With a powerful CDP on board, digital experts can combine all customer data and build rich individual profiles. However, with more sources, new data types, and higher volumes, traditional rule-based automation techniques just don’t manage to keep up in order to build highly personalized customer journeys.
Artificial Intelligence (AI) empowers digital experts to crunch huge amounts of data, allowing them to understand their customers' behavior and anticipate their next actions.
Traditional AI methods are slow and require machine learning expertise. That's why we created our own AI module, Journey AI (JAI). It's a complete game changer for marketing teams. With JAI digital experts can create customized prediction models within hours and without the need for an AI expert.
Traditional models are built by and for data science teams. Though the need for AI comes from the business, AI is out of reach for the marketing team. JAI is built with digital experts in mind. With an easy-to-use interface, marketing teams can create, train, and deploy models themselves — no technical skills and involvement from AI teams are required.
Building AI models takes a lot of resources and a lot of time from the analysts with an unknown outcome. With Relay42’s Journey AI, digital experts can build and test AI models in hours. As a result, JAI enables marketing teams to become more time-efficient and have a faster time to market.
Traditional AI-driven prediction modules follow the one-model-fits-all practice. With Journey AI, digital experts get a fully customized solution for their business. JAI uses a generic trainer which allows the user to build models based on the available data, making each new model highly customized, accurate, and easy to implement.
AI models are often a black box for marketers. With conventional AI models, marketers need a team of analytics experts to measure and analyze the outcome of the model which takes time and resources. And it’s always retrospective. With JAI, metrics are generated every time a model is trained, re-trained, and deployed. This makes it fully transparent allowing marketers to see immediately the outcome of the model and tweak it in real-time.