Companies might think writing and maintaining a blog takes up huge chunks of time but these following ways will prove them wrong about this strong marketing tool. Blogging is pretty easy as there are a lot of blog themes available to get you going. Companies can share their expert status to consumers by their blog, also increase their sales leads by more traffic on their blog. Blogging helps in better customer retention as you get their feedback via comments on the blog. Increase the sales as customers might trust you by something they read on your blog and come back to you. Also, with a lot of traffic, you may publish according to your customers interests and let SEO take care of the rest. Read more at :

http://www.business2community.com/blogging/6-reasons-marketing-efforts-include-blog-01879648#mfu6udB02rI0WxJ3.97

Transparency in companies, publishing dashboards to everyone to keep everyone updated of the progress and not being able to adjust data can be scary for some people. A BI fail in a large corporation, we often consider faulty process or management to be the reason but it might be due to lack transparency between managers, board members and shareholders. Managers always refer to preferring  accuracy over speed, but accuracy takes months to implement so managers tweak the data which makes it useless. Nowadays, new generation managers are politics free and depend on technology and SaaS apps for improvement and speedy delivery of data. They don’t mind sacrificing 100% accuracy to 80% if they can get the job done 5-10 times faster. Read more at :

http://www.business2community.com/business-intelligence/dark-side-business-intelligence-01845255#7ot2lqmRUYVhQfAj.97

There are many ways in which a first-time customer will feel enticed to be a full-time customer and maintain a long relationship with the company. One should understand the profile of the typical customer of the company and segment the group both geographically and demographically. Giving customer's a positive experience by accurately replying to their queries goes a long way. Companies should understand that customer retention is much more than the cost incurred in the advertising campaigns. While offering subscription information, companies should keep in mind not to cost their customers anything. Rather, moving subscriptions to social media can reach thousands customers within minutes. Hence social media posts should be updated according to the customers interests. Read more at :

https://www.smartdatacollective.com/customer-feedback-data-analysis-keys-good-customer-retention-rate/

Organizations are evolving from a traditional environment to  digital workplace reveals that gaining competitive advantage and improving business process are among the top goals of digital transformation strategy. Today, the digital workplace is no longer just made up of managers and co-workers collaborating with one another to complete projects, It’s increasingly populated by ‘virtual employees’ who do not exist in a physically , but play an important role. While AI technology is still in its infancy, it is sufficiently advanced to be working its way into companies in the form of virtual assistants, in certain industries such as banking, virtual tellers and advisors. Embedded into  applications, virtual assistants draw on AI engines and machine learning technology to respond to basic queries. 64% use analytics to improve their customer services, 58% use analytics to benchmark their workplace technologies. Read more at :

http://www.dataversity.net/artificial-intelligence-analytics-accelerate-pace-digital-workplace-transformation/

Data is an important aspect of decision making and for valuable insights over the data, BI has emerged crucial in organizations. Some useful ways to manage your data and team are : 1.Invest in a robust BI service like Google Analytics or CoolaData so as to get better insights on behavioral analytics and better collaboration. 2.Break down silos - when organizations go through silo effect and information stops flowing, BI can prevent this through transparency. 3.Teams should acquire data analysis skills and grow as they work. 4.One should relate to the context, not depend solely on the numbers but on the why, how. 5.Decide on how to decide for better data implementation. 6.Drive action through insights, study how trends correlate and act accordingly. Read more at :

http://www.networkworld.com/article/3197753/big-data-business-intelligence/6-ways-to-manage-your-data-and-team.html

Smart-phones have widely changed our standard of living and access and management of our money. A recent study by EY and BBA states that customer usage of banking apps have risen by 354% in last five years, with an average of 159 logins per second. Not only for banking purposes, UK customers use mobile tools to manage their mortgage and investments, credit cards and savings. Some suggest that this increased usage on financial apps isn't  short term but will have a long term effect. The technology is helping customers in this financial revolution by adding check imaging, contactless payments and biometric identification. This will help in the launching  of Open Banking in 2018 when customers will have greater choice and control over their financial lives. Read more at :

http://banking.com/news/apps-transforming-personal-finances/

 In the recent days, prevention of fraud is a very difficult task and banks should keep in mind some non-financial signals that might prevent a fraud. Fraudsters take advantage of the growing technology where a simple code interception can lead a criminal to hack a person's credentials. It is difficult to suspect any change in contact details as people change phone numbers very frequently and so the bank managers should put this down as a sign of potential threat. Bank managers should have the correct  solutions for these fraudulent actions happening. Fraud managers should have the latest fraud-preventing programs in order to receive the signals of a fraud before hand and can prevent it from causing severe damage. Read more at :

http://banking.com/analysis/non-financial-events-must-play-role-fraud-prevention-program/

Internet has opened up new possibilities for communicating, from emailing and blogging to mobile video chatting. Most businesses now communicate with their customers through multiple online channels. As brands prioritize this digital experience, they often overlook communicating by voice is faster, easier, and more effective than typing messages. According to the advertising and marketing advisory firm BIA/Kelsey, calls to businesses are expected to exceed 169 billion per year by 2020. These calls are 10-15 times more likely to generate a successful sale or follow-up activity than digital form submissions, which means they are more efficient in generating revenue. Voice is central to communication, and because it’s not strictly an online channel, it presents a challenge for brands that treat digital transformation as a matter of generating clicks and website views. The challenge is particularly acute for businesses that operate in categories such as insurance, lending, travel, or healthcare. In these “considered purchase” categories, consumers typically reach out to a brand after conducting preliminary research online, and are thus well qualified to buy. Read more at https://hbr.org/2017/07/your-customers-still-want-to-talk-to-a-human-being

Nobody sets out with a plan to fail, but so often people let obstacles get in the way of their success. They start off towards their goal, full of energy and ambition, and then years later we may find them still stuck in the same dead-end job or dreaming of the life they could have had. The author here, Daniel Milstein, CEO of Goldstar Family of Companies mentioned here that through his own successes in starting up four companies, he figured out a few things that can stall us. They are Time, Lack of Focus, Holding Back, Attitude and Fear. According to the author, one should obliterate the obstacles and move ahead. Read more at https://www.entrepreneur.com/article/297278

Major reasons why chatbots fail is their inability to understand the context if someone is being sarcastic. They fail to decipher if customers try to mix two languages or more. More than aiming for convenience, it ends up harming the user experience. Trying to make the bot answer every query rather than on a particular area makes it dysfunctional. In many cases, bots may fail to have human intervene into a problem or escalate the issue that it is not able to answer. It is more about how the chatbot is deployed. Disconnect occurs when businesses put chatbots without thinking through the customer or internal user journey. Nonetheless, chatbots would still make sense for functional activities for e.g. looking for nearby restaurants, flights between two cities, weather etc., instead of evolved transactions like choosing products and adding to cart that’s more suited to a browser experience. The technology is here to stay but it is not mature currently. In next three-five years, there will be a  lot of industry segments replaced by chatbots. Read more at https://www.entrepreneur.com/article/297633

GST regime necessitates a high level of synchronization between tax payer’s application, invoicing software, and  GST system, which without automation would be difficult. These include item level detail in invoices, maintenance of trail of all amended entries, reconciliation of sales and purchase register between vendors and buyers on a minimum three monthly returns and other events such as auto reversals demand or automation of tax compliance process within any tax entity. If anything is a miss, it will directly impact the business’s compliance rating and act as a deciding factor for the buyers, lenders and insurers, whether to deal with that business or not. Till now, Goods and Services Network (GSTN), a private company set up to provide IT infrastructure to the government, taxpayers and stakeholders for GST implementation have appointed 34 GSPs which will offer support and services in form of GST APIs to help tax payers and businesses in compliance. Functionalities available through GST APIs includes registration of tax payer and consultants, return filling , payments, ledger maintenance, etc. Factors such as intuitiveness of reconciliation, validation and tax determination engine, data security, storage and privacy policies etc. should be taken into consideration by taxpayers while choosing the right technology vendor to ensure smooth compliance. Read more at https://www.entrepreneur.com/article/297632

To all voracious readers, here is an ideal list of books to have in bookshelf of every data scientist and analyst. These books cover a wide range of topics and perspective, which would help to become a well-rounded data scientist and analyst. Here are a few:

• R Cookbook by Paul Teetor

• Python for Data Analysis by Wes McKinney 

• Web Analytics: An Hour a Day by Avinash Kaushik 

• Web Analytics 2.0 by Avinash Kaushik 

• How to Measure Social Media: A Step-By-Step Guide to Developing and Assessing Social Media ROI by Nichole Kelly

• The Visual Display of Quantitative Information by Edward R. Tufte

• Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics by Nathan Yau

• The Wall Street Journal Guide to Information Graphics: The Dos & Don’ts of Presenting Data, Facts, & Figures by Dona M. Wong

• Now You See It: Simple Visualization Techniques for Quantitative Analysis by Stephen Few

Read more at https://www.analyticsvidhya.com/blog/2015/06/infographic-read-books-analytics-data-science/

Every business wants to improve its customer experiences and they want to turn its ordinary customers into a loyal customer. In order to make a fabulous customer experience there are 4 ways to attract customers and foster lifelong loyalty. 1) Use Technology to provide Top-Notch Customer support- Customer is needed to provide with mobile customer support, live chat, self-service management, social media support and Omni channel support.  2) Create Personalized Experiences-Customers are needed to be treated in the more personalized manner, or by catering messaging, offers and creating more communication. 3) Leverage Big Data to Get to Know your customer on an Individual level- Understanding the customer on different levels- behavioral, contextual, service-interaction ,social and consumption  4) Reward Customer Loyalty to Foster Brand Ambassadorship- Customers are needed to be given loyalty awards through brand leveraging loyalty programs. These all over enhance the customer experience and the business will able to get loyal customers. Read more at: https://www.ngdata.com/ways-to-improve-customer-experience/

Nowadays companies are on the hunt for analytics executives and organizations in the industry have created hundreds of executive roles in analytics. Employers are hunt for leaders who understand the data and threats and opportunities related to it. In order to identify for the analytics initiatives the males and females are divided according to age groups and experiences which lead them to their roles. The executives landed into their current positions by one of their career paths- 1) Linear- It’s an upward movement of the analysis function who has experience in computer experience, statistics and analytics and ability to gain customer attraction 2) Nonlinear- it’s a movement between and within analysis function and are experience in IT, marketing and accounting.  3) Parachute- there is no previous work experience needed in engineering and technology and should have knowledge of project management, telecommunications, mobile systems, project management and security. Read more at: http://www.cio.com/article/3182718/analytics/3-paths-to-analytics-leadership-roles.html

Both terms web analytics and digital analytics are interchangeable. But there is a difference between two of them. When Web analytics association changed its name to the digital analytics association then the word digital analytics came up. During the early days of the internet, Web analytics were analyzing the website data, such as users, visitors, links and many more alike. When other forms of online came like emails, search, social, etc., then a new term called digital analytics came into being where all these channels were analyzed. Now all the online channels have been transformed from web analytics tools to digital analytics tools. Web analytics is the analysis of website data, whereas digital analytics is an analysis of all data from digital channels that includes websites also. But till now web analytics are still searched more than digital analytics according to Google Trends chart. Read more at: http://webanalysis.blogspot.in/#axzz4hutH4lMG

Few challenges being faced in translating the lessons of predicting analytics from other verticals in manufacturing. The objective of this predictive analytics is to get the correct business decisions and it will impact the design and service of the product. The data is being updated continuously through their supply chain. The predictive models are used to connect the real world data to digital twin models of the virtual world. This helps in better understanding and working of their business plus with the on the factory work. Predictive analytics help to find the issues related with the product quality, performance and its features. These helps in better designing the product features and make it to optimum use of it. The predictive model is quite accurate in giving information about the risk failure, improving the machines to put in a better use as well as it gives the best correlation between job characteristics and job failure. Models are being trained through environmental data and IoT data and few factors which affect such data too such as environmental hazards, weather and many more. Its benefit for the business to take predictive analytics into consideration. https://www.ngdata.com/ways-to-improve-customer-experience/

According to authors, innovations in the areas of Artificial Intelligence(AI),Machine Learning and Deep Learning are beginning to dominate the technology landscape but the actual user experience and concerns about privacy and security are obstacles that can prevent AI from reaching its potential. Despite it’s negative implications, a Consumer Intelligence Report by PwC, revealed, that most consumers believe AI will help humankind, by solving complex problems, like fatal diseases, city traffic, cybercrime, infrastructure and fraud, that plague modern societies , thereby helping people to live more fulfilling lives. AI could revolutionize  personalized healthcare by analyzing data thus helping in maximizing life expectancy and enhancing wellbeing.AI will expand access to financial, medical, legal and transportation services to those with lower incomes thus emerging  both as a process and a product that instills trust and transparency in consumers. Read more at https://aitrends.com/security/consumers-welcome-ai-despite-lingering-privacy-concerns/

According to authors, modern-day marvels are the result of machine learning, which are programs that combine through millions of pieces of data and start making correlations and predictions about the world , by using machines that uses cold hard data to make decisions that are sometimes  more accurate than a human’s, thereby reducing biases. Computers don’t hold any inherent biases, as machine  knows only one approach i.e. the objective analysis and are capable of analyzing massive amounts of information, thus having  a distinct advantage over humans. Utilizing the data for machine learning, can uncover contradictory and surprising results by making data more accessible, more understandable and  enabling the organization to achieve a new level of business intelligence, thus empowering decision makers at all levels with a powerful tool. Read more at https://aitrends.com/machine-learning/machine-learning-cure-decision-bias/

According to authors, the implication of big data is the quantity is paramount, the returns generated do not match the quantity of data generated. Experts point out, it is not per se the data that should be big, but the primary factor that counts is the diversity of data, the amount of richness they provide and the focus on accelerating human understanding of data , which has the potential to create output subject to increasing returns. More data retards innovation, the speed of experimentation and iteration. However IT teams helps in bringing order to chaos, in data and analytics, by managing data infrastructure, such as data warehouses and production processes . Data scientists, who’re occupying the space between IT and business consumers , have made enormous strides in getting grip on their data, analyzing and acting on it, thereby avoiding imbalance. Read more at https://aitrends.com/big-data/three-big-data-developments-no-one-is-talking-about/

According to authors, the development of Artificial Intelligence (AI) creates several opportunities for retailers to improve their customer services , insights and business processes. AI makes it possible to generate insights on a scale like never before, it does this by combining customer data  across all platforms( from social media to CRM) like past purchases, search habits, click behavior, age, gender, season of the year and various other variables and self learning algorithms. By crawling the web and aggregating various forms of customer data, AI gives retailers the opportunity to engage with customers on a more personal level. Through chat applications such as Facebook and Messenger and by using chat bots on websites, the potential customers can communicate with the retailers using speech or text, that will assess and answer customer queries, thereby assisting in the selection process and helping in the execution of simple tasks. Read more at https://aitrends.com/retail/robots-ai-retail-8-things-must-know/