Category Archives: site metrics

Advanced Segments in Google Analytics…Advanced turns out to be a Relative Term

Some caveats if you are contemplating using the free Google Analytics tool (and free advice to the product manager). Before bringing you down, there are some positives of this tool and feature:


  • It’s FREE.
  • Better than filters which are not retroactive.

Minuses (in no particular order):

  • Buried deep in the tool, several tedious clicks to get to them
  • No way to suppress GA’s canned segments
  • No way to export or import segments or filters (get a piece of paper and pen out)
  • Cumbersome drag and drop interface; it feels like a toy
  • Limit of 20 criteria per segment (are you kidding?)
  • Inability to join or combine segments themselves using Boolean operators
  • Segments are tied to you, the user and your GA account; in practice this means that all of your segments follow you across site profiles (no way to manage them) but not across GA accounts.
  • No way to categorize the segments you have
  • Cannot be used with Absolute Unique Visitors (why is this?)
  • Of course it is subject to the limitations that all JS-based site metrics tools have, i.e. ignores all of these accesses. See my other post on the subject.

This post is subject to update…afterall Google Analytics is still in Beta!


RSS Advertising Part I – Cat & Mouse

Why RSS Advertising?
So, it has been decided that you want to target that hard-to-reach segment. The one that hates advertising and doesn’t click anyway. RSS advertising with in-feed ad networks like Pheedo show great promise at reaching these folks; more interesting is that they seem to be getting them to respond at significantly higher rates. Measurement on the other hand is still a bit dicey.

First a quick marketer-friendly primer on RSS. Typically, RSS feeds are accessed or consumed with either a dedicated standalone reader application or through a standard Web-browser accessible service like Google Reader; dedicated reader applications can be used on both desktop/laptop computers and when reading feeds while mobile. Using a special version of XML, RSS (Really Simple Syndication) is published and syndicated out to subscribers that opt-in to receive your regularly updated content.

They’re Just Not that Into You
RSS has taken off and in a sense has enabled publishers to cannibalize themselves by allowing access to their content in a largely ad-free environment. Almost all major media now have at least one feed and many have multiple feeds – some even personalizable. Being able to avoiding ad-cluttered Web sites is part of the RSS appeal: think 100% signal with 0% noise. Clearly,

many are very comfortable receiving information this way.

At the same time, media companies are clamoring to sell advertising against this new platform and online markters are eager to reach these consumers. Anecdotally, the RSS audience constitutes a very desireable market segment: influential, tech-savvy, affluent and naturally early-adopters. From a behavioral standpoint, these folks are known to be much less responsive to display advertising (wrong target audience, see Natural Born Clickers by ComScore). In addition, they are more likely to actively delete cookies, opt-out of email/ad targeting and employ ad blockers to avoid advertising. With these very media-literate people – it is a game of cat and mouse.
With so much going for RSS Advertising and promising results – the challenge then is, how to definitively measure success.
To Be Continued…
RSS Advertising Part II – The Measurement Crater

Comparing Visits & Clicks…

In this business, we often get distracted by technologies on the way to the business ends they are supposed to help achieve. The purpose of this post is to outline a basic process that should shed some light on the very thorny issues involved when comparing numbers derived from agency-side ad servers like DART aka DFA and client-side site metrics tools like Omniture.

Complicating matters is a situation whereby landing page tracking by the ad server cannot be implemented. What to do?
  1. Determine the Purpose. If the marketing objective is performance-oriented, or post-click engagement is essential then you are on the right track. However, if your campaign is focused on a branding objective, how important is it really to get numbers to match?
  2. Choose your Measures. Which measures make sense? Stefane Hamel provides a good backgrounder on Instances vs. Visits. If you are in the paid display advertising/non-search business then most likely clicks and visits are closest; unique clicks and visits/visitors even better. If you are working with search, instances may make more sense…view-through offers even more insight on post-click engagement.
  3. Leverage Standards. The Internet Advertising Bureau (IAB) & Web Analytics Association (WAA) are probably the most relevant industry groups that are working on measurement standards; terms and definitions vary.
  4. Manage Expectations. The reality is that numbers from different systems are unlikely to match; there are a variety of reasons but to make a long story short, they won’t match without serious integration and that has not yet happened. However, the recent announcement of a multi-faceted strategic alliance between agency holding group WPP & Omniture is very promising.
  5. Baseline. Given #1, the best alternative to is to create a simple baseline, e.g. an average over a safe period of time, e.g. a week or a month.
  6. Drop-off/Match. Breathe deep – acknowledge the causes are most likely latency, clickthrough URL parameter coding, landing page tag placement, application filters and counting methods that may never be in sync.
  7. Test & Debug. Understand that campaign trafficking and set-up processes are rife with glitches…clients, creative shops, media agencies and publishers rarely have the staff, or luxury of training to make all of this work flawlessly all of the time. One could spend significant quality time on process engineering these tasks.
Seems simple enough, right? Easier said than done!