Hyper-personalisation
Hyper-personalisation - discover the benefits
- Increasing satisfaction of customers with company mobile applications
By providing personalised content, offers and interactions customised to customer needs companies can significantly improve satisfaction of their customers. Customer satisfaction is crucial for building positive relations and loyalty, and this translates into long-term financial benefits for the company.
- Competitiveness
Progressing development of technologies offers increasingly advanced options for personalised customer involvement. By investing in hyper-personalisation, a company can chart a route into the future, where personalisation becomes increasingly advanced, using advanced machine learning and AI algorithms.
- A reusable platform for real time machine learning projects
By creating a dedicated platform for machine learning projects, data can be effectively collected, analysed and used in real time. The reusable platform enables the company to quickly implement new personalisation projects, and this accelerates processes, reduces costs, and increases effectiveness of actions in the area of personalisation.
Analysis
It covers a detailed analysis of user preferences, behaviours, and needs to adapt to them the content, services, and methods for interacting with them. Within this process, demographic data, purchase behaviour, and historical interactions between users and the platform are collected and analysed. The use of advanced tools and algorithms for data analyses, such as machine learning, enables generation of personalised recommendation, customising the user interface to a relevant person, and improving experience of using our product by the user. Data analysis enables continuous improvement of methods for hyper-personalisation, understanding of changing user preferences and making accurate decisions.
Implementation
Implementation includes machine learning and recommendation algorithms, using collected data about the user to generate personalised content and proposals. In this process, first the prepared “taught” solution is tested in the test environment, and then, when all test metrics are positive, the solution is launched in the production environment, where its effectiveness is further monitored and user experiences are continued to be optimised on the basis of results of new data analyses. During implementation, it is important to take into account protection of privacy and compliance with personal data regulations, while providing users with optimum experiences in the use of the end platform/product/service.
Integration
It consists of combining many system components for its effective operation. Channels for communication between components are designed to enable real time transfer of information. Integration involves synchronising personalisation algorithms with a system for content management by supplying personalised results to the user interface. At this stage, correctness of the entire system performance is tested and it is adjusted to ensure smooth cooperation between individual components. In consequence, a consistent and effective hyper-personalisation environment is created, which can deliver personalised content and experiences to users. The extensive experience of GFT experts in integrations contributes to finding the most optimal solution for the implemented project.
