museum web metrics a crash course

This week I’m at the Museums and the Web conference in Philadelphia. I really struggle with jetlag and insomnia, so my brain is already frazzled, so I will be blogging a lot in attempt to make sense of all of the interesting conversations, people, presentations and workshops I am going to.

Day 1: Getting more from Metrics Workshop, lead by Seb Chan from the Powerhouse museum

I am not a fan of numbers. Particularly big numbers with attached graphs.  But I am finding more and more that I am faced with enormously large numbers of web traffic data, and I don’t really know quite what to do with it.  I claim to know the basics of Web analytics, but really it is a tricky beast and the different ways of measuring things confuse me and I don’t know whether the buttons I am pressing and the filters I am creating are actually making it easier, or just more complicated.

I went for the GA workshop because a part of my PhD focuses on metrics.  Quantitative data for my PhD will be gathered using web traffic data to find out levels of use, where users come from and what they access.   I am going to be looking at whether or not quantitative metrics like this are suitable to gain an understanding of user experience.  Quantitative data and log analysis can determine which pages are accessed, but not whether the content was actually read or understood or if a user was satisfied with what they found. I particularly interested if impact relating to museum content can be measured as well as whether users actual end use of digital museum content can be assessed, and whether metrics can help with this.  I went to the workshop to see how far I can take the numbers to into gaining an understanding of visitor use. Google analytics is generating huge amounts of quantitative data about museum visitors, which is great, but really without knowledge of what the numbers mean, they really are pointless.

The workshop was intensive, but brilliant (I think – it’s going to take me a while to take it all in).  I really got the feeling that you need to spend a lot of time working your way through google analytics before you can get to grips with it properly and really start to break things down with segmentation goals, and filters.

One of the key things that came across is that it is about the patterns – don’t obsess on the raw numbers! Month by month you don’t see the patterns clearly.  Quarterly or yearly is much better.

Over the day we looked at loads of stuff and went through a lot of examples of:

  • Site based user metrics – improve user experience, identify potential new user types
  • ISP level metrics – find comparative data, spot macro trends. Patterns of web use beyond your website – allows you to see comparative data – macro trends ( is website traffic growing or shrinking how am I doing on the website as a whole)
  • Social metrics – identify social content and issues, understand users better
  • Qualitative research – understand user needs

Seb always brought it back to key questions to ask yourself when looking at web metrics and creating goals to measure:

o   What are you trying to do?

o   Who are you trying to reach? Be precise

o   How will you know you have been successful?

o   What does success actually look like?

o   What methods best measure this success?

o   Can I find comparative data?

o   What insights are you gaining form your data?

o   Does success equate with visitor satisfaction?

The final question is what I am really interested in does success equate with visitor satisfaction?  And if it does, can you actually measure that?

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