It is a fact that ERP or resource planning platform can manage the key business activities like production and supply chain operations. But, nowadays, this ERP system when integrated with machine learning technology, also plays a vital role in keeping your customers happy. And this ERP system can have greater control over the products they eventually receive, thus cutting down on errors. Read more at:  

https://it.toolbox.com/article/how-erp-can-help-boost-your-customers-satisfaction

Many businesses spend a ton of time, effort, and budget to get visitors to B2B website but do not put any effort into staying in front of a website visitor once they leave the website.  Building brand awareness is important as creating brand awareness is critical to the success of your business. There are many reasons as to why it is significant to create brand awareness. Read more at: 

https://www.business2community.com/b2b-marketing/7-b2b-marketing-strategies-to-build-brand-awareness-02233409

According to a research, it was found that 58% of companies do not even believe performance management is an effective use of time. And that is why nowadays, organizations are continually updating their performance management systems to achieve better results and improve the process. This article explores some of the most common trends that can add value if implemented effectively. Read more at: 

https://www.business2community.com/leadership/8-tips-for-improving-performance-management-02234109

Nowadays, the internet is transforming the way companies find and reach their customers. It is a fact that these small businesses are no longer reliant on billboards and television ads to gain visibility as they can launch powerful, focused campaigns to target their specific niche in the market. In a study it was found that organic searches are favored 94% of the time, and according to another research, the first page of links receives 92% of all clicks. This article explores why a strong search engine optimized content strategy is needed for small businesses. Read more at : 

https://www.business2community.com/seo/seo-for-startups-how-your-business-can-benefit-02233145

The Artificial Intelligence industry is growing at an exponential rate and the artificial intelligence market is projected to grow in value to $191 billion by 2024 with a CAGR of 37%. Artificial industry has the capability for machines to make decisions based on logic, data, and information from the past is impacting several industries. From self-driving vehicles to chatbots, thus transforming the way business is done on a global scale. Read more at: https://www.business2community.com/business-intelligence/artificial-intelligence-is-redefining-these-5-major-industries-02232853

As the phrase goes, “everything that can be digitized, will be digitized”, is fast replaced by “If something can be run by algorithms, it will be”. Algorithms are supposed to be performing the following tasks: • Reading resumes: With natural language processing, resumes can be read faster and with more careful eyes. • Using spreadsheets: Soon the analysis made by experts using spreadsheets would be taken over by AI. • Hiring consultants: Since the analysis will all be done by algorithms, hiring consultants is really not needed as before. Hence, for coping up with the changes, one needs to get acquainted with the programs, rent a machine learning expert to design algorithms or make it on your own and invest for the future by learning new software. Read more at:https://www.experfy.com/blog/algorithms-are-replacing-leadership-strategies

NASA has used AI in human spaceflight, scientific analysis and autonomous systems. Multiple programs like CIMON, ExMC, ASE, Multi-temporal Anomaly Detection for SAR Earth Observations, FDL, robots and rovers are currently available at NASA. It is now working on overcoming the barriers that once blocked it from innovations in AI and Machine Learning. Although Machine Learning has been in existence for 60 years, benefits couldn’t be reaped by NASA because according to Brian Thomas, a NASA agency data scientist and program manager for Open Innovation, they are being held back. Read more at: https://www.aitrends.com/ai-world-government/how-nasa-wants-to-explore-ai/

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

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

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

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

With every passing day, data and not instincts, are used for the expanding of business. Data is the new gold, as it helps in determining trend, offering better customer experience, responding better to market demands. However, given the data size is so big, Data Visualization is opted for, making the interpretations easier. The major reasons that data visualization is crucial are: • Data visualizations amplify a story with pictures and visuals. • Data visualizations makes difficult data comprehensible. • Data visualizations help in decision analysis. Read more at: https://www.experfy.com/blog/the-value-of-visual-data-in-decision-making

Financial analysis s beneficial for businesses in the following ways: • Cutting costs: Financial data relating to investments and cash flows are analysed. • Making investments: Financial analysis helps in predicting the returns from investments, thereby enabling the companies to go for profitable investments only. • Forecasting the future: The future of the company can also be forecasted. • Following business trends: Financial analysis relies upon the current business trends and success rates of businesses in the sector. Such analysis helps in recovering faster in case the market suddenly drops. • Management: Financial management is also tracked by the financial analysts which helps in increasing efficiency overtime. Read more at: https://bigdataanalyticsnews.com/big-data-improve-ecommerce-for-businesses-customers/

Predictive modelling software is known for training the model with the dataset with known results to predict outcomes for the new data. The two common types of predictive models are, classification model (example, predict outcome when a component fails) and regression models (predicts a number). The benefits of predictive analysis are: • Improved production efficiency: It allows for effective inventory forecasting, production rates for meeting demand, and the like. • Improved Decision making: It identifies patterns and trends for the data, enabling easy decision making. • Enhanced risk reduction: Predictive analysis, as the name suggests, enables prediction about the future. This is most helpful for a firm to save it from the upcoming risks. • Enhanced fraud detection: Being aware of the trend, a change becomes helpful in detection of fraud. • Targeted, personalized marketing campaigns: Predictive analysis helps in knowing the structure of the market and helps in closely targeting and personalizing marketing campaigns to attract customers. Read more at: https://blogs.opentext.com/predictive-analytics/

Before the introduction of Big Data, only calculated guesses were made by the companies to optimize pricing and forecast demand. Big Data has contributed big time in facilitating eCommerce activities. Some of the ways are: • Predicting trends: This helps in determining the trend, and the type of customers they will face in near future, and keep the inventory accordingly. • Pricing optimization: It helps in calculating the competitors’ position and make decisions about the set of products. • Demand forecast: Studying the data, the expected time of high or low sales can be predicted. • Flexible pricing policy: Prices can be changed time to time depending upon the concerned factors. Big Data provides the data required by managers for expanding the business, taking into consideration every possible factor. Read more at: https://bigdataanalyticsnews.com/big-data-improve-ecommerce-for-businesses-customers/

Machine Learning and Deep Learning both uses the algorithms fed into them. While in the first, the algorithm needs to be told how to make accurate prediction, in the latter, the algorithms are fed via neural networks, making the operation similar to a human brain and involving lower chances of mistakes as compared to Machine Learning. While Machine Learning gives result for a numerical and text field, Deep Learning also enables face, voice and handwriting recognition. Also, with new data fed into the system, the accuracy rates by Deep Learning are much more than by Machine Learning. Although Deep Learning is anyday better than Machine Learning, Machine Learning plays a vital role in the existing economy. Read more at https://www.analyticsindiamag.com/understanding-difference-deep-learning-machine-learning/

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

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