Develop data-driven marketing in 3 steps:
Goal: Collect cross-channel user data, create demand and probability profiles for each user and derive a precise customer approach. This leads to more customers coming, staying, trusting the brand and buying more. Another objective is to improve the efficiency of marketing activities through automated processes.
All campaigns, promotions and marketing measures, which were previously created manually by the marketer, can be optimized and automated in a digital sales process. With marketing automation solutions, the commitment of your website visitors and newsletter subscribers can be observed, documented and analyzed in detail. The system automatically plays out campaigns to selected personas, imported segment groups or individuals and it enables collaboration between marketing and sales.
>> Rule-based, automated campaigns with detailed reporting
The prerequisite for digital marketing with AI applications is a solid, high-quality database. Precise statements about customer needs and behavior can only be derived the more data is collected and made available. Marketing automation systems deliver marketing data. Other systems provide additional transaction data such as purchases, complaints, enquiries, etc. The data from various databases is collected in a central data system. The data can then be processed and enriched with AI models for AI-supported marketing.
There are several ways to improve your return on investment (ROI) by integrating AI and automation.
Marketing platforms equipped with AI are able to gain more meaningful insights and further optimize personalized marketing. Artificial intelligence brings greater precision and efficiency to customer communication and thus to the company. With a solid database, AI algorithms can predict much more accurately when the right time to interact with the lead or customer is, and what tactical marketing action is needed through the Marketing Automation tool to make a customer buy, stay, or return.
The impact of campaigns can be enhanced by AI-supported segmentation and analysis of customer data. Segmentation, probability models and intelligent recommendations are essential techniques.