HTC Call Center Analytics

Transcription

1 HTC Call Center Analytics Breakthrough Results using Call Center Analytics

2 Breakthrough Results using Call Center Analytics from HTC Global Services! Call Centers can now get fully use worthy results for the humungous and unstructured call center data in just minutes. Our Analytics is capable of handling 1000 chats at any given time and identify the sentiments of customers by using artificial intelligence. The analytics can give a solution to forward the call centers business by improving on customers pain points. HTC Global Services Business Intelligence division offers an innovative solution to call centers that can cause a revolution in the way call center data is perceived. This solution can cause ripples in the way future is predicted with regard to the call center business. Call centers can thrive by utilizing the solution and make a difference in real time performance. It is cost-cutting analytics! Call center analytics is a recent phenomenon that attempts to collect unstructured voice recordings or text based conversations between business help-desk representatives and customers. Analyzing the unstructured data stream in real-time for content classification and sentiment adds value to the business as this gives valuable insights. This can provide critical awareness on what are the backlogs that customers are facing and about the product requirement that is essential for customer retention. Change management will be a big issue in the integration of the new systems and processes, when a business undergoes enhancement of current business process to overcome backlogs. Enhanced analysis actually delivers more than the analyses of the recent past. Real-time text classification of unstructured data enables near accurate tagging of words under a taxonomy of categories. 1

3 Call Center is an Enabler for Continual Improvement Conversations between customers and executives on the call-center call or help desk, throws light on the scope of isolating the words and statements in queries or concerns. It facilitates to produce results that are most relevant to the business value needs and the categorization happens based on context. Such analytics are very useful when things go haywire while a product or service of businesses are supported via help-desk, or a call-center. It facilitates to categorize the issues based on support staff and customer or user. Call center analytics can reveal the missing process for using the service for a business. It helps business for setting specific goals that align with the expectation of the customer experience. This kind of classification and analysis of frequency of issues provides insights that can be used to make changes to improve customer experience. Analyzing the Unstructured Data in Real-time Unstructured data has no data formats or structure. These can include audio, video and streaming text data. With clear use-case, a business can make use of the unstructured data for gathering perceptions. It is critical to understand which 2

4 data to collect, analyze and retain. There is a need for alignment of data sources to suit the business goals. Unstructured data has to be governed properly for quality to perform text analytics, classification based on auto-taxonomy generation, auto categorization, auto-tagging and other information-retrieval techniques are necessary for gathering additional value from unstructured data. Challenges of Classifying Sandwiched Data Real-time Real-time analytics of unstructured data [4] requires dynamic analysis based on data in a system. HTC s analytics solution actually accesses and analyzes the unstructured data in less than a minute. Usually, customer or business users commonly describe their queries and concerns in a blended manner to a call-center or help-desk executive. This includes both the exact issues and the sandwiched statements. Such conversations are very difficult to classify based on our tags of words that are maintained for natural language processing [5]. In call-center or help-desk, the queries are raised over multiple events where the true categories could be identified over chunks of data received as a stream. Sometimes, the usage of words may not directly relate to the actual content and to worsen the situation, customers speak in idiomatic expressions or slangs making analytics difficult. Another challenge is that a single word may mean differently in a different situation. Customers usually don't express their queries in the same way. This poses problems in classification because in traditional classification these differences of the same word don t alter the context. This may end up in a diametrically wrong classification. Classification: The Way of Organizing Data classification is the process of organizing data into categories for its most effective and efficient use [Source: Whatis.com]. Data classification throws light over the taxonomy of data sets that are crucial for business decision making. It can enable business in finding out what categories and criteria the organization uses to classify data for such that the metrics on those classifiers could be benefited. 3

5 Need for Opinion Mining before Classification by Analyzing the Customers Comments before Classification Opinion mining analyzes the customer comments where Natural Language Processing (NLP) is used to determine the queries or concerns of the users or customers about a particular product or service, during a call-center or help desk chat or call. The result simplifies the business to identify the hidden backlog and opens room for continual improvement. It involves developing a methodology to detect, collect, and classify the areas, based on conversation that is happening in real time. However, when automation is required, machine learning techniques similar to artificial intelligence (AI) come handy. This mines large amounts of texts or or audio data received from trusted sources of call-center or helpdesk to apply analytic methodologies over real-time data set. Opinion mining acts as a business enabler, especially for business with customers to evaluate the current status of a new product or service, evaluate the issues faced and their frequency, and impact of issues on customer retention. It helps in determining the success and failure factors of the product or service based on analyzing the frequency on each category that we classified. This enables business to identify particular issues of a product or service, identifying demographics, customers likes or dislikes for a particular product feature etc. 4

6 or audio data received from trusted sources of call-center or helpdesk to apply analytic methodologies over real-time data set. Opinion mining acts as a business enabler, especially for business with customers to evaluate the current status of a new product or service, evaluate the issues faced and their frequency, and impact of issues on customer retention. It helps in determining the success and failure factors of the product or service based on analyzing the frequency on each category that we classified. This enables business to identify particular issues of a product or service, identifying demographics, customers likes or dislikes for a particular product feature etc. Essential Text mining for Classification in Analytics Business value could be given through Text analytics by means of extracting themes, phrases, comments from large data sets by applying Natural Language Processing (NLP) based on current business needs. Classification is done based on the polarity of each word. In addition to this the tagging, which refers to a taxonomy, words are identified to act as classifiers and the conversations are tagged to all possible queries or concerns to gain the business value. The classification is carried out by performing advanced analytics to reach the core value of the business backlog. Choosing a Development Platform It is necessary to find an appropriate platform for data to perform analysis and get the desired result when working with large scale real time data. An inappropriate platform leads to inaccurate results that impact the trustworthiness. This NLP classification on customer's opinion could be applied overall while segregating the topic of conversation in call centers or help-desk. This facilitates the business to understand the hidden bottlenecks in current business trend that is offered via product or a service. 5

7 HTC Global Services Solution for Call Center Analytics HTC Global Service has the capability to design a call center analytics platform in which a call-center or help-desk business process could gather consumer insights faster and accelerate to discover new opportunities, business impact factors, link entities and also helps in finding out which entity is entity is influencing and how. Our analytics combines extractors, data processing algorithms, and data analyzing modules in a single application to connect, extract, analyze and classify the real-time unstructured data. Benefits of Call Center Analytics: Improve the customer experience Gain competitive advantage Gain Business Intelligence Revitalize brand value Involve in continual improvement of service to customers Perform corrective actions Enhances business continuity Predicts probable future World Headquarters Reaching out through IT 3270 West Big Beaver Road Troy, MI 48084, U.S.A Phone: Fax: U S A l U K l G e r m a n y l I n d i a l Malaysia l S i n g a p o r e l U A E l A u s t ralia l I ndonesia