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Category: Metrics Understanding

Track Offline Marketing with Google Analytics – Whitepaper

Categories: GA & GTM, Metrics Understanding, Pro Lounge / Comments: 10

When it comes to tracking offline marketing campaigns, many marketers are unaware of the potential of using their existing web analytics tool to measure success. Typically, the reliance is on traditional, imprecise data such as print distribution figures (a.k.a. readership numbers), viewing figures (TV audience metrics), or footfall metrics ("20,000 people walk pass this sign every day"). However, none of Read more

Show Me the Money: How much value is your website generating?

Categories: Metrics Understanding, SEO & Analytics / Comments: 0

It never ceases to amaze me how much emphasis organisations still put on measuring website volume - "How many visits (or conversions) did our last campaign generate?" It surprises me because volume metrics are a very useful guide to failure - but not success. That is, low traffic and conversion numbers tell you that something went wrong. For example, wrong message, wrong Read more

Understanding Web Analytics Accuracy – Whitepaper

Categories: GDPR & Privacy, Metrics Understanding, Pro Lounge, Setup Accuracy / Comments: 8

I first wrote about web analytics accuracy in 2007 while working at Google. At that time numerous clients (big spending Google advertisers my team helped) were contacting their Adwords account managers asking why Google Analytics numbers did not match their AdWords click-through reports, or for that matter, match the other web measurement tools they were using. These of course are legitimate Read more

How to choose between Advanced Segments versus View Filters in Google Analytics

Categories: GA & GTM, Metrics Understanding / Comments: 15

As anyone who has looked at the plethora of web metrics data available knows, even for a moderately active website, segmentation is the key to gaining insight. It allows you to group similar visitors e.g. customers, subscribers, contributors, engagers etc. together for comparison. Therefore instead of viewing metrics that are average of averages, the numbers actually mean something. For example, Read more

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