Email marketing remains one of the most effective tools for attracting and retaining customers. However, to succeed, you need to keep up with the times and use advanced techniques such as personalization and machine learning. In this article, we will look at how user behavior data helps create more relevant and effective email campaigns.
Machine learning automation in email marketing can be done europe cell phone number list in practice using specialized platforms and tools. Below we will try to schematically describe the processes and software used to automate direct marketing.
Collection and storage of data
The first step to successful email campaign personalization is collecting user behavior data. This includes information about what products users view, what website pages they visit, their purchase history, and more. Modern CRM systems and analytical tools help collect and process this data very quickly and accurately. It is important to keep in mind that the data must be structured and accessible for analysis.
Examples of software that allow you to collect, store and structure databases for e-mail newsletters:
Google Analytics: to track user activity on the site.
CRM systems, such as Salesforce, HubSpot, or Mailchimp, for collecting and managing customer data. They integrate with various sources to collect customer information, centralize customer, deal, and interaction information, and allow you to create tasks, send emails, and automate processes. CRMs also provide tools for analyzing and tracking results and can integrate with other marketing and customer management tools.
