SigmaWay Blog

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/

According to authors, the days of journeying to a travel agency and sitting at the desk of an agent to book a trip have all but disappeared as technology is increasingly putting that level of personalised service in the palms of our hands by launching travel apps that incorporate artificial intelligence and technology .One such app is the Green Card app, that simplifies the process of getting a green card to  enter  into a foreign country, on the basis of a bot, that files out a questionnaire ,which when answered,  generates  a package of documents that can be filed with U.S. Citizenship and Immigration Services to complete the application process. This saves ample time. Another personal travel assistant Mezi,  designed for travel management companies, corporate and travel agents was launched two years ago and claims to have AI capabilities that customises travel suggestions based on past searches and online habits. Read more at https://aitrends.com/mobile/a-i-innovation-finds-a-home-on-mobile-devices/

According to authors, two of the machine learning APIs introduced by Google in the month of March, has moved forward into a new dimension i.e. open beta status. Cloud Natural Language APIs which analyses syntactically and assigns a constituent structure to the meaning of texts, helps in finding out the sentiments expressed via texts and online reviews, the syntax of the text and assists in understanding  entities like people, places, events, products, and media. New York used this techie for exploring sentiment analysis of  the stories published in The  New York Times and it was found that relevant updates about news didn’t enjoy a favourable environment, whereas, the arts stories enjoyed positive support. Read more at https://aitrends.com/business/googles-cloud-adds-machine-learning-apis/

Deep Learning(DL) is a subfield of Machine learning concerned with algorithms inspired by the structure and function of the brain called Artificial Neural Networks. It  interprets the raw data through multiple processing layers, where each of these layers, uses the output of the previous one as its input, thus  creating more abstract presentation, tackling conceptual problems ,like image classification and natural language processing  and helping to infer logically. Industries that leverage Machine Learning at present , can switch over to DL approaches in future as it’s an approach of AI , which is showing great promise when it comes to developing the autonomous, self-teaching systems which are revolutionising many industries. DL drives sales, increases engagement  and improves user experience, thus it  will be the future of Personalization, which enables a business organization to enjoy amass customer appreciation. Read more at  https://aitrends.com/deep-learning/deep-learning-personalizing-internet/

Business analytics and business intelligence are like two sides of a coin. But there is a difference between them. Business analytics is like an umbrella term and intelligence is a part of it together with other aspects of business applications. Once a person runs a business, that person will be able to understand the difference between them, that is, business intelligence is like accessing to all kinds of business related data and software's and put them into the analysis. Business analytics is something using your business intelligence into your data and optimizing the performance of the business. To have a successful business, it is important to follow both. Business intelligence is generally used to look over the previous data, whereas business analytics look to the future needs of the business. It's necessary for a businessman to understand its difference for making any business decisions or predicting for the future. Read more at: http://www.analyticbridge.com/profiles/blogs/business-analytics-and-intelligence-compared

As from the past record, Indian retail industry transformed a lot. It can cross over USS $1.3 trillion by 2020. It accounts over 10 per cent of the Indian GDP. And now as GST implementation brings over greater transparency, reduced trade barriers and improved credit. 1.) pricing and promotions: Due to GST product pricing will be affected and also companies in B2C segment will be significantly affected. GST will impact prices of goods at every stage in the supply chain and retailers will need to review their prices studies by vendors. 2.) EOSS(end of season sale): there will be difficulty in clearing the stock of last year.3.) reduced rates of apparel and  changing purchase pattern. Read more at:  http://analyticsindiamag.com/can-retail-analytics-step-game-big-box-stores-rush-embrace-gst/

So you have heard of these 2 brothers (Chetan and Rishi), but you didn’t know how they re-built the success of their family business. So Chetan did Bachelors in petrochemical engineering, & MBA . Rishi did Bachelors in Science and Business Administration. But they came to re-built their family business of manufacturing ceramic tiles, Kajaria Ceramics Limited. It was an year of 2000, IT revolution in India had just started, and Rishi started an online platform Floortoroof.com to combine the agents all over country. After their visit to China, they found out, they can easily import and sell the tiles into India, of course they have to cut off certain costs. Also to expand Chetan added partners to increase their reach to the local market. Also with introduction of SAP and IT integration, Rishi transformed day to day business. And it turns out all in favor with the highest profitability margin of over 18 percent and now it is all set to open a new plant in Rajasthan. Read more at: https://www.entrepreneur.com/article/296656

We all know Watson(IBM computer) ‘s prowess already been tested in cancer research. Watson has proven its worth in editing a thriller film trailer, composing music, providing excellent customer service. But has Watson proven its worth in the field of fashion? The fact that IBM is betting big on Watson is abundantly clear and it is now being leveraged by big fashion houses to utilize social data to better interact with customers, improve sales with highly targeted marketing campaigns and predict customer orders.  The AI-based collection, aptly titled Future of Bollywood Fashion was created by analyzing around 600,000 publicly available historical fashion runway images from the last decade. Read more at: http://analyticsindiamag.com/future-indian-fashion-ai-watson-makes-splashy-debut-indian-runway/