SigmaWay Blog

SigmaWay Blog tries to aggregate original and third party content for the site users. It caters to articles on Process Improvement, Lean Six Sigma, Analytics, Market Intelligence, Training ,IT Services and industries which SigmaWay caters to

Artificial Intelligence: A powerful tool for mental health crisis

Mental health crisis is a matter of huge concern in recent times where one-fourth of the adult population is estimated to be affected by mental disorders. Depression alone affects roughly 300 million people around the globe, as stated by World Health Organization. Artificial Intelligence (AI) offers multiple opportunities to people suffering from mental disorders. Computational Psychiatry and specialized chatbots for counselling and therapeutic services are the two emerging fields where AI is expected to yield the biggest benefit. Computational Psychiatry combines multiple levels and types of computation with multiple types of data to improve understanding, diagnostics, prediction and treatment of mental disorders. Besides, AI can help researches discover physical symptoms of mental illness and track within the body the effectiveness of various interventions. Moreover chatbots provide immediate counselling services to the patients at a cost which is lower than seeing a psychiatrist or psychologist. This has expanded the coverage to a broader circle of people who require treatment. Thus the development of AI for mental health promises better access and better care at a cost that won’t break the bank. Read more at: https://datafloq.com/read/artificial-intelligence-for-mental-health/6558

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Machine learning and the future of beauty industry

Machine learning is progressively transforming the way we work, live and interact. It is effectively applied in almost all sectors with beauty industry being no exception. Machine learning can help the beauty industry in several ways. It is expected that computer vision would help recognize facial features, analyze the data obtained and come up with a prediction or conclusion about the appearance. At present, data scientists are working on AI systems that have the ability to understand human face. If it works out, we no longer require to physically test out new looks and products. Data analysis will lead to better cosmetics. Leveraging data means better, long-lasting formulas. Nowadays, startups and industry leaders are offering machine-based advice on finding one’s personal style. For instance, Sephora and Mira uses worldwide tests and computer vision helping customers choose the perfect combination of foundation, complexion, etc. Some businesses like Olay have developed applications to determine skin needs of customers and come up with personalized products. Thus Artificial Intelligence with its machine learning and computer vision can go a long way in ensuring customer satisfaction. Read more at: https://medium.com/sciforce/machine-learning-changing-the-beauty-industry-ab3a2fa0aaf

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Big Data in Economic Prosperity

Big Data, if utilized properly, is believed to become the historic driver of progress. It plays an important role in the fields of public security, healthcare, poverty, to name a few. Video surveillance and facial recognition using big data is far more effective than reviewing the footages manually, which can be erroneous. It also helps in avoiding cybersecurity threats. Predictive models using big data can predict for future attacks even before their occurrence. With the application of big data in healthcare sector, there has been a shift from treating illnesses to proactively maintaining our health and taking certain measure for preventive care. It plays an immense role in the education sector as well. By understanding the needs of each district, it gives schools the opportunity to build innovative educational techniques. Big data solves urban transportation problem by enabling government agencies develop alternate routes to ease traffic. It helps in alleviating the dangers of food scarcity. It is time to embrace big data as it opens up opportunities to encourage economic prosperity. Read more at: https://datafloq.com/read/5-applications-big-data-in-government/65

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Why Reputation Management matters so much?

Reputation management deals with maintaining and controlling a group’s, an individual’s or a brand’s reputation. The reviews that the customers give on a brand greatly impact how search engines and prospective customers make decisions about that brand everyday. Every business tries to take its reputation management strategy to a next level. Sentiment analysis determines the nature of response to a particular product or brand- if its positive, negative or neutral. It helps to analyze customer feedback or how they feel towards a brand. Besides, competitive intelligence is the key to winning and maintaining business. Understanding one brand’s performance relative to others is necessary. Generating new reviews help businesses to stand out which in turn helps in maintaining the reputation. This can be done by simply asking customers at checkout to write a review if they are willing to. However asking for reviews too often is not a good idea as this can annoy the customers. Hence businesses must learn to create an effective review response. Read more at: https://www.thedrum.com/industryinsights/2019/06/25/how-take-your-reputation-management-strategy-the-next-level

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Utilization of AI to refine the entertainment marketing strategies

Merging entertainment with data is a well-known concept. The marketers and content-creators have always focused on strategies that will resonate with the audiences and keep them engaged. Over the past few years, there has been an evolution of AI in the marketing strategies of content creators, brands, networks, etc. AI uses the deep learning algorithms that can digest, asses and contextualize unstructured data quickly to derive actionable insights. AI can analyze millions of pieces of content at a time, with the help of deep learning which is undoubtedly beneficial for the content creators and marketers. Deep learning helps in predicting whether a campaign will be successful even before it starts. Thus marketers are increasingly turning to deep learning algorithms to make better sense of the contents. Read more at: https://www.thedrum.com/industryinsights/2019/04/03/the-evolution-ai-entertainment-marketing

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The era of Influencer Marketing

Over the last few years, industries have become more sophisticated due to the increasing demands of influencer marketing. Many companies are planning to increase their influencer marketing investments to develop long-term partnerships with creative influencers on social media. Influencer marketing is nothing but a hybrid of old and new marketing tools, taking the idea of celebrity endorsement and placing it into a modern day marketing campaign. However the Influencer marketing faces a lot of challenges. Due to inconsistency in data, companies tend to jump from one influence marketing provider to another. However, we can expect to see an evolution in gathering and usage of data in the coming years. Brands are increasingly becoming more educated and competent. Marketers and brands want tools that gather all metrics relevant to value generation and tools that can track the performance from multiple social media platforms. Those providers that fail to deliver these requirements often fall behind as the market evolves. Moreover influencer industry is built on trust and authenticity, so the rise of fake followers erode business and consumer trust. Hence in order to protect the customers, the influencers must take a stand against the rise of fake followers. Read more at: https://www.thedrum.com/industryinsights/2018/12/21/why-we-need-get-little-smarter-about-influencer-marketing

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Criminals making felonious use of Artificial Intelligence

Cyber criminals, also known as hackers, use computer systems to access business and personal information for malicious purposes. There is no doubt that criminals are the most creative people in the world and the development of Artificial Intelligence has only made them stronger. Since the tutorials and tools for its development is widely available in the public domain, AIs use for attacking purpose is hugely unrestrained. Machine learning poisoning is one of the ways for criminals to circumvent the effectiveness of AI. Today we live in a world of chatbots. Most people do not realize how much personal information AI-driven bots may know about them, which makes them easy prey for experienced cybercriminals. Moreover criminals could harness machine learning technology to sift through huge quantities of stolen records of individuals to create more targeted phishing emails. However the biggest fear remains in the fact that the fully unstoppable AI creature will seize the world one day. Thus AI security abuse must be prevented and humans being much better than machines must understand its cause and effect. Read more at: https://resources.infosecinstitute.com/criminals-can-exploit-ai/#gref

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Predictive Analytics helping retailers in customer retention

Predictive Analytics make predictions about the future events based on current data. These days retailers use it to determine the future needs of the customers. The biggest challenge faced by retailers today is customer retention. Predictive Analytics is bringing about a huge change in the retail experience altogether. Eminent retailers like Amazon is using predictive analytics to make customer recommendations based on purchasing history. Furthermore, development in Artificial Intelligence and machine learning is boosting its use. These developments in turn are helping the retailers gain a competitive edge. However tech giants like Google, Microsoft tend to keep the cutting-edge innovations for them. The new and innovative predictive analytics must level the playing field for small medium industries. Read more at: https://channels.theinnovationenterprise.com/articles/retail-reaping-rewards-predictive-analysis

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Revolutionizing Indian Agriculture with digital farming tools

Since the emergence of Green Revolution in the 1960s, Indian policies have focused on ensuring national food security. However the small and the marginal farmers suffered a lot as the Green Revolution policies failed to increase their income. This has resulted in an increase in farm indebtedness and distress leading to farmer suicides all over the country. Over the last few decades Indian agriculture has seen massive technological developments and opportunities. The recent policies focus on increasing farmer incomes through digital innovations to give the farmers greater access to technology, risk management, finance and markets. Digital innovations enable the farmers to have credits at lesser risk and cost. Digital extension services provide real-time advice to farmers .Among the innumerable obstacles faced by Indian farmers, some include distance from the market, dependence on moneylenders for access to capital, huge cost of transportation, etc. Digital solutions are seen as a way to overcome these obstacles by providing farmers transparency and unmediated market access. Thus digital innovations are greatly helpful in improving farmers’ livelihoods and Indian Agriculture as a whole by making it more market-oriented. Read more at: https://www.thehindubusinessline.com/opinion/the-digital-route-to-transforming-farm-sector/article26006290.ece

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MACHINE LEARNING OPTIMIZING CUSTOMER EXPERIENCE

Machine learning applies artificial intelligence to automatically learn and improve from experience without being explicitly programmed. Machine learning applications are generally applied to those areas which involve processing lots of a data; a field where humans aren’t well-equipped. Machine learning applies discovered insights in ways that can optimize the customer experience. Chatbots provide effective solutions by stimulating an interaction with a customer service representative or resolving simple inquiries. Machine learning helps chatbots learn when to give specific responses, from where to gather necessary information and most importantly when they should hand off a conversation to a human agent. Virtual assistants, with the help of machine learning focus on specific areas where they can provide assistance to the customers. In order to continually optimize, customer service needs measurable analytics. Machine learning can help add a predictive element to support analytics. Thus machine learning helps in delivering better customer experiences. Read more at: https://www.business2community.com/brandviews/zendesk/how-is-machine-learning-being-used-in-customer-service-02215814

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ARE EMPLOYEES THE WEAKEST LINK IN COMPANY’S SECURITY CHAIN?

Irrespective of the business size, employees are always on the front lines of the company’s cybersecurity. Based on studies, it has been concluded that two out of three cybersecurity incidents occur because of employee negligence. Employees can be the company’s best defense or its biggest liability. Therefore, cybersecurity training is very important. Employees tend to reuse the same password everywhere. This is a risky practice making it easier for sensitive information to go in the wrong hands. Company Policies must ensure that employees change their passwords every few months. Moreover employees should be taught to spot phishing attempts, including spelling and grammatical errors, suspicious attachments, request for personal information, free offers etc. Sometimes just visiting a site can infect the entire network. In order to maintain security, employees should be taught to hover over the links before clicking on them to see the actual URL; if it looks suspicious it would be best to avoid it. Thus as we see, untrained employees can be the biggest cybersecurity threat. Hence companies should shore up their security systems, starting right from its employees. Read more at: https://channels.theinnovationenterprise.com/articles/employees-cybersecurity-threat

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THE PHENOMENON OF ‘’PINK TAX’’ IN CAR INSURANCE RATES

The existence of a gender based price discrimination where women’s products are typically more expensive than men without any reasonable cause is widely known as ‘’pink tax’’. Lately, this gender discrimination has extended to car insurance with women paying more despite men being risky drivers. A recent study concluded that women especially older ones pay higher care insurance in at least 25 states. The Consumer Federation of America (CFA) revealed that insurance company not only charges different rates based on gender but also on the city in which a particular person lives in. While some countries including California, Massachusetts have already prohibited gender based car insurance pricing, we can hope that greater reliance on big data can provide some solution. Big data is greatly helpful in determining fairer and accurate insurance rates based on relevant factors. Read more at: https://channels.theinnovationenterprise.com/articles/inconsistent-correlations-between-gender-car-insurance-rates

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BUSINESS INTELLIGENCE TOOLS: THE GAME CHANGER IN SMALL BUSINESSES

Business intelligence (BI) tools, used to prepare, present and analyze data are now transforming the small businesses. The chief role of BI is to convert tons of raw data into useful information that the business executives can use. Small businesses will grow if and only if it can break down and analyze the information available on its server. BI tools help businesses make smarter decisions and also in Customer Relationship Management (CRM). Businesses must always find ways to understand their customers better. This is where BI solutions like YellowFin and Looker play a massive role.BI tools also help in boosting data governance and compliance. Thus BI helps small business owners avoid mistakes by keeping data accurate and up to date.Read more at: https://www.business2community.com/business-intelligence/how-business-intelligence-tools-are-transforming-small-businesses-02208030

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NEURAL NETWORKS: UNFOLDING THE BLACK BOX

The most powerful algorithms extensively used in the field of deep learning are neural networks. Here we focus on the artificial neural networks which are nothing but the computing system based on the structure of human brain. It is a type of machine learning which is used for detecting patterns in unstructured data. A lot of business applications today depend on neural networks to solve various complicated problems. However companies use neural networks in various ways. For instance, as explained by LinkedIn’s Deepak Agarwal, neural networks are used in LinkedIn along with text classifiers to detect spams. Neural networks are widely used in activities like marketing, finance, operations management, insurance etc. Thus the capabilities of artificial neural networks are inexhaustible. Read more at: https://www.cmswire.com/digital-experience/what-is-a-neural-network-and-how-are-businesses-using-it/

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USING VIDEOS IN EMAIL MARKETING

Nowadays video based marketing is a great way to engage with customers and increase followers. Recent studies have found that open rate increases by almost six percent if videos are included in emails. Not only that it is an implausible way to ensure engagement and increase sales substantially. Videos in email save time and are easily understandable to the viewer. Apart from that, it is cost effective and it quickly grabs audiences’ attention. However companies must be well aware of the fact that using videos in each and every email can go against the marketing tactics resulting in ignorance by the subscribers. Being creative, choosing the right email provider and monitoring open rates are some of the important tasks that should not be neglected while using videos in email marketing. Read more at: https://www.business2community.com/video-marketing/your-2019-guide-on-how-to-use-video-in-email-marketing-02211325

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IS YOUR BUSINESS A VICTIM OF BAD DATA?

Bad data generally refers to the faulty or flawed data. All the marketing strategies and tactics become futile if the business falls prey to bad data. Studies have found that bad data are expensive and can cost upto $3.1 trillion per year. One of the important contributors of bad data is the reliance on traditional lead generation tactics by the companies. Third party intent data is a savior to the bad data problem. It helps companies overcome the inaccuracies that might have existed in their Customer Relationship Management (CRM) for years. Companies must ensure that the data provider is a trusted one. To overcome bad data problem, the intent data must be accurate, actionable and targeted. Read more at: https://www.business2community.com/marketing/solving-the-bad-data-problem-in-marketing-02210818

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Do emotional intelligence training and sales go hand in hand?

Nowadays emotional intelligence is changing the way we view sales. It is an effective way of understanding customers’ emotions and analyzing their buying behavior. An emotionally intelligent sales person must possess qualities like managing client relationships, self-awareness and self-management. Convincing the customers to buy products is an important task. An emotionally intelligent sales person must be able to resolve any issue that might arise. Being aware of how one’s action affect others can help develop a sense of self awareness. A self aware salesperson should know the right time to talk and should be an active listener. To be able to control one’s emotion is an important trait that a salesperson must possess. Emotional intelligence training therefore gives an all new perspective to sales. Read more at: https://www.business2community.com/sales-management/why-emotional-intelligence-training-is-vital-for-sales-02208645

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Big Data Analytics: Helping Organizations detect frauds in early stages!

Big Data gained popularity during mid-1990s. But what exactly ‘’Big Data’’ means? It generally refers to the voluminous data, which the conventional data processing system is unable to process. It is widely used because of its advanced fraud detection and prevention techniques. The severity of frauds in credit card industry, insurance fraud and email based frauds are not new. Using big data to understand the card usage pattern of every customer, building specific fraud detection models, analyzing the geographical location of a person, can help companies prevent fraud. Pattern analysis with the help of big data helps banking sector detect fraud beforehand. Big Data helps prevent Medicare fraud  within minutes! Thus Big Data helps companies perform tasks on a much broader scale than a human being can actually do. Read more at: https://channels.theinnovationenterprise.com/articles/how-big-data-is-being-used-to-improve-fraud-detection

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Artificial Intelligence and Healthcare

In the modern era, with almost all industrial sector adopting new technologies, healthcare sector is no exception. Artificial Intelligence has changed the way in which we seek medical care.The use of artificial intelligence in medicine has reduced manual tasks and increased efficiency and patient care. With robots already assisting in various surgeries, few other AI systems used in medical sectors are WOEBOT,DA VINCI, PARO etc. As of now, there is always a high skilled surgeon in total control of the robots. It is believed that we have to still go a long way before robots have the sensitivity to perform surgeries on their own. They lack the common sense and the experience that humans possess. Thus a balance between human and machine is required. Read more at: https://community.nasscom.in/communities/iot-ai/artificial-intelligence-in-the-healthcare-sector.html

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Are we learning data science the right way?

In the words of Favio Vazquez, “Data Science is not just knowing some programming languages,math,statistics and having domain knowledge.’’Data science enables a person to evaluate the data and predict the present and future of the world. The solution to the optimization problems must add value to the business or organization. Mastering the craft is what it takes to be a successful data scientist. Having a good knowledge of statistics or math is never enough; practicing hard so that one can apply the tools to solve real business problem is the key. Interpretation is an important part of data science. Through modeling, we can decode the complex data and transform it into something useful and simple. Finally questioning and analyzing our understanding make us better learners.  Read more at: https://medium.com/swlh/the-3-biggest-mistakes-on-learning-data-science-f782e1a8abec

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