Conversion Track, Tuesday 10:30 AM – 12:00 noon
Web Analytics & Measuring Success Overview
Matt Bailey started things off with a fantastic presentation. Probably the best I’ve seen so far. He’s very dynamic and engaging…. and funny. I’d hate to follow him. He talked not so much about the need for analytics, but the need for analytics done right. Matt makes it look fun, and I suppose, it can be. I tend to look at analytics as a process of interpretation. And it is, but if you take a different approach and look at it as a process of discovery you’ll find it much more engaging. He makes a great point when he says that analytics starts with a question and then we dive in to discover the answers from the data provided.
You may have read Matt’s post on the Star Trek Red Shirt Theory and he included some of that information in his presentation here, which was very entertaining and really simplified the concept and need for segmentation. Numbers without segmentation are pretty useless. Matt says that numbers need to be put into context and then you need to compare and contrast the different segments to really
interpret discover what your data means.
Lionel Largaespada was a last minute replacement and tells us this is his first presentation in front such a large audience. He did fine giving an overview of what analytics is. His presentation should have come before Matt’s. Lionel echoes some of what Matt said by starting with an objective (question). He also points out that we should not be stuck with stats from only one source. That’s a great point about pulling information from multiple sources in order to really confirm the validity, especially when looking at spikes and anything out of the ordinary. One source may have glitched, using a second or even third will really identify such things for what they are.
Laura Thieme re-iterated the need to use multiple data gathering sources. Not every one provides the same information and you may need various tools to get different levels of data that you need. She says the 3-6 month lag time for rankings is a myth because with blogs, Google can index your content within hours. True, true, but good optimized content doesn’t always shoot to the top of search positions… there are many other factors involved. The lag time is often the process of making the site worthy of top rankings (see my piece on Destination Search Engine Marketing) and not just optimized for top rankings.
She says that blogs can increase page rank and traffic, but bounce rates are higher than before. If you’re obsessed with bounce rates, segment it by keyword. Some keywords (especially from blogs) will show higher bounce rates, while others, that are targeted, shouldn’t. Laura says that ranking reports are back in, you need to know where you’re ranking and who’s ranking next to you. She concluded by saying that analytics themselves don’t give you answers, you need the right tools and the right people to do the job.
From the Q&A Alan Dick said that you’re better off watching five statistics that have meaning to you than 30 stats that don’t. Makes sense. Start with a few questions, figure out how to answer them and keep an eye on it.