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In essence, when done correctly data analysis can allow vast amounts of information to be compressed into manageable and tangible pieces of real-world knowledge. By such definition, it is easy to see why analytics has driven digital marketing innovation; visual displays of Google search trends, purchasing behaviours and browsing history can give a much clearer picture of where one’s target audience is. However, as we will see, it is important not to get too caught up in such metrics alone.

Big companies have always relied on vast amounts of data. Companies like Google and Amazon have led the way in the digital marketing space in terms of innovation. However, Google Analytics has played a big role in spreading the importance of web analytics to smaller businesses and to a much wider audience.

Obviously, this has had tremendous positives for those who have implemented these tools correctly, but it has also had a negative side effect: an increased weight on vanity metrics – metrics that are not really indicative of what is happening to a business. For example, pageviews and time spent on site can often look appeasing. Such metrics can be useful in some regards, but the most important metrics show one thing: action. Meaningful data analysis tracks actions such as who is converting, where are they converting, who is buying multiple times?

While the importance of meaningful marketing analytics is clear, as suggested, there still seems to be a lack of quality data analysis within businesses. However, this is not just confined to small business. Managing large amounts of data has also become an issue for large organisations in terms of data storage (36%), data quality (23%) and making the data relevant (15%).

Many companies seem to be simply collecting data without using it in a meaningful way. The picture becomes clearer once the typical use of data analytics within digital marketing departments is examined; nearly three quarters (72%) use web analytics, but far less use analytics for assessing the voice of the customer (36%), customer journey analysis (35%) or segmentation (34%); even less emphasis is put on social media analytics, particularly in terms of measuring engagement and influence (20%) and sentiment (8%). In the current market where consumers are becoming more and more multi-screen literate, simply measuring the first and last points on a single platform is simply not good enough anymore.

In the beginning, data analysis was a foreign unknown entity to many businesses, but now it is essential for survival. Companies have recognised this at least, with over half (51%) planning investment towards in-house analytic teams. Due to the rise of multi-screen use, the key to quality analytics is not to focus on a single platform such as Google analytics, but to use scope and breadth on various platforms to create a clear overall picture of the consumer.

Challenges still lie in areas of managing data storage and data quality as well as forming a good data strategy. However, those who have invested in quality data analysis have found improvements in customer targeting (71%), conversion (58%), marketing personalisation (51%) and customer experience (51%). Therefore, quality data analysis has become a vital ingredient to successful digital marketing and businesses as a whole; it is something to be embraced and invested in.

By Eóin O’Donoghue

Neil Ryan