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Google Analytics Intelligence Feature is Brilliant!

Published by Eric T. Peterson on November 10, 2009 All posts from Eric T. Peterson

Long-time blog readers are likely aware that I’m not prone to writing about individual technologies or product features unless I have the opportunity to break the news about something new and cool (or not, as the case is from time to time.) But once and awhile a single feature comes along that in my mind is so compelling and cool I need to bend my own rules; Google Analytics new “Intelligence” offering is exactly that feature.

Just in case you’ve been living under a rock for the past month and haven’t already heard about “Intelligence” have a quick watch of the following video pulled from the Google Analytics blog:

Pretty awesome, huh? What’s more, now that I’ve had a few weeks to play with the feature and think about it in the context of my published views on the Coming Revolution in Web Analytics, I think that “Intelligence” is one of the most important advances in web analytics since the JavaScript page tag.

While Google is certainly not the first vendor to apply some level of statistical and mathematical rigor to web analytics data, an honor that would likely go to Technology Leaders for their Dynamic Alert product or Yahoo for their use of confidence intervals when exposing demographic data in Yahoo Web Analytics, in my humble opinion Google has done the best possible job making statistical analysis of web analytics data accessible, useful, and valuable.

Some things I really like:

  • An approachable way to determine confidence intervals via their “Alert Sensitivity” slider. While the implementation doesn’t necessarily impart the level of detail some folks would like, the slider mitigates the prevalent concern that “people won’t understand confidence intervals.”
  • Great visual cues for alerts, especially when statistically relevant changes are not obvious based on traffic patterns. Sometimes traffic patterns just look like hills and valleys, even when something important is happening — for example, the next figure shows two alerts at the lowest threshold setting on September 16th that, upon exploration, turned out to be great news (that I might have missed otherwise.)

  • Good visual cues regarding the statistical relevance of the insight being communicated. This is tough since Google is trying to present moderately complex information regarding the underlying calculations and how much emphasis you should be putting on the insight. By showing a relative scale for “significance” I think Google has more or less nailed it.

  • Google Analytics finally starts communicating about web analytics data in terms of “expectations” instead of absolutes. All of us (present company included) have a tendency to get wrapped up in whole numbers, hard counts, and complete data sets. But we also know that Internet-based data collection just isn’t that accurate, and so any push to get us to start thinking in terms of predicted ranges and estimates is a step in the right direction. For example, I love knowing that on a given day Google Analytics “expects” between 311 and 388 people to come to my site from the UK!

  • Lots more, including the ability to pivot the views and look from a “metric-centric” and “dimension-centric” perspective, the ability to aggregate on day, week, and month, and the ability to add your own custom alerts based on changes in traffic patterns. Perhaps ironically this last functionality (“Custom Alerts”) is how we’ve all historically thought about “Intelligence” in reporting, and while useful seems somewhat weak compared to Google’s stats-based implementation.

While awesome in it’s first instantiation there are some obvious things that the Great GOOG could improve in the feature. Some ideas include:

  • More dimensions and metrics, although I believe both Nick and Avinash have commented that they are already working on adding intelligence to other data collected.
  • Some way to expose confidence intervals and p-values would be useful (perhaps as a mouse-over) so that the increasing number of analysts with experience in statistics could have that data in their back pocket when they went to present results.
  • Email alerts for the automatically generated insights, for example when “Intelligence” determines that five or more alerts have been generated it would be cool to get an email/SMS/Tweet/Wave notification.
  • The ability to generate alerts against defined segments, so that I could see the same analysis for different audiences that I’m tracking.

Mostly ticky-tack stuff, but again I’m pretty damn impressed with their freshman effort. I suppose I shouldn’t be surprised since evangelist Avinash has been talking about the need for statistics in web analytics for an awfully long time, but given that so many in our industry have balked at bringing more mathematical rigor to our work (including said evangelist, oh well) it’s encouraging to see Google move in this direction.

What do you think? Are you using “Intelligence”? Is it helping you make better decisions? Do you like the implementation as much as I do? I’d love to hear your thoughts and comments.

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Categorized under Random Thoughts, Vendors, White Papers

  • http://www.baranyi-eriksen.com Kenneth Baranyi Eriksen

    I’ve just starting to use it, and it seems uneblievable that we now can get “webanalytics on autopilot”.

    Although fantastic, I have found some limitations in the automatic alerts. The Daily and Weekly intelligence feature/alerts are very limited.

    It’s seems like there is some correlations with traffic volume. Low traffic means less alerts, while sites with more volume get more alerts also in the Daily and Weekly features. Probably something to do with significanse. Is this a correct observation?

    Anyway, the monthly feature always gives valuable advice, and very often gives such advice that I would otherwise miss out on if I was to do it manually.

  • http://www.waomarketing.com/blog Jacques Warren

    Just one question: whose a** to I have to kiss to get it?

  • Nicole Rawski

    Uh… ditto to what Jacques said! It sounds awesome and I can’t wait to get my hands on it. Thanks for the review Eric.

  • http://www.twitter.com/bigbryc Bryan Cristina

    I like new features like this, I think it’s useful to have some things right at your fingertips if you know what you’re looking for. And to be honest, sometimes you’re so deep into the numbers that changes are meaningless, so having some of them highlighted could be a good way to ensure you’re not missing things.

    The only problem I see is if people start out with these types of reports they may lack learning some useful skills they would have gotten by digging into a bunch of seemingly independent data that didn’t have any correlations. That and even seasoned vets could get lazy and never look beyond the surface of what Google is showing them. Not that it’s Google’s fault, of course, but it could lead to some embarrassment as important stones are left unturned. Especially if someone within the area/company you’re working for overturns it for you.

  • http://www.savio.no Eivind Savio

    GA Intelligence is awesome, but I could always wish for more.

    Adding context to the data is always useful. Reason for this change is caused by (ex. campaign, viral etc.), and flagging activities (campaign start/end). I mentioned this earlier on Avinash’ blog, so hopefully since it’s Christmas soon…

    Haven’t played long enough with GA Intelligence to be absolutely certain, but from what I can see, Custom Alerts will only be triggered/shown for future data, not historical(?). Or?

  • http://www.webanalyticsdemystified.com eric

    Kenneth: Without a doubt the “Intelligence” feature would depend on your total traffic volume, that’s just the way statistics and samples work. Great idea about using the Weekly and Monthly view to get enough data to make the feature useful!

    Jacques and Nicole: My understanding was that they were rolling the feature out relatively quickly following the announcement in D.C. a few weeks back. Maybe someone from Google will see your pleas for help and comment on the roll-out plan here.

    Suffice to say it’s worth the wait.

    Bryan: Good point, but I respectfully disagree. What Google has given us is another tool in our tool chest, one that allows us to quickly identify opportunities that might otherwise go unnoticed. And keep in mind that I’m saying that this is a good step in the right direction, not the final product. If you want my thoughts on where features like this eventually take us take a look at my recent white paper with SAS.

    Elvind: Yeah, custom (“un-intelligent”) alerts seem to only work on a move-forward basis … but that makes sense. It would be hard to get historical alerts after the fact (or at least hard to put them to use.)

    Thanks to all for your comments!

  • http://immeria.net Stephane Hamel

    I also LOVE the new features. And I must admit that I have few arguments left for the other big players out there. It almost becomes a purely contractual/procurement/legal aspects…

    One thing however: the actual Intelligence applies to Visits only… I outcomes were the most important! I’m surprised Avinash has let this go by. I simply can’t apply Intelligence to, say, my revenues, or any other Goals I might have defined.

    But then again… as much as this might be a huge miss, who would complain?

    Another thing: I can set custom metrics through SetCustomVar(), I have just not found how to view them in the reports or through the API…

    Stéphane

  • http://www.webanalyticsdemystified.com eric

    Stephane: Really? I can see my different revenue-based Goal values represented in “Intelligence.” For example, here is what I see when folks on the East Coast step up and purchase a copy of my KPI book:

    That, especially when the new custom variable stuff is loaded and incorporated into Intelligence, will be pretty valuable from my perspective.

    Also, for the record and as much as Avinash is loved by all, here are the guys ** really ** responsible for a lot of what you see in Google Analytics:

    (Obviously the guy in the middle has nothing to do with the product …)

    Since you’re on the iPerceptions board with AK perhaps you can get the skinny on when the roll-out will be complete? ;-) Thanks for writing Stephane!

  • http://insightr.com James Dutton

    Eric,

    While this is certainly a step in the right direction for Google (and all other vendors to follow) I would hesitate to describe this as statistical analysis.

    Statistical significance is not a measure that can be determined by a slider bar, or through a pretty greyed out bar. Statistical significance is a boolean value at levels of confidence:

    Is Significant @ 95%: NO
    Is Significant @ 90%: NO
    Is Significant @ 80%: YES **

    With this in mind, I worry that many folks who have little or no experience in statistics (and this is basic stuff we’re talking about here) will start misinterpreting data because an ‘intelligent’ tool is now telling them to look at things which perhaps aren’t really that important to look at.

    Then again, the flipside of this is that with the exception of what I can scribe into an Excel based report using Omniture, or with the Significance reports by YWA – none of the other vendors are offering anything like this yet: and for that Google get kudos.

    Here’s what Google, and well, all the other vendors should do: integrate statistical measures into all reports. How? Well, let’s take a simple trend-line — we add UCL and LCL limits to this to identify outliers. Let’s take a keyword report, highlight that keyword X with only 3 visits and 1 conversion is not statistically significant compared with control. Help analysts make sense of these drill down, segmented reports that the tools are offering…

    Note: I am yet to see this feature in any of my client accounts so am basing this analysis off screenshots and videos only. When I see the feature, I may be tempted to revise my somewhat negative opinion today.

    Cheers, J

  • http://padicode.com/blog/ Claudiu Murariu

    Hi Eric,

    I guess I’m one of the lucky ones who got access to the new Intelligence feature. And yes, I’ve received access just one day after I read your “Coming Revolution in Web Analytics”.

    The GA platform is getting more and more complex and of course smarter which is super cool for web analysts but little less for web site owners. Most of the people I start working with consider Google Analytics too complex and always say they don’t understand what everything means. Half of my job is to do Google Analytics training and the other half is for doing consultancy. :)

    I think new features will mean web analysts will become more popular, which is great, right? But I think it should mean also that web people should become more “analytics” oriented. I hope the latest move from WAA of getting more international branches will help in this matter.

    I have to say I am little surprised (in a good way that is) to read on your blog such a great review for Google Analytics. :)

  • http://www.webanalytiker.dk Jacob Kildebogaard

    Hi

    I have played with the feature for a few weeks now, and it is great. But is does not take over jobs – it gives insight to now where to focus in the analysis.

    I have made a blog about the tool (in danish, but maybe you can translate it with Google Translate) http://www.webanalytiker.dk/2009/10/27/google-analytics-intelligence-intelligent-analyse/ where i talk about other challenges.

    The comparison of a given day, week or month are made on ALL data in the profile. In the “old days” (before we had 20 goals) we made more than one profile with the same data, to have more goals. Sometimes they were not made the same day. That means that the Intelligence results are NOT simular, even though the two profiles in your thougts contains the same data.

    As the next step of the developing it could be real nice to compare last thursday with the last 10 thursdays, and not all days of week, all data.

    The results shown are always with a significance level of 95%, but the significance bar is actually a measure on the numbers of standard deviation away from the expected mean.

    It is a really great tool, but beware and remember how the data are made.

  • http://www.webanalyticsdemystified.com eric

    James: While it is difficult to disagree with anything you say I fear you have focused on the eventual outcome and not taken a step back to enjoy one of the first widely available steps in the right direction.

    While I’m not familiar with the “Significance report by YWA” you reference (could you send me a link to that please?) I’m not that sold on the “export to Excel” method that we’ve all been using for so long. The strategy is so dependent on your data export functionality and it fundamentally separates “data” and “analysis” in a way that I think is sort of unhelpful.

    I think that any effort to get us to think about more powerful and useful ways to leverage all this data is great news. And again, I don’t disagree that some people might be tempted to use “Intelligence” as a crutch I don’t think that’s a Google Analytics (or any application) issue, that’s a people issue …

    … which is an entirely different ball of wax!

    I hope you get access to Intelligence soon as I cannot wait for your review. Based on the slides you created to compare GA and YWA I have little doubt the review will be a “must read!”

    Thanks for your comment!

    Claudiu: Interesting to hear you think that Google Analytics is becoming “too complex” … but I suppose that is inevitable as the application comes up-market and deploys more and more Enterprise (sic) features. Still, after seeing this latest feature set and thinking about how Google is bringing custom variables of different scope to market (another great strategy IMHO) I am encouraged by the “Think Different” attitude that Avinash, Brett, Phil, Nick, and others are bringing to the process.

    It’s not to say that the other vendors aren’t innovating, they certainly are, but GA is a different beast given their footprint today.

    Regarding your surprise in reading a positive review of Google Analytics … fair enough. I can be kind of a grouch at times but I am working on that, I promise! My goal for 2010 is to find a more healthy balance of critique and compliment in my writing and research (wish me luck!)

    Jacob: Great comments about the feature here and I will see if I can find translation for your blog post. Without a doubt Google, or perhaps their competitors, can improve on this recent innovation but as I have said a few times now I am just really happy to see a vendor with Google’s might pushing us to expand the way we use our data (and the way our data gets used!)

    Thanks for the note about the alert threshold as well. I must have missed that but as soon as I get confirmation from GA about your point I will update the blog post as well!

    All the best!

  • http://www.webanalytiker.dk Jacob Kildebogaard

    @Eric: Thank you :-) I consider making a english version of my site, but so far I hope you are able to read with translate…

    I DO really think this is one of the best steps seen in webanalytics for a long time. I wrote some questions to Dennis Mortensen, as an interview, where one of them where: Will we see more statistics integrated in the future. And then Google gives me the answer. So nice.

    Maybe this i already step 2 in the development, but I am soo thrilled about the feature that i cant wait to get my hands on version 10 :-) But the glass IS half Full, not half empty ;-)

  • http://www.keywebmetrics.com sameer

    I would not say the GA intelligence feature is brilliant because most advanced web analyst have already been using statistical significance for long time. I agree that it definitely simplifies and promotes the use of statistics for day to day analysis.

  • http://brandingme.tumblr.com Adrian Palacios

    I’m surprised about the comments that, in a round about (or direct) fashion deride Google for this step; that, this new feature is for the “lazy” or “non-sophisticate” crowd.

    Okay, you’re right in one sense: this new feature is not for those who know what a confidence interval is, or can calculate two-way ANOVA or some multiple linear regression in their sleep. But that’s the *POINT*: it lowers the bar of entry for those who have not graduated with a degree in statistics but still have a stake in a company’s bottom line.

    Assuming that the “predicted” values in this new feature are lower and upper control limits, and that anything deemed significant is at least 95%, GA Intelligence drastically lowers the bar of entry for (somewhat) more sophisticated analysis. Now, the mom and pop shop in your neighborhood that can’t afford fancy consultants or know their way around SPSS can at least have somewhat intelligent (pun intended) information on the upcoming business decisions they need to make.

    Will people misuse the information? Sure. Do people understand how it got there? Probably not entirely. But now the stakeholders for small to mid size businesses who don’t know how to calculate an upper and lower control limit with the SUM, AVERAGE and STDEV function in Microsoft Excel have at least another valuable piece of information about their business than they did yesterday. That’s great.

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  • http://trendly.com Avi Bryant

    I definitely think this is a step in the right direction, and Google should be given kudos for bringing some level of statistical analysis rather than raw presentation of the data. However, I think that “Google has done the best possible job making statistical analysis of web analytics data accessible, useful, and valuable” is a pretty strong statement and isn’t justified by what I’ve seen of Intelligence so far.

    (Note: I work on an arguably competing product, so may be biased.)

    For one thing, I think the use of standard deviations from the mean as the “significance” measure (as Jacob pointed out, and this jibes what I’ve seen) is a mistake – it’s too easy to get swamped with alerts for meaningless outliers on small-N datasets.

    For another, I think the focus on outliers in general is too shallow an analysis. Yes, it will pick up referral spikes or sudden drops in traffic due to misconfigured spikes, but it doesn’t help with the more interesting questions like “did this subtle change to my website improve conversion rate” or “was there a residual traffic increase from that spate of publicity last month” – these are the questions that most cry out for statistical analysis.

    I’ve written more about this here: http://bit.ly/42BkRv . Eric, love to hear your thoughts.

  • http://www.unpublishedguy.com Kurt

    I also do not have this feature with Analytics and would like it. My site also has a fairly low number of visits/month (hundreds), so it might be a matter of visitor volume as to whether you get to use the feature.

    It could also be a matter of being invited. I had not been receiving the Google Marketing newsletter, so perhaps I missed an invite.

  • http://www.RetailShakenNotStirred.com Kevin Ertell

    Great post, Eric. Sorry I’m a little late in reading it. I am very much in agreement with you on this one. It’s great that Google is recognizing the importance of understanding expected ranges in data and providing the ability to highlight outliers. Of course, it’s still going to be important for web analysts to determine when an alert is calling out the inevitable expected outlier versus a truly meaningful change in trend, but the fact that there is a least the ability to differentiate between expected ranges and outliers is great. I also agree with some of the other commenters here on the need to take this even deeper, but I applaud the early efforts.

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Whether you have a single toe dipped in the waters of social media analytics or are fully submerged and drowning, you’ve almost certainly grappled with "engagement." This post isn’t going to answer the question "Is engagement ROI?" ...

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It’s not about "Big Data", it’s about the "RIGHT data"
Michele Kiss, Partner

Unless you’ve been living under a rock, you have heard (and perhaps grown tired) of the buzzword "big data." But in attempts to chase the "next shiny thing", companies may focus too much on "big data" rather than the "right data."

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Eric T.
Peterson

John
Lovett

Adam
Greco

Brian
Hawkins

Kevin
Willeitner

Michele
Kiss

Josh
West

Tim
Wilson

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(503) 282-2601


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