The 3 Most Critical Skills for Marketing Analytics. Digital Marketing is the most data-rich field in all of Business, and also has the most pitfalls.
Perhaps more than any other field, marketing, especially digital marketing, revolves almost entirely around data. This makes it a rich and rewarding business to support as an analyst or a data scientist, as the volume and utility of data can be incredibly high, increasing the need and the scope of potential projects for the analytics professional.
Marketing data has some important pitfalls, however, that can de-rail Marketing analytics programs:
In this article, I’ll explain the 3 critical skills that will enable you to overcome these pitfalls.
SQL and data manipulation skills aren’t going to be enough to effectively get all the data you’ll need to measure marketing programs — unless you want to manually download excel spreadsheets every day. You’ll need to learn how to code with REST APIs to automatically pull ad platform/click-stream/and other marketing data.
The biggest lie that you may have been told is that you need to be a developer to work with APIs. The truth: you don’t. Here are a couple of tips and tricks that will get you 80% of the way there:
It’s more than likely that your website is the primary place you send traffic and clicks with your marketing campaigns. Subsequently, to tell a complete marketing story you need to understand web analytics, clickstream data, and how that data ties to the ads you are creating.
Here’s a simple example of some raw click-stream data:
You can see there is a timestamp, a unique identifier, the URL, and an SDID column that contains the unique campaign identifier from the URL tracking parameters (The tracking parameters are the values after the ‘?’ in the URL).
When campaigns are created in an ad platform (Facebook, Linkedin, Twitter, etc.) — information from those campaigns or ads needs to tie back to the URL where traffic is being directed. This typically happens with URL tracking parameters, but you’d be surprised how many marketing teams are either a) not tagging anything, or b) tagging ads inconsistently or incorrectly. Any discrepancy between tagging and analytics is going to mean huge gaps in the data that you are trying to collect, which will make it extremely challenging, or impossible to effectively measure marketing campaigns.
For Big Data Analytics, the challenges faced by businesses are unique and so will be the solution required to help access the full potential of Big Data.
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