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How data analytics can improve your marketing campaigns

Aaron Beach, Senior Data Scientist at SendGrid (opens in new tab), gives his advice on how data and analytics can be used to improve your marketing campaign.

Today, only 5-10 per cent of advanced companies consult data ahead of sending their email marketing campaigns.

However, email and marketing data are becoming more relied upon for the purposes of sending out email marketing campaigns, and it is important that marketing teams know how to use it for their benefit.

Email delivery platforms work by tracking and analysing delivery, open and click rates through data. They track all the meta-data in every email you send, including bounce back rates and unsubscribes. Open and click through data is the most important data for email marketing campaigns, and it is gathered in both of the following ways:

Open and click through data is the most important data for email marketing campaigns, and it is gathered in both of the following ways:

  • When images are opened the pixel URL is tracked. Each URL can be made unique and so can be tracked when it is opened.
  • Once you click on a link through your email you are automatically redirected to the website. As you are being redirected the information is sent to your email delivery platform before you reach the retailer’s website. Customers don’t normally see this because it takes fractions of a second for that information to be sent.

Although email delivery platforms analyse data, it is important that marketers are analysing this data as well; as it is, we still have a long way to go before a ‘data-driven’ culture is baked into the marketing organisation.

Marketers need to start weaving data insights into their marketing strategies. For example, if you’re a daily deal sender and a specific customer doesn’t engage with your email within 60 days, it is best to remove that customer from your email lists to prevent being marked as spam.

To do this automatically, you need to build a model to determine engagement frequency, which is one way to bake a data-driven culture into a marketing organisation.

The most enlightening result of data-driven marketing is being able to see the difference between the highest and lowest levels of engagement. It is often wrongly assumed that the most engaged recipients are just 2-3 times more engaged than less engaged recipients; an assumption which often leads to bad sending strategies.

In fact, the top 10 per cent of engaged recipients are 100 times more likely to engage with your email marketing campaign than the bottom 10 per cent. By recognising this, marketers will see that sending strategies can’t be ‘one size fits all’, but rather, outliers and extremes are the norm, not the exception. In understanding this, data can have a huge impact.

One challenge being faced is how to determine the difference between a good and bad email marketing sender. Current email providers like Yahoo and Google use algorithms to track email engagement and determine if they are going to deliver the email to the inbox or the spam folder.

Instead of fixing the problem by using data to enhance and add value to their email marketing campaigns, many marketers are trying to find loop holes in the algorithms which allow them to fake a good email; meaning, at the moment, it’s really an arm’s race.

Although there is still room for intuition and ‘gut-level’ decision making, it is important that these decisions are data driven. For example, when you send an email to recipients of different levels of engagement, different levels of frequency are required, and this should be driven by data.

Email aesthetics such as colours and images should be left to the creative teams, since assuming data is going to solve all your problems will lead marketing teams to miss things that creative teams can bring to the table.

Therefore, whatever decision data leads you to make, always make sure you hold it up against the light of human reason.