Customers nowadays expect much more from organizations. So, every business must provide a world class customer experience that wants to win and keep customers. Hence, more and more contact centers are using analytics to collect both structured and unstructured data – from phone conversations to e-mails to social media to buying habits. This helps companies are to customize the experience for each customer. Analytics, can help organizations to go far beyond offering personalized support to each customer and also help you to understand what your customers want from you at the product and service level. Read more at: http://www.tmcnet.com/channels/call-center-management/articles/416191-benefits-customer-analytics-go-beyond-customer-relationship.htm

It is said that a very small percentage of the retailers are keen on using the customer analysis tool in spite of the retail industry being the most refined tool across sectors for analysis of customer behaviour. Dave Nash(director at consultancy West Monroe Partners), has mentioned that this tool is still not as popular as it should be for the very reason of the dearth of relevant customer data that cannot be assimilated into other operational data and also due to lack of skill and the knowledge to use them appropriately. But Elaneor McDonnell Feit (assistant professor of marketing at Drexel University) believe otherwise. According to her, the percentage of retailers investing in developing their customer data set is high. She is of the view that what is required using these data appropriately to take the right decisions for various functions of the firm and implementing them in the most efficient way. Feit has also mentioned a very innovative and out of the box tool for this purpose: Recommendation engine. The recommendation engine is a mechanized tool to facilitate the buying process of the customers, by guiding them find the thing they need. These recommendation engines are tailored for specific businesses and its customers making it unique as a retailer.
Hence, every firm should have a data driven approach within the retail industry which will help the entire economy to grow progressively and efficiently.
Read more at: http://www.cmswire.com/analytics/retail-could-make-better-use-of-customer-analytics/

Companies can use data scientists to prepare data sets, business analysts to develop models using both statistical and machine learning algorithms, application developers can be used to deploy and manage predictive analytics life-cycles, and tools. There are many vendors in the categories of customer analytics, cross-selling, smarter logistics, e-commerce etc. Open source software community is driving predictive analytics into the mainstream. Many Business Intelligence platforms also offer “some predictive analytics capabilities."  Rapid Miner’s predictive analytics platform can also be integrated into the cloud. Read more about this article at: http://www.cmswire.com/cms/big-data/3-vendors-lead-the-wave-for-big-data-predictive-analytics-028684.php?mkt_tok=3RkMMJWWfF9wsRomrfCcI63Em2iQPJWpsrB0B/DC18kX3RUnJb6Wfkz6htBZF5s8TM3DVlJGXqlI4UEKTLE%3D 

In modern world, there has been an increase in communication channels and hence this customer-centric era presents both challenges and opportunities for businesses. Companies must have the skill to connect to the data sources relating to customer experience. Hence, nowadays the big data challenge has gained more importance. In case of customer experience management, the data needs to be combined with unstructured customer feedback data and this is important in order to have a complete picture of customer experience. Data governance plays a crucial role here. One big challenge of customer data is that they don't know which data is more relevant in the first place. Data governance creates the base for the common understanding of the customer across the business.

To read more about customer data governance, please follow the link :

http://www.computerweekly.com/blogs/Data-Matters/2015/05/the-growing-importance-of-data-governance.html

According to Tali Yahalom, consumers want to be treated indivually and not like any other consumer you deal with every day. Companies should realize that changing rules once in a while is less costly than losing a customer. Moreover, social mediums like Facebook, Twitter, and Yelp have become extremely useful in tracking one's reputation online. One should be considerate towards a customer's emotional state of frustration and listen calmly to him/her instead of becoming defensive. Nowadays, companies have tools for collecting consumer feedbacks and suggestions which are extremely important. A company should be optimistic towards feedbacks and try and learn from it. To know more, follow this link: http://www.inc.com/guides/2010/12/the-new-rules-of-handling-customer-complaints.html

Big data is extending the range of data types in banks that can be covered beyond those common transaction data, and it helps to address problems. Some important areas in banking like fraud analytics, customer analytics and web analytics are also enhanced by big data. Today's improved technologies and frameworks enable banks to get customer data, graph data and geo-location data easily from customers, other banking channels etc. which in turn yields significant insights that can be used in customer marketing, risk management and infrastructure optimization. Big data projects are beneficial as they enhance areas like web security, compliance checks and customer analytics and thus cause the banks to make relevant investments in it. Banks need to know and understand the characteristics of the data they need and need to capture more information beyond risk and marketing data. If the users have sound idea of the nature of the available data, their strategies of making a rough analysis and then use the results to guide them in refining the analysis, will be more effective. This approach helps banks to analyze more data and gain insights that were previously difficult to achieve, without changing the current analytical infrastructure of the banks. Read more about this in Jaroslaw Knapik (Senior Analyst, Financial Services Technology)'s article link:http://www.cloudcomputing-news.net/news/2014/jun/16/big-data-set-to-boost-the-effectiveness-of-analytics-in-banking/