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Machine Learning in Business Analytics

Reading Time: 2 minutes
What is business analytics? Using data to improve business outcomes | CIO

Analytics is an essential part of every business. It helps to assess a market and company’s sales, identify customers’ needs and modern trends, realize which products or services of an organization are in demand, and overall gives a perspective on possibilities of growth. Machine learning for analytics is the process of using ML algorithms to aid the analytics process of evaluating data and discovering insights with the purpose of making decisions that improve business outcomes.

Customer Segmentation

Machine learning algorithms can automatically segment customers into distinct groups based on various criteria, such as purchasing behavior, location, or product preferences. This segmentation allows marketers to target each group with highly relevant content and offers.

Predictive Analytics

Machine learning models can predict future customer behavior, such as which products of the company a customer is likely to purchase next or when they are most likely to make a purchase. This information enables businesses to time their marketing campaigns effectively.

Demand Anticipation

By analyzing historical sales data, competitor activity, and external factors like weather and economic trends, ML models can predict future demand with remarkable accuracy. This empowers businesses to optimize inventory levels and respond effectively to fluctuating market conditions.

Personalized Recommendations

You’ve probably seen personalized product recommendations on e-commerce websites like Amazon. Machine learning algorithms analyze a customer’s past behavior and recommend products or content that are most likely to interest them, increasing the chances of conversion.

Fraud Detection

Machine learning-based fraud detection systems rely on ML algorithms that can be trained with historical data on past fraudulent or legitimate activities to autonomously identify the characteristic patterns of these events and recognize them once they recur.

Moreover, by analyzing transaction patterns and identifying anomalies of a particular entity, ML models can flag suspicious activity in real-time, preventing fraudulent transactions and mitigating financial losses. This proactive approach safeguards not only businesses but also their customers, fostering trust and security.

Operations Optimization

ML algorithms can analyze vast operational data to identify bottlenecks, inefficiencies, and potential areas for improvement. This allows businesses to optimize resource allocation, scheduling, and logistics, leading to cost savings and increased productivity.

Employee Performance and Human Resources

Machine learning can be used in HR analytics to assess employee performance, predict employee turnover, and identify factors contributing to job satisfaction. This helps in making data-driven decisions related to workforce management and employee engagement.

Text Analytics

Machine learning models can analyze text data from sources like social media, customer reviews, and surveys to gauge sentiment. This information is valuable for understanding public opinion, improving customer satisfaction, and managing brand reputation.

These are some functions of machine learning in business analytics. It’s a very powerful tool which sheds light on the market and ongoing processes in economy, resulting in enhanced accuracy of predictions and, therefore, contributes to the success and margins of a company.

Sources:

  1. https://www.techtarget.com/searchenterpriseai/feature/10-common-uses-for-machine-learning-applications-in-business
  2. https://www.linkedin.com/pulse/role-machine-learning-personalized-marketing#:~:text=Machine%20Learning’s%20Contribution&text=Machine%20learning%20algorithms%20can%20automatically,highly%20relevant%20content%20and%20offers.
  3. https://www.itransition.com/machine-learning/fraud-detection#:~:text=Machine%20learning%2Dbased%20fraud%20detection,recognize%20them%20once%20they%20recur.
  4. https://www.oracle.com/business-analytics/what-is-machine-learning-for-analytics/#:~:text=Machine%20learning%20for%20analytics%20is,Providing%20analytics%2Ddriven%20insights.
  5. https://bard.google.com/chat/616ccd3957c0cc71 (as a source for some features of ML)

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Starbucks Phenomenon

Reading Time: 4 minutes

Coffee is one of the most popular drinks which finds its lovers all over the world. Thus, coffee industry is a great place to set up your business and start getting decent margins. However, the rivalry is flourishing there, and it’s not that easy to surprise customers with something new, while internationally known giants are taking the most of the industry. One of the best examples is Starbucks. What constitutes its popularity? Why do people choose it over and over? The article below will answer all these questions.

  1. Mission Statement

The company is consistent in their vision across all levels of the business. This consistency creates a culture of living the mission statement which, in turn, encourages everyone in the company to promote the same vision to the customers. Every employee is coached on embodying the Starbucks ways of being, which establishes a consistently fresh and delightful experience for customers:

  • Be welcoming
  • Be genuine
  • Be considerable
  • Be involved

So, it’s always pleasant to visit a place where you will be welcomed, respected, your desires will be understood and realized as best as possible.

2. Personalization

This process started with the emphasis on personalizing the process of ordering your beverage. For Customers can choose a type of milk, name the syrup they want and even specify the amount of it.

What is more, Starbucks takes into account season changes and customers’ feelings and associations about them. So, in winter customers can enjoy gingerbread flavor in iconic red cups with Christmas ornaments, autumn presents us a lovely pumpkin spice drink which warms hearts and create a whole vibe around it, etc.

The last but not least is names on cups. It facilitates baristas to differ orders of consumers to prevent any sort of a mistake. However, it’s also a smart trick to create a bond with customers because a worker writes a name by his hand (sometimes with a smiling face or a heart). Therefore, an individual sees that the drink is made for them specifically, and according to Instagram posts, the writing adds some aesthetic on the look of the cup.

3. Consistency

Starbucks has over 20,000 stores, but it doesn’t engage into the simple mass-producing path to save money. Starbucks stores are consistent with the image and the message of the brand. One of the most critical aspects of Starbucks branding is the manner in which every part of the store emphasizes the importance of crafted elements. And though signage is obviously mass-produced, it never looks mass-produced. The signage still looks like somebody made it painstakingly by hand.

Surfaces are never regular, and rarely circular, but they are generally bent and formed in odd ways to emphasize the fact that someone took time to construct it by hand. There are also pictures which show the background of the café which opens a soul of the place. Nothing there is meaningless.

4. Affordable Luxury

Starbucks isn’t famous for its low prices; they have the opposite situation. Moreover, the brand positions itself as trendy and solid. So, the brand positioning and fancy cups make customers feel superior, and it’s always noticeable if somebody enters a room with a Starbucks cup in a hand. 

5. Work or Relax in Peace

This is where Starbucks really bucks the trend. Their coffee shops have been created to make you linger.

Want to go work somewhere different for a few hours? Starbucks and their strategically placed cafeterias will let you plug in and get to work for the price of one of their coffees. Similarly, if you want to rest with a good book, simply purchase the coffee of your choice, pick a comfy-looking chair, and have at it.

No one will bother you or request that you spend more money, stay as long as you need.

6. Social Media

Their full and active presence on social media is done in a way that speaks directly to the customers. Starbucks’ promotions on social media are strategically targeted to the audience in question which enforces online visibility as well.

What’s interesting is that Starbucks’s interior and exterior designs as well as the look of their beverage motivates consumers to post on social to appear modern, stylish and to beautify their pages in general.

7. Decent App

As part of its digital prowess, Starbucks has upped the game with its app. Instead of waiting in a boring line, you can choose, order, and pay for your drink using only your phone. A quick ping will tell you your drink is ready, so all you need to do is extract yourself from that cozy chair and go get it.

You’ll find all the promotions and deals on the app too. It saves you the hassle of hunting them down. Simply open up the app and see what takes your fancy. 

8. Quality and Approach to Serving

First, the ratio of coffee to water in every Starbucks coffee brew is much higher than in most other coffee houses. This makes the Starbucks coffee produce a more intense or stronger flavor. People who are used to a less concentrated coffee might find the strong taste of Starbucks coffee bitter or burnt.

Second, the Starbucks’ barristers undergo intense training, usually over 30 hours of training on every Starbucks drink from Frappuccino to Hot Chocolates. They’re also trained on the origins of the Starbucks coffee beans make them understand the beans and how to make them taste great.

Conclusion

These aren’t the only points that explain the success of Starbucks, but they are the most noticeable for customers. Through reading the article it’s also understandable how much we value the convenience and innovations of the brand which is made to condition us come back more and more, share opinion with mates, invite beloved ones there and help the franchise to get higher and higher incomes.

Sorces:

  1. https://avada.io/resources/why-starbucks-so-popular.html#:~:text=Starbucks%20has%20been%20helping%20customers,coffee%20into%20a%20customized%20experience.
  2. https://yourdreamcoffee.com/why-is-starbucks-so-popular/
  3. https://starbmag.com/why-is-starbucks-so-popular/
  4. https://www.thecommonscafe.com/the-global-phenomenon-of-starbucks/
  5. https://medium.com/@prakritimahato22/why-starbucks-is-famous-4557a38dd2f6

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Disadvantages of Digital Economy

Reading Time: 3 minutes
Pros And Cons Of The Growing Digital Economy Both Economically And  Psychologically - Asiana Times

 A good word is spread about digital economy. The advantages of it definitely open many doors for businesses and facilitates users’ experience: reduced costs, extended reach, more data are available, personalization, etc. But what about its downsides? Let’s dive deep into this topic.

Privacy and Security Concerns

 The typical digital footprint is massive — the average user has 90 online accounts, and in the U.S., there’s an average of 130 accounts linked to a single email address.

 Digital economy is significantly dependent on the acquisition and storage of personal data, which can create data privacy and security issues. Your search history, the ‘likes’ on social media made on digital devices — you may expect this information to be private, but too often it is not. Cyber-criminals exploit personal data for profit. Trillions of usernames, passwords, personal information, and confidential documents are for sale on all levels of the Internet.

 Striking a balance between innovation and individual privacy is not only feasible but essential for the long-term sustainability of the digital economy.

 Disruption

 The digital economy has created new companies and new ways of interacting. However, many entities and industries that didn’t or couldn’t capitalize on the technologies to change their operations have faced declining sales, falling market share, and even complete collapse. So, in many cases digital economy “demands” you to be included in order to be relevant even if you don’t want it.

 Job Displacement

 Automation and digitalization have taken many tasks from people, which facilitates the processes but also steals jobs from employees. Individuals might need to acquire new skills and even education what isn’t affordable for and even not that easy for understanding for everyone.

 Monopoly

 The digitalization of the economy has resulted in a small number of large providers such as Apple, Amazon, and Google gaining substantial power, resulting in monopolistic conditions in certain sectors. These giants push out smaller competitors from the market and don’t let them embrace themselves, as the rivals have less trust yet.

 Environmental Footprint

 The digital economy’s energy use in data centers and electronic device production has environmental consequences, with rising demand for digital services leading to greater carbon emissions, e-waste, and a bigger environmental footprint. It brings us closer to the climate catastrophe and leaves us less time to prevent it.

 E-waste – electronic waste, also known as end-of-life electronics or e-waste, refers to discarded, recycled or refurbished.

 Fraudulent Activities

 It’s easier to fool someone via the internet because:      

  • It can be done anonymously
  • It’s easier to take more money from a person as he doesn’t “see” the amount of it
  • There are more schemes to do so (spam, advertisements, casino)
  • Your personal data may be simply stolen and be sold/used to pay on your behalf

Loss of Social Element

 On the one hand, digital space connects millions of people from different corners of the world. However, on the other hand, it reduces a face-to-face contact with individuals which isn’t favorable for many potential customers. It also may lead to a declined understanding of human’s reactions and ways of thinking in interpersonal dialogues.  

Conclution

 Digital economy provides humanity with a wide range of great innovations made to enrich our experience. However, we should take into consideration the right ways of its exploitation and all the pitfalls from both sides: as businessmen/businesswomen and as customers.

Sources:

  1. https://www.linkedin.com/pulse/future-privacy-digital-economy-navigating-challenges-data-eenee-ph-d
  2. https://www.idx.us/knowledge-center/what-is-digital-privacy-and-how-can-it-be protected#:~:text=There%20are%20two%20main%20threats,breaches%20and%20personal%20data%20availability.
  3. https://www.idx.us/knowledge-center/what-is-digital-privacy-and-how-can-it-be-protected#:~:text=There%20are%20two%20main%20threats,breaches%20and%20personal%20data%20availability.
  4. https://www.wallstreetmojo.com/digital-economy/
  5. https://desklib.com/blog/digital-economy/

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Algorithms in E-commerce

Reading Time: 2 minutes
Online spending study regarding Estonia, Latvia and Lithuania in the light  of pandemic. - - Gemius – Knowledge that supports business decisions

Nowadays AI and machine learning are used in many spheres of business. They are very effective tools which bring a plenty of benefits to those who utilize them. I propose to have a look at algorithms that are implemented in e-commerce and how they influence our decisions and experience of online shopping.

Product recommendation engines

The recommendation engine is one of the hottest trends in the global e-commerce space. Using algorithms, product recommendation engines are used to surface products for customers based on various factors.

They benefit retailers by showing visitors the products that, based on the data fed into the engine, they are most likely to buy. For the shopper, the improved relevance means a better shopping experience.

Personalization

Properly personalized content on the website or mobile application increases conversion and customer engagement. The selection of the best content is possible thanks to machine learning algorithms for e-commerce. 

The results on the website are adapted to the personal preferences of each individual person. In this way recommendations for using machine learning in e-commerce could help you to increase your revenues.

On-site search

Traditional site search relies on finding an item in the product database which matches all or some of the shoppers’ search query.

Machine learning algorithms can be applied here, which allow additional data such as add to cart and purchase behavior around products influence the sorting of results, meaning shoppers will see more relevant output. It leads to higher chances of purchasing which is very favorable for the shop.

Dynamic pricing

Algorithms can be used to control and set pricing levels and optimize inventory for online retailers.

For the vendors, it can help them to find the right price point for their products and maximize profitability. It can take into account several variables to get, testing for different visitors, before finding the best blend.

Chatbots

Chatbots are designed to have online conversations with users and assist them in the purchase process in the most effective way.

However, from my point of view, conversations with these bots aren’t always effective and may lead to a need to still contact someone from the support team, as not all bots create replies according to your specific situation.

Image recognition

Image recognition can be used in site search to find visual matches for products entered and show relevant results for users.

Retailers invest in AI and image recognition systems to influence customers’ behavior and also for a process automatization. This could be defined by user’s preferences based on the category of products the person usually buys (what color, what brand) and based on the data from social media (Instagram, Twitter, Facebook).

Fraud detection

The cost that online stores lose due to fraud continues to increase steadily. Therefore, fraud identification and protection are important processes for all online stores. Machine learning algorithms for e-commerce can improve these processes and make them more effective.

These are the most important features of algorithms in e-commerce for both businesses and shoppers. We have a great possibility to make our sales more profitable and make our shopping experience more enjoyable by using them. The impact of these innovations is impressive, and for sure they will be developed even more in the future.

Resources:

  1. https://addepto.com/blog/best-machine-learning-use-cases-ecommerce/
  2. https://dotknowledge.uk/articles/view-article/how-online-retailers-can-use-algorithms-to-grow-their-business
  3. https://searchspring.com/blog/what-merchandisers-should-know-about-ecommerce-search-algorithms/
  4. https://www.eukhost.com/blog/webhosting/6-ways-ecommerce-stores-benefit-from-algorithms/
  5. https://www.itransition.com/machine-learning/ecommerce

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AI in Medicine

Reading Time: 2 minutes

Healthcare is one of the most important and in-demand services we have. Tens of millions of patients need diagnosis, treatment, and care daily. However, the declining number of specialists and their limited resources are not always able to perform efficiently. It’s where external help is required, and by now Artificial Intelligence (AI) has facilitated a lot. Let’s have a look on its role in medicine.

                                              The utilization of AI

The application of AI in medicine has two main branches: virtual and physical. The virtual part includes machine learning (mathematical algorithms). It’s applied to collect and manage patient data, improve the accuracy of diagnoses, recommend treatments, and develop medication. Moreover, you can use machine learning to program computers to make connections and predictions and discover critical insights from large amounts of data that health care providers may otherwise miss. The main goal of machine learning is to improve patient outcomes and discover solutions which were unavailable before.

The physical branch includes physical objects, medical devices and sophisticated robots taking part in the delivery of care (carebots). Some robots assist surgeons during complex procedures that require precise movements. Sometimes they also take the role of solo performers. In many cases, robotic surgery reduces the procedure’s invasiveness, which can also lower complications and improve outcomes. AI-driven robotic devices assist patients with tasks like rehabilitation exercises, providing real-time feedback and adapting routines based on the patient’s progress. The aim is to reduce potential life threatening aftermath, save specialists’ time, and give a faster conduction of treatment.

                                                     Conclusion

AI does a great job in saving lives and making medicine more accurate and efficient. Due to its rapid development we can wait for inventions and upgrades. Nevertheless, it all should be done through ensuring solid data privacy and guaranteeing high-quality and accurate solutions for patients.

Sources:

  1. https://www.sciencedirect.com/science/article/abs/pii/S1096288319300816
  2. https://www.who.int/news-room/facts-in-pictures/detail/patient-safety
  3. https://www.coursera.org/articles/machine-learning-in-health-care?utm_medium=sem&utm_source=gg&utm_campaign=B2C_EMEA__coursera_FTCOF_career-academy_pmax-multiple-audiences-country-multi&campaignid=20665163467&adgroupid=&device=c&keyword=&matchtype=&network=x&devicemodel=&adposition=&creativeid=&hide_mobile_promo&gclid=CjwKCAjwp8OpBhAFEiwAG7NaEi7mKzm7WBJJp_p5xHiC77xQ2mYxuOmMXDInA9YPMF9wGf_6w8Z2kxoCU2UQAvD_BwE
  4. https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-020-01191-1#Ack1
  5. The information about the role of the robots was partly taken from https://chat.openai.com/c/d26a2b3b-0925-4f2c-ba75-ac72083e9c06
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