Lies, Damned Lies...

Wading into the Google Secure Search fray

There’s been quite the hullabaloo since Google announced last week that it was going to send signed-in users to Google Secure Search by default. Back when Google first announced Secure Search in May, there was some commentary about how it would reduce the amount of data available to web analytics tools. This is because browsers do not make page referrer information available in the HTTP header or in the page Document Object Model (accessible via JavaScript) when a user clicks a link from an SSL-secured page through to a non-secure page. This in turn means that a web analytics tool pointed at the destination site is unable to see the referring URLs for any SSL-secured pages that visitors arrived from.

This is all desired behavior, of course, because if you’ve been doing something super-secret on a secure website, you don’t want to suddenly pass info about what you’ve been doing to any old non-secure site when you click an off-site link (though shame on the web developer who places sensitive information in the URL of a site, even if the URL is encrypted).

At the time, the web analytics industry’s concerns were mitigated by the expectation that relatively few users would proactively choose to search on Google’s secure site, and that consequently the data impact would be minimal. But the impact will jump significantly once the choice becomes a default.

One curious quirk of Google’s announcement is this sentence (my highlighting):

When you search from https://www.google.com, websites you visit from our organic search listings will still know that you came from Google, but won't receive information about each individual query.

This sentence caused me to waste my morning running tests of exactly what referrer information is made available by different browsers in a secure-to-insecure referral situation. The answer (as I expected) is absolutely nothing – no domain data, and certainly no URL parameter (keyword) data is available. So I am left wondering whether the sentence above is just an inaccuracy on Google’s part – when you click through from Google Secure Search, sites will not know that you came from Google. Am I missing something here? [Update: Seems I am. See bottom of the post for more details]

I should say that I generally applaud Google’s commitment to protecting privacy online in this way – despite the fact that it has been demonstrated many times that an individual’s keyword history is a valuable asset for online identity thieves, most users would not bother to secure their searches when left to their own devices. On the other hand, this move does come with a fair amount of collateral damage for anyone engaged in SEO work. Google’s hope seems to be that over time more and more sites will adopt SSL as the default, which would enable sites to capture the referring information again – but that seems like a long way off.

It seems like Google Analytics is as affected by this change as any other web analytics tool. Interestingly, though, if Google chose to, it could make the click-through information available to GA, since it captures this information via the redirect it uses on the outbound links from the Search Results page. But if it were to do this, I think there would be something of an outcry, unless Google provided a way of making that same data to other tools, perhaps via an API.

So for the time being the industry is going to have to adjust to incomplete referrer information from Google, and indeed from other search engines (such as Bing) that follow suit. Always seems to be two steps forward, one step back for the web analytics industry. Ah well, plus ca change…

Update, 10/25: Thanks to commenter Anthony below for pointing me to this post on Google+ (of course). In the comments, Eric Wu nails what is actually happening that enables Google to say that it will still be passing its domain over when users click to non-secure sites. It seems that Google will be using a non-secure redirect that has the query parameter value removed from the redirect URL. Because the redirect is non-secure, its URL will appear in the referrer logs of the destination site, but without the actual keyword. As Eric points out, this has the further unfortunate side-effect of ensuring that destination sites will not receive query information, even if they themselves set SSL as their default (though it’s not clear to me how one can force Google to link to the SSL version of a site by default). The plot thickens…

Adobe + Omniture = …what?

By now, almost 12 hours after the announcement, you’ll have heard the news that Adobe is to buy Omniture for $1.8bn. If you haven’t heard, then, I mean, duh. It’s all over Twitter, dude:

(As an aside, the guys at Omniture should be proud of themselves that they managed to beat out Joe Wilson as a trending topic for a little while, even as the latter was busy facing down Congress).

I don’t think I’m putting myself in the minority when I say that I was totally blind-sided by this announcement. And while I’ve had time to think about it since my first reaction, I’m still a bit mystified by this acquisition.

The official line from the press release is that Omniture’s products will help Adobe’s customers optimize, track and monetize their websites & apps. Unofficially, the rationale for the deal seems to be that Adobe needs Omniture’s revenue to supplement its declining income from its range of software. I can see the logic of the official rationale, but I have serious reservations about Adobe’s ability to extract value from this deal, for the following reasons:

No pedigree in services: Adobe is primarily a software company; whilst it offers a full range of support services around its products, it doesn’t really have experience in providing the very deep, consultancy-like services that Omniture provides. This means that it’ll likely be challenging to attach Omniture offerings to Adobe’s customers; the opposite may be more likely to be true, but does Omniture bring enough customers to make this worthwhile?

No online scale: I’ve said before that one of Omniture’s key challenges as it strives for profitability is to scale out its infrastructure on a cost-effective basis.Adobe does offer a range of online services, but not on any kind of scale that could enable it to really drive cost out of the provision of Omniture’s services. So it’s unlikely that Omniture’s bottom line will improve in the wake of this deal.

Channel/partner conflict: The presence of the Omniture toolset in Adobe’s product lineup will complicate Adobe’s efforts to work with other agencies, EMM and web analytics tool providers, who in turn may find themselves more reluctant to encourage their clients to embrace Adobe technology for fear that it may lead to Omniture making calls on them.

Overall, I just find myself wondering whether Adobe really needed to do this deal in order to be able to leverage Omniture’s capabilities. Adobe has to be looking at some kind of synergy effect to extract value from the deal, because Omniture’s financials aren’t strong enough on their own to move the needle on Adobe’s bottom line. Would a strategic partnership not have been a simpler (and undoubtedly cheaper) option? One possible answer that presents itself is that Adobe had its hand forced by an imminent sale of Omniture to another party. What do you think?

 

Disclaimer
This is one of those posts where I perhaps need to remind you that this is a personal blog which does not reflect the opinions of my employer, Microsoft. Furthermore, you shouldn’t infer that anything I’ve written above implies any foreknowledge or special knowledge of this deal, especially in the context of Microsoft. That is all.

My face, on the Internet

I have just noticed (rather belatedly, to say the least) that Laura Lee Dooley has posted a complete video of my encounter with Avinash Kaushik at the May E-metrics Summit in San Jose on Vimeo. The sound quality is a little poor, but you can more or less follow the thread of the conversation.

I come across as a cross between Prince Charles, Alastair Campbell and my Dad. Avinash does rather better, particularly around the 26 minute mark. Anyway, watch it for yourself and see who comes out on top.

Does Display help Search? Or does Search help Display?

One of the topics that we didn’t get quite enough time to cover in detail in my face-off with Avinash Kaushik at last week’s eMetrics Summit (of which more in another post) was the thorny issue of conversion attribution. When I asked Avinash about it, he made the sensible point that trying to correctly “attribute” a conversion to a mix of the interactions that preceded it ends up being a very subjective process, and that adopting a more experimental approach – tweaking aspects of a campaign and seeing which tweaks result in higher conversion rates – is more sound.

I asked the question in part because conversion attribution is conspicuously absent from Google Analytics – a fact which raises an interesting question about whether it’s in Google’s interest to include a feature like this, since it may stand to lose more than it gains by doing so (since the effective ROI of search will almost certainly go down when other channels are mixed into an attribution model).

Our own Atlas Institute is quite vocal on this topic, and has published a number of white papers such as this one [PDF] about the consideration/conversion funnel, and this one [PDF], on which channels are winners and losers in the new world of Engagement Mapping (our term for multi-channel conversion attribution).

The Atlas Institute has also opined about how adding display to a search campaign can raise the effectiveness of that campaign by 22% compared to search alone – in other words, how display helps search to be better.

However, a recent study from iProspect throws some new light on this discussion. The study – a survey of 1,575 web consumers – attempted to discover how people respond to display advertising. And one of the most interesting findings from the study is that, whilst 31% of users claim to have clicked on a display ad in the last 6 months, almost as many – 27% – claimed that they responded to the ad by searching for that product or brand:

This raises the interesting idea that search can actually help display be better, by providing a response mechanism that differs from the traditional ad click behavior that we expect. Of course, this still doesn’t mean that search should get 100% of the credit for a conversion in this kind of scenario – in fact, it makes a stronger case for “view-through” attribution of display campaigns – something that ad networks (like, er, our own Microsoft Media Network) are keen to encourage people to do, to make performance-based campaigns look better.

All this really means that, of course, it’s not a case of display vs. search, but display and search (and a whole lot of other ways of reaching consumers). Whether you take the view that it’s your display campaign that helps your search to be more effective, or your search keywords that help your display campaign to drive more response, multi-channel online marketing – and the complexity that goes with measuring it – looks set for the big time. And by “big time”, I mean the army of small advertisers currently using systems like Google’s AdWords, or our own adCenter. So maybe we’ll see multi-channel conversion attribution in Google Analytics before long.

What would you like to ask Avinash Kaushik?

The gloves will be tied tight. Brightly colored silk dressing gowns will be shrugged to the floor; gum-shields inserted. In the blue corner: yours truly. In the red (and blue, yellow and green) corner, web analytics heavyweight, Avinash Kaushik. As the crowd bays for blood, battle will be joined. The Garden never saw anything like this.

Well, ok, it’ll probably be a bit more civilized (well, a lot more civilized) than that. But at next week’s E-metrics Summit in San Jose, Avinash and I will indeed be going head to head in the “Rules for Analytics Revolutionaries” session on Wednesday May 6 at 3.25. In that session, I’ll be asking Avinash some genuinely tricky questions to really get to the heart of some of the thorniest issues around web analytics today, such as campaign attribution, free versus paid tools, and what, really, the point of all this electronic navel-gazing really is.

But I could use your help. In my comments box below, or via e-mail, suggest the question(s) you’d most like me to ask Avinash next week. This is your big chance to ask Avinash the question you’re too embarrassed/polite/nervous to ask him in person. If you’re going to be at the Summit, then be sure to come to the session to see if your question gets asked; if not, I’ll post a follow-up post here after the event and shall be sure to include Avinash’s answers to any questions from the blog.

So come on – what have you got to lose? It’s not like it’s you who’s going to be picking a fight with one of the industry’s most revered and respected advocates, is it? Leave that to old numb-knuckles here.

Google adds rank information to referral URLs

An interesting post on the official Google Analytics blog from Brett Crosby appeared last week, in which he announced that Google is to start introducing a new URL format in its referring click-through URLs for organic (i.e. non-paid) results. From Brett’s post:

Starting this week, you may start seeing a new referring URL format for visitors coming from Google search result pages. Up to now, the usual referrer for clicks on search results for the term "flowers", for example, would be something like this:

http://www.google.com/search?hl=en&q=flowers&btnG=Google+Search

Now you will start seeing some referrer strings that look like this:

http://www.google.com/url?sa=t&source=web&ct=res&cd=7&url=http%3A%2F%2Fwww.example.com%2Fmypage.htm&ei=0SjdSa-1N5O8M_qW8dQN&rct=j&q=flowers&usg=AFQjCNHJXSUh7Vw7oubPaO3tZOzz-F-u_w&sig2=X8uCFh6IoPtnwmvGMULQfw

Brett points out that the referring URL now starts with /url? rather than /search? (which is interesting in itself in its implication for the way Google is starting to think about its search engine as a dynamic content generation engine); but the really interesting thing, which Brett doesn’t call out but which was confirmed by Jason Burby in his ClickZ column today, is the appearance of the cd parameter in the revised URL, which indicates the position of the result in the search results page (SRP). So in the example above, where cd=7, the link that was clicked was 7th in the list.

As Jason points out, this new information is highly useful for SEO companies, who can use it to analyze where in the SRPs their clients’ sites are appearing for given terms. Assuming, of course, that web analytics vendors make the necessary changes to their software to extract the new parameter and make it available for reporting (or, alternatively, you use a web analytics package that is flexible enough to enable you to make this configuration change yourself).

As you can see from the example above, there are various other new parameters that are included in the new referring URL, which may prove useful from an analytics perspective (such as the source parameter). It’s also worth noting that whereas the old referring URL is the URL of the search results page itself, the new URL is inserted by some kind of redirection (this must be the case, since it includes the URL of the click destination page).

Using a redirect in this way means that as well as providing more information to you, Google is now also capturing more information about user click behavior, since the redirect can be logged and analyzed. Crafty, huh?

Omniture stumbles

Chatter is building on the interwebs about Omniture’s recent (and ongoing) latency woes. Looks like both SiteCatalyst and Discover are days behind in processing data (according to messages on Twitter, up to around 5 – 7 days in some cases). And it looks like the situation is still getting worse, rather than better.

I have no insight into the cause of Omniture’s difficulties, or how widespread they are. It may be that they’re related to the December release of SiteCatalyst 14.3, which seems to contain a number of new features which are fairly broad in scope, and which may have had an impact on the platform’s ETL stability. Behind the scenes, Omniture may have made some changes to start integrating HBX’s feature set (especially its Active Segmentation) into SiteCatalyst as a prelude to a final migration push for the remaining HBX customers. Omniture’s certainly not saying – they’ve been conspicuously silent since the start of these problems.

Whatever the cause, I can certainly empathize with this kind of situation – we had all sorts of difficulty dealing with latency issues in my WebAbacus days. And we can be confident that Omniture will (eventually) fix these problems, and will probably not lose very many customers as a result (though, in the teeth of a recession, it can’t be great for attracting new customers).

But do these problems tells us something more about Omniture’s (or any other web analytics company’s) ability to run a viable business? Infrastructure costs are a big part of a web analytics firm’s cost base (at least, those with a hosted offering, which is all of them). And unfortunately, these costs don’t really scale linearly with the charging method that most Enterprise vendors use – charging by page views captured. Factors like the amount a tool is used, and the complexity of the reports that are being called upon, have a big impact on the load placed on a web analytics system, and the resulting infrastructure cost. It’s tricky for a vendor to recoup this cost without seeming avaricious.

As Omniture’s business grows, it has a constant need to invest in its infrastructure to keep pace with the demand for its services. But as the economy has worsened, it must be terribly tempting to see if a little more juice can be squeezed out of the existing kit, especially with its 2008 earnings due later this month. This will be as true for any other vendor (such as Webtrends or Coremetrics) as it is for Omniture, and these remarks shouldn’t be seen as a pop at our friends in Orem. But the nub is, can Enterprise web analytics pay the bills for its own infrastructure cost? Or will all web analytics ultimately need to be subsidized by something else (such as, oh, I don’t know, advertising)?

Your thoughts, please.

Sifting through the Twitter noise

I was checking my blog stats last week and noticed and noticed that I had a sudden spike in traffic in the week of Thanksgiving (yes, I know, I should check my numbers more often, but I have a day job):

 

A quick glance at my favorite web analytics tool revealed that the culprit seemed to be none other than Twitter (with a decent bit of help from Techmeme):

Twitter is not normally anywhere in my top referrals, let alone Techmeme, so I was by now aglow with excitement. Furthermore, it looked like none other than the world’s pre-eminent ex-blogger (although he, er, appears to have started again), Jason Calacanis, is to be thanked for my brief elevation. A glance at the top pages being looked at confirmed which post:

But what did Mr Calacanis have to say about my lowly blog? The referral information in my web analytics data was not very much help – it just told me that the link came from Jason’s Twitter page at the URL www.twitter.com/jasoncalacanis. How do I find out what he said? I hustled over to Twitter to look through his recent tweets to see if I can find the one about my post. This is where I hit a snag. Jason Calacanis is a prolific tweeter, sharing insights into the profound currents that swirl in his brain many times a day. So I had to trawl through several (to be accurate, thirteen) pages to find the post, which turned out to be this one:

It was only when I did this that I realized how much of a pain in the butt it is to locate a specific tweet that’s sent you traffic. The job is made much harder by the use of services like tinyurl.com and is.gd  which make it impossible to determine whether a tweet links to your site simply by looking at it. But the lack of informative data in the referring URL means I have no other choice but to try out the various links in the hope that one of them will lead to my site. Which, when some of the links are like this, is a bit nerve-wracking:

Of course, given how infrequently my lowly blog is referenced on Twitter, this isn’t such a problem for me – and tweet-based links from less prolific Twitterers would be easier to track down simply by a process of time-based elimination. But if I were doing analytics for a larger site and I wanted to track and analyze the traffic being driven from Twitter, it would be a right royal pain in the ass.

It’s hard to see what Twitter can (or should) do about this. Even if Twitter were able to push meaningful referrer values through with clicks from twitter.com, no such data would be available if a reader clicked through a desktop-based reader such as Twhirl. The problem wouldn’t yield to the kind of solutions used for RSS tracking (i.e. republishing your RSS feed through a tracking service such as Feedburner).

What do you think? If you’ve come up with a creative way of tracking Twitter referrals, let me know in the comments.

Brandt Dainow gets over-excited again

After his breathless article last year, proclaiming Google Analytics to be something like a cross between the second coming and Barack Obama, Brandt Dainow seems to have soured on the big G, proclaiming this week that GA contains ‘disturbing inaccuracies’:

Google Analytics is different from other products in that it has been intentionally designed by Google to be inaccurate over and above the normal inaccuracies that are inevitable. These inaccuracies are so glaring that most people are getting a very false picture of what is happening in their sites.

Dainow’s main beef with GA is two-fold:

• It treats single-page visit as valid visits (i.e. it doesn’t remove them from visit counts or other related measures)
• It includes single-page visits in average visit duration calculations

He also remarks that Google did in fact change the way that GA calculated average visit duration last year, but then changed the calculation back in the face of user pressure:

Google intentionally rolled Google Analytics back so that it produced an incorrect average duration…It's been that way ever since -- Google is intentionally and knowingly providing inaccurate numbers because a few people preferred neatness to truth.

Brandt then proposes two alternative measures - ‘retained visits’ (the count of visits with more than one page impression) and ‘true average duration’ (the average duration of retained visits). These metrics are not without some merit – it’s useful to know how many visits contained more than one page view, and the average duration of these visits. But Brandt goes on to assert that these two metrics should replace the standard measurements of visits and average duration in GA and (presumably) other tools. This suggestion is ridiculous, for the following reasons:

• Contrary to Brandt’s assertions, there are a host of scenarios where a single-page visit is a perfectly valid visit, including, for example, this blog, for crying out loud, which has a high proportion of single-page visits because readers either just read the homepage and leave, or click through to an article from their RSS reader. So chucking all these kinds of visits out is crazy.
• Whilst the inaccuracy of including single-page visits in average visit duration calculations is known to be a problem, removing these visits from the calculation doesn’t yield a magically ‘accurate’ number, it just yields one that is inaccurate in a different way. You still have no idea how long people looked at the final page of their visit for, and with a two-page visit this can introduce a huge potential inaccuracy.
• Such standard metrics as exist in the web analytics industry are the result of long and arduous wrangling. There are no sacred cows, but you need a really good reason to exchange a simple and easy-to-understand metric for one which is more complex and offers no discernible benefit.

Whilst I can understand Brandt’s motivations for posting these ideas (which, I imagine, lie somewhere on a spectrum between a genuine desire to spark debate and a desire to generate a lot of traffic to his blog, in which regard I am obliging him), his remarks do irk me a bit (can you tell?), principally because he commits the unpardonable sin of absolutism when talking about web analytics, bandying about words like “truth” and “wrong” when really he is just presenting his own preferences.

When, as an industry, we can’t even agree what constitutes a visit, it’s pretty rich to start decrying one tool or another as ‘inaccurate’ simply because it takes an approach to data that you don’t believe in. And besides, as Brandt surely knows, Google Analytics now has the capability (via its custom segmentation) to calculate the metrics he seeks.

Finally, as every half-experienced web practitioner (of whom Brandt seems to have a low opinion also) knows, the key to success in web analytics is to pick your metrics, stick to them, and measure them continuously as you make changes to your site and your marketing, to see what is working. If you’re looking to increase engagement, and have decided that visit duration is a good measure of this (a debatable point, as it happens), then it doesn’t matter whether you include single-page visits in your duration calculation – if your visit durations are going up, you’re happy. And if your visit durations suddenly jump because your web analytics vendor has changed the way they calculate the metric, this could in fact cause more pain than benefit, perhaps causing you to go to said vendor and say, “Oi! Change it back to how it was!”.

So feel free to read the article, but be warned: it’s not very accurate.

Applied Insights falls into the gaping Foviance maw

Ok, it’s not quite Omniture acquiring TouchClarity, but I was delighted to read yesterday that my old pals at Foviance have secured the services of none other than Neil Mason through the acquisition of his company, Applied Insights. Neil (whose ClickZ column you should read) has been flying the flag for web analytics – especially from a marketing-effectiveness point of view – for many years, and he’ll be a great asset to the Foviance team. Congratulations Neil and Paul. Neil’s partner and co-founder of Applied Insights, John McConnell, will leave to pursue independent interests.

The only note of sadness for me in this announcement is that the background to the acquisition is the change in the focus of Foviance’s web analytics efforts away from a WebAbacus-oriented technology/consulting solution to a services-only offering based around Omniture, WebTrends and the like. Of course, this is precisely the right thing for Foviance to do, since the web analytics market is now firmly consolidating around the major players; but I’m sad because WebAbacus (which I spent so many years on) isn’t one of them. But I like to think that its influence in the industry lives on.