Market Challenges And Opportunities

Market Dynamics- Drivers

Growing need to understand customers’ behavior is expected to drive growth of the global natural language generation market during the forecast period

Understanding customers’ buying behavior has become crucial for business owners. Since products are made to cater to consumers’ needs and wants, the product should be designed and marketed accordingly. The study of customer behavior helps organizations to analyze different factors that influence buying decisions of consumers. NLG can create unlimited content variations for every individual for a personalized experience with better customer engagement. It also helps companies to execute targeted marketing and provide individualized content for increased sales. This also means less amount of time is spent on routine tasks, which can be otherwise used for improving digital experiences. NLG can make different variations of product descriptions precisely in multiple languages very efficiently. Thus, these factors are expected to drive growth of the global natural language generation market during the forecast period.

Rising penetration of big data and related technologies is expected to propel the global natural language generation market growth over the forecast period

Big data refers to an efficient way to analyze and systematically extract valuable insights from a vast amount of unstructured data. Big data is far more efficient than conventional data processing application software. NLG is a cutting-edge technology that can boost data visualization solutions. By leveraging NLG, interpretation of data visualization software such as SAP, Tableau, and Qlik has become significantly easy. Furthermore, NLG can provide a coherent and inclusive analysis of a vast and complex dataset. In fact, it also reduces human cognitive efforts, enabling end users to make decisions based on valuable insights. Therefore, these factors are expected to propel the global natural language generation market growth over the forecast period.

Market Restraint

Lack of skilled personnel to deploy NLG solutions is expected to hinder the global natural language generation market growth over the forecast period

Understanding and deploying natural language generation requires skilled personnel. Such expertise is scarcely available, especially in emerging regions such as Latin America, Asia Pacific, and MEA. As a result of this, the adoption of NLG is significantly hindered. Thus, these factors are expected to hinder the global natural language generation market growth over the forecast period.

Low awareness regarding NLG solutions is expected to restrain growth of the global natural language generation market during the forecast period

Despite its numerous advantages, the adoption of NLG is significantly low. This is owing to low awareness regarding NLG solutions and their advantages among many business owners. Thus, these factors are expected to restrain growth of the global natural language generation market during the forecast period.

Market Opportunity

Emerging options in application areas can present lucrative growth opportunities in the global natural language generation market

Natural language generation is being used in various applications such as automated editorial content creation, e-commerce content creation, chatbots, auto-generated software patent application, financial assessment automation, and more. In this, chatbots are one of the most recent applications of NLG where they are required to converse or interact with people in a way that a human would. The best chatbots would the ones that can give users the impression that they are interacting with actual humans.

Rising demand for intelligent business processes can provide major business opportunities in the global natural language generation market

NLG is finding applications in intelligent business processes. NLG tools can analyze, interpret, and identify the most significant data and generate reports in simple English. Furthermore, NLG offers artificial intelligence (AI) to business intelligence by automating the routine analysis, which saves both time and money for the business.