To a great many, the following probably rings true…
Web analytics is something you know you need, but when you get it, you’re not sure really what to do with it.
It’s that elephant in the corner…once you get it home, you think “Umm, well, that’s nice…now what!”
The value from web analytics is not measurement. It’s about optimising your business goals, your audience needs, measuring the gap between the two and acting on the results.
But you can’t manage what you don’t measure and if you don’t understand what you’re measuring, you can’t improve.
Improving internal search should be one of your primary goals. It’s probably used by an extraordinary amount of people, searching for all sorts of things. In this post, I show how to capture the number of times people search, a breakdown of keywords and search attempts, and also demonstrate how much search is costing your organisation.
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So, still want to know certain things like what pages were viewed from visitors conducting a search, or which campaigns are driving most page views – and you don’t have Discover. Well, there’s two parts to this post and a bunch of answers…so read on.
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Ever wondered how to show bounce rates by different campaigns, or other segments? Read on, becuase there’s a relatively easy way to do it in SiteCatalyst, which also brings other benefits with it.
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Ok, it’s been way too long since I posted an update, and loads has happened since November. I’ve been to the Omniture Summit in the US, I’ve presented again at the Education Marketing Conference in Sydney and I presented twice at the Omniture Client Briefings in Sydney and Melbourne. That was all in March.
A couple of conversations at the (incredible) Omniture summit sparked an interest and I thought I’d share with you how we implemented. Long pages. Well, pages that go beyond the fold.
Do you know if your users are scrolling down to read the content? Did you know you can get this insight?
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One of the little-used nuggets in SiteCatalyst is “participation”.
It’s a given that you want to know how many sales you’ve made, or how much revenue you’ve generated, but what about which pages have helped to contribute to that conversion. Not every visitor follows the same path through the content, and it’s therefore beneficial to be able to see which pages are more likely to drive a conversion than others, thereby exposing your most valuable pages.
Read the rest of this entry...Albert Einstein once had a picture hanging on his wall at Princeton that read:
“Not everything that can be counted counts, and not everything that counts can be counted.”
He was a smart cookie and often referred to it…and it definitely rings true for web analytics.
Read the rest of this entry...Bit of surprising news, Adobe is buying Omniture for $1.8billion.
Still taking this in and many thoughts running through my mind at the moment. Seen Adobe purchase a few companies in the past and the results have been varied. They are, after all, a product-based company, offering little in the way of services. Omniture on the other hand, is a service-based company. Very different business models, very different thought processes.
Read the rest of this entry...Just presented on how to get value from your analytics platform to around 150 people at the Marketing Higher Education Symposium 2009, at the Sydney Convention Center.
Slides are available on my blog.
Read the rest of this entry...If you’re thinking of trying to compare web analytics results by vendor, or even by the original log file, you’re in a for a very tough time.
Genie + bottle + uncork = Long time, not good time.
The problem is that while there are basically two different methods of data collection (via server logfiles or via JavaScript tags), the variables associated with both, in a real world environment, make it almost impossible to compare results.
And therein lies your genie out of bottle, and you scrabbling around trying to justify the results. You’re best off not even trying.
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In my previous post on People who liked this, also liked…, I put forward an idea how to generate “related” products of interest, based on what users were looking at, which could then be automated and re-published back to a site, based on Omniture data.
Having implemented this, we’ve made an interesting observation, which changes one our user assumptions, and I thought it was worthy of a quick posting.
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