June Dershewitz on Web Analytics

Top 10 Things I Wish I Knew When I Started in Web Analytics

Here's a short-but-sweet article I wrote 2 years ago for the Web Analytics Association, in which I reflect on my first job in web analytics - at a dot-com, almost 12 years ago. Ancient stale content, right? Actually it remains pretty timely so I thought I'd repost it:

I remember what it was like to walk through the door at my brand new job, my very first job as a web analyst, wondering what I’d gotten myself into. In retrospect, what did I wind up learning the hard way? What would been helpful to know up front? What should I have been prepared to expect? With that in mind, here are 10 things I wish I knew when I started in web analytics:

1. You will sit between the techies and the marketers. Figuratively, and maybe literally. Make friends on both sides of the fence.
2. You will learn all about your business. Not just the stats part. Not just the web part. The work you do in web analytics will only make sense once you’ve put it in the general context of your business.
3. Ahem, what is this thing you call a "Visit"? Know your standard web metric definitions by heart, and be able to recite them concisely for people who ask. They will ask.
4. Dirty, dirty, dirty. Numbers won't match, they won’t add up, they won’t make sense, sometimes they won’t even exist. Know how much dirt you’re willing to live with, then accept it and move on.
5. You will learn to love the query string. You will come to see it as a beautiful haiku. You will know it backwards and forwards. You will repeatedly explain its usage to people who need to append campaign codes to URLs.
6. CSV stands for "comma-separated value" ... it's a file format, every data analyst's friend, and - inexplicably - it doesn't even have to be comma-separated. Huh.
7. Operators are standing by. Know the support hotline number for your commercial web analytics vendor of choice, and don't be afraid to call. If you have one sticky note on your monitor it should be that number. Actually two sticky notes. The other one should say, “Patience is a Virtue.”
8.  Don’t fall into the “report monkey” trap. Manually-repetitious activities are not a good use of your time, so automate wherever possible. Strive to spend your cycles doing thinking fellers work, and leave robot work to the robots.
9. You are not alone. Right now there are other web analysts sitting at their own desks, somewhere between the techies and the marketers, and they’re facing exactly the same issues that you are. You will meet them at Web Analytics Wednesday.
10. Think long-term. From the very beginning, think about where you want your career to go and make every effort to develop in that direction. Your entry-level position in web analytics can/should/will lead to other things, so know what you're targeting and go for it. 

Photo credit: Ibai Acevedo

Beyond Web Analytics Podcast on Functionalism

In lucky episode #13 of Beyond Web Analytics you'll find a podcast with me on the topic of functionalism. It's a 40-minute recording of my conversation with Adam Greco, Rudi Shumpert and Gary Angel; we cover basic definitions, explore several examples and discuss implementation options.

Adam Greco's very practical post on page type pathing - written long before our podcast - describes a functional analysis technique that any Omniture customer can use.

Also, I have written several blog posts exploring the topic of functionalism; check out the series here.

Flickr Stats vs Other Photo Sharing Analytics

Just after the public launch of Flickr Stats back in 2007, I posted a positive review of the tool, musing that it could serve as a good model for other social media measurement systems.

Fast forward to 2010, I am no longer so content with Flickr Stats. I'm convinced we can do better. Perhaps my attitude is influenced by the recent buzz about how anyone can track stats on their Facebook Fan page using Google Analytics or Webtrends. Or perhaps I've just grown tired of the limitations of Flickr Stats.

Is Photobucket any better, or Picasa, or something else? This post serves as a summary of my quest to find the best photo sharing analytics. Here's what I found.

Flickr: A shortcoming and a workaround

For paying Flickr Pro customers, Flickr Stats currently reports a host of metrics including the number of views over time, favorite/comment activity, top content, referring domains/URLs and search keywords.

The thing I used to like best about Flickr Stats was the all-time referrers report, since it provided insight into my photostream's findability over time. Unfortunately, about a year ago Flickr chose to scale back the referrer stats it reported. Referrer information is now only available by day for the last month. Judging from the volume of support forum comments on this subject, I'm not the only Flickr member who's unhappy with this change.

As a workaround, one Flickr member has created an app called F*Stats that scrapes Flickr Stats and stores historic referrer information in a local database. This seems like a complicated solution, but right now it's the best way for Flickr members to retain their referrer info.

[March 3, 2010, 4pm Pacific. Update: Several hours after I published this blog post, Flickr announced the release of their shiny new Flickr Stats API. Also, members can now download CSV files containing all historic referrer data. Ah, timing.]

Photobucket: Easy social media sharing and pretty good stats

Less than a year ago Photobucket launched a stats dashboard for all members, with limited metrics in the free version and more in the Pro version. In terms of functionality, I'd rank the stats dashboard just below Flickr Stats. It does appear to provide referrer information over time, but it only reports referring domains - not referring URLs or search keywords.

On the positive side, the ability to easily share Photobucket content on Twitter, Facebook and other social media sites - and then get referrer stats - is an excellent feature and may be reason enough to use the service.

Picasa: Perhaps Google Analytics integration on the way?

Activity tracking on Google's Picasa photo sharing site is currently very limited - you simply get the number of views of each photo. However, there's quite a bit of user feedback regarding the desire to track Picasa with Google Analytics. In this wish list of most desired Picasa features, Google Analytics integration is one of the top requests. Come on Google, grant our wish.

Other Alternatives: Again, with GA integration

Although I've covered 3 of the most popular photo sharing sites, there are plenty of others to choose from. A quick search turned up 2 less well-known sites that currently allow Google Analytics tagging: SmugMug and PhotoSwarm.

What do you think? Are there better solutions that I have overlooked? Or, are photo sharing stats not worth anyone's time? I welcome your feedback.