How to Interpret Web Metrics

Technology is at the forefront of the digital age. Brands are spending hundreds of thousands to millions for platforms, desktop licenses etcetera. It is only after the bill has been paid and the product delivered that training for these platforms in earnest can begin. Here is the rub, no matter how powerful the technology, all recommendations that truly drive results will have a human touch. This is when a talented analyst can help augment your existing technology with knowledge of what metrics should be important, how to retrieve important metrics and how to refine the raw data into direct recommendations that will drive business growth.

What Metrics Should I Interpret?

This is the most vital question you should ask yourself before beginning to aggregate data, build models, or visualize trends. All of the analysis in the world won’t help you if you are just reporting for reporting’s sake. The most easily identified metrics are frequently tied to revenue, if your business is ecommerce then that is the best place to start. Other efforts are further removed, registrations for a free seminar are a clear conversion point, but you would also want to track lead value and lead quality. Sometimes you don’t even require a conversion from your effort, this would be the case for pure awareness efforts, even with well placed conversion pixels it can be impossible to track your upper funnel ad spend back to conversion or revenue, in this case it is prudent to monitor the volume of impressions and the cost per impression and click.

Interpreting Ecommerce Data with Web Analytics

Ecommerce websites with more than a couple dozen products can usually be divided into these familiar sections, the home page, category page, product detail page and checkout. All of these experiences can be modified to drive revenue with AB testing, and it is important to test directing paid traffic to these different sections with different messaging and creative. Your reporting should be divided into three sections acquisition, behavior and conversion (ABC’s). Acquisition data involves the quantity of traffic coming to your site and the source. Behavioral data is focused on what users do when the get there, what page did the land on? Where did the browse to? Did the user add a product to their cart? Is there a high bounce rate (users leaving the page after loading it) Is there a common path being used for big ticket items? Every question you ask is a potential report, when looking at your data you want to see the biggest winners and the biggest losers this will inform your decisions to through more fuel on the fire for a successful effort and to avoid content that doesn’t drive revenue.

Interpreting Lead Data with Web Analytics

Lead data is difficult to evaluate because there are two data sources that have a wealth of information. All of the most detailed traffic source and behavioral information will live in your web analytics suite and all of the rich information about how a lead becomes a closed sale will live in your CRM. Optimizing your efforts for all leads can lead to a disconnect that wastes money on low quality leads, but failure to look into a web analytics suite can lead to ignorance about which specific marketing efforts are working and which are not. One example of this is keywords, because platforms like Google Analytics can retrieve keyword information they can be used to understand what your leads are typing into Google. This level of data can be achieved for your most valuable leads by creating a CRM integration with Google Analytics. This is a procedure that passes the “client id” from Google Analytics into CRM and creates a key value that will link bottom line customer revenue to their on-page journey.

It is important to monitor the conversion rate of all traffic being driven to the lead form against lead creation, but it is also important to understand the value of your closed sales against the cost of advertising efforts.

Interpreting Awareness Data

Awareness campaigns won’t have a conversion point that is measurable in relation to your ad dollars. In this case you want to ensure that your have powerful audience targeting and a low cost per impression to make sure the correct people get the right message. There are at least two sources of data for this type of campaign. Google Analytics will show what on-site content your awareness campaigns have brought and your advertising engine will have detailed impression information that shows how far your message has reached.

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