One of the great things about working in the SEO business is that there are lots of very smart people thinking about new ways to measure how well a site is performing. At the Search Engine Strategies conference in London this week, I was able to take a bit of time out from showing Analytics SEO to all the attendees, and catch a couple of great presentations about new ways to use web analytics.
One new metric caught my eye in particular. Brian Clifton (@brianclifton, author of “Advanced Web Metrics with Google Analytics” – essential reading if you want to get the most out of your Google Analytics data) talked about how to measure brand engagement. This is basically a measure of the proportion of your site visitors who found your site because of your brand, and is calculated as
Measuring this in Google Analytics is a little tricky. First, you have to create a regular expression filter to find all the keywords which brought traffic to your site based on brand keywords, which is easy enough if you have one easily-identifiable brand, but can rapidly get rather painful. You then have to manually look up the total visits, and those from direct traffic, and plug them all into the formula.
As Brian described this process, I realised that we already have all this information in Analytics SEO (you have set up your brand keyword filters using the task on your Objectives tab, haven’t you?), and we can give you that number without you having to do any further work.
So, it’s been done. You can now see Brand Engagement as one of the key site metrics displayed on your site’s Measure tab, and see how it has changed since your campaign started. You can also use this as one of your campaign KPIs, and we’ll track your progress towards achieving that objective throughout your campaign. For example, a large, well-known brand may set a KPI to increase their brand engagement, while smaller less well-known brands may actually want to decrease their brand engagement, as this would roughly correspond to an increase in their traffic from more generic search terms, which are likely to have much greater search volumes.
By: Mark Bennett