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Web Analytics tools are great for providing a good view of one channel i.e. your website (ok, maybe slightly more than one channel e.g. some email, some social media, some offline). They worked great in silo for first few years of the internet because the only way for customers to interact with your brand online was on your site and websites were not an integral part of the business. Nowadays the story is different, customers interact with your brand in so many way, your website is just one small part of the whole "web" ecosystem and "web" is just one part of the whole "customer" experience and buying cycle ecosystem. Customer’s don’t think and operate in one channel i.e. your website. However, many "web analytics" tools do not even provide you full view of a customer journey and interactions online let alone the offline journey. To understand today's customer and performance of your marketing efforts, web analytics data has to move out of it...

Not all display advertising is created equal, though when you look at your web analytics reports you are most likely not going to find the reasons that makes each campaign and each ad so unique. Web Analytics tools generally start tracking the performance of a display advertising campaign only after the visitors have clicked on an ad and landed on your site. What happens before a visitor clicks resides in an Ad Server or in a spreadsheet on someone’s desktop . In my last post I wrote 5 tips for Analyzing and Optimizing Display Advertising and one of those tips was to Improve Click-Through-Rate (CTR). In this post I am focusing on elements you should analyze and optimize to increase the CTR of your display advertising. (Note: I am not saying that you should solely focus on CTR, but assuming conversion rate remains the same, increase CTR on your ads will result in more visitors on top of the funnel causing higher number of conversions. ) 7 Things to Analyze for Improving CTR Publisher ...

This is part III of my post on Analyzing and Optimizing Campaigns. In part I I talked about why your campaign analysis is probably is wrong . In part II I showed an example of how obsessing over reducing bounce rate might not get you anywhere . In this post I am going to provide you 5 tips for analyzing and optimizing your campaign. Here those 5 tips: Optimize Cost of Advertising Cost is dependent on how much you pay per click or pay per 1000 impressions (CPC and CPM). You have control over these cost factors. Those who are running Paid Search campaigns should already be familiar with and should be working hard to reduce the cost (CPC). Those dealing with CPM display ads should know that those rates are highly negotiable. Do you research about pricing etc., play with these numbers and see what will yield the optimal result,. Take your analysis and recommendation to your media buying team. Improve Click-Through-Rate (CTR ) CTR depends on several factors such placement, creative, uniq...

This is part II of the series on Analyzing and Optimizing Campaigns . I wrote in my previous post that when analyzing campaigns many web analysts just focus on the web analytics data. Some venture to include the cost and impression data of the campaign but they still don’t have a complete view. In this post I will show you how their lack of complete view results in wrong analysis and wrong conclusions. Below is the data I used in my last post. This is the type of data most Web Analytics tools provide and hence “Web Analysts” tend to use. What is missing? Where is the cost of products and profit margin data? Without that information, you don’t know if this campaign is successful or not. Right? The sad reality is that many web analysts don’t have access to profit margin data and hence they look at what is available to them and start recommending A/B testing (see my post One Awesome Web Analytics Tip: Think Beyond Web Analytics ). And their first target generally is Bounce Rate. Oh… ...