Artificial intelligence (AI) has been pushing its way into the marketing scene for the past few years, using customer data and machine learning to anticipate customer needs and improve their experience. In email marketing, AI has the ability to remove a lot of guesswork, helping to create content and assets that speak to customers, delivering higher conversions, and increasing your ROI.
We all know how important personalization and optimization have become in email marketing. Customers are looking for partners who understand their needs, and that understanding has to come across in the emails we send to them. Personalization is only as good as the data you have. In order to use customer data in field merges, dynamic content, or for deployment send time, you would need to verify, or blindly trust, that the data is available, clean, and up to date. Sending email with bad data could wind up being more detrimental than not using the personalization at all.
By implementing AI tools, predictive analysis will, over time, clean up your customer data and put it to work in your campaigns. Below are some key components of AI and how they can be used to improve your email marketing.
Machine learning is the use of AI where systems can learn from data collected over time, identifying patterns in customer behavior and delivering outcomes based on that behavior.
Timing: Knowing when to send email is a big pain point for marketers. We want our emails to hit inboxes at the time when customers are most likely to engage. Machine learning can be used for send time optimization (STO), learning over time when each customer opens and clicks through your emails. Many email service providers and marketing automation tools are now offering STO out of the box, so that as you send email, the system will learn customer patterns and adjust when the email is delivered to them, automatically.
Segmentation: Identifying the best target audience for your campaigns can be challenging. AI has the ability to group your contacts by identifying behaviors within their digital footprint. By identifying customer interests, purchasing history, and personal data, delivering messaging that is timely and relevant will become more automated.
Big Data Analytics
Big Data is “larger, more complex data sets, especially from new data sources” (Oracle, 2020) that are too large in their footprint to be able to analyze with traditional methods. Having data is great, but it has no value if it can’t be used. By incorporating AI, marketers have the benefit of not only capturing these data points but automating the use of them to personalize their campaigns and messaging.
Subject lines and email content: A lot of time is spent on developing subject lines and email content that will resonate with customers so that they will open and engage with your messages. AI has the ability to remove the guesswork by using datapoints captured based on past interactions and personal information. This can be as simple as incorporating contact name or as complex as using industry or purchasing behavior to personalize a call-to-action through dynamic content.
Progressive Profiling: Form submissions have historically been one of the mainstays of data capture in marketing. It’s an easy way for marketers to collect data straight from a customer with the hope that it will be accurate and help to increase their database and pipeline. The downfall is that, for the most part, humans do not enjoy filling out forms. The time involved and concern with privacy may increase drop-off and bad data (Mickey Mouse, anyone?). Progressive profiling is predictive analysis that will populate forms with different fields each time a contact will access your forms. This keeps the number of fields per form low while still increasing the data captured.
Contact Washing Machines: Progressive profiling will work hand-in-hand with contact washing machines that will help to keep your database clean so that it can be used. As contacts enter your database they should enter a CWM to make sure that data matches the criteria you’ve identified as standard in your system (2 character country codes, job functions, removal of ‘celebrity’ names, etc.).
Remember that machines are only as smart as the humans who work with them. It’s important to stay on top of your programs and data by consistently reviewing and reporting and making changes to your campaigns based on those results.
To learn more about the different features impacted by AI visit the Relationship One blog or reach out directly.
Citation: Oracle. (n.d.). What Is Big Data? Retrieved April 14, 2020, from https://www.oracle.com/big-data/guide/what-is-big-data.html
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