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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… ...

I am going to start this series of post with few questions for you.  Here is some data pulled from a Web Analytics tool. This data is for a “Display Ad” campaign: Most of the web analysts today get the following view of display advertising from their Web Analytics tool.  Looking at this data and some publicly available information they will get started on the analysis and recommendation. Though some other analysts will say, Wait… I need more information.  Google Adwords has done such a great job in providing cost data and almost all of the analysts have dealt with some kind of paid search campaign, so they know that cost of campaign plays a role in the analysis of campaign.  So they demand it.  Well this is where most of the web analytics tools fell short, cost data generally resides in some other tool and it is not easy to get that data. But how said that Analytics was easy.   However, I am providing full data with cost so that we can continue with this po...

Are you obsessing over the total number of mentions, number of positive mentions and negative mentions? If you are then you are not alone. This same issue came up recently while I was speaking on the subject of Social Media at a local event. One person got very concerned when I said that a lot of social media conversations are marked “Neutral” in most of the social media monitoring tools. The reason is that tools are not yet advanced enough to classify everything and so when in doubt the conversation is marked “Neutral” rather than “Positive” or “Negative” . So what do you do in this situation, when you know that the sentiment numbers are not right? Short answer is: Don’t obsess over the raw counts. Let’s face it; you will never get an exact count of mentions about your brand, products etc. let alone the sentiment counts. Here are few reasons why the number won’t be accurate Tools - The number of mentions will change with the tool you are using. Different tools have different sourc...

I am sure you have heard of a story about a guy lost his ring in a dark alley. It was really dark and he could not see anything, so he went to a nearby lamppost and started searching for his ring underneath it. When asked why he was looking for ring under the lamppost, he said “because it is bright here”. That’s what most of the web analyst do. Even when the problem might exist somewhere other than what their web analytics data can show majority of the web analytics folks just look at “Web Data” for the answers. Why? Because that’s all the data they have easy access too. It is brighter there. Here are some other things which are in the “dark” areas. It is time for you to shine light on them: Ad Server – There are several factors that impact a performance of a campaign, many of them don’t show up in your web analytics tools, they reside within ad servers or with 3rd parties. Example: Which pages the ads was shown, what time was the ad shown etc. I will write more on this in a future ...