The goal of this post is to clearly outline the difference between a data driven strategy and a standard campaign strategy. The campaign is a hypothetical and simple situation for a freelance wedding photographer whom wants to advertise on Facebook. The target market are those users whom have a relationship status of “engaged” on Facebook.

Standard Execution of This Facebook Ad Campaign
The photographer creates ad content with a catchy headline, possible promotion, and a link to either their Facebook Fan Page or website. The ads are targeted locally and to only those users with the “engaged” status. The ad budget is set and the ads are run.

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Many have questioned what to test. In fact, A/B testing is a growing interest in many organizations where many teams get involved. This makes it quite difficult to control at times as everyone has input on what to test. The following is a way to find tests and prioritize what you should test on your website and mobile apps.

Low Hanging Fruit Method
This method is generally finding the page that performs the worst when it comes to your goals. An eCommerce site it is a page that gets little to no revenue, or transactions. Lead generation websites, it is a page that has a very low form conversion rate. Mobile websites and applications, you want to find the pages with actions that get the least clicks or activities.

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When you evaluate the effectiveness of your keywords, you cannot look at the granular most level. Some of your keywords will not have the statistical significance in volume and conversion that will allow you to make a confident decision. This is why it is very important to look at your SEO strategy from a high level.

SEO Lift Measurement
SEO Analysis based on conversion is great, but you may have situations where a keyword had 5 conversions with 10 visits and a conversion rate of .500% which is highly misleading. This is exactly why we measure the Lift in SEO, as it normalizes the traffic volume and the conversion for each keyword. Below is an example of a Lift Measurement report.

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The files are large. The complexity is great. Data processing takes time. So where is the money in it?

There is a big difference between the data miners that have a vision and those that do not. In this case bigger isn’t exactly better, it’s just bigger. The software will only pick up the relationships between the variables that you put in and provide you with a statistical output. If those variables have no relationship to your business goals, you’re just spinning your wheels.

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