The vision, one can surmise from Omniture’s acquisitions and visible product strategy, was to create a closed-loop web management platform, that included content targeting and optimization, search and display marketing management, complex customer analysis via a warehouse (or warehouse-like product), and other commerce-enabling technologies.  Data collection to empower automated decision making and optimization would enable the whole platform (Omniture’s core competency).  What was missing, of course, was a true web-content management system (with a run-time for dynamically targeting and optimizing content) and some form of digital asset management.

The acquisition of Day Software is a significant step toward realization of this vision for Adobe.  Day’s products provide web content management and asset management, and they have a run-time on which they’ve built content targeting.  With that runtime already in place, it should be fairly easy to integrate more robust, data-driven targeting from Omniture.   And, Day has been noted for their back-end savvy and integration prowess.  I suspect that Day’s engineering team will have a lot to do with the products that result from this union, which is good, because while Omniture was great at strategy and execution, things could be a bit clunky on the product side.

Adobe has other assets that will probably be a part of this vision, too.  Namely, Scene7, a provider of product visualization solutions.

Ultimately, this means that web data is taking another step out of the Web Analytics Department.  As the unified web marketing / management platform begins to take hold, data collection will be automated (the run-time engine will generate tags dynamically at run-time – or simply bypass tagging and send data directly to the data-collection systems) and data analysis will be automated (personalization and optimization will be based on calculations and analyses done by the products themselves).   As this happens, the role of the web analyst will be less and less about tactical optimization of content and marketing programs, and more about analyzing customer patterns to find new insights to drive marketing strategy.  Essentially, the web analyst and the customer marketing analyst roles will begin to merge.   If the role of web data analyst exists, it’ll probably be a specialty in the customer marketing group.

Of course, this vision of things is a long way out from being the norm.  But I think we’re on that trajectory.  And, smaller companies may never run things this way (unless Google decides to offer a unified web management platform – which isn’t too far fetched).  In the mean time, smart web analysts will continue to have to straddle the fence between tactical optimization, and true, customer insight work.

Your job as a marketer or site operator, is to optimize the efficiency at which your machine is working.  You want it to produce more value for less cost.  To manage the efficiency of this machine, you need to understand two things very clearly: how does your site contribute value to your business; and what are the visitor behaviors that lead to that value.

If you don’t have clear understanding of those two things, or buy-in from all of your stakeholders on those two things, no web measurement tool in the world can help you.   When you do gain a clear understanding of those two things, and when you become comfortable with them — when they are second nature — it will be easy to figure out what you should be measuring to help you manage and tweak your machine.  When you know what you need to measure to manage and tweak your machine, web analytics tools will cease to seem overwhelming and daunting.   You’ll know just what you need them to do, and, conversely, you’ll know what features of your tools you can ignore as simply more noise.

SearchFest is happening on March 9th, at the Governor Hotel in Portland.  I’ve you haven’t registered yet, go register now!  And don’t forget to use my discount code (save $30!): SPKR-SEMPDXSF1020. While you’re there, you can check out Todd Mintz’s mini-interview of me on a/b testing.

Hope to see you there!  As usual, see my Plancast stream to see where else you can find me.

Chase Reeves, Director of Marketing at Iterasi
Chase presented Iterasi’s PositivePress application, which allows PR pros to track “earned media” online, and has the benefit of archiving your mentions in its system, so you can always go back and see it.

Margaret Francis, VP of Product at Scout Labs
Margaret presented Scout Labs‘ social monitoring, reporting and workflow management application, highlighting their powerful tools for generating abstractions of the data quickly and easily, allowing strategic planners to easily understand the prevailing mood around a brand, and act accordingly.

Justin Kistner, Sr. Manager of Social Media Marketing at Webtrends
Justin presented Webtrends’ integration with Radian6, showing how social can be measured as a part of the traditional marketing funnel, and that social marketing can be optimized for conversion (not just traffic), like any other marketing tactic.  Justin also demonstrated Webtrends’ upcoming release of Facebook page and app measurement.

Thanks to the Social Media Club of Portland for organizing the event and inviting me to moderate.  I’d love to do this again!

I’m looking forward to what should be a very lively, impassioned discussion.  More information is available at the SMCPDX website.  Register for the event on Upcoming.

Don’t forget to check my Plancast stream to see where else you can find me.

If you want to register, hurry.  Registration closes in two days (2/12).  To find me at other events, subscribe to my Plancast feed.

On the upcoming panel, I’ll be talking about how you can better track search results in Google’s Universal Search results page, allowing you to understand not only what search terms drive traffic to your site and/or or value for your business, but which type of result (blog, image, etc.) is working best for you so you can optimize for the specific words and result types that best benefit your business.

Join me and the other panelists from PSU’s Digital Marketing Strategies certificate program for a lively and informative discussion about Google Universal Search.

Update:

If you were at the panel discussion and didn’t get a chance to jot down the blog posts I mentioned here they are…

This post, by Martijn Beijk at SearchCowboys.com explains how to set up Google Analytics to track which type of search result was clicked on the Google search engine results page.

This post, by Mike Belasco at seOverflow explains how to set up Google Analytics to track clicks on local search results on the Google search engine results page.

Goals are pretty simple, and need to be stated in simple terms.  Sure, there’s lots of complexity underneath the goals, but don’t worry about the complexity until you understand the goals in a simply stated form.  Goals are measurable things you want people to do, like buy!, join!, volunteer!, donate!  If these are your organizational goals, then they should also be reflected and enabled or furthered somehow on the site.  (If they’re not, don’t bother measuring  – go fix your site first.)

What doesn’t seem to have sunk in yet is that measurement should also be goal directed.  When you look at your analytics data, the first thing you should be looking at is your performance against the goals you have.  Don’t look at visits, or pageviews or traffic sources.  That data is contextual, but it doesn’t help you understand how the website is contributing to the goals of the organization, and it certainly won’t help your higher-ups understand the value of your contribution to the operational goals of the organization.

Of course, the analytics vendors don’t make a goal-oriented approach to measurement easy.  When you login to most analytics packages, you’re showered with overview data about things that have nothing to do with your goals and with navigation to ever deeper and deeper reports.  It’s an interface only a web analyst could love.  Therein lies the problem.  The people running the web channel are business managers, not web analysts.  If they’re not web analysts, why should they understand web data you ask?  Well, they understand balance sheets and P/L statements, yet they’re not accountants.  The reason they understand these accounting statements is because they’re organized and standardized around a key business goal – money.

Analytics reports for everyone who isn’t a web analyst (that is to say, most people) should be the same.  They should be organized to show, first and foremost, performance against goals.  And, they probably shouldn’t be in the analytics package at all.  Leave that to the analysts, and surface performance against goals, and key contextual data, for the managers to see in a format they can use.  Excel is a good option.  But with the proliferation of APIs in analytics packages, it’s becoming easier and easier to pull that data into other applications, including web-based dashboards and scorecards, which can be made widely available in the organization while keeping most people out of the weeds in the analytics package.

Now, go forth and make it happen.  Get your people out of the weeds and focused on the goals.  Eyes on the prize.

If finally dawned on me, though, that this deal isn’t about advancing how analytics is used in the enterprise.  Much more simply, it’s a business development dream come true.  For Omniture, it is simply about gaining access to more page views.  The more Adobe assets that can be tagged automatically upon creation (or delivery), the more revenue can be generated through the Omniture business.

Adobe benefits from this too, as any incremental revenue to Omniture benefits Adobe overall.  But, for Adobe, the deal is not about owning an analytics solution provider.  It’s about being able to provide performance measurement data at the asset level.  Its not about getting data into Omniture, but rather, using the Omniture infrastructure to provide performance data in whatever applications Adobe wants to.

The synergies, upon thinking about it this way, are stunning.  And its easy to imagine adobe developing new applications or solutions based on this newly acquired analytical capability.  With some work and maybe another acquisition, I wouldn’t be surprised to see Adobe become a serious contender in CMS with an offering that married asset (content, images, applications) creation, storage, delivery with a runtime that does targeting and testing, and with data available from the perspective of each of these tools processed and provided back to the system by Omniture.  This deal is more about adding value to Adobe’s existing assets and creating something new than it is about bringing something new to Omniture customers or advancing how “web analytics” are used in the enterprise.

I also would not be surprised to see Adobe get into the ad serving game, taking advantage of the move toward social apps in advertising.  Adobe Air is positioned here for app development, and Scene7 as well as other products have serving capability.  Leveraging the data infrastructure of Omniture could provide for built in measurement, without needing an Omniture account directly.

One of the big criticisms of Omniture (and other web analytics vendors) has been that they’re headed headlong into competing directly with Google Analytics.  The underlying assumption of that criticism has been that Omniture somehow didn’t get that.  I think Omniture understands that at its core.  This deal reflects Omniture’s understanding that Google will completely commoditize the stand-alone web analytics solution market, and that the future of any current stand-alone analytics solution is to become embedded in other solutions.

We as an industry have been trying to understand this deal based on our own navel gazing about the importance of web analytics to the enterprise, making projections about how the vendors’ products would have to evolve for our daydreams to come true.   We forgot that just because analytics has growing strategic importance to the enterprise doesn’t mean that the products we know today are what will ultimately provide the data and insight needed by the enterprise.

We all forgot to put on our strategic business development hat and so missed the the real factors that drive a deal like this…the need to make more money.  Analytics, at least from a market perspective, is not an academic pursuit. It’s a commercial pursuit, and the industry will move in the direction that leads to greater commercial success for the participants. With this deal, Omniture is leaving the “analytics as a standalone product” market behind while they still can.  What they have triggered is a new era of processed and enriched data embedded where it is needed, and Omniture (or what was Omniture) is powering that new era.

Similar deals for the other vendors are inevitable.  They cannot continue to function independently indefinitely with Google at their heels.  The challenge for them will be to figure out what their core value is, and start looking for deals where that core value can be leveraged as an asset embedded in a larger solution.

Many companies have invested hundreds of thousands of dollars in web analytics tools and talent, and still find themselves frustrated by a lack of demonstrable value — a lack of real, calculable return on that investment.

It’s not a good situation to be in.  It’s bad personally for the managers and executives who have overseen the investment.  It’s bad for the vendors who take the blame for providing no value.  And it’s bad for the business which, unless corrective action is taken, will continue to throw good money after bad.

What to Do?

Typically, the response to this situation is to blame the vendor and put out an RFP.  It’s a natural response.  But is it the right response?  Most of the time, it isn’t.  The problems preventing you from getting value with your current vendor likely stem from unclear roles and responsibilities in the organization, a lack of defined and well-understood processes, and out-of-date or missing business rules for data collection and reporting.

These problems will still exist if you simply go to RFP, and will cause you not to get value from a new vendor.  Even if one of your problems is a poor implementation or a poor fit of vendor to business requirements, invariably issues of process, roles and responsibilities, and business rules (governance, essentially) lie at the heart of how you get to the point where your implementation fails to suit your need.

What, then, is the right response?  When a business is underperforming, do the owners demand that you rip out your accounting technology and replace it?  No.  They usually initiate a turnaround process — a process that involves bringing in experts to assess the current situation and develop a plan to get the operation back on track and providing value to the owners.

Turn it Around

That’s also the appropriate response to an underperforming web analytics investment — a web analytics turnaround.  And that’s why Greater Returns is now offering Web Analytics Turnaround as a service offering.  It makes much more sense to evaluate your overall strengths and weaknesses with web analytics before deciding on a course of action.  Are your problems with process?  People? The technology?  If your problems are the technology, is it a shortcoming of the technology or a shortcoming of your process for governing management of that technology?

Once you understand where your true problems with web analytics lie it becomes easy to develop a prioritized plan for turning around your web analytics operation.  You may well decide that you need to rip out your vendor and start over — but you should never take that course of action based merely on an assumption.  You’ll likely find yourself in the same place 12 months from now.

Check out the Web Analytics Turnaround offering here.

In my experience, friction is often introduced by the very features that were intended to reduce friction and drive conversion and revenue performance improvements.  The result?  As friction goes up, return on investment tanks, and so, too, does revenue.  That’s why, to maximize success, it’s critical to isolate and understand the bottom-line impact of any new site feature and to eliminate (or modify and retest) any features that drag down performance of the site.

Here are 5 things you can do to reduce friction on your site.

Allow Guest Checkout

It’s easy to allow people to check out as guest, without requiring them to create an account. Sometimes people are positive that they’ll never come back to the site, and don’t want to bother.  Wouldn’t you rather have their money than not have it because creating an account adds too much friction?  You can always offer to “save” their “info” for future orders at the end of the process.  If they take you up on it, you both win.  The customer got their friction-free checkout process, and you still got a registered customer.

Allow authentication with 3rd Party Authentication Providers

With the increasing popularity of 3rd party authentication systems such as oAuth and OpenID (which allow you to log-in to a site with your Facebook, Twitter, Google, or any number of other site IDs)  inability to use these credentials to authenticate on your site will increasingly be perceived as friction — you standing in the way of how consumers want to be able to interact with you.  There are other good reasons to adopt 3rd party login, too.  Principally, the data that becomes available to you from most 3rd party credentialing services about registrants is more robust than you’d get from consumers by having them register directly with you.  While it can be complicated to implement more than one 3rd party authentication protocol, companies like JanRain make it easy to authenticate with and consume data from multiple authentication providers with a single API that abstracts the functions from multiple providers and normalizes the data that comes back into a unified format.

Offer only highly relevant up- and cross-sells

It’s important to have a considered strategy around cross-sells and up-sells.  There are many product recommendation companies who can provide the technology for you, but only you can drive the strategy and decisions around where on the site products should be recommended, and what the goal is for each location on the site.  Be explicit with your goals, because without explicit goals you can’t measure the performance of the recommendations against goals.  On a product page, your goal for up-sells should be something like “move shoppers to higher margin items without negatively impacting overall revenue or conversion rate.”  Since your strategy is to drive up margin and revenue, don’t suggest products at a lower margin.  It’ll be bad for your business, and will add unnecessary cognitive weight to the buying process.

Even if you only offer products that make sense from a business standpoint, the potential for friction is still there.  If you offer too many choices, you may end up simply killing the sale by introducing cognitive drag.  If the customer can’t make up their mind because there are too many choices, you both lose. The added cognitive weight of additional suggested items, which take attention away from completing a purchase, is likely to cause some people to bail on the sale.  The product you’re suggesting has to make up for that either by converting at a higher than average rate, by having a significantly higher margin, or both.

Sometimes it may be better to suggest nothing at all.  Testing well will tell.

Eliminate or mask complex cart editing and other unnecessary features during checkout

It’s tempting to offer complete item editing functionality in the cart, and through the checkout process.  It is often wise to check this temptation, however.  How often am I really likely going to change size or color in the cart?  Does the need to completely change an order happen often enough to overcome the cognitive drag — the friction — introduced by the presence of the capability?  Changing quantity makes sense in most contexts, but simple testing will reveal the true impact of more complex functionality on conversion performance.

If you must retain the ability to edit all properties of an item in the cart, mask them behind a well placed “edit” link or button so most people don’t have to deal with them.

Deploy no new features that add drag

As noted at the beginning of the post, friction produces drag on conversion rate and revenue.  As such, there’s an easy test for friction, and you should be employing it rigorously.  Every major change or new feature on the site should be tested for added drag.  Features or changes that add drag should be yanked from the site, and either tossed in the trash bin or re-thought out and re-tested.  Under no circumstances should you leave a feature on the site that adds even the slightest drag.  There isn’t an argument in the world that should persuade you to leave it.

Your friction test is a simple A/B split test, with equal percentages of your visitors getting A (the site as it is now) and B (the site with your new feature).  If B (the new feature) drives higher conversion and revenue than A, the deploy the feature globally.  If not, kill the feature and move on.

You don’t need any fancy multivariate testing tool to run this test.  You simply need a web analytics package with the ability to pass either a custom parameter for segment reporting, or the ability create a segment based on a non-custom parameter.  Most of the work is done with JavaScript and cookies (identifying who is A, who is B, who is not participating in either group, and setting the appropriate parameter).  The segment parameter allows you do do the reporting in your web analytics tool.  I’ve done this in both Webtrends and Coremetrics, and I know it’s possible in the other major tools.

Of course, there are many other things you could be doing to reduce eCommerce friction, but this should keep you busy for a while.  And if you start to think that you’ve reduced all the friction possible, you can always go back and start retesting some of your site features for friction.  Friction is a fluid concept related to consumer expectations, wants and paradigms which themselves are dynamic and change over time, sometimes very rapidly.