Building Your Personal Brand on LinkedIn - Expert Planet- 2024
Getting the most from Google Analytics by Dave Chaffey
1. Getting the most from Google Analytics Dr Dave Chaffey, CEO Smart Insights March 23 rd 2011 Fusion Marketing Expererience, Brussels Download presentation from: SmartInsights.com
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5. Enhancing key pages have resulted in increases in conversion rate of 20%, 63% and 115%. Source:
10. Content drilldown shows relative page type efficiency Practical tip Review % age of visits by different landing page types (for first time and repeat visitors)
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12. Example Pivot + Filter Practical tip Use New Weighted Sort to gain a similar effect
13. Use GA’s “Intelligence” Read post on setting up Intelligence Tip : Use Custom Alerts in your system
19. ‘ How to’ example of a custom segment Notes: 1. Chose a Dimension of ‘Keyword’ and ‘matches exactly’ , ‘contains’ or RegEx for your brand names 2. No metrics are required. 3. Test the segment first, but you will need to enter a name for the segment to do this. 4. For brand name variants use “Matches regular expressions” and separate by a pipe symbol ‘|’. 5. Note that segments are specific to a profile initially – you may want to share them.
30. Advanced segmentation for social media Source (Step 10) : http://www.davechaffey.com/blog/web-analytics/configuring-google-analytics-guide / See also: www.davechaffey.com/online-reputation-management-tools
31. New May 2010 Google Adwords Beta and Search Funnels
32. Modifying profile setup within “Google Analytics Settings” Customisation technique 5 Goals and funnels
33. “ How does our conversion compare?” Source: http://www.marketing-online.co.uk/wiki/ Ecommerce_Conversion_Rates_Statistics
40. Example of simple funnel setup and what NOT to do Gotchas 1. The match type also applies to the funnel care with exact match Gotchas 2. Not actually the URL start with /<page> Gotchas 4. Missing/wrongly assigning goal value Gotchas 5. Required step may exclude some behaviour e.g. entry deeper into funnel Gotchas 3. Including a trailing slash / http://www.lunametrics.com/blog/2008/06/25/funnel-problems-google-analytics/ NB – Segmenting funnel: http://www.lunametrics.com/blog/2010/06/04/segment-goal-funnel-google-analytics/
41. Segment your funnels! Source: http://www.lunametrics.com/blog/2010/06/04/segment-goal-funnel-google-analytics
42. Tracking on-site search Tip find the search query parameter from the URL of a search results page Coremetrics UK Retail benchmarks
43. Case study: Next.co.uk Aim: Evaluate business case for improving onsite search merchandising Methodology : For example search use Google Website Optimizer to AB Test current search results page for “ Boys socks ” against a static “ideal” example Results : The new results page caused a reduction in search exit rate of 19% . If this reduction was replicated across all onsite searches, it would result in a 4.1% increase in online revenue .
52. Segmenting pages/product by performance Conversion rate Or conversion rate variance (add to basket) compared to average Page or product popularity (views) or page view variance (compared to average) High Potential (Problems) Top Performers (Stars) Low Potential, Low Performance (Dogs) Consistent Performers (Cash Cows)
58. Google Website Optimizer case study Source: Moneyspyder blog (with permission): http://blog.moneyspyder.co.uk/2009/06/enhanced-google-website-optimiser.html
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60. Use Feedback tools for… “ Why ” not “ What ” http://www.smartinsights.com/digital-marketing-software/website-feedback-tools-review/
61. What do customers value? Think? Analytics will only show you ‘ What ’ not ‘ Why ’ – other tools can help iPerceptions http://www.4qsurvey.com / “ Bad web site. Difficult to find item as no search box provided for short cut ” “ I can't find any prices on your website ” “ Would like to see where I can buy products from ” .
When analysing Website Optimiser test data, we've identified a serious need for more fine grained data to get really crisp results. For example, Website Optimiser will tell you how many visits have occurred to each of your experiment variations and how many visits have converted. The nature of the conversion may change of course as might the secondary and tertiary effects of tests. How can we see whether a test of the on-site search functionality has increased ecommerce conversion? Can we see whether customers engage better with the site if they see more featured products? Website Optimiser data won't necessarily answer these questions out of the box. We've identified a couple of techniques that will help though. No great surprise - search usage is improved by nearly 40%. The other test is still running though. So, were searchers buying more? Are featured products engaging customers? Are test subjects spending longer on the site? Are these changes adding value to the bottom line? We'll consider event tracking first of all: