CrossView's "Working Together to Drive Optimization: Google's Universal Analytics & Optimizely" Webinar

Editor's Notes

• #3: Taken piecemeal, today we’re going to talk about Enhanced Ecommerce from Google, and we’ll talk through A/B testing with Optimizely, but the real message today is to connect the dots. Connect the dots between systems, such as between Optmizely and Google Analytics, between teams, analytics and UX, and between strategies. Successful companies are connecting the what (analytics) with the why (UX) and actually making changes on the site. Far too often the analytics team is pulling loads of data, and the UX team is running some qualitative tests, but they don’t work together as often as they should. We are absolutely going to be talking about features and implementation specifics when it comes to EE, as well as how Optmizely functions and feeds valuable data back into Google, but the goal, the focus is showing you the whole strategy of taking all this information, and driving business change. Technical vs creative execution Tools – GA is good at XYZ vs Optmizely is good at PDQ Customer and Agency – good at understanding their goals vs good at understanding how to turn opportunities into results While the analytics piece is focused on Google Analytics, the use cases we’ll walk through of using data to identify an opportunity, hypothesize a reason qhy and then act on it via A/B testing is something that absolutely is applicable to any team, regardless of whether GA was the source of your data or if you used Coremetrics or Omniture.
• #4: Image of a cliff with a bunch of great ideas thrown over into the valley. A/B testing helps us build that bridge to carry great ideas over to
• #6: Enhanced Ecommerce is Exciting, Engaging, (not without Effort) The missing link – other analytics tools had this data out of the box, but we had to hack at it to get something similar. EE completes the view of the visitor experience. Understanding how visitors find and interact with an eCommerce retailers greatest assets Hack view vs new and improved – repurpose the timeline for optimization Value in looking at both high-level (vital checks) vs deep dive
• #7: Looking at metrics more in line with how you view your business – merchandiser’s view.
• #8: Old way – URLs, Events, custom vars/dimensions, vlookups, pivot tables being refreshed New way – preformatted reports Add Custom Event for Prod Views and Prod Add to Cart -> Export data to Excel -> Create calculation on your own
• #10: Can be done via Google Tag Manager or hard coded. Recommend using Google Tag Manager. Anytime you need to invest development resources into Google and you’re NOT already on GTM, you should take this opportunity to do so Prioritize Product View, Add, Buy
• #11: Font: Helvetica 12pt for body copy
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• #13: Details on Customizations such as product finding method, margin
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• #15: Font: Helvetica 12pt for body copy
• #16: Fewer steps = more time for action
• #17: Let’s say EE showed us low add to cart rate for a certain product category. When I’ve collected this data, the questions that come to mind initially are 1) is there information missing from this page that could help someone click the add to cart button and/or 2) is there some usability issue with button placement/color that is confusing the visitor? Efficiency
• #27: Let’s say EE showed us low add to cart rate for a certain product category. When I’ve collected this data, the questions that come to mind initially are 1) is there information missing from this page that could help someone click the add to cart button and/or 2) is there some usability issue with button placement/color that is confusing the visitor?