The AI-based recommender: the AI tool for customer services of the future
Recommendation systems are essential for every company that can no longer serve its end customers exclusively via direct customer touchpoints. It is almost impossible for large retail groups such as finance and insurance companies to know all of their end customers personally. At the same time, their portfolios are getting bigger and bigger and with them the possibilities of finding suitable products for end customers are increasing. Recommendation systems such as the AI-based recommender from Kapsch BusinessCom ensure that the product and the end customer come together - quickly, directly and accurately.
It's a match!
The AI-based recommender from Kapsch BusinessCom finds the products that are precisely tailored to the needs of your end customers by recognizing their affinities and directing specific suggestions to them. In addition, the AI-based recommender recognizes in good time when one of your end customers is willing to churn and transmits valuable data on the basis of which you can take measures to prevent churn. This saves you expensive recovery measures and binds your customers to you in the long term - through significantly improved and continuously ensured customer satisfaction.
Everything is fine!
All of this is done using artificial intelligence - which in the case of the AI-based recommender from Kapsch BusinessCom is both "trained" on the basis of your company data and rule-based. The relationship between these two properties is as follows: If there is not enough data available at the beginning of a project, a fixed set of rules will be drawn up together with your company's domain expert. Used during operation, this collects feedback data, which in turn is used to train a data-driven machine learning model. This process is called cold start and is often at the beginning of an AI-based recommender project.
In particular, due to the rule-based aspect, the artificial intelligence in the AI-based recommender has the essential advantage that the decisions it makes are fully traceable and transparent. This is particularly essential for insurance companies and financial institutions, as they always have to be able to explain to their customers the reasons for which proposals and decisions are made. In order to guarantee this explainability, Kapsch BusinessCom has used numerous methods for the AI-based recommender so that its decisions are always comprehensible: for example, an optical tool that shows which characteristics of a service or person were particularly decisive for a particular decision.
The best from both worlds
Thus, the AI-based recommender from Kapsch BusinessCom is not an opaque and no longer controllable black box, as can be the case with systems based purely on machine learning. Nevertheless, these also have certain advantages, such as a high level of adaptability to any application area and an intelligent, autonomous mode of operation that brings with it a high potential for automation. In addition, they offer the possibility of modeling relationships that are too complex to be mapped using a rigid set of rules. The AI-based recommender from Kapsch BusinessCom takes exactly these advantages of the self-learning AIs and integrates them into its otherwise rule-based system. This results in a highly efficient and modern integrated hybrid model that provides a safe,
Getting there without detours
The AI-based recommender is therefore used successfully to automate, simplify and shorten company processes. For companies there is the favorable situation that end customers can independently come to a product that is relevant to them without having to go through the usual hurdles and barriers. The users take a shortcut: They no longer necessarily need brokers or consultants to familiarize them with the complex product catalog, but are guided through the sales process by the recommender. The AI-based recommender is either used directly in the self-service portal or as a supporting tool in customer service. The quality of the advice and the accuracy of the suggestions always remain the same.
What is included in the scope of delivery? A look at the overall package:
- Basic component: An essential part of the AI-based recommender is initially the technical framework of Artificial Intelligence. It is a generic basic set of rules consisting of various AI algorithms.
- Made to measure: In addition, there is the exact, individual adaptation to the product body of the respective company. This is developed on site together with the technical experts in the company and adapted to their special needs and requirements.
- Reporting and auditing: In addition, Kapsch BusinessCom provides regular reports, i.e. evaluations of the functionality of the AI-based recommender, including auditing: a tool that precisely validates the decisions of the AI, collects data sources and makes them available to the experts for interpretation.
- Integration and testing: Another building block is the regular testing and review of the recommendation system to ensure that it works properly and delivers the desired results.
- Expertise: To top it off, Kapsch BusinessCom provides its extensive wealth of experience from numerous projects, extensive technical expertise and multi-layered competencies in order to support its customers in every phase of the implementation of the AI-based recommender.
As a customer: from Kapsch BusinessCom you always get one thing when it comes to AI solutions - especially with the AI-based recommender: a comprehensive overall package.
One better than the other: What sets the AI-based recommender apart from the competition?
Many providers only deliver the basic technology - Kapsch BusinessCom does this too, but also fine-tunes the process with the respective customers. As a result, the AI-based recommender is precisely integrated into the systems of the respective company and anchored in its landscape. In addition, the finely granulated presentation of the product catalog results in a potentially far higher sales quota than with a generic product presentation, as is often found in large corporations.
Another advantage of the AI-based Recommender is the pronounced flexibility of Kapsch BusinessCom with regard to its application in your company. Depending on the extent to which you need support, Kapsch BusinessCom will design the right, individual solution for you. By feeding the AI recommender with data from your company, for example, it adapts to the circumstances in your company. The individual approach, however, always takes place within the framework of an all-in-one approach    or an end-to-end principle. This means that Kapsch BusinessCom accompanies you throughout the entire project - from start to finish - and provides everything you need for your individual solution.
Another reason to choose Kapsch BusinessCom as your number 1 digitization partner for recommendation systems is a large, diversified network of partners and an accompanying diverse project portfolio. As a result, business processes from a wide variety of sectors were learned and relevant, interdisciplinary experience was gained, which in turn is used in your company.
Go for Recommender
All of these factors together make it clear that Kapsch BusinessCom is the go-to partner when it comes to the successful optimization and further development of customer experience management in your company. The AI-based recommender is an indispensable tool for insurance and financial companies in particular, as it enables a compact overview of a complex product portfolio. In addition, he stands like no other for explainability, individual adaptation and a comprehensive end-to-end principle. The resulting increased customer satisfaction leads to a reduced churn rate, as more and more customers will decide to remain loyal to your company. This significantly increases the sales and contract conclusion rate and significantly increases the cross-selling and upselling potential. Satisfied customers - isn't that what every company wants? Modern, innovative AI solutions from Kapsch BusinessCom make it possible.