combinations of text, images or layouts are most effective for increasing conversions. Using an easy webpage editor, you can setup up variations of a page on your own, without help from IT, select the audience you want to test and analyze the results. You don’t need to be a statistics genius to use AB Tasty – everything has been designed to make A/B testing accessible and understandable for everyone. The setup process is fairly simple and the results dashboard gives a clear view of your goals, results and of course, the statistical reliability of your tests. A/B TESTING TOOL Optimize your webpage conversion rate Basic plans include standard features like website editor, testing, reporting, plus a module to deliver personalized content to custom audience segments. Subsequent plans add extra features to meet enterprise requirements such as different types of tests, reporting integrations, training and account management.
- http://www.ecrirepourleweb.com/heat-map/ La heat map ou comment mieux comprendre vos utilisateurs 23 FÉVRIER 2015 HOUDAYFA CHERKAOUI 1 COMMENTAIRE heat map 5 2 0 Ce billet a été lu 61 fois. À votre tour? Une heat map ou carte de densité de clics identifie les zones les plus cliquées par vos utilisateurs. En voilà un outil qui vous veut du bien. Les zones chaudes de votre site web sont un indicateur qu’il vaut mieux prendre en compte. Nous vous en parlions dans cet article. Pourquoi? Parce qu’elles procurent des statistiques en temps réel sur les clics des utilisateurs. Les heat map aident les concepteurs de sites, webmasters, marketeurs et autres acteurs du Web à comprendre en quelques secondes quels sont les contenus les plus performants, les parcours préférés des utilisateurs, les rubriques et fonctionnalités les plus recherchées. Les cartes à densité de clics sont utilisées pour améliorer le trafic, augmenter la conversion, améliorer l’architecture et l’expérience utilisateur et donc, réduire les taux de rebond, encourager les visites récurrentes, augmenter le temps de visite, etc. Tu parles d’un allié pour mieux performer en ligne! Le côté gauche de votre écran reçoit 69% de l’attention de vos visiteurs. Le haut de vos pages est la zone la plus chaude Placez toujours votre contenu important en haut de votre page. De nombreuses recherches l’ont démontré, dont cette étude qui révèle qu’en moyenne 80% des utilisateurs d’un site web restent « above the fold » (au-dessus du pli de la page). Même si ce chiffre est certainement à nuancer, surtout sur un dispositif éditorial tel qu’un blog, il importe de respecter ce fondamental. Le haut de la page est critique car c’est le premier point de contact avec votre utilisateur. A titre d’exemple, on conseille toujours d’ajouter une baseline près de votre logo, qu’on situera dans le haut de la page, à gauche. De cette manière, vous indiquez directement le propos mais aussi la proposition de valeur de votre enseigne. C’est d’autant plus adéquat si le nom de votre marque ou société ne suggère pas suffisamment vos services et produits comme Locordia (non, ce n’est pas un voyagiste) ou Pipsa (non ce n’est pas du soda) ou encore Peaudevache (non ce n’est pas un dictionnaire des injures). Les utilisateurs passent de moins en moins de temps sur les sites Internet qu’ils visitent. Là encore, les études sont nombreuses qui montrent un déficit d’attention sur les dispositifs en ligne. L’internaute serait même moins attentif que le poisson rouge… Il faut donc l’appâter directement, avec les bons nutriments. Les heat map déterminent que la partie gauche des sites reçoit le plus d’attention Selon cette étude de « nngroup » si on sépare symétriquement votre site web en deux parties verticales, la partie de gauche reçoit 69% de l’attention de vos visiteurs. Qu’en est-il dans votre cas? Une heat map peut vous aider à déterminer le ratio d’attention que suscite le côté gauche de votre écran, et les zones les plus favorables au clic. C’est là que vous devrez placer les contenus intéressants. Voici un exemple de plugin (si votre blog utilise WordPress comme CMS) pour générer vos Heat map : https://wordpress.org/plugins/heatmap-for-wp/ Et vous? Quels autres usages voyez-vous dans les heat map? Etes-vous convaincu en leurs utilisations? - See more at: http://www.ecrirepourleweb.com/heat-map/#sthash.xskPVQ1x.dpuf
- http://www.smashingmagazine.com/2010/06/24/the-ultimate-guide-to-a-b-testing/ A/B testing isn’t a buzz term. A lot of savvy marketers and designs are using it right now to gain insight into visitor behavior and to increase conversion rate. And yet A/B testing is still not as common as such Internet marketing subjects as SEO, Web analytics and usability. People just aren’t as aware of it. They don’t completely understand what it is or how it could benefit them or how they should use it. This article is meant to be the best guide you will ever need for A/B testing. (Smashing’s Note: If you are looking for quality books on Web design, have a look at ourPrinted Smashing Books. We love them, and so will you: delivering in-depth knowledge by experts, one book at a time. Learn more...) What Is A/B Testing? At its core, A/B testing is exactly what it sounds like: you have two versions of an element (A and B) and a metric that defines success. To determine which version is better, you subject both versions to experimentation simultaneously. In the end, you measure which version was more successful and select that version for real-world use. This is similar to the experiments you did in Science 101. Remember the experiment in which you tested various substances to see which supports plant growth and which suppresses it. At different intervals, you measured the growth of plants as they were subjected to different conditions, and in the end you tallied the increase in height of the different plants. Large version A/B testing on the Web is similar. You have two designs of a website: A and B. Typically, A is the existing design (called the control), and B is the new design. You split your website traffic between these two versions and measure their performance using metrics that you care about (conversion rate, sales, bounce rate, etc.). In the end, you select the version that performs best. What To Test? Your choice of what to test will obviously depend on your goals. For example, if your goal is to increase the number of sign-ups, then you might test the following: length of the sign-up form, types of fields in the form, display of privacy policy, “social proof,” etc. The goal of A/B testing in this case is to figure out what prevents visitors from signing up. Is the form’s length intimidating? Are visitors concerned about privacy? Or does the website do a bad job of convincing visitors to sign up? All of these questions can be answered one by one by testing the appropriate website elements. Even though every A/B test is unique, certain elements are usually tested: The call to action’s (i.e. the button’s) wording, size, color and placement, Headline or product description, Form’s length and types of fields, Layout and style of website, Product pricing and promotional offers, Images on landing and product pages, Amount of text on the page (short vs. long). Create Your First A/B Test Once you’ve decided what to test, the next step, of course, is to select a tool for the job. If you want a free basic tool and don’t mind fiddling with HTML and JavaScript, go with Google Website Optimizer. If you want an easier alternative with extra features, go with Visual Website Optimizer (disclaimer: my start-up). Other options are available, which I discuss at the end of this post. Setting up the core test is more or less similar for all tools, so we can discuss it while remaining tool-agnostic. You can set up an A/B test in one of two ways: Replace the element to be tested before the page loads If you are testing a single element on a Web page—say, the sign-up button—then you’ll need to create variations of that button (in HTML) in your testing tool. When the test is live, the A/B tool will randomly replace the original button on the page with one of the variations before displaying the page to the visitor. Redirect to another page If you want to A/B test an entire page—say, a green theme vs. a red theme—then you’ll need to create and upload a new page on your website. For example, if your home page is http://www.example.com/index.html, then you’ll need to create a variation located at http://www.example.com/index1.html. When the test runs, your tool will redirect some visitors to one of your alternate URLs. Once you have set up your variations using one of these two methods, the next step is to set up your conversion goal. Typically, you will get a piece of JavaScript code, which you would copy and paste onto a page that would represent a successful test were a visitor to arrive there. For example, if you have an e-commerce store and you are testing the color of the “Buy now” button, then your conversion goal would be the “Thank you” page that is displayed to visitors after they complete a purchase. As soon as a conversion event occurs on your website, the A/B testing tool records the variation that was shown to the visitor. After a sufficient number of visitors and conversions, you can check the results to find out which variation drove the most conversions. That’s it! Setting up and running an A/B test is indeed quite simple. Do’s And Don’ts Even though A/B testing is super-simple in concept, keep some practical things in mind. These suggestions are a result of my real-world experience of doing many A/B tests (read: making numerous mistakes). DON’TS When doing A/B testing, never ever wait to test the variation until after you’ve tested the control. Always test both versions simultaneously. If you test one version one week and the second the next, you’re doing it wrong. It’s possible that version B was actually worse but you just happened to have better sales while testing it. Always split traffic between two versions. Don’t conclude too early. There is a concept called “statistical confidence” that determines whether your test results are significant (that is, whether you should take the results seriously). It prevents you from reading too much into the results if you have only a few conversions or visitors for each variation. Most A/B testing tools report statistical confidence, but if you are testing manually, consider accounting for it with anonline calculator. Don’t surprise regular visitors. If you are testing a core part of your website, include only new visitors in the test. You want to avoid shocking regular visitors, especially because the variations may not ultimately be implemented. Don’t let your gut feeling overrule test results. The winners in A/B tests are often surprising or unintuitive. On a green-themed website, a stark red button could emerge as the winner. Even if the red button isn’t easy on the eye, don’t reject it outright. Your goal with the test is a better conversion rate, not aesthetics, so don’t reject the results because of your arbitrary judgment. DO’S Know how long to run a test before giving up. Giving up too early can cost you because you may have gotten meaningful results had you waited a little longer. Giving up too late isn’t good either, because poorly performing variations could cost you conversions and sales. Use a calculator (like this one) to determine exactly how long to run a test before giving up. Show repeat visitors the same variations. Your tool should have a mechanism for remembering which variation a visitor has seen. This prevents blunders, such as showing a user a different price or a different promotional offer. Make your A/B test consistent across the whole website. If you are testing a sign-up button that appears in multiple locations, then a visitor should see the same variation everywhere. Showing one variation on page 1 and another variation on page 2 will skew the results. Do many A/B tests. Let’s face it: chances are, your first A/B test will turn out a lemon. But don’t despair. An A/B test can have only three outcomes: no result, a negative result or a positive result. The key to optimizing conversion rates is to do a ton of A/B tests, so that all positive results add up to a huge boost to your sales and achieved goals. Classic A/B Testing Case Studies Here are some case studies to give you an idea of how people test in the wild. Writing Decisions: Headline Tests on the Highrise Sign-Up Page 37signals tested the headline on its pricing page. It found that “30-Day Free Trial on All Accounts” generated 30% more sign-ups than the original “Start a Highrise Account.” “You Should Follow Me on Twitter Here” (Dustin Curtis) This much-hyped split-test involved testing multiple versions of a call to action for Twitter followers. Dustin found that “You should follow me on Twitter here” worked 173% better than his control text, “I’m on Twitter.” Human Photos Double Conversion Rates A surprising conclusion from two separate A/B tests: putting human photos on a website increases conversion rates by as much as double. Scientific research backs this up, saying that we are subconsciously attracted to images with people. Google Website Optimizer Case Study: Daily Burn, 20%+ Improvement (Tim Ferriss) A simple variation that gave visitors fewer options too choose from resulted in a 20% increase in conversions. The winning version was also much easier on the eye than the control in its detail and text. Two Magical Words Increased Conversion Rate by 28% The words “It’s free” increased the clicks on this sign-up button by 28%, illustrating the importance of testing call-to-action buttons and how minor changes can have surprisingly major results. Changing the Sign-Up Button from Green to Red Along with its other A/B tests, CareLogger increased its conversion rate by 34% simply by changing the color of the sign-up button from green to red! Single page vs. multi-step checkout If you have an online store, it is quite common to see visitors abandoning the purchase process at the time of checkout. This A/B test found out that a single page checkout process works much better at completing sales than multiple-page checkout process. "Mad Libs" style form increases conversion 25-40% Defeating conventional wisdom, in this A/B test it was found out that a paragraph-styled form with inline input fields worked much better than traditional form layout. Though the result was probably specific to their offering as it wasn’t replicated in another, separate A/B test. Complete redesign of product page increased sales by 20% A software product company redesigned their product page to give it a modern look and added trust building elements (such as seals, guarentees, etc.). End result: they managed to increase total sales by 20%. This case study demonstrates the effect of design on sales. Marketing Experiments response capture case study – triple digit increase in conversions Through a series of A/B tests they optimized the mailing list opt-in rate by 258%. Focus was to remove all distractions and require the visitor to only provide email address. For completing his/her complete profile, the landing page motivated the visitors with an Amazon gift card (which was again split tested). Tools For A/B Testing A number of tools are available for A/B testing, with different focuses, price points and feature sets. Here are some: Google Website Optimizer A free A/B testing tool from the search giant. A great option to get started, but lacks advanced features. A/Bingo and Vanity Server-side frameworks for Ruby on Rails developers. Requires programming and integration in code. Visual Website Optimizer An easy-to-use A/B testing tool, with advanced features such as WYSIWYG editor, click maps, visitor segmentation and tag-less integration. (Disclaimer: my start-up.) Unbounce and Performable Landing-page creators with integrated A/B testing. Vertster, SiteSpect, Webtrends Optimize and Omniture’s Test&Target Enterprise testing tools. Resources For Deep-Diving Into A/B Testing If you’ve read this far, then A/B testing has presumably piqued your interest. Here, then, are some cherry-picked resources on A/B testing from across the Web. GET IDEAS FOR YOUR NEXT A/B TEST Which Test Won? A game in which you guess which variation won in a test. 101 A/B Testing Tips A comprehensive resource of tips, tricks and ideas. ABtests.com A place to share and read A/B test results. A/B Ideafox A search engine for A/B and multivariate case studies. INTRODUCTORY PRESENTATIONS AND ARTICLES Effective A/B Testing By Ben Tilly. Practical Guide to Controlled Experiments on the Web (PDF) From Microsoft Research. Introduction to A/B Testing From the 20bits blog THE MATHEMATICS OF A/B TESTING Statistics for A/B Testing From the 20bits blog. How Not to Do A/B Testing What You Should Know About the Mathematics of A/B Testing From my own blog. Easy Statistics for AdWords A/B Testing, and Hamsters Statistical Significance and Other A/B Test Pitfalls
- http://www.marketingcharts.com/wp/online/senior-marketers-on-the-balance-between-analytical-and-creative-skills-42643/ Senior Marketers on the Balance Between Analytical and Creative Skills 7 in 10 senior marketing leaders believe that creativity and analytical ability have been equally important for marketing leaders over the past few years, according to survey results from Spencer Stuart, although only about 1 in 5 believe their teams have struck the right balance between the two talents. In time, though, respondents believe that analytical orientation will become a more important skill for CMOs to possess, while creativity will become less of a priority. Advertisement Some 29% of respondents ranked analytical orientation as one of the top 3 skills CMOs are expected to possess today, versus 21% ranking creativity among their top-3. Even so, twice as many gave creativity the top ranking as did analytical orientation (7% vs. 3%). Asked the key skills CMOs will be expected to possess in the future, though, and the gap widened. About one-third (34%) of respondents indicated that analytical orientation will be a top-3 expertise, compared to just 13% feeling the same way about creativity. Additionally, respondents were more likely to to rank analytical orientation as their top future skill (8% vs. 3%). Senior marketing leaders clearly believe that the most important skill for CMOs today and tomorrow is a strategic mindset, though. Almost 8 in 10 respondents indicated this to be a top-3 expertise today, and about 3 in 4 feel that it will be a top-3 skill in the future. Interestingly, while respondents perceive customer insight (37%) to be a more important skill today than an analytical orientation, they feel that the two will be equally as important in the future. Also of note: while some research finds marketers perceiving their analytics talent to be weak, a majority 52% of respondents to the Spencer Stuart survey said that their teams’ skill-sets lean towards the analytical side, versus 29% who feel that their teams are more creative. How to find and develop future marketing leaders that have a blend of creative and analytical talent? A plurality of senior marketers are finding them from competitors within their sector, while others are looking to the tech industry and to historically creative sectors such as advertising and media. Only 9% are looking internally at their own team. That may be either a cause or result of the finding that 89% don’t believe organizations are doing a good job of training and developing future marketing leaders. About the Data: Spencer Stuart surveyed more than 160 senior marketing leaders. The greatest share of survey respondents (38%) came from the consumer industry; 21% came from financial services and 15% from “other” sectors, including telecommunications, retail, entertainment and travel. Some 13% of respondents work in the technology industry, 7% in life sciences/healthcare, 5% in media, 5% in advertising, 3% in nonprofit and 1% in industrial.
- Web = going data-driven rather than aesthetics driven http://www.insidefacebook.com/2011/12/27/edgerank-and-graph-rank-defined/ EdgeRank and Graph Rank Defined Comment Brittany Darwell•Dec 27th, 2011Applications, Facebook, News Feed, Open Graph, Open Graph Apps, Pages Facebook has two algorithms that are important to marketers and developers but are largely misunderstood by people across industries. Graph Rank and EdgeRank are what the social network uses to organize the massive amount of activity generated by people, pages and apps and to decide what stories to show whom. Graph Rank applies to Open Graph applications, not page posts or friend’s status updates. Those are affected by EdgeRank, which determines what shows up in your News Feed. Neither of these is a global score. Every bit of activity on the site has a different rank for different users. And because time and affinity plays a role, the rank of each object is not constant. EdgeRank is the algorithm that determines what items populate your News Feed. With all the friends people have and pages they like, most users would be overwhelmed to see all of the activity generated by these connections. Facebook, therefore, assigns a value to every possible story that could end up in the feed. This value is based on affinity, weight and time. Affinity is the relationship between the user and the page or friend that created an item. Weight is affected by the type of story, for instance, whether it is a photo upload or a comment on another person’s status. Facebook tends to value rich media content and often when it introduces something new like Questions, it temporarily weights activity from that feature higher. The third factor affecting EdgeRank is how recently an action was taken. These factors are why you might see every check-in and linked shared by your best friend, but only see whole photo albums from someone else. EdgeRank is also the reason most fans don’t see every post from pages they like. The more users interact with the page, however, the greater the affinity score becomes and the more likely they are to see page posts in the future. Graph Rank is a new algorithm Facebook is using to determine how Open Graph application activity will be distributed through News Feed, Ticker and Timeline. Graph Rank was introduced at F8 with the announcement of a new type of app that can continuously publish user activity to Ticker and Timeline. Because Facebook expects a proliferation of sharing through these Open Graph apps, it developed a system to manage the amount and type of activity that each user will see. Graph Rank seeks to show users highly relevant application stories based on the other connections they’ve made on Facebook. So if a user plays Words With Friends, they are more likely to see a friend’s story about another word game than a story about an arcade shooter. This seems to be a reaction to the negative feedback Facebook received after first allowing third-party apps on the platform. Many users were frustrated with the amount of app activity that filled their feeds. The social network initially responded by cutting off several viral channels that allowed apps to grow organically. This left a sour taste in the mouths of many developers. With Graph Rank, Facebook hopes to strike a balance that helps users discover apps they are likely to enjoy without compromising the site or turning off developers. Together, EdgeRank and Graph Rank help personalize Facebook for each user. Marketers and developers who understand the way the platform ranks content can find ways to optimize their efforts there. —————————— EdgeRank Is Dead: Facebook’s News Feed Algorithm Now Has Close To 100K Weight Factors Aug 16, 2013 at 9:00am ET by Matt McGee inShare 545 facebook-newsfeed-240pxThe next time you tell a client how Facebook selects and ranks the content that shows up in the News Feed, you’ll need to do it without using the word EdgeRank. EdgeRank, Facebook’s original News Feed ranking system, is dead. Facebook hasn’t used the word internally for about two-and-a-half years. That’s when the company began employing a more complex ranking algorithm based on machine learning. The current News Feed algorithm doesn’t have a catchy name, but it’s clear from talking to the company’s engineers that EdgeRank is a thing of the past. During a phone call this week, Lars Backstrom, Engineering Manager for News Feed Ranking at Facebook, estimated that there are as many as “100,000 individual weights in the model that produces News Feed.” The three original EdgeRank elements — Affinity, Weight and Time Decay — are still factors in News Feed ranking, but “other things are equally important,” he says. In other words, the News Feed algorithm of today is much more sophisticated than just a couple years ago. “The easiest analogy is to search engines and how they rank web pages,” Backstrom says. “It’s like comparing the Google of today with Alta Vista. Both Google and Bing have a lot of new signals, like personalization, that they use. It’s more sophisticated than the early days of search, when the words on a page were the most important thing.” This has implications for marketers and business owners far beyond the wording used to describe News Feed rankings. It’s a reflection — and a cause, too — of today’s complex battle to reach Facebook users organically. The winners? They’ll be the ones who understand how Facebook has moved past Affinity, Weight and Time Decay, and move past it themselves. Before we get into today’s News Feed algorithm, let’s go back a few years. knobs In The Beginning It Was … Turning Knobs Facebook’s News Feed was born in September 2006, promising to provide … and I quote … “a personalized list of news stories throughout the day, so you’ll know when Mark adds Britney Spears to his Favorites or when your crush is single again.” Yep, that’s a direct quote from the announcement. Cute, huh? With the launch of News Feed, Facebook wanted to show users the most important content from their social network without making them click to visit their friends’ profiles. And it had to figure out a way to decide what was important to each person. “In the beginning, News Feed ranking was turning knobs,” said Facebook VP of Product Chris Cox during Facebook’s recent News Feed media event. “Turn up photos a little bit, turn down platform stories a little bit.” Cox gave a funny account of how he and a co-worker sat in Facebook’s offices and changed the ranking “knobs” based on feedback from users — feedback in the form of often angry emails and conversations with users outside the Facebook office. Times were much simpler then. From Knobs To EdgeRank facebook-edgerank-240pxFacebook has obviously grown up a lot since then, particularly with the simultaneous launch of Facebook Ads and Pages in November 2007. Businesses, clubs, and organizations began creating Facebook Pages and using them to try to reach existing and new fans. That meant more content and more chances for users’ News Feeds to get crowded and unwieldy. The company advanced from “turning knobs” to EdgeRank, the algorithm that a) determined which of the thousands of stories (or “edges” as Facebook called them) qualified to show up in a user’s News Feed, and b) ranked them for display purposes. EdgeRank had three primary pieces: Affinity — i.e., how close is the relationship between the user and the content/source? Weight — i.e., what type of action was taken on the content? Decay — i.e., how recent/current is the content? EdgeRank made it possible for Facebook to give users a more personalized NewsFeed. As Cox explained, users that played a lot of games on Facebook could see more game-related content in their News Feed. Users that took part in a lot of Group discussions would see more content like that. And so forth. From EdgeRank To… ? With EdgeRank, the way you used Facebook largely determined what showed up in your News Feed. And it still does because, as Cox said last week, “We’re in the business of giving our users the most interesting possible experience every time they visit.” But now that job is a lot more complicated than ever. Consider that there are more than a billion people using Facebook each month. And 128 million in the U.S. that use Facebook every day. They’re using dozens of different mobile devices with different capabilities for displaying content. There are 18 million Pages, many of which are actively looking for attention and a way to show up the News Feed as often as possible. And that number doesn’t include the numerous businesses that are using Facebook via regular accounts rather than Pages. With all of that going on, Facebook says that the typical user has about 1,500 stories that could show in the News Feed on every visit. So how does Facebook decide what users see, and what content from Facebook Pages make it into the News Feed? As you can imagine, Facebook isn’t about to give away all the details, but Backstrom did talk openly about several ways that the algorithm has grown up in recent years. Affinity, Weight & Time Decay These are “still important,” Backstrom says, but there are now multiple weight levels. “There are a lot of different facets. We have categories and sub-categories of affinity.” Facebook is attempting to measure how close each user is to friends and Pages, but that measurement isn’t just based on personal interactions. Backstrom says Facebook looks at global interactions, too, and those can outweigh personal interactions if the signal is strong enough. “For example, if we show an update to 100 users, but only a couple of them interact with it, we may not show it in your News Feed. But if a lot of people are interacting with it, we might decide to show it to you, too.” Relationship Settings Another factor is the relationship settings that Facebook users can apply. With each friend, you can go a step further and label the person a “close friend” or “acquaintance.” With liked Pages, users can choose to “Get notifications” or “Receive updates,” and there are deeper settings to control what kind of content the user wants to see. facebook-settings “We try to extract affinity naturally,” Backstrom says, “but if you go to the trouble to tell us more about your relationships, we will factor that in.” Post Types The News Feed algorithm takes into account the type of posts that each user tends to like. Users that often interact with photo posts are more likely to see more photo posts in the News Feed, and users that tend to click more on links will see more posts with links. Backstrom says this is also applied on a deeper level. “It’s not just about global interactions. We also look at what types of posts you interact with the most from each friend.” In other words, Facebook Page owners that continually publish one type of post are likely not having those posts seen by fans that interact with other types of posts. Hide Post / Spam Reporting News Feed visibility can also be impacted by users’ ability to hide posts or mark them as spam. But it’s not as simple as having a set threshold that will cause posts to stop showing in users’ News Feeds. “For every story, we do the same computation,” Backstrom explains. “Given this story, and given the user’s history, what’s the probability that you’ll like this story? What’s the probably that you’ll hide it? We’re looking at this and trying to decide, is it a net positive to show this story in the News Feed?” Further, Backstrom says there’s an element of decay when considering posts that have been hidden. Recent “hides” may carry more weight when deciding if a post shows in the News Feed, but those “hides” will have less impact as they decay over time. Clicking On Ads, Viewing Other Timelines The News Feed algorithm is completely separate from the algorithm that decides what ads to show, when to show ads, and where to show them. But how a user interacts with Facebook ads can influence what shows in the News Feed. “Nothing is off the table when we’re looking at what we should show users,” Backstrom says. “It can be clicking on ads or looking at other timelines. It doesn’t have to be just what the user interacts with in the News Feed.” Device & Technical Considerations Yep, the News Feed algorithm even considers what device is being used and things like the speed of a user’s internet connection when deciding what to show. “The technical limitations of some old feature phones make it impossible to show some content,” Backstrom. “We also know that some content doesn’t perform as well with Facebook users on certain devices. And if the user has a slow internet connection, we may show more text updates. We’re trying to show users content that they’ll find interesting and want to interact with.” Story Bumping & Last Actor Don’t forget these two changes that Facebook just announced last week. Story Bumping bends the “decay” rules by giving older, unseen posts a second chance at News Feed visibility if they’re still getting interaction. Last Actor puts a premium on recency. Facebook is tracking a user’s most recent 50 interactions and giving them more weight when deciding what to show in the News Feed. This works on a rolling basis, so the value of an interaction will decline after the user has made 50 more recent interactions. Final Thoughts It should be clear that Facebook’s News Feed algorithm has developed significantly over the past few years. EdgeRank is a thing of the past, and it’s been replaced by a machine learning-based algorithm that, as Backstrom says, “only ever gets more complicated.” That poses new challenges for brands and marketers hoping to get attention on Facebook, but the company says its advice to Page owners and others is the same: Create and publish and a variety of interesting content that will attract shares, comments, likes and clicks. That requires understanding your Facebook fans — from the types of posts they interact with to the different devices they might be using when they’re on Facebook. We’ll keep reporting on Facebook’s News Feed changes, and our contributing writers will keep sharing tips and advice, too. You might also keep an eye on the new Facebook for Business news page because the company has promised to be more open in the future about changes that affect how the News Feed works. http://marketingland.com/edgerank-is-dead-facebooks-news-feed-algorithm-now-has-close-to-100k-weight-factors-55908
- Important element = no longer the number of visitors but: The quantity of visitors analysed in terms of conversion rather than visit – bounce rate The quality must be analysed: where are they coming from – how long are they staying – what are they doing – where are they going to Diversify your traffic sources – there are basically 3 sources: direct access – referring sites – search engines – rule of thumb: 1/3 each, to avoid dependence on a specific SE