Google Analytics: Flow Visualization
Google introduces Flow Visualization for Google Analytics: visitors flow and goal flow; http://eicker.at/GAFlowVisualization
Google introduces Flow Visualization for Google Analytics: visitors flow and goal flow; http://eicker.at/GAFlowVisualization
Chitika: Google Plus growth spurt short lived after it went public. – What’s its USP? http://eicker.at/GooglePlusLaunch
Chitika: “Mid-morning September 20th, Google+ officially entered public beta, drumming up the level of interest of the site far and wide across the web. Although able to boast 25 million unique visitors after only four weeks of operation, Google’s newest attempt at a social network saw its user base dwindle as shown by a recent article from Chitika Insights. … Reportedly, Google+ saw a surge in traffic of over 1200% due to the additional publicity, but the increased user base was only temporary, as was projected in an earlier insights post. – The data shows that, on the day of its public debut, Google+ traffic skyrocketed to peak levels. But, soon after, traffic fell by over 60% as it returned to its normal, underwhelming state. It would appear that although high levels of publicity were able to draw new traffic to Google+, few of them saw reason to stay. … The supply of users for social media sites is limited. To survive you must stand out and provide a service that others do not. – Features unique to your site must be just that – unique and difficult to duplicate – if they are not, the competitive advantage quickly disappears.”
RWW: “We at RWW can informally corroborate Chitika’s findings that interest in Google Plus is on the wane. Our monthly referrals from there are down 38% since their peak, while Facebook referrals are up 67% and Twitter referrals up 51% over the same period. – As we reported last week, the +1 button isn’t gaining much traction, either. Despite all the new features and responsiveness to user feedback, Google Plus just doesn’t seem to be catching on. There’s only so much time in a day for social networking, and this newcomer isn’t converting many users.”
Inquirer: “Google’s problem is not getting users in the first place, it seems, but rather keeping them after they have arrived. For now it appears that a lot of users are merely curious about Google+, but return to the tried and tested format of Facebook when the lustre fades. … While the jury is still out on which firm will win this battle, there’s no denying that the intense competition could make both social networks considerably better than they were before.”
RWW: “Many people say they don’t find [Google Plus] compelling though. We asked on Twitter and on Facebook and most people said that the value proposition was too unclear, that it wasn’t valuable enough to warrant the investment of time relative to the already heavy burden of Twitter and Facebook engagement. Google knows it needs to make changes to the service to increase its user retention. But you know who else has always struggled with new user retention? Twitter!”
UG: “While this is interesting, Chitika doesn’t provide much information about its data-gathering technique. Because it is an ad-network, one may suspect that it can see the referrer (Google+) to sites using its ad code. If that’s the case (and I’m not saying that it is), the method is not very accurate but one could argue that they should be able to pick up a (very) gross trend snapshot.The bottom-line is that Google+ saw a traffic spike during its public opening and that it subsequently faded, and I can believe that. This sound quite ‘normal’ to me, though. Secondly, second-hand data sampling on a 10-day period is hardly enough to tell if Google+ is a ‘failure to launch’ as Chitika puts it, so I think that there’s a bit of over-dramatization here. – It will take months (or years) and many evolution before we realize how well (or not) Google+ does/did. In the meantime, and as long as we don’t know how this data was measured, I would advise taking this with a grain of salt.”
Google Analytics now starts a new session when any traffic source value for a user changes; http://eicker.at/GASession
Google: “Beginning today [August 11, 2011], there will be a small change [sic!] in how sessions are calculated in Google Analytics. We think this update will lead to a clearer understanding of website interactions. We also want to explain how these changes might impact your reports. … Currently, Google Analytics ends a session when: More than 30 minutes have elapsed between pageviews for a single visitor. At the end of a day. When a visitor closes their browser. – If any of these events occur, then the next pageview from the visitor will start a new session. – In the new model, Google Analytics will end a session when: More than 30 minutes have elapsed between pageviews for a single visitor. At the end of a day. When any traffic source value for the user changes. Traffic source information includes: utm_source, utm_medium, utm_term, utm_content, utm_id, utm_campaign, and gelid. – As before, if any of these events occur, then the next pageview from the user will be the start of a new session.”
Kaushik: “A minor version of the butterfly effect occurred, one small change in a part of the system caused a few other smaller changes in other parts of the system. Some people freaked out. Others wondered what the fuss was all about. Still others wondered what they were going to eat for lunch. :) … Change is always hard to accept, especially when it comes with even the slightest impact on status quo. But if there has to be progress in life, then change is just the thing that puts us in a higher, more optimal orbit. It makes a better existence possible. – Go give the new data and reports a try. Thinking in a new way will require effort and brain power. But real happiness is worth it.”
Whitaker: “As with any model, it’s not so much about being ‘right’ or ‘wrong’, but whether the model is useful. Does your model help you understand your customers a little bit better and make smarter decisions? If there is a better model then you should change to that one. – Ironically, the data causing higher visit numbers was there all along! It was just hidden due to the way Google Analytics used to count visits, pageviews, etc. Anyone remember 0 visits? … Finally, I am not a huge fan of visit-based metrics anyway. Who cares if your dear customers take 1 or 2 visits before placing an order? The main thing is that they accomplished their goals during each visit, i.e. browse in the first visit, have a cup of tea, then buy in the second visit.“
Gerrit Eicker 09:06 on 20. October 2011 Permalink |
Google: “[A]t Web 2.0 Summit [we] unveiled the release of ‘Flow Visualization’ in Google Analytics, a tool that allows you to analyze site insights graphically, and instantly understand how visitors flow across pages on your site. Starting this week, ‘Visitors Flow’ and ‘Goal Flow’ will be rolling out to all accounts. Other types of visualizers will be coming to Google Analytics in the coming few months, but in the meantime, here’s what you can expect from this initial release. … The Visitors Flow view provides a graphical representation of visitors’ flow through the site by traffic source (or any other dimensions) so you can see their journey, as well as where they dropped off. … Goal Flow provides a graphical representation for how visitors flow through your goal steps and where they dropped off. Because the goal steps are defined by the site owner, they should reflect the important steps and page groups of interest to the site. In this first iteration, we’re supporting only URL goals, but we’ll soon be adding events and possibly other goal types. … These two views are our first step in tackling flow visualization for visitors through a site, and we look forward to hearing your feedback as all users begin experiencing it in the coming weeks. We’re excited to bring useful and beautiful tools like these to help you understand your site, so stayed tuned for more!”
SEL: “Path analysis has historically been a feature that provided little insights on user behavior, mainly because visitors behave in such non linear ways that it is hard to learn something from their paths, even when looking at aggregated data. The best option to path analysis has been to analyze micro conversions, i.e. looking at each page and trying to learn if the page has fulfilled its objective. However, the visualizations below bring some interesting approaches that will be very helpful for web analysts. … As some might recognize, the visualization used on this feature is very similar to the one created by Charles J. Mainard shown below. This image, created in a 1869 to describe Napoleon’s disastrous Russian campaign of 1812, displays several variables in a single two-dimensional image…”
LM: “I need Red Bull. Seriously, I can’t keep up with all the new features and announcement coming from Google Analytics lately. In the last few months, they’ve released a new interface, real-time data, multi-channel funnels, Google Analytics Premium, Google Webmaster Tools integration, plot rows, site speed report, new mobile reports, social media tracking, and now Flow Visualization. You can read their official announcement, but ours is much more informative [and we have video!]. … Navigation Flow: provides a graphical representation of your start/end nodes, and the paths to or from your site that your visitors follow. When you create a navigation flow, you have the option to identify a single page by URL, or to create a node that represents a group of pages whose URLs match a condition, for example, all pages whose URL contains a particular product identifier like shirts or jackets. … Sometimes, things are best explained with video. This is one of those times, so sit back, relax, and enjoy this brief tour through this new feature.“