FREMONT, CA – The implementation of artificial intelligence (AI) and data-driven approaches carry immense potential in the marketing and sales divisions across different sectors. Industries and businesses have acknowledged the benefits of AI integration and implemented successful data-driven initiatives. The successful incorporation of AI has led to an increase in data-driven marketing and sales solutions. AI has augmented human expertise, enhancing the marketing and sales performance of organizations.
AI-based natural language processing (NLP) enables simple interaction with data within the language function of the brain. Employees without a firm grasp on technology can now leverage NLP to evaluate the data and make informed decisions. It is used by many organizations to index keywords and map visits to determine customer interests.
Natural language translation (NLG) is similar to NLP. It leverages machine learning (ML) to translate complex data and machine language into an understandable format. NLG learns from common customer queries to deliver the output. It empowers the NLG algorithms to enhance its recommendation function continuously.
AI has taken predictive and prescriptive analysis to the next level. Traditional predictive capabilities leverage historical data and static predictive analysis. The incorporation of AI has enabled the upgrading of the older models, thus enhancing the quality of predictions. Prescriptive analytics is also an extension of the predictive model that suggests the optimal course of action based on the available data. AI has transformed predictive analytics, introducing better learning capabilities which enable the system to update its recommendations according to previous results continually. Many organizations are leveraging ML to predict profitable buyers effectively and cater to their needs.
Also, AI has brought new opportunities in the field of streaming analytics and internet of things (IoT). The machine-generated data has enabled efficient incorporation of AI and machine learning in the organizations. The massive amount of streaming data created by the myriad of devices connected via the IoT can be leveraged for machine learning analytics approaches. The integration of AI has significantly simplified the process of collecting and synthesizing billions of terabytes of data. As technology advances, the role of AI technology in finding, processing, and extracting vital insights from the endless pool of information will only become more significant.