Big blow for web analytics: Google search is going secure and along the way hiding all referrer data
Currently, conversions in AdWords are attributed to the last ad someone clicks before making a conversion, masking the fact that many customers perform multiple searches before finally converting. AdWords Search Funnels help you see the full picture by giving you insight into the ads your customers interact with during their shopping process.

AdWords Search Funnels are a set of reports describing the ad click and impression behavior on Google.com that leads up to a conversion. In addition to a Top Conversions report, Search Funnels consist of 7 reports including Assisted Conversions, First and Last Click Analysis, Time Lag, and Path Length. For an overview of these new reports, check out this video:
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The debate around whether display influences search behaviour or not has been going on for a while but I don't think anyone really doubts the impact on search anymore, the question is how much. So it's nice to see some research on how this differs by vertical. The below Eyeblaster graph shows the share of search and display conversions by vertical.
Interesting to see would be how the impact of display on search behaviour differs depending on the brand awareness in market for a particular brand. Datalicious client research indicates that the weaker the brand awareness in market for a particular brand, the stronger the impact of display advertising on search behaviour and conversions.
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Implement, maintain and manage an advanced web analytics platform to optimise media designed to driving website subscriptions and generate additional customer preference insights.
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The guys at AdGooroo have published another one of their search advertising reports which contains some really interesting data.
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Challenge
Implement, maintain and manage an end-to-end analytics and online optimisation platform designed to increase media effectiveness and website conversion as well as overall user experience.
Solution
Design, implementation and ongoing management of advanced Omniture analytics and online optimisation platform across all Vodafone website properties in general and the online store in particular. The final solution combined data from various different sources, measuring performance across multiple channels above and below the line as well as visitor behaviour down to an individual customer level, both online and through call centres. By combining data sets and technologies that were separate up until then, Datalicious was able to generate additional insights, eliminate inefficiencies and execute highly targeted campaigns which were previously impossible.
Results
Advanced analytics and multi-channel media attribution enabled us to deliver a 400% return on investment on paid search in the highly competitive Telco market and establish organic search as a profitable cost centre. Identification of existing customers allowed us to save 30% of the annual display-advertising budget dedicated to acquisition messaging, which was essentially being wasted on already existing customers and re-purpose it for brand and self-service messaging. The addition of targeting parameters and coordination of on and off page re-targeting campaigns increased response rates by 25% on average. The planning and execution of an online testing strategy increased the visit to sale conversion rate by 5%. All of the above measures combined delivered an approximate return on investment on advanced analytics of over 600%.
Testimonials
“I’ve been working with SiteCatalyst for over six years, 3 years as a customer and 3 years as an employee, consulting to some of our largest customers around the world. The current Vodafone implementation of SiteCatalyst is one of the most impressive I have seen and ranks in the top 10 [globally] from my perspective. It is an amazing foundation for taking action on the data and improving online return on investment.” Adam Greco, Team Lead Business Consulting at Omniture.
“The Datalicious guys are great to work along side and to have on your team. They have a 'no stone unturned' approach to finding solutions to challenges that come up and were at ease working with different providers. Their knowledge and passion for web analytics and best of breed web optimisation was second to none. The advise on best practice use of the Omniture suite and how to make it work for me personally and Vodafone as a whole made the learning and training of others easy. I would thoroughly recommend Datalicious to anyone and they will be my first point of call.” Steve Brown, Senior Business Analyst, Vodafone
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A little while back, Google discretely introduced a “Show Options” tab that lets you filter your results by media, time or in other interesting ways. Filters are not new, but combined with Google’s awesome search, have become quite useful to me.
Filtering by Visited Pages. Google is being used more and more as a navigational device towards content you already know. Google is good, but if you’re deep in research sometimes it’s hard to find that site again, and this is a brilliant tool for this purpose.
This behaviour is not uncommon, and an interesting trend I don’t feel is getting enough attention. Search has become less and less about discovery, and more about meeting basic usability requirements about finding existing content... Something search marketers are adjusting for. How often do you already know exactly what content you are looking for before you search? What chance do the other sites have of capturing your click for that impression? if you’re a search marketer, how do you adjust your optimisation metrics to cater for navigational search and usability from something traditionally focused on acquisition?
Here is my search for Domain names. I searched for this last week and couldn’t remember the name of the site which I decided was the way to go.
Another feature in the options is the wonder wheel – we haven’t seen a lot of people using this from our analytics data, and I am thinking it probably would be more useful for internal search where you have a more defined content set. There are some implications for search, and with adoption will come more users entering your site via more specific keywords and the reduction in broad search terms.
We’ll be interested to see adoption rates of these filters and any considerations for search marketing – we’re monitoring our logs and see about 5% of visits contain at least 1 filter, and will be looking to use this data in the future to enrich insights around keywords and what users are looking for when they use them.
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All marketers would have seen the below graph before and understand how the theory behind it impacts their marketing campaigns but most might wonder in which phase certain products actually are. Some might know for their own products based on sales numbers but these might not be that easy to come by in large organisations and when it comes to competitor products the guesswork really starts.
So why not use search term trends provided by Google free of charge to establish what lifecycle stage a particular product is in? The search term volume over time shows the change in interest in the product pretty well. Check out the below search term trends for the most popular N-Series Nokia products and how closely each resembles the lifecycle curve vs. the iPhone.

The below graphs shows nicely how the interest in the respective Nokia product grows over time with adoption and then finally drops back down with new products being introduced. Overall sales numbers probably correlating quite nicely with search term volume.
Interesting is the trend for the iPhone. As you can see it doesn't follow the standard product lifecycle curve at all but so far manages to keep growing rather than declining which is a prime example for how you can keep products alive by introducing additional features and services. Just think about the iPhone integration with iTunes and the growing number of applications and you get the drift.
Read some more about the product lifecycle theory here
http://en.wikipedia.org/wiki/Product_life_cycle_management
Check out the original Nokia Google Trends data here
http://www.google.com/trends?q=n95%2C+n73%2C+n96%2C+n70%2C+n82&ctab=0&geo=all&geor=all&date=all&sort=0
Check out the original iPhone Google Trends data here
http://www.google.com/trends?q=iphone&ctab=0&geo=all&geor=all&date=all&sort=0
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