Text mining is one of the main tools unleashed by the fast-growing A.I./IT/Computer industry to help companies analyze, filter and process in real-time any valuable text language information found on the worldwideweb that may be useful for one or multiple business solutions. Its application and deployment in conjunction with natural language processing software solutions offered by leading providers such as Expertsystem have revolutionized the E-commerce industry, helping these companies to identify trends and patterns in consumer preference and anticipate fluctuations in consumer behaviour and tastes, increase their market visibility/prestige, cut costs by reducing bureaucracy levels and—by maximizing the sharing of input and ideas from all company levels—increase productivity to achieve a higher level of customer satisfaction, in the end leading to enduring customer/client loyalty.
Innovative advancements in the A.I. field of Natural Language Processing (NLP) as applied to E-Commerce include Automated A.I. Assistants to help customers with any queries, and demonstrate A.I.’s increasing capacity to understand and recognize human cognitive behaviour and language, and respond appropriately. The world wide web is the open domain where the text mining process takes place, and in E-commerce it is being effectively employed to recognize purchasing trends and find out as much as possible about consumer tastes—sifting through everything from websites, social media networks (Facebook, Twitter, LinkedIn, Youtube, and more) to consumer blogs, news articles and business data/statistcs from professional business organizations/networks so as to identify and target specific consumer demographics and customer audiences with personalized offers based on an analysis of their tastes. By analyzing the web search history of a customer, for example, the company can customize products, services and special offers based on the consumer’s search and purchasing patterns, thus tailoring the consumer shopping experience to their personal preferences.
The capacity to extract and recognize human concepts from language and text data is also extremely useful to gauge customer opinions on a certain product or service, making it possible to differentiate between negative and positive feedback. For instance, text mining and NLP can determine based on a conversation whether a customer likes a product or not, what they do or do not like about it (cost or quality and other factors), and what changes they would like to see in a product or service. It also gives companies a stronger competitive edge because thanks to the unlimited amount of information on the internet they can measure their potential vis a vis other—and even bigger—competitors.
In a reciprocal manner, both companies and customers can thereby benefit from the impact and results of text mining applications and Natural Language Processing software, especially because they increase the circulation and development of innovative ideas among companies and the general public. The advantages for E-commerce businesses and consumers are endless because based on their analysis of consumer response across multiple demographics, sellers/providers can discover new market strategies to help them succeed while at the same time bringing reciprocal benefits for customers, such as better upgrades or lower prices—while simultaneously learning directly from consumer opinions about new ideas for useful apps to integrate into their products. It is, in other words, no longer a ‘one way street’ journey where commercialization is dictated by sellers/providers (always under the watchful eye of consumer groups), but a ‘two way street’ in which consumers as a whole can also recommend new products and suggest changes, bringing advantages to both parties.