Understanding the AI
We have included Artificial Intelligence (AI) and Machine Learning (ML) in the receeve platform, so you can manage your clients in a more efficient way.
With the help of AI you'll be able to:
- Analyse customers' behaviour by expanding the data set
- Access real-time data and have full visibility of the most successful and unsuccessful content
- Optimise communications based on live data analysis and AI predictions
- Provide personalised, sought-after customer experiences
- Identify and approach high-risk customers in individual perspective
The right approach and the use of advanced technology enables companies to minimise manual work. The automation, however, helps to segment data making it easier to access detailed information.
You will have full control over where and when to leverage our AI capabilities in the process; receeve offers a variety of AI features, all of which are ready to use. Let's have a look:
- AI Messaging Optimisation
The AI Messaging Optimisation is a vital tool in content analysis and evaluation. The comparison of 2 or more messaging contents highlights the most successful approach and provides correct predictions on the best approach depending on the behaviour of your customers.
- AI View
The AI Viewis a visual representation of AI Optimisation processes. It brings full visibility on Email, SMS and their outcome. It highlights the necessary trends. It allows tracking AI performance in real-time which leads to a full view of the best practices.
- AI Delivery Time Optimisation
The AI Delivery Time Optimisation picks the best day of the week and the best time of the day to send out communications to your customers. The automatic execution is easily adaptable to the timing and day in order to bring the best results from dunning.
How do we do this?
The receeve AI uses Reinforcement Learning (RL) frameworks to better understand customer behaviour and come up with solutions that improve business performance.
receeve leverages an RL model called Multi-Armed Bandits (MAB) that addresses the problem of identifying the most appropriate strategy and content at the best time for individual customers. MABs are extensively used in recommendation systems where they use explicit or implicit feedback, with the aim of increasing customer engagement and revenue.
receeve uses both A/B testing and MAB. A/B tests are purely exploratory and are done to collect data with associated statistical confidence. In contrast, MAB are optimisation algorithms that maximise a given metric. The MAB algorithm is adjusting traffic automatically based on the configured optimisation goals and boundary conditions.