Posts tagged Analytics
How to Analyze Google Analytics (not provided) Data – SEOmoz (blog)
Feb 10th
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How to Analyze Google Analytics (not provided) Data
SEOmoz (blog) If you don't like this kind of uncertainty in a career, then maybe SEO isn't for you. However, if you love a challenge and finding creative ways to overcome obstacles, read on. One of the most immediate problems that the Google update caused was the … Google Places Can Greatly Help Boost Agents' Real Estate SEO Marketing Efforts … |
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Google Analytics Update to Organic Reports
Feb 10th
As many of you know, organic traffic is auto-populated in Google Analytics reports using a default search engine list curated by Google. It is also possible to add smaller search engines manually into the tracking code snippet, using the _addOrganic method; but it’s nicer when Google does it…
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The New Google Analytics Fuels an On-Site Revolution
Feb 9th
The new version of Google Analytics has been a hit-or-miss type of implementation. I personally think that most resistance to change is a type of “Professional Inertia”; where people get to know the tools they use so often, that any modification of those tools is greeted with resistance. I myself also found myself disliking the [...]
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Apsalar’s Daily Cohorts Gives Mobile Developers Real-Time Analytics to Engage Users
Feb 7th
When a person downloads an app to a smartphone, the first interactions the user has with the app will determine its overall success ands potential longevity. If a user likes an app, its long-term potential greatly increases. If not, well, it is destined to the black hole of app oblivion.
That is why the ability to track the first few sessions a user has with an app in real-time is critical. Mobile marketing and analytics startup Apsalar is releasing an update to its platform called Daily Cohorts that allows publishers to track app analytics in real-time the day it is published. Developers can then make determinations on how best to market and monetize the app while it is still fresh in the users’ mind.
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Oiknine describes the results of updating Xco’s app after the first batch of analytics:
“After the update is released, Xco looks at the cohorts of users who first launched the app for the 3 days after the update. Both revenue and retention is up for each cohort – not quite yet reaching the benchmarks, but a significant overall improvement can be seen. In addition, more users are now completing the tutorial, with the rate up to 75% of new users. Xco is pleased with the results but knows it needs to do more and so it will begin the iteration process over again.”
“After the update is released, Xco looks at the cohorts of users who first launched the app for the 3 days after the update. Both revenue and retention is up for each cohort – not quite yet reaching the benchmarks, but a significant overall improvement can be seen. In addition, more users are now completing the tutorial, with the rate up to 75% of new users. Xco is pleased with the results but knows it needs to do more and so it will begin the iteration process over again.”
The ability to retain users after the launch of an app is critical. All the best plans for marketing, engagement and monetization will go for naught if a user has stopped using the app after the first few days.
Apsalar CEO Michael Oiknine describes the scenario of a mobile game from a theoretical mobile gaming company called “Xco.” The company set up several cohorts to track the retention of users and finds that after three days the app is not living up to expectations and revenues are falling short. Xco finds that users that completed the app tutorial are more likely to keep using the app while those that do not are letting it slide into app oblivion.
“As Xco takes a closer look at the data they realize that by looking at the segment of users who completed the tutorial, retention and revenue are slightly ahead of their benchmarks and those users are leveling up more frequently than other users,” Oiknine said in an email to ReadWriteMobile. “However, only 65% of users are completing the tutorial. Based on this data, Xco goes into action and decides to make the tutorial more prominent in the UX after first launch of the app.”
This is a familiar scenario for many mobile games. The ability to track early sessions is extremely important. In this case, a quick tweak to the app to push more people towards the tutorial would benefit the longevity of the app.
The cohort method of analytics differs from just tracking sessions or daily average users. It provides a level of detail that other metrics (what Oiknine calls “vanity metrics”) do not.
“With daily cohorts, app developers can make critical changes fast enough so that they don’t lose the valuable users they’ve acquired,” Oiknine said.
Apsalar’s Daily Cohorts allows publishers to group users together in a single segment by the day they launched the app. For instance, users that downloaded the app the first day it was available can be grouped as “Day 1″ users and their history can be tracked as a single segment. Same with Day 2 users etc.
Apsalar’s platform focuses on engagement and monetization. Daily Cohorts is a change for the company as it used to provide weekly cohort analysis, which means that the information gained from initial users could not be acted upon immediately. A week is a long time for a newly-downloaded app and can cost the publisher thousands of dollars (and a plethora of poor reviews) if the app is subpar or users are not sticking with it.
To a certain extent, Apsalar’s Daily Cohorts falls into the realm of “predictive analytics” but with real-time data. The ability to track and group user sessions from the earliest possible moment will give developers a better understanding of how future users will interact with the app. The idea is to get actionable data as soon as possinle. Apsalar can then engage the user across apps with its Mobile Engagement Management (MEM) system that segments the user base on a common criteria.
Apsalar’s puts up its Daily Cohorts against a variety of other services that offer similar functions. Mobile analytics company Flurry, what Apsalar considers its chief competitor, tracks user sessions and has a “Re-Engagement” model to monetize user behavior. PlayHaven has the ability to track user behavior in real-time in mobile games and update an app accordingly.
Developers: What do you think of Apsalar’s Daily Cohorts? Is there anything similar on the market that you prefer to use? How important are early-stage analytics to the success of your app? Let us know in the comments.
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Analytics From “Most Social Super Bowl” Reveals Chat Wasn’t About Football
Feb 6th
Although predictions last week raised expectations about the role that social media would play in reshaping what has historically been one of the most engaging non-holiday events in the U.S. every year, the first analysis of yesterday’s public social network data by advertising analysis firm Networked Insights makes a compelling revelation: Almost three-fourths of the chat taking place among Twitter and Facebook users Sunday night had nothing to do with the game itself.
In fact, according to Networked Insights’ data, the Super Bowl topic that trended in third place was “Brady,” but when you break that topic down, you realize it may actually have been more about Mrs. Tom Brady – supermodel Gisele Bundchen, who appeared on camera perhaps once during the game, whom Tweeters evidently referred to as “Mrs. Brady” or perhaps “Lady Brady” – than about the New England Patriots quarterback.
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Though it may not be entirely surprising that commercials constitute the bulk of online chatter during the event, it’s astonishing to see that TV commercials make up some 42% of all Super Bowl-related online chatter. Although New York Giants running back Ahmad Bradshaw scored what Super Bowl history may record as the most awkward game winning touchdown – slowly being seated on the goal line after trying to stop himself short at the 1-yard line – his maneuver only elicited a minor wave compared with Mrs. Brady.
A spokesperson for Networked Insights told RWW this afternoon that part of the reason for the lopsided topic mix may have to do partly with the game. It was a low-scoring game with only one interception, whose outcome was only sealed when the clock reached zero. It may have been such a nail-biter, in other words, that true football fans may have been biting their nails rather than tapping their keys.
“It’s not surprising to see viewers’ commentary of Super Bowl advertisements surpass those of the game itself,” Dan Neely, NI’s CEO, tells RWW this afternoon. “Brands can partly attribute this social lift as a by-product of a low-scoring game that allowed viewers to discuss the commercials.”
A word about the volume of tweets: Naturally, NI’s tracking included tweets that included the hashtag #superbowl. NI estimates tweets to that hashtag alone to have numbered around 1.6 million, though it will have updated, hardened data later in the week. That’s as many tweets as are normally archived in a single day, the NI spokesperson tells us.
As an analysis firm for advertisers, NI itself was concerned more with the commercials than the football. Gaining the most overall viewer response among celebrity endorsers was the tattooed, underwear-wearing veteran of what “far’ners” call football, David Beckham. His shorts reached out to 39% of folks talking about just the Super Bowl commercials (as opposed to the game), according to NI’s figures. This is what NI means by “share of value.” Sentiment among chatting consumers was 23% more positive than negative, suggesting the H&M undies went over well. Coming in second was Clint Eastwood, whose two-minute ad that may have been for Chrysler but may really have been for the city of Detroit, had 21% “share of value,” while 9% of the discussion was more positive than negative.
Though NI gives Chrysler kudos for choosing Eastwood, it notes that the resulting chatter was three times more about him than about Chrysler.
By comparison, as much as 28% of folks chatting about Super Bowl topics during halftime were discussing Madonna’s halftime show. Their discussion constituted 32% of Super Bowl-related social traffic by volume. Sentiment for Madonna was generally negative (-21%), with tweets about her staying relatively short, with a particularly negative peak towards the end where the lights converged to reveal the message, “WORLD PEACE.” By contrast, sentiment for her on-stage co-star MIA – whose little birdie expressed exactly the opposite sentiment – ran generally positive at +6%, commanding 3% of the discussion. The star of the halftime show ended up being Nicki Minaj, whom perhaps more viewers recognized than Clint Eastwood. Minaj commanded a 7% share of value, with 26% of it more positive than negative.
Breaking down just the Madonna comments, MI found that as much as 2% of this subgroup were making comments about her age (53). This group was split down the middle as to whether she looked great for her age, with the negative group making snarky comments about such things as her “veiny” arms. Sentiment turned positive when she began singing “Like a Prayer,” which was originally released in 1989, though it tipped downward to -11% after she began her latest single, “Give Me All Your Luvin.’” (NI does not appear to have data regarding consumer sentiment about its spelling.)
“The takeaway for networks, producers, and sports leagues is the need to create multiple engagement points around content that is in sync with the interests of a target audience,” states NI’s Dan Neely. “Going forward, the winners will be the programs that leverage social technology to drive participation.”
What the Twitterers of the world may have missed Sunday night was the terrific sense of community and shared excitement. Just the NFL Experience – the week-long slate of activities in downtown Indianapolis among football fans who love the game and who keep their phones mostly in their pockets except to take pictures – pulled in some 265,000 people over a nine-day period, according to the latest estimates.
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Flurry Adds HTML5 to Mobile Analytics Platform
Feb 1st
Mobile analytics and monetization platform Flurry is adding a new vertical to it platform offering today. Recognizing the coming growth of mobile Web apps, Flurry will begin tracking HTML5 mobile Web apps starting with a beta software developer kit today.
Flurry supports five other mobile platforms. That includes BlackBerry, iOS, Android, Windows Phone and J2ME. Flurry notes a recent survey by Kony that says that 74% of Fortune 500 companies were planning on some type of HTML5 integration. That does not mean those companies will replace their native apps though, with only 7% saying that HTML5 would supplant native applications. In an ecosystem that is becoming increasingly diverse, Flurry is making sure it can be everything to everybody.
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Flurry is one of the companies that is directly benefiting from the explosive growth of the mobile app ecosystem. Since launching in 2008 the sessions that Flurry tracks have doubled every six months. At the end of 2011, the company had tracked more than 240 billion sessions.
“It took Flurry a full two years, from August 2008 to August 2010, to track one hundred million daily sessions,” said Flurry CEO Simon Khalaf in a release. “Now we’re adding another hundred million daily sessions every three weeks.”
Flurry is now used by 60,000 developers with 150,000 apps in its publisher network. Overall, that works to about 15% of all apps published to the variety of platforms. Flurry’s VP of marketing Peter Farango said in an email that the company predicts that Flurry analytics is embedded in one out of every three downloads from the Android Market, Apple App Store, Amazon Appstore etc.
“We are officially a very big, big data company,” Farango said.
Flurry’s growth threatens to overshadow some of the other players in the mobile analytics field like Kontagent, Localytics and Apsalar. Flurry has a head start and has become a popular free offering for many developers looking for an SDK to track analytics in their apps. That is not to say that Flurry is a one-stop shop for all of your analytics needs, but the company has a forward looking approach that can fit well for many developers.
What is your view on Flurry? Do you use them for analytics or monetization purposes? How does the company stack up to the competition in overall quality of service? Let us know your experience in the comments.
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The SEO’s Guide to Google Analytics 5: Getting Used to New Features Part I – Search Engine Journal
Feb 1st
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The SEO's Guide to Google Analytics 5: Getting Used to New Features Part I
Search Engine Journal And in the final part of this series, we will get all super geek with your analytics by creating fancy SEO dashboards. In this article, I'll show you a few places you can look along to get used to the new layout and reporting features. Google Analytics – New Version Update |
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The SEO’s Guide to Google Analytics 5: Getting Used to New Features Part I
Feb 1st
This is part one of three in a geeky Google Analytics version 5 series to help you get accustomed to the new Google Analytics and use the new neat reporting features to impress your clients and bosses. In the next article, I will share my top 6 new features in Google Analytics version 5. And [...]
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Google Analytics Alternatives: Hosted vs. Self-Hosted Solutions
Jan 25th
While Google Analytics has its own set of merits, there are drawbacks. Many people don’t want to continue to feed Google more data – and this trend is growing. Here are some ideas to help you choose the best web analytics solution for you.
View full post on Search Engine Watch – Latest
New Malware Protection Using Big Data Analytics From Sourcefire
Jan 23rd
Security software vendor Sourcefire announced today a new kind of endpoint security solution called FireAMP that couples the power of big data analytics with real-time threat detection and prevention. The idea is to use what is happening around the Internet in real time to lock down Windows endpoints and prevent them from running malware.
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As you can imagine, this is not a completely new concept. Network Box gathers intelligence from data collected around the world at major Internet peering points. What is new is the ability to take this intelligence and remove the infection from the actual endpoint. The catch is that you have to run Sourcefire’s agents on every endpoint on your network. And if you have non-Windows endpoints, you will have to wait: the company is planning on widening its net but right now only Windows is instrumented.
One of the more interesting features is called File Trajectory. This tracks file movement within the enterprise, allowing organizations to identify the entry point and propagation path of malware. As you see from the below display, you have a list of every endpoint that has touched a particular file.
You can get more information about FireAMP here. Prices start at $30 per seat annually. This single price includes 24×7 platinum technical support, all maintenance releases and content updates, the Sourcefire hosted FireAMP Management Console, and access to Sourcefire’s FireCLOUD analytics platform.
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