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Google Analytics: The Top 5 Mistakes Young Marketing Analysts Make

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Digital marketing analysts have become a crucial component to any Digital Marketing team.

From tracking website performance, analyzing CPC’s and measuring social engagement, analysts oversee a lot of moving parts.

In 2014, Forbes Magazine announced nearly 40 percent of companies surveyed reported they needed data analysis professionals. With more than $4 million in data jobs available, it only makes sense to jump on the bandwagon. But for those who are interested in entering or who have just recently entered the analytics field, it is so easy to become overwhelmed by the scope and scale of data analysis.

As a young analyst myself, I’m going to share the five most common mistakes young/new analysts make and the simple steps to fix them.

1) Failing to think about the client/company’s end goal as a business

Many of us newbies can get wrapped up in the numbers of every metric versus focusing on what the client/company really cares about. For one, don’t let the data overwhelm you or else you’ll turn into that freak in the corner uncovering a conspiracy theory with a corkboard, images and yarn. Instead, sit in on meetings to get to know your client/company, evaluate their website structure, look into their social media strategy, email campaign, etc. Build a foundation of historical information to see what has worked, what hasn’t and what could be improved.

From there you can build, maintain and focus on what needs to be tracked and know what metrics and stats you need to review during presentations. Getting organized is crucial prior to starting an analysis. Otherwise, you won’t even know where to begin.

2) Focusing on “vanity metrics” instead of focusing on consumer trends

Whether you are using Google Analytics, KISSmetrics or any other analysis platform, understand how metrics correlate with one another rather than read of one specific metric. Bring everything back to a big picture versus the granularity of one data point, especially something as meaningless as a bounce metric, general traffic, etc.

From the wisdom of Neil Patel, co-founder of KISSmetrics, analyze the lifecycle of a customer, find the commonalities among these consumers and see their loyalty versus tracking the page performance itself. Instead of seeing page performance, see consumer conversion. Of course, page performance plays a role in this; however, if you find the formula that helps generate loyal customers, advocates, et al., implement that into your strategy. Remember, it all ties back to the customer’s end goal.

3) Ensure your data is clean and backed up

For obvious reasons, you have to do some housekeeping to design a sound and trustworthy sample of data. This holds even truer if you’re using the free Google Analytics platform. Make sure you are not acquiring bloated traffic numbers from internal traffic, Ghost and Crawler Spam. Either of these can directly affect your acquisition channels causing you to report tainted data. Although Google Analytics has added features to try and prevent this problem, I still recommend placing filters to help clean up the rest. Here is a great article to get rid of it once and for all with just a couple filters: http://www.ohow.co/what-is-referrer-spam-how-stop-it-guide/

In reference to Google Analytics, you should also create multiple views to maintain the integrity of your data. Although these best practices are a no-brainer, they are essential. Have at least one view of raw data (unfiltered/untouched) for self-assurance, a testing view to try out filters and see how they affect your traffic, and finally a view that you present off of (#perfection). Creating this safety net is key, and you will thank me for doing so!

4) Create a visually interactive presentation to showcase data

As an analyst, whenever you have a presentation (and you will), it’s imperative the data is digestible. Remember, not everyone nerds out on data like you do, so be sure to keep it simple, yet effective. On top of that, it’s important your message is engaging and captivates the audience — whether it’s good or bad. Don’t just regurgitate the numbers; explain causes/effects for the data or else you’ll get tuned out by your audience. Bringing data and comparisons into perspective is paramount in a presentation. This can be accomplished in a variety of pie charts, line graphs etc. Don’t be afraid to use colors; show thought-provoking data sets and ask for listeners to engage. Periodically throughout the presentation, check in to see if they have any questions thus far. Make it conversational, but professional, and apply nomenclature that they will understand. The more thorough and basic, the better.

5) Never stop researching and learning

If you are in the digital marketing industry, you understand how often it changes. This industry is constantly offering a new platform, function or best practice. Same goes for the data. We have to know a lot about the mechanics of the strategy and realize potential factors that can ultimately change our performance online.

Jim Sterne, the founder of eMetrics Marketing Optimization Summit, slaps down some serious wisdom on this outlook. He says, “You can’t effectively measure what you can’t manage.” Translation: Marketing and analytics coincide so it is essential to understand both. After an analysis, whether the data is good or bad, we must know what our next course of action should be. So by all means, research, learn and grow.

These quick tips only scratch the surface of the analytics field, but will provide any new analyst a point in the right direction.

 

 

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