(2 minute read)
As we have discussed in other blog articles, the immense amount of data that many companies currently have will only be useful to the extent that we are able to determine which of that data should be used and how it should be processed in order to provide real value to the company and have a positive impact on the business.
As we know, there are programs and processes operated and executed by specialist technicians with the necessary knowledge to do so in the most optimal way possible, but we are also aware that these are not available to all companies.
Taking this into account, at Bionline we have developed our technology around three key concepts, among which in this article we highlight the usability designed for business users.
In the same way that the driver of a car does not have to know all the technical details of the engine, but still knows how to drive it and take advantage of it; business users do not have to master the process of generating predictions for our solutions, nor do they have to know the nature of the algorithms behind them; they just have to get the most out of it.
To achieve this, we have different elements whose objective is to ensure the exceptional usability that characterizes our solutions.
- Bionline Academy: digital environment developed exclusively for customers whose objective is to train them in a dynamic and simple way, reviewing the main concepts and promoting familiarization with the solution apps that will be used.
- Customer Success Department: Bionline team dedicated exclusively to the continuous, personal and personalized monitoring of each customer
- Autonomous learning of the models: quality inherent to models based on Artificial Intelligence that endows them with the ability to self-adjust based on learning thanks to commercial and marketing actions carried out over time.
- Continuous monitoring and review: service carried out by Bionline’s team of data management specialists that manages to optimize the operational performance of the contracted solutions to the maximum.
Finally, it is also important that companies that have large amounts of data about their customers and operations, are aware that they are just one step away from optimizing their activity to unattainable levels in any other way.