NLP optimizing user request resolution | Venturus

NLP optimizing user request resolution

“Every day Software” we could say these days. In fact, the role that software plays in our daily lives is undeniable.

It is present in all kinds of electronic machines and devices — from computers to smartphones, from payment terminals to modern cars.

What may go unnoticed is that these software are actually complex systems. They require highly specialized technical teams to build, test, maintain, and improve them to meet customers’ needs and demands, as well as ongoing training and support to keep them in working order.

It is not surprising, therefore, the impact of the costs involved in the entire software life cycle and the resulting need to optimize the work by development teams.

 

Correction and improvement tools

Luckily, there are several tools available that assist software teams in managing the entire project lifecycle. They cover aspects such as:

  • resource allocation;
  • time management;
  • setting priorities
  • registration of collected data.

Among the range of options, there is an important category: bug tracking systems and new demands.

Generally speaking, they are platforms or applications packages that track, record and report requests for inclusion of new features or problems in software — encountered by users or by the teams themselves.

 

How user requests work

Typically, within an organization, bug tracking tools operate from customer service centers (internal or external) by requests.

 

Man working on user reuqests with NLP

 

When a request is opened, the system records the report submitted by the requester. This request can range from a bug, licenses, proposing improvements to requesting new features or other information such as descriptions, ogs, versions etc.

Based on this set of information and anchored in the knowledge and decisions of the team, the tracking system tries to establish a workflow as personalized as possible to solve the request in the shortest time possible.

It’s then that the opportunities to optimize the performance of this process arise.

 

The challenge of meeting requests

As soon as the tracking system opens a request, its level of prioritization is evaluated, based on its urgency, relevance and the team’s ability to solve the problem.

In this scenario, a database with a history of bugs already solved can be of great value. Details such as the nature of the problem, the team members who dealt with it previously and the solutions adopted can be identified — greatly speeding up the resolution of the request.

Unfortunately, this is not always readily applicable. Software is constantly evolving, so that new types of problems and needs will always appear, further expanding the database collected.

Teams also change over time, requiring different technical expertise of the group. Not to mention other internal and external factors that may affect the activities of the support team.

This results, for companies, in issues in estimating time for completion of requests and in informing customers. That is, screening processes can be considered time-consuming and inefficient processes.

 

NLP may be the way!

With a reasonable volume of data referring to the history of call resolutions and considering the difficulties in manually dealing with them, artificial intelligence would allow teams to automate the process of screening requests, delegating tasks of estimating the deadlines for solving open requests to trained algorithms.

Usually, requests are permeated with reports of the problems and needs of users, as well as all the exchange of messages that occurred until the completion of the process.

In situations like these, in which we are dealing with texts, the artificial intelligence technique most suited is Natural Language Processing (NLP).

This area of AI deals with the study of the problems related to the automatic generation and understanding of natural human language, employing modern computational resources and mathematical models.

 

How NLP works

NLP has been studied since the beginnings of artificial intelligence research in the 1950s. It has attracted strong interest in recent years thanks to the interesting results provided by powerful machine learning algorithms based on modern artificial neural network architectures.

The state of the art in this field has brought to the fore answers to complex tasks such as:

  • summarization and generation of texts and speech (chatbots and virtual assistants);
  • analysis of feelings and trends in different materials (texts and audio);
  • automatic translation of texts between many different existing languages;
  • speech recognition and segmentation, among other applications.

 

NLP in the requests

In the case of the call tracking system, NLP can act in several aspects. The texts generated and recorded by the system involve a certain degree of subjectivity, as is to be expected, since the description of a given problem can be reported in different ways depending on the author of the request.

It is up to the algorithm, then, to capture the similarities, compare and correctly classify the data according to the type of demand.

Another point is that in certain cases, such as multinational organizations, users tend to employ the local language, resulting in a multilingual database. Fortunately, NLP has tools to deal with situations like this.

Finally, based on the analysis of the presented data, NLP models trained with historical databases can make predictions about the estimated time to solve the open request.

 

Benefits

By automating and accelerating lead time estimates for resolving customer requests and logging insights, support teams can be optimized.

Additionally, they acquire greater performance and can be better allocated, taking advantage of the full technical potential of the team.

The advantages of an NLP system are obvious. By providing better call management, it increases both the quality and volume of requests processed.

Thus, NLP generates productivity gains that positively and directly impact all business operations involved.

 

Venturus is an Innovation and Technology Center that has been conducting research and development and providing services to multiple markets for over 25 years. We have experts in Artificial Intelligence, focused on NLP and Computer Vision that can help automate and optimize your systems, redirecting the productivity of teams.

To learn more, contact one of our experts in the form below!

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