AI, Analytics and Data Science improves CX
By using Analytics, Data Science and Artificial Intelligence tools, companies can improve the consumer experience through algorithms that can analyze behavior and feelings, predict needs, guide strategies and teach machines based on experiences to provide increasingly humanized service. Information obtained by Data Science applications is used to outline business processes and reach organizational goals.
Yet... what exactly does Data Science mean?Data Science is a general term that encompasses data collection, storage, organization, preparation and management. The goal is to maintain data groups to extract meaning that allows for guidance of business processes and attainment of organizational goals. A data strategy must be established to do this. Because it will orient data management across the organization, it should consider various factors, such as:
- Collection: Creation of a model for data collection methodologies;
- Management: Structuring, security, integrity and updating of information stored in databases;
- Governance: Management of policies, processes, people and technologies, in order to structure information assets within the organization;
- Data access and control;
- Privacy and security.
- Retail chains - predict behavior, increase sales opportunities, reduce risks and make more assertive choices;
- E-commerce - improve customer recommendations and user survey results, chatbot service, and filter spam and comments;
- Finance - identify good customers, minimize costs and get better results for your products;
- Insurers - gain more predictability and agility in decisions to bolster results;
- Health - maximize efficiency in administrative tasks, perform assisted diagnoses, monitor physical and emotional signs, perform robotic surgeries;
- Human Resources - analyze employee data and place employees on the right teams, delegate projects based on competencies, analyze resumes;
Atento uses Data Science and Artificial Intelligence to assess behavior and feelings and predict consumer needs, with the overriding goal of improving the consumer experience and consequently resulting in returns on business for companies.Bruno Silveira Gardel, Head of Data Science at Atento Brasil, explains that these technologies - digital capabilities found in the companies deliverables - means that predictive models can be created to improve business efficiency by offering fast and more accurate solutions based on the ability to understand consumer feelings and predict consumer behavior, using analysis and cross-referencing of deconstructed data. Use of this type of digital capacity allows for increased satisfaction and even prevents complaints from taking on a larger dimension and ending up going to the ombudsman or even a regulatory agency. Atento applies these capabilities to a variety of deliverables. One example is our business efficiency models. "We carry out a demographic and behavioral analysis of their customers to find out what they should do next and improve product recommendations, for instance. The more data there is, the more efficient the system will be, and it is also enhanced by the results obtained. The goal is to increasingly understand consumer needs, the point of the journey they are at, and serve them more and more quickly," says Bruno. Another product is the Stress-o-meter, which assesses someone's emotional state in terms of both voice and text messages, based on processing of natural language, tone of voice, typing speed, use of certain positive and negative words, proximity between words, etc. This is how Atento builds a new customer service journey, with more appropriate channels, more precise and cohesive language, and automation of processes that simplify service and offer better results in customer relations.