Web Analytics Rock Stars

Leave a comment I’m currently working on a campaign that combines a variety of Social Media platforms (Twitter, Facebook, YouTube, Flickr) as well as a microsite.  As you might imagine or may have experienced yourself, gathering all of useful metrics from these sources are like hearding cats.

Here are a few tips that might help in measuring your cross-platform campaigns:

Tag Everything!
If you’re posting links to Twitter via a URL shortening service (my favorite is tr.im since it’s the shortest) embed a tracking parameter with the original URL.  For example, if you’re going to shorten www.somewebsitewithalongurl.com, add a parameter to the end to identify what source it came from and then shorten the URL.  That way, the source can be pulled from the parameter rather than having to rely on sometimes unreliable referrer reports.

Even if you’re not Tweeting, this is a good way to link from blogs, Facebook, forums, etc.

Track Your Videos
On my current campaign, we initially rolled out videos that were around two minutes long.  By adding video tracking (using Omniture’s new media tracking capabilities), we were able to determine that people are willing to watch around one minute.  Shorter videos made for better watched videos which also greatly increased the willingness of viewers to watch more videos and forward links to our videos.

YouTube and Facebook also provide metrics around audience engagement and demographics.  Be sure to use these and not just the number of views.

Followers, Friends and Fans
At the beginning of the campaign, be sure to baseline the number of Twitter followers, Facebook/MySpace (there, I said it in case you were wondering) Friends, and Facebook fanpage fans.  Assuming you’re actively promoting through these platforms, you’ll be able to trend your growth through the duration of the campaign.

Many out there seem to believe that these numbers are the most important things to track… not so!  Monitoring the conversation, retweets, and context is extremely important.  While this may be tough without some advanced analytics tools, it is definitely do-able with a little hardwork.  In my opinion, it’s key to watch who is the most communicative (positive and negative), who passes on your message (retweets, posts…) so you can identify brand fans/ambassadors, and what content draws the most reaction and interaction.

Read Referrer Reports
Even if their reliability may not be 100%, most referrer reports do a pretty good job at telling you where site traffic is coming from.  It’s useful to figure out not just which sites, but what type of sites are promoting your campaign.  An often overlooked piece of information contained in these reports are for webmail.  Considering the reported clients as a sample, you can deduce from the report how often you campaign was forwarded around by people viewing it.

Hopefully these quick tips help out in your campaigns.  As always, I welcome any further questions, comments or feedback.

Tags: campaign measurement, facebook, myspace, social, twitter, viral, youtube
Posted in: Online Analytics, Online Marketing by Greg Asman
No Comments »

Vendors can be a great training ground for new entrants in the field. They offer a variety of positions, locations, and technologies that make for a good jumping-off point. If you are looking to break into the field or to move up in the field, my first advice would be to read Judah’s post about how to get that analytics job by immersing yourself in the community (Judah’s Post ). His post is filled with great tips to use to build your network. Next, consider working for a vendor as a great place to start a career in analytics or to take it to the next level.

When I say vendor, I don’t mean just an analytics vendor, as there are really only a handful of pure analytics vendors, and they aren’t all going gangbusters right now. But, if you think of the entire ecosystem, there are tons of vendors in the space. I’m talking about mobile analytics, testing and targeting platforms, voice of the customer vendors, email vendors, etc. Go look at the sponsor list of eMetrics or Web Analytics Wednesday and you’ll get the idea.

Here are a few reasons why I think vendors are a great place to get your start (and I’m talking from experience here).

1. Sizeable staff - They have large teams of professional services, account management, and support folks who do some form of analytics all day every day. Companies such as WebTrends or ComScore have technical consultants, data analysts, strategists, account managers, tech support, trainers, and sales engineers who are all responsible for helping the customer base learn the tool, use the tool, and be successful. This means there are often job opportunities at vendors, even when in-house analytics staff at non-vendors aren’t growing.
2. On the job training - Vendors will teach you what you need to know to be successful. The experience won’t always be fun or pretty, but you can bet that by the time you’ve worked with a few customers, you will know A LOT about that product, analytics, data collection, tags, and everything else you need to know. Some vendors do this methodically with a rigorous onboarding process. Some do it by throwing you into the deep end. Either way, if you make it out the other side, you are now an expert! Vendors will often provide opportunities to participate in industry events (such as eMetrics) and will often pay for you to go (especially if you spend time at the exhibit booth).
3. Integration points - Most vendors claim or actually do integrate with other vendors in the space. The email marketing solution should be able to pass data or accept data from the analytics solution, the content management system should be able to publish tags, the testing solution should be passing test data to the analytics solution. Sometimes these integrations are klugey and sometimes they are easy. But either way, by helping out with an integration for a few customers, you’ve just learned a bit about some other part of the industry. Cha ching.
4. Big names - All vendors thrive on growing their referenceable and recognizable account names. You too can grow and thrive on that as well. If you get to help large companies measure mobile or realize ROI, you’ve got a great story to tell. Those customer names can go on your resume and can also help you build your network.
5. Industry connections - The product manager, the marketing manager, the CEO, and the VPs at these vendors are industry thought leaders. They are networking at industry events, they are leading panels, and they are writing white papers. In your time with the vendor, you will rub shoulders with some big names in the space. Get to know these people and learn what you can while you are there, and keep in touch with them when you or they move on.
6. Work from anywhere - Most vendors’ professional services teams are global, which means you don’t have to live in Utah to work for Omniture. This means, for the right job, you can work on a remote team and work in your bathrobe when you aren’t on the road.
7. Subject matter expert - Vendors are always looking for a competitive edge either with the product or their people. If you come into the team with an expertise, say in Search, Marketing, Javascripting, or what-have-you, you can quickly build a reputation as well as a niche. If you come into the role green, you can build an expertise on the job by the customers you take on, the projects you volunteer for or the late-night studying you do on your own.
8. Peek under the hood - Being able to see how the product (and company) actually work is invaluable. Knowing how the products really work, what they do well (and not so well) helps you design and deliver better solutions - as a vendor, agency consultant, or in-house client analyst.
9. Vendors pay more - According to Eric Peterson’s Web Analytics Salaries 2007 report, web analytics vendors pay the highest salaries. He gives some reasons and numbers to back it up.

So there’s the good news. But it isn’t all sweetness and light. There are definite caveats to everything I just said above. Here are some of the things to keep in mind when you are evaluating a job with a vendor:

1. Burn and churn - Some vendors hire staff and bury them with work or travel or utilization targets and spit them out. Try to figure out their turnover rate and also meet with who has been with the team the longest. You don’t want to work for a team that is a revolving door, because you’ll be picking up the slack and the people that came before definitely were onto something.
2. Road warriors - Consultants at most vendors (and agencies) are required to travel to customer sites to do the job. Know before you sign how much travel is expected (and add 20% to whatever the recruiter tells you) and make sure your personal life supports that amount (or a little more).
3. Financial Health - Obviously times are tough and there are many vendors who are laying people off as I write this. You need to make sure you get a handle on the vendor and their financial footing before you join the team.
4. The product and services - Not all products are created equal. Do not work for a product that you do not believe in or for a team/company that has a bad reputation. Don’t believe everything you read about the vendors, but certainly do your due diligence. Go to analytics events (WAW, etc.), check the message boards (http://tech.groups.yahoo.com/group/webanalytics/), and blogs and ask around. Find out the word on the street about the vendor from customers, prospects, analysts, etc.

Times are tough and certainly anyone with an open position will be looking for the right fit. That’s where Judah’s post is critical - build your network, your resume, and your skill set as much as possible where ever you are right now. There are opportunities out there. At the time of this posting, I see 4 analytics positions with Omniture, 3 with WideMile, 5+ with ComScore, 2+ with Interwoven, SiteSpect is hiring (where I used to work) as is WebTrends (where I currently work)…you get the idea. If you want to make a leap into analytics, I’d say a vendor is a good bet.

Tags: Analytics Career, analytics vendor, career advice, carerr, ComScore, eMetrics, Interwoven, networking, omniture, SiteSpect, Web Analytics Wednesday, webtrends, WideMile
Posted in: Online Analytics by Elizabeth Robillard
No Comments »

In my role at Intuit colleagues are always asking me what a “good” conversion rate is, what the “average” is, or what ours “should be. If you want people to take action on your data insights, you have to put it within the right context, and the fact is that many business folks don’t have the right context for their conversion rate. Recently I caught wind that some articles were floating around my company and they were shedding doubt on the old maxim that the average conversion rates for websites are in the 2-3% range. I decided to dig a bit deeper and share my point-of-view on this topic.

Because both articles present the question of average conversion rates as a “debate” but also list out sites with conversion rates in the 10-15% range, the casual reader may be tempted to come to some spurious conclusions. So let’s be clear: conversion rates ARE in the 2-3% range.

Here is the article in ClickZ by the well-respected Bryan Eisenberg. Bryan’s article is basically a response to a post by “Dr. Pete”. Dr. Pete asserts that 2-3% rate is a “myth” and that the data sources for this factoid are mysterious and therefore untrustworthy as a benchmark. He sets out a conjecture that when you factor in rates for sites that aren’t even savvy enough to measure the rate, it may be much lower than 2-3%.

Bryan goes the other way, saying that whatever they are, conversion rates should be much higher than 2-3% because most sites waste money bringing in unqualified traffic. His logic: sharpening your target audience lowers your overall traffic, but raises the conversion rate. And while that math is unassailable, I would heavily caution Executives from using it to drive business strategy.

Are the Data Sources Mysterious?
Dr. Pete says tracking down the source of the 2-3% figure is like “Bigfoot”. Bryan admits the sources are published and clearly out there. And it’s not just once source that has data around the 2-3% — it’s many, and year after year. Shop.org is one as he mentions, and I’d add InternetRetailer to the list. They have company-by-company estimate.

In addition there is FireClick and Coremetrics — which are very close to one another on conversion (pulled from individual reports, conversion rate was 2.7% and 3.1% respectively). And indeed they are calculated precisely the way many sites measure conversion — both are “orders/sessions” . These are not “estimates” but rather aggregated from real-time clickstream systems from paying clients. Dr. Pete conjectures that Google won’t publish their data, but in fact they do — inside GA you can get benchmarks as well.
From all this, we are to conclude that the data sources are real, verifiable, and triangulate around the same number. Of course if you were to include every site, no matter how small or amateur, conversion rates may be lower. But there seems little use in this as a benchmark for any serious company of any size.

How High Is “Up”?
OK, so the average is indeed 2-3%. But what are we to make of the list Bryan presents of websites with conversion rates above 10%? Should this be the “gold standard”? Does this represent “world-class”? Is anything lower than this a reason for concern?

Every statistic has a distribution of values, and though the mean score is in the 2-3% range, there are outliers on the right tail of the distribution. This is indeed that list of outliers. So, what can we learn from it?

Well let’s take a closer look at the list.

Do you see anything unusual? How about the fact that three of the 10 top sites are online florists?

Do flower sales make up anywhere close to 30% of all ecommerce sales? Of course not. Nowhere close.

So what’s more likely… By random chance these three companies all happen to have hired the most brilliant online marketers and each independently figured out the secrets to website experience design? Or is it simply that consumers of flower arrangements are very motivated buyers, only shopping at time-limited events. They don’t simply browse flowers “to find out what’s new in the floral world”.

Thus we have a much smaller conversion denominator and therefore a higher conversion rate.

Also, shoppers may do less comparison shopping because the bouquets are often fulfilled by the same local florists in the end anyway for a product the consumer himself does not use.

Last point on flower sites, they have the PERFECT setup for email marketing. They know EXACTLY when you need flower for national events (e..g, Valentine’s Day, Secretaries Day) and once you buy flowers once for your wife’s birthday, they know your personal events as well!

It’s brilliant really: they know what you’re buying of course, but because you select an occasion, select a card, and fill it out, they know exactly what you’re buying it FOR (which is what a lot of ecommerce sites are missing). And lucky them, it re-occurs same date every year.

Then they can send out highly TARGETED and most importantly highly TIMELY email messages. That’s why their upstream traffic has a higher concentration of email services than almost any other site you’ll find. Here’s the upstream traffic for one the flower sites listed above.

Who else is on the list?

Tickets.com is an exclusive seller of tickets for a given event — largely sporting events. Exclusivity is a pretty cherry deal. They don’t do the marketing of the event, they do the checkout piece. So you’re only on their site when you’ve already decided you want to go that game, and they are happy to take your money.

It’s like a pure shopping cart without all those messy marketing pages. I’m a bit surprised their conversion rate isn’t even higher. Upstream traffic to tickets.com uncovers who are some of the websites that are actually doing the marketing, and “absorbing” all those unconverting visitors.

Next on the list of top sites, you’ve got paper catalog companies and TV shopping networks: QVC, Land’s End, Coldwatercreek.

These are all what I’d call “high-cost, split-distribution” industries. Their higher website conversion rate hides their high overall marketing costs. In sum, few people would buy their products if they didn’t aggressively (and expensively) get in front of people on a very regular basis. The bulk of the “wasted” prospects shows up in another venue — TV or print. Somewhat akin to tickets.com where the “wasted” prospects show up on Boston Red Sox’ website.

What if you had to build and run a TV studio buy up an entire TV network running 24/7 nationwide just to attract visitors to your website or phone lines? What if you had to produce, print, and mail $20 Million worth of 200-page color catalogues every month just to keep your phone and website traffic humming? In both cases it is largely the “other” venue that’s absorbing the unconverted prospects, and the website plays largely a fulfillment role.

As for eBay and Amazon.com — they’re just awesome businesses and I’ll leave out the analysis on why they earned their spot amongst this list. If I had to bet, I’d guess OfficeDepot.com ranks because they are a truly insane (paper) direct marketer (I receive two mailers a month from OfficeDepot) with highly exhaustible products like paper, pens, and toner which must be replaced frequently.

In conclusion, it very much matters what your business model and customer acquisition strategy are before you can answer “how high is up?” for conversion rate. Sometimes a great sounding number in one channel hides a more somber number in another. In other cases there is a strong forcing factor. Always present your metrics in the context of your stated business strategy. You’ll have better success in leading your management away from “shiny objects” (like ProFlowers.com conversion rate) and towards your true growth opportunities.

Feel free to share your thoughts on this topic with me. You can reach me at jared@benchmark-analytics.com. You might also enjoy my report on how to benchmarking your analytics practice which is available at www.benchmark-analytics.com.

Tags: benchmarks, conversion rates, intuit
Posted in: Online Analytics by Jared Waxman
No Comments »

Throughout my career in web analytics I have had the opportunity to work on web projects for some of the largest and most well-known websites in the world, and I’ve been able to do this from many different perspectives, including client-side, vendor-side, and advertising agency-side. While I expected these websites to be immature in some of the more advanced web analytics topics such as behavioral targeting, multivariate testing, and tagging, I didn’t expect for most of them to have problems with ongoing performance reporting and representation of data, which they did. These companies all struggled with most of the aspects related to putting together a dynamic and effective monthly report: extracting accurate data from their measurement tools, data organization and visualization, report formatting (including delivery vehicle), and analysis/insights/recommendations. Most of them were decent with analysis; however, because everything else took so much longer than it should they didn’t have the proper amount of time to spend on analysis, so even that suffered. Fortunately, the solution to this is relatively simple in explanation and not much more complex in execution: data quality, automation, and a consistent, accessible report format - what we call an Integrated Digital Marketing Scorecard.

At this point you’re probably making a decision as to whether or not you should read the rest of this article — I don’t blame you but I’d like to give you a few reasons to continue reading. While this topic has been written about and discussed quite a bit, I feel that it still has yet to sink in because I’m not seeing it take hold in the work that I do. And while I don’t profess to be a true EXPERT at anything (I have been practicing Web Analytics for about 6 years now), I am an intelligent, logical, and creative thinker and like to think that I just get it. And as previously noted, I’ve had the opportunity to do this type of work for lots of different websites from a multitude of perspectives — the most helpful being my time at a very large and well-known digital advertising agency. Most of what comes next are lessons I learned while managing Measurement Operations at that agency.

To formally define the problem, analysts are spending a much larger % of their available time extracting and formatting report data and not enough time on the analysis, insights, and recommendations - where the true utility of the data comes into play as it is converted to decision-making information. In my rough estimation analysts are spending about 75-80% of their time on the tactical reporting work and only about 25% of their time on the real analysis work. In a perfect world this would be reversed - spending just 25% of their time on tactical work and 75% on analysis.

As mentioned, the solution that we have come up with to address these problems is what we call an Integrated Digital Marketing Scorecard (or IDMS). “Integrated” because it is a single report that includes data from multiple data sources, “Digital Marketing” because it contains data from all online marketing and website measurement systems, and “Scorecard” because it is a visual display of key performance indicators on a single screen, providing user-driven comparison and progress metrics and used to make management decisions.

Let’s look at each of the problems individually, as well as how they are addressed with the IDMS…

Extracting accurate data from their measurement tools
At one point not too long ago in my Web Analytics career I was managing the monthly reporting for nearly 15 separate websites, all of which wanted their report as close to the beginning of the month as possible. Each of the sites had their own set of complexities and issues: tagging problems, custom report issues, communication breakdowns with clients, etc. There always seemed to be some issue with some data point each month that meant I could not fully automate my data extracts because I had to scrub the data in some way. This is where Data Quality comes in. At the core of any good, automated reporting solution is high quality data. It can sometimes take a good amount of money and/or resources and certainly process changes to achieve the quality of data needed to support this style of reporting, but from experience I can say that it will pay for itself in time saving and decision making support.

In this role I was so incredibly busy during the first few weeks of the month that I chose to only partially automate my data extractions and pull the remainder of the data manually. I justified this by telling myself that it would actually take longer to automate the query for a data point than to pull it manually. I also failed to consistently document how I would manually derive a certain data point and would need to reconstruct it and compare it to the previous month’s number to make sure I did it correctly. This was incredibly time consuming. This speaks to the second component of the solution, automation. The bottom line is that if the calculation of a data point can be done fully automated, always do it. It will save time and reduce the occurrences of errors compared to pulling the data manually. When we build an IDMS for a client our goal is for there to be as few steps as possible each month to update the data and populate all charts and graphs. In many cases we’re able to get this down to 4 steps: select a new month, click button to run queries, validate new data, click button to update tables/charts/graphs.

Data organization and visualization
Analysts struggle to find the best way to organize, visualize, and present the information in their reports. It is very rare that I’m impressed when an analyst shows me a report they authored that they feel is one of their best pieces of work (by the way, don’t bring an example report to an interview unless it looks like something you would see on TV - you know who you are). It amazes me the lack of attention to detail that is pervasive across the industry. Presentation of the report can, in some cases, determine its success or failure. If you have bad data to report, at least make sure it is presented professionally.

There are a few guidelines we follow when organizing and visualizing the data in an IDMS:

• Organize the data in a tabular or navigational format so that the user can page through different sets of data while remaining on the same screen.
• Group similar data points together into the different tabs and have them follow some type of logical progression (i.e. Acquire-Convert-Retain)
• Show a minimal amount of data on a screen, but allow the viewer to interact with the report to show historical data and compare it against more recent data.
• Only show one or two data points on a graph that are related — don’t overcomplicate it with 3 dimensions and multiple metrics, etc.

Report formatting (including delivery vehicle)
It can take a very long time to manually update all of the charts and graphs and screenshots necessary for a given report, we get around this by extending the automation to include updating the charts and graphs in the IDMS, not just run the queries. Most people don’t fully understand the formatting capabilities of Excel but there are a lot of fancy things that can be done with formatting and interactivity - especially in Excel 2007. Have you ever heard of the camera function? If not, Google it and I’m sure you’ll find a great use for it.

Speaking of Excel 2007, that is our preferred vehicle for delivering monthly reports. It supports the tabular navigation previously discussed, all historical data can be included within the file in hidden sheets, the Scorecard can be made to look like a polished web application, and most importantly, it’s in Excel - something that everyone has access to. Alternatively, tools like Excelcius can be used to build this same type of functionality but publish it as an interactive Flash object embedded within a PDF file. I also love the idea of delivering these via the web, but that would require some web development because as of yet there is still not an available tool that I know of that can WYSIWYG a Scorecard.

There are quite a few other report formatting topics that I could discuss, but to keep this relatively readable I’ll add just one more that truly sets the IDMS apart from other solutions — specific real estate is set aside in the Scorecard for the analysts’ insights, observations, and recommendations. This section updates when the viewer pages through the different tabs in the Scorecard so that it corresponds with the data they are viewing. This is where data is turned into information that can drive decisions - without this analysis a report is not incredibly useful for obvious reasons.

The best way to approach writing the commentary is to first understand the business questions that need to be answered every month. The questions shouldn’t simply be worded versions of KPIs like “How many visitors came to the site this month compared to next month?” — they should be business questions like “Which media tactics drove the highest engagement with product content?” These are the questions that will be answered in the analysis section every month, supported by the KPIs and data in the Scorecard.

So what does this look like when it’s all said and done? Something like this:

If you made it through this article, THANKS FOR READING. I sincerely hope that it was worth the time you spent reading it. If you’d like to chat further about this topic or others, please feel free to reach out to me via email at Jason.Widup@WebTrends.com. My business partner and I recently rejoined WebTrends (yes, we used to work there a few years ago) to start a Digital Marketing Optimization consulting practice where one of our core service offerings will be to design and develop Integrated Digital Marketing Scorecards like those described in this article. Happy Analyzing!

Posted in: Online Analytics by Jason Widup
3 Comments »

(LunaMetrics, a Google Analytics Authorized Consultant, will be doing a Google Analytics Training Day in New York City on Dec. 9)

Recently, Google Analytics announced six new features, some of which really make GA better for the enterprise-level user. Today, I’d really like to look at what kinds of things GA has done to make itself ready for enterprise analytics — and what they still have to do.
We’ve come really far in the area of enterprise-level analytics:

• Google Analytics now has an Applications Programming Interface (API) – a way to access the data and interface with external applications.  It’s in closed beta (we’ve been working with it here at LunaMetrics).  An API is vital to enterprises – organizations that often need to export their data into custom dashboards and other enterprises systems, such as CRMs, bid management tools, web personalization engines, and more.

• Now, there’s an easy new way to do segmentation (called Advanced Segments). For the first time, you can easily create a segment of everyone who came on paid search, or who came from a specific country (or both, or whatever you need) and do segment-specific analysis. Best of all, the segments work retrospectively on your data. In the past, you had to anticipate your needs and create special profiles and filters. When your boss asked, “What was the average order size of individuals who came from our recent email campaign?” you had to have hoped you had anticipated that question a few weeks (or months!) in advance. Now, you can whip up an Advanced Segment and see that information right away.

• Also introduced a couple of weeks ago: Custom reporting. Now, you can make reports very specific to what you need and save them, so that you can use them over and over again (and run the same report requirements over different profiles and even different accounts that have the same login.) Different individuals in an enterprise have the need for narrow, specific reports. It gives each of them just what they want.

• There’s also a new interface for viewing accounts and profiles, so that you can easily compare different sites. This is pretty vital to enterprises, because understanding the profitability and performance of business units is one of the many ways that they measure themselves.

• Google Analytics introduced object-oriented programming when they brought out their new code a year ago (known as ga.js). The new code made it much easier to have multiple sets of code on a single page.  Imagine an enterprise like a university – each department may want to keep their data confidential.  But at the provost or president level, there may be a need to roll up all the data and see how the total site is performing. The “new” (ok, it’s not so new) code makes having two sets of code much easier.

• Event Tracking.  This was a capability that Google Analytics announced a year ago and which is still in limited beta. It enables the site to track not just pages and clicks, but events, such as, “Did they look at a movie? Which movie did they start? How far did they get into the movie?” There are lots of other events that can be tracked, but the movie example is an excellent one, because it gets to the core of how event tracking works.  Here at Luna, we agree that many sites need event tracking (not just enterprises) but that there are some enterprises who cannot live without it.

Still on my wish list for enterprise Google Analytics:

• Multiple user defined variables.  Right now, you can create only one user defined variable (like “member” or “purchaser.”). But an enterprise will want to pick up the fact that the user is female and Dutch and blonde and a member of the organization – they need many user defined variables to help understand their users.  (Like all the items on my wish list, this one has a workaround too, but we need some additional user defined variables “out of the box.”)

• Cross domain tracking needs to be easier. Google Analytics uses first party cookies. That means, as soon as you move from one domain to another, it thinks you are a different person. There are great ways built into GA to track across domains, but they aren’t scalable.  It’s one thing to track from your small site to your third party shopping cart, and something else entirely to track among hundreds of sites. Yes, there are workarounds (and we developed one of them here at LunaMetrics), but again, we need out of the box solutions.

• Unique visitor tracking across multiple domains.  Even once we solve the cross domain tracking problem, we have another. Media sites – like a radio company such as Clear Channel, or a magazine company with multiple magazines — really care about unique visitors (in addition to visits.) So if someone visits one Clear Channel site and then another day, visits a different ClearChannel property without going through the first one that they had already visited on the prior day, that person will be seen as two unique visitors even if the cross-domain tracking is set up. Why? Unless the visitor actual travels from one site to the other, the cookies are never transferred. Again, there are workarounds right now.

• More robust user permissions.  Enterprises need three levels of permissions: read only, admin access limited to parts of the site, and administrative access for the whole account. Right now, GA has the first one (read only) and administrative access for the whole account, but there is no ability to give admin access for only certain profiles.

Having said all that – wow, are we getting there!! Every single problem I pointed out above can be solved with workarounds, and the ones that couldn’t – like an API, and retroactive segmentation – are now being solved by Google Analytics themselves.

Posted in: Uncategorized by Corry Prohens
1 Comment »