Outbound Calling

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  • On June 23, 2016
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  • Outbound calling
A call centre is a place which is set up for the purpose of taking or making phone calls, i.e for inbound and outbound calling. The flow of call continues through 24 hours of the day for 365 days. Thus, you can get an idea about the large number of phone calls taking place in […]
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  • Sales Calls Training can be conducted during off-peak periods.
    • The tone of speech is very significant. How you say something is more important than what you say. In fact a loan defaulter already knows what is going to be said when there is a call from someone on behalf of the bank. An insulting tone can disturb the call recipient. He may not receive further calls or may block the number, in which case the very purpose of outbound calling will fail. An unpleasant dose can be neatly wrapped in a sweet tone to succeed in the purpose of calling.
    • Imagine that you are face-to-face with the person whom you are addressing. Direct communication is always more effective.
    • You may believe that because the listener cannot see you, non-verbal communication is redundant. However, if you speak naturally as you speak to a person standing in front and employ all verbal and non-verbal techniques, the speech part will sound more convincing and have a greater impact. Thus, irrespective of whether people can see you or not, speak naturally.
    • Plan your calls in advance. Decide what you are going to say. Present the content logically, point by point. Remember to say everything that is necessary. Do not miss any point. You can keep a note of paper in front of you while making the call to remind you of what you have to say and in what order.
    • Be sure to gather all necessary information about the product, about the defaulter, donor etc. Careful and thorough study of the case is essential while making an outbound call.
    • Anticipate questions and be prepared to answer them.
    • It is difficult to deal with irate customers. Maintain complete control, be calm and polite while talking to angry customers. A single wrong word can create trouble at both ends, setting up a series of unpleasant incidents.
    • Be prepared for knock-backs. People may just put down the receivers abruptly or tell you that they are not interested. You need a lot of patience in handling outbound calls. Even if you get 20% success, you may consider yourself lucky!
    • A single call never fulfils the purpose. Make calls repeatedly at regular intervals. Keep not of what the recipient had said in the previous calls and take the matter forward.
    There is risk involved in outbound calls as much as in inbound calls. Firewalls can be set as guards to control traffic of outbound calls and check their outward passage. Outbound calls use metrics such as cost per call, revenue earned, total calls made and tasks completed for measuring agent success. While making outbound calls, these factors should be kept in mind. Outbound calling can be marked as successful when the purpose of calls is achieved through least number of calls and in minimum time. iTivia Technologies offers 24 hours outbound calling services using advanced technologies like Automatic Call Distribution (ACD), Outbound System (Predictive), Interactive Voice Response System (IVR) and Computer Telephony Integration (CTI)" target="_blank">

B2C Marketing & B2C Lead Generation

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  • On June 23, 2016
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  • B2C Lead Generation, B2C Marketing
B2C marketing is a matter of pleasure for buyers/service providers and customers/clients for the one important reason that it brings the two parties face-to-face, it brings about direct communication, leading to human interaction. Human beings are social creatures and buying and selling are two of the numerous elements that contribute to a state of happiness […]
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  • lead generation tactics. Some are tried and tested, proved successful. Some are unimaginable. Innovative ideas come up once in a while and are soon adopted by all. In spite of general marketing strategies, B2C lead generation has to take certain factors into consideration like the age group of consumers, the period, the location, type of buyers, the kind of goods, products and services etc. For example, a water pump will have demand in rural areas and no requirement in metro cities. Old people will not be much interested in cosmetics. Hence, the key strategy is to assess all conditions and decide the best strategies that suit every criterion." target="_blank">

Market Research

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  • On June 23, 2016
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  • market research
A business chain is a complicated and lengthy process consisting of elements like the manufacturers, agents/dealers, retailers, customers and end market consumers. They are all linked together in the entire process. When one wants to understand market position, one has to understand each element individually, how it is linked with the previous and following element […]
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Big Data Analytics

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  • On June 23, 2016
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  • big data analytics
According to the Gartner IT Glossary, Big Data is high-volume, high-velocity, and high-variety information assets that demand cost effective, innovative forms of information processing for enhanced insight and decision making. Volume refers to the amount of data generated from numerous sources like network and social media. Variety refers to the types of data; greater the […]
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  • Gartner IT Glossary, Big Data is high-volume, high-velocity, and high-variety information assets that demand cost effective, innovative forms of information processing for enhanced insight and decision making. Volume refers to the amount of data generated from numerous sources like network and social media. Variety refers to the types of data; greater the number of sources, greater will be the variety. Velocity refers to the speed of data processing; faster the speed of processing, faster will be the analytics. Some data sets are very large and they contain a variety of data types. The process of analysing big data is called big data analytics. Big data analytics is carried out in order to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information. The data that is analysed may be semi-structured or unstructured. The analytical findings can be used to promote marketing, to investigate new markets, to provide better customer service, improve operational efficiency, to gain advantages over competitors and for overall benefits in the business. Until now people avoided doing certain things simply because the data volumes were too large and unmanageable. However, special software allows you to perform operations that were impossible heretofore. Big data analytics gives you timely insights so that golden opportunities are not lost, timely decisions can be made, difficult problems can be solved and new growth opportunities can be tapped.

    Big data analytics tools

    There is no single magic technique that can be applied for big data analytics. Of course, advanced analytics is applied, yet, several types of technology work together to help you get the best results.
    • Data management: large amount of data flows in and out of business organizations constantly. Some standards must be set for data that is acceptable to ensure high quality and reliability of data. Once quality data is well-organized, a master data management programme can be established.
    • Hadoop: This has become a key tool for big data management since it can store large amounts of data and run applications. It can process big data speedily. It is an open source framework and available free of cost. It uses commodity hardware to store data.
    • Data mining: This technology helps you to identify patterns in the data. With data mining software you can sift the data, delete noises, pinpoint what you need and use the information for further analysis or for answering complex questions.
    • Text-mining: With this technology, data can be analysed from the web, books and other sources. You can discover hidden facts from text-based sources to enable you to take informed decisions. Text mining uses machine learning or natural language processing technology to comb through documents – emails, blogs, Twitter feeds, surveys, competitive intelligence and more – to help you analyse large amounts of information and discover new topics.
    • In-memory analytics: Data analysed from the system memory rather than from the hard disk drive, fetches immediate results. This technology helps to create new models. It makes business decisions easy and fast and interactive.
    • Predictive analytics: The technology implies predicting future outcomes on the basis of historical data. It uses statistical data and machine learning techniques to make predictions. It boosts the confidence of organizations by assuring that they are on the right path. It is useful in fraud detection and risky deals.
    • Apache Spark: This is also an open source framework and is often used as an alternative to Hadoop. It is able to analyse data 100 times faster than Hadoop for certain applications. Hence, it is useful for streaming data and interactive analysis.
    • Apache Hive: It works best for batch processing of ETL jobs and SQL series. It uses a language called HiveQL. It is based on SQL.
    • NoSQL Databases: They are No SQL databases and have become popular because of their flexibility for big data analytics.
    • Data lakes: The data that is gathered from various sources has to be stored in repositories which are called lakes. Data is kept in raw form in the lakes before performing any analytics. Data lakes don’t use the traditional structure of files or folders but rather use a flat architecture where each element has its own identifier, making it easy to find when queried. Massive data can be stored in data lakes. Data lakes allow handling of numerous jobs at a time.

    big data analytics

    Advantages of Big Data Analytics:

    • Cost reduction: Big data analytics uses technologies like Hadoop which is cloud based. Large amounts of data can be stored at low costs. Data is also secure in cloud.
    • Quick decisions: Hadoop and in-memory analytics work fast; organization and analysis takes little time, hence, decisions based on results can be taken immediately. Valuable time is saved and profits increased.
    • Customer satisfaction: Analytics provides reliable information about customer needs and satisfaction. It is possible to give the customers what they need and meet their complaints and solve problems efficiently. It also helps companies to conceptualize new products as per customer needs.

    Where is Big Data Analytics used?

    • Big data analytics enables financial firms to predict frauds preventing further loss.
    • Big data analytics enables governments to increase security and be prepared for cyber threats.
    • The healthcare industry uses big data to improve patient care and discover better ways to manage resources and personnel.
    • Telecommunications companies utilize big data analytics for planning the best ways to optimize new and existing wireless networks.
    • Marketers have quite a few ways they can use big data. One involves sentiment analysis, where marketers can collect data on how customers feel about certain products and services by analysing what consumers post on social media sites like Facebook and Twitter.
    Big data analytics is used in multiple industries. Data analytics is useful to every industry in some way or another, which explains its popularity. As companies become aware of the capabilities of big data analytics, they will exploit it in every possible way for the benefit of their business. Like any other developing technology, it will take time, but more and more utilities will be discovered. iTivia Technologies provides all kinds of data management and big data analytics solutions to process and analyse any amount of data and lead to tangible and reliable results that will enable you to take informed decisions for the growth of your business.  " target="_blank">

Data Acquisition And Data Integration

  • Posted by admin
  • On June 23, 2016
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  • data acquisition, data conversion, data integration
People have been acquiring scientific data for thousands of years. From the ancient days until very recent times, it has always been done in the same way. A person looks at a scientific instrument and writes down what he  observes. This continued on unchanged until the early 20th century.  Finally, data could be acquired and stored automatically. […]
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  • iTIVIA provides Data Entry, Data Conversion, Forms Processing, OCR Clean up and Image Keying services. Our Services are ideally suited for voluminous data entry applications such as Airway Bills, Driver Logs, Mail in Rebates, Medical Claims, Architectural Drawings, e-books Publishing, Plant Title Extraction." target="_blank">