The user experience is a key aspect when it comes to attracting customers and the algorithms are gaining prominence with the aim of improving it.
Artificial intelligence is beginning to be present in the interaction with customers. This means that machine learning will be increasingly present because it directly affects the decision process.
The algorithms have the potential to improve the functioning of the websites, but must overcome the barrier that may involve the interaction with users and customers.
Analysis of the competition
First, one must know where the competition is located.
In this way, we will know if a company is more backward or more advanced than its competitors. In turn, if the development team is carrying out a level project, or conversely uncompetitive.
Being an unknown terrain, it forces us to inform ourselves about the environment in order to know what kind of strategy to carry out and in what terms to do it.
Are users prepared?
The first question we must ask ourselves in this area is whether it is necessary to apply AI, a response that is practically affirmative at present. It is advisable to try a group of users in which it was not necessary to implement it, and with those in which it was necessary, to observe the difference and the degree of satisfaction of the clients with and without it.
There is still some reluctance on the part of users to interact with machines. The custom is to associate, not talking directly with a person with bad service by a company.
This trend is changing at the same pace that the algorithms are optimized. Generally, what users appreciate most is adapting to changes gradually and progressively without difficulties.
Machine learning is a key aspect in the application of the algorithms in the user experience. It is possible to predict the functioning of software that interacts with people, but a large percentage of its correct functioning will come from the experience acquired through automatic learning.
How do algorithms work?
The learning of the algorithms focused on improving the user experience consists of three steps. First, the algorithm collects data (with predetermined responses) and predicts a solution . The third and last step is to compare the predictions with the answers and to calibrate the percentage of error .
Repeating this process over and over again, the algorithm optimizes its ability to give a correct answer more and more.
conclusion
In the case of algorithms, the key will be to overcome the initial period of testing and learning without harming users or customers. After all, it will be a necessary step to be able to evolve towards a more effective user experience that allows to stand out above the competition.
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