T-OMT: A Novel Opinion Mining Tool for Improving Global Customer Relationship Management

نویسندگان

  • María del Carmen Rodríguez Gancedo
  • Francisco Javier Caminero Gil
  • José Relaño-Gil
  • Carlos Picazo
چکیده

For IT companies, a quick reaction when a new product is being deployed into the market is crucial, so a very dynamic response is required, mainly analyzing the new channels used by their customers to express their satisfaction or concerns. This quick response can only be achieved if companies count with the support of powerful Opinion Mining Tools able to analyze the sentiment evolution over the new channels like social networks or corporate blogs and forums, then these have become the most common choice for obtaining a valuable feedback and traditional channels like filling out forms or call centers have been relegated to a secondary position. In the present paper, we present a novel and powerful tool for opinion mining developed by Telefonica R&D in the framework of the Render project, able to produce quick reports with userfriendly charts to analyze information coming from different sources and providing the company with a powerful weapon to be able to react to negative sentiment when releasing new products or services, and adapting them to the needs of the customers, that will actually be the final beneficiaries, then the products and services will be much more adapted to their currents needs. INTRODUCTION & MOTIVATION Nowadays, companies involved in a global and dynamic market should be very careful with the needs of their actual customers to keep their loyalty. Therefore, new products to be launched must always take into account the current needs of the customers and the community related with them in order to be able to attract new customers with

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Modelling Customer Attraction Prediction in Customer Relation Management using Decision Tree: A Data Mining Approach

In Today’s quality- based competitive world, known as knowledge age, customer attraction is of ultimate importance. In respect to the slogan “customer is always right”, customer relation management is the core of an organizational strategy playing an important role in four aspects of customer identification, customer attraction, customer retaining, and customer satisfaction. Commercial organiza...

متن کامل

Opinion Mining Using Decision Tree Based Feature Selection through Manhattan Hierarchical Cluster Measure

Opinion mining plays a major role in text mining applications in consumer attitude detection, brand and product positioning, customer relationship management, and market research. These applications led to a new generation of companies and products meant for online market perception, reputation management and online content monitoring. Subjectivity and sentiment analysis focus on private states...

متن کامل

Customer Relationship Management and Data Mining: A Classification Decision Tree to Predict Customer Purchasing Behavior in Global Market

In the global market of today, Customer Relationship Management (CRM) plays a fundamental role in market-oriented companies to understand customer behaviors, achieve and maintain a long-term relationship with them, and maximize the customer value. Moreover, the digital revolution has made information easy and fairly inexpensive to capture. Thus, companies have stored a large amount of data abou...

متن کامل

Customer behavior mining based on RFM model to improve the customer relationship management

Companies’ managers are very enthusiastic to extract the hidden and valuable knowledge from their organization data. Data mining is a new and well-known technique, which can be implemented on customers data and discover the hidden knowledge and information from customers' behaviors. Organizations use data mining to improve their customer relationship management processes. In this paper R, F, an...

متن کامل

A Novel Utility and Frequency Based Itemset Mining Approach for Improving CRM in Retail Business

The paradigm shift from 'data-centered pattern mining' to 'domain driven actionable knowledge discovery' has increased the need for considering the business yield (utility) and demand or rate of recurrence of the items (frequency) while mining a retail business transaction database. Such a data mining process will help in mining different types of itemsets of varying business utility and demand...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013