Digital marketers use automation and machine learning to discover new and efficient ways to reach and engage customers.
Automation allows them to automate repetitive tasks such as email campaigns, social media posts, and ad targeting, which frees up time for more strategic and creative work. Machine learning, on the other hand, allows them to analyze large amounts of data and identify patterns and insights that can inform their marketing efforts.
For example, a digital marketer may use automation to set up a series of targeted email campaigns that are triggered based on a customer’s behavior on the website or app. For example, if a customer abandons a shopping cart, the marketer can set up an automation to send an email with a special offer to encourage the customer to complete the purchase.
Machine learning, on the other hand, can be used to analyze customer data, such as browsing and purchase history, to predict which products they might be interested in, and to target them with personalized recommendations.
Digital marketers also use machine learning to analyze the performance of their campaigns and optimize them in real-time. For example, by analyzing data on which ads are performing best and which are not, a digital marketer can adjust targeting and messaging to improve the performance of their campaigns.
Automation and machine learning help digital marketers to more efficiently and effectively reach and engage customers by allowing them to gather data, analyze it, and make data-driven decisions.