THREE CORE PHASES OF DIGITAL ANALYSIS

A digital analysis that relies primarily on hunches rather than proven intelligence t a reliable analysis at all. Analysts use data to make decisions. Going the extra mile to transform data into true marketing intelligence is key.

Digital Analysis is split into three core phases: Reporting, Data and Statistical Analysis. A mediocre analyst might consider his or her job finished after Phase One, but a skilled analyst knows that each phase is an important step toward developing transformative insights.

Lets take a closer look at each phase of a successful digital analysis:

Phase One: Reporting

In this step, an analyst uses a digital analytics platform such as Google Analytics or Adobe SiteCatalyst to find data trends, which are presented in a report to a specific audience. This information can be very important for an organization, but only if it answers the question Why?. Lets say I run a report on display ads for a client, and I notice a few campaigns perform significantly better than the others, so I advise the client to end the display ads that performed poorly. Even though there is supporting data, my suggestion is based on a hunch because I havent pinpointed the reason why certain campaigns are more effective than others.

Phase Two: Data Mining

Data mining helps uncover more information about why the effective ads performed well. Continuing with the same example, lets say I take a closer look at the ads and use every type of data point possible in a data visualization tool like Tableau. With this program, I am able to drill down into the data, which shows that square ads with a call to action get more clicks than the others. This extra knowledge adds more validity to the suggested marketing decision because it pinpoints the campaigns shape/size and message as reasons for success.

Phase Three: Statistical Analysis

Running data through statistical analysis software like SPSS or SAS not only ensures that your data is statistically but can narrow down more specific insights. In the example of the display ad campaigns, I used software to discover that the ad messaging is statically significant to success, while the size of the ad is not. This insight is sound in addition to being actionable, making it valuable marketing intelligence

that can be used to tweak future campaigns.

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