What is the Best AI-Driven App for Video Conferencing?

What is the Best AI-Driven App for Video Conferencing?

Artificial intelligence is helping facilitate many aspects of business. Many companies have been forced to lean more heavily on AI technology than ever during the pandemic, because they had to find new ways to encourage social distancing.

Even as the pandemic starts to wind down, many companies are still relying more heavily on AI technology to adapt to a new age that is dependent on digital strategies. In fact, we talked about the benefits of this software a few years before the pandemic and it has clearly become even more popular since.

One of the most promising applications of AI technology is the utilization of new video conferencing technology. But what app is the best for these purposes?

Leveraging AI Video Conferencing Apps to Improve Communication

It’s no doubt that all video conferencing apps have more or less similar functions with a little difference. While most of them are relying on AI to provide the features that they need. Some programs are suitable for one-on-one conversations; some are perfect for chats in small groups; while others are capable of handling large webinars and masterclasses involving hundreds of people. 

Back in January, Adilin Beatrice wrote an article about the use of artificial intelligence in video conferencing apps. There is no denying the fact that AI has been invaluable.

But is there an ideal app that can arrange various kinds of virtual events regardless of the number of participants? Luckily, yes. Meet CallOut – the service that boasts all the features a modern video calls software is required to have by using sophisticated AI technology.

Their team of experienced developers selected the most useful AI tools for arranging video conferences, upgraded them, and created something unique. Let’s examine the best features CallOut offers its customers:

1. Outstanding connection quality

When you want to hold a video call, its quality is highly important. Their team has already taken care of that by using AI to improve the development process.

CallOut offers Full-HD video and audio for each user. Forget about times, when the connection was lost or you see just a pixelated version of a person on the other side of the screen. 

Additionally, we put the sound under full control:

Speech separation by audio splittingMuted background noise

It really is a great example of the benefits of AI-driven video conferencing software.

2. Unique AI and ML-based software

Let a bit of artificial intelligence into your everyday life:

Gesture recognition

Make use of your body language turning gestures into emojis, changing presentation slides with a single handwave!

Beautification tools

Videoconferencing with AI takes virtual meetings to a whole new level. It allows fixing camera drawbacks, reaching the ideal balance between the natural look and retouching, and letting you keep rocking a work-from-home aesthetic.

Virtual 3D backgrounds

Breathe life into plain white walls, designing your own stylish virtual space. Say no to meeting rescheduling because your home is a mess. In a couple of taps, you can replace any background with a preferred one!

Cloud recording

Save missed business meetings, conferences, and webinars to the cloud storage for future playback. The smart technology assesses the displayed emotions and prepares short footage of every call. Don’t have time to watch it? Just read the transcript of the most relevant information.

3. 100% secured chats

One of the biggest advantages of using a video conferencing tool that is developed with AI is that it has much more robust security. There are no more leakages of personal data! The service uses the latest web protection to ensure the total encryption of everything said and shared at any online gathering. No one will ever get access to your personal data, even the CallOut team. 

Moreover, we offer some extra security tools, such as:

Private in-meeting chatCustom personal meeting IDHost controls (lock meeting, mute all, and participant control)

4. User-friendly interface

Their service is developed based on customers’ needs. 89% of the clients say an ideal application for online video conferencing should be quick and easy to use. AI has been very helpful in improving usability.

That’s why it takes a minute to start a conversation in CallOut.

Forget about the long registration process, just open the link a meeting host shared with you and you’re in a virtual room keeping in touch with your colleagues, family, and friends.

5. Compatible with all modern devices

Use their service on any of your devices – PC, laptop, tablet, or smartphone. 

You can install the application from the market, or just open your favorite browser, go to the official website and start chatting with anyone you want, any time it’s required.

Make the right choice!

Whether you’re a part of a large corporation with hundreds of employees, a small startup with a huge desire to succeed, or just an individual looking for an online video calls service, be sure – CallOut is built to satisfy your needs.

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6 Data-Driven Tips to Dramatically Improve User Experience on Your Site

6 Data-Driven Tips to Dramatically Improve User Experience on Your Site

We have talked about the benefits of using big data in web design. One of the most important benefits of data analytics is improving user experience.

Jenny Booth highlighted this in her post Data-informed design: Getting started with UX analytics. We wanted to cover this topic in more depth.

Big Data is Crucial for Improving Online User Experience

Companies that use data technology strategically are able to significantly boost their overall conversion rates. One of the most important reasons is that they can use data from their users to see how they respond to various webpage elements. This allows them to take a data-driven web optimization approach for better user engagement.

Users are the lifeblood of any website. The more the end-users enjoy your site, the more likely they will return and recommend it to others. If you want to keep your leads coming back again and again, you need to make sure that each visit is as engaging as possible. This is where data-driven customer engagement strategies comes into play.

Your website might be the most aesthetically arranged piece of code on the block, but that won’t mean much if it isn’t well-designed. Good web design means that every element of your web presence—from content strategy and usability testing to design conception and development—should consider target demographic and user experience. You need to take all of this into consideration when using big data in your web design approach.

Implementing even one of these methods can lead to fundamental changes in how customers interact with your brand. Here are six tips for designing a web presence that does more than just load code. 

Consult a conversion optimization agency with a focus on data analytics

If you’re not already working with an agency that has experience optimizing the customer journey for conversions, then now is a great time to explore hiring one. You need to make sure that this company has a background in data analytics and knows how to use it in their design process.

By taking advantage of relevant big data tools and methods during the design process, you can ensure you’re directing users down an efficient path toward conversion without wasting their time clicking in circles around your site. In addition, using a conversion optimization agency like Ampry can help provide insight into how users use your site, arming you with valuable data for any future development projects. 

Conduct A/B testing

Another way to increase conversions is with A/B testing. This is one of the biggest benefits of data analytics. This website design and optimization method involves running two different versions of the same page against each other and then measuring which one converts more users into leads or sales.

While you’ll need to hire a web development company for this one, it does show just how vital user experience can be. If you don’t get it right on the front end, then there’s no point in worrying about how well your site converts visitors when they arrive at the home page.

Leverage persuasive storytelling

The most effective marketing campaigns tell a story, and this rule applies to websites as well. These stories don’t necessarily have fictional villains and plots with characters like novels or films, but rather real-life narratives about people who have benefitted from using a particular product or service. A narrative engages users and draws them in while also allowing you to demonstrate your value proposition.

You can use data analytics for this process as well. There are a lot of online advertising spy tools that allow you to mine data from other advertisers to see what types of storytelling approaches work for them, so you can replicate them yourself.

Make it personal, make it human

Creating a website that feels like it’s part of a larger community can also boost conversions. This personalization is something that isn’t easy for every company. Still, if you have the resources to implement this approach onto your site, then you’ll be rewarded with increased engagement among users and repeat visits.

Just remember to keep the human element front and center at all times. Suppose visitors feel like they are speaking directly with an actual person rather than just another money-hungry business entity. In that case, consumers are more likely to form emotional connections with your brand and align with your values.

Simplify forms and pages

Forms and landing pages are some of the most critical components of user experience on any website. That’s why it’s essential to keep these pages as simple as possible to encourage users to move through the conversion funnel more quickly.

Using minimal entry fields is one way to do this, but another is by personalizing these requests with information users have already provided through social media integrations. This is one of the areas where AI tools can help with the design process. You can even use AI and data design technology to make sure the forms are sized according to the user device and integrate other personalization factors.

Focusing on the user journey

Despite what some might say, a website is not all about the home page. Your homepage is just one small piece of the puzzle that unfolds as users move throughout your site–think of your homepage as the welcome mat and foyer of your business’s home. First impressions are essential, but that doesn’t mean you should put the cart before the horse when designing your page.

Suppose you’re able to map out exactly how each page contributes to or affects other parts of this journey. In that case, you’ll better understand your users and their needs, which means more opportunities for conversion optimization and higher conversions overall. 

This is the biggest benefit of data analytics. You can use tools like Google Analytics to map their journey and optimize accordingly.

Data Technology is Invaluable for UX Optimization

Consumers are spoiled for choice in today’s e-commerce market, but that doesn’t mean you can’t be a cut above the rest. By integrating data-driven design principles and prioritizing user experience, you can convert your leads into sales with the best of them.

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Be the Best – 9 Ways to Market Your Business with Big Data

Be the Best – 9 Ways to Market Your Business with Big Data

Big data technology has been a highly valuable asset for many companies around the world. Countless companies are utilizing big data to improve many aspects of their business. Some of the best applications of data analytics and AI technology has been in the field of marketing.

Data-Driven Marketing is More Important than Ever

The competition out there is fierce, so it is vital that you find ways to make your business stand out from the crowd. Your approach to marketing your company should be unique and exciting to snare customers. Your product and service should be top class to retain them. This is where data-driven marketing strategies come into play.

If you are looking to increase your customer base, here are 9 ways to successfully market your business by leveraging big data tools.

Exercise Search Engine Optimization

Big data has become essential for modern SEO. We talked about the applications of using big data in SEO in the past. However, before you can create a data-driven SEO strategy, you should understand the benefits of SEO in the first place.

When you have a fantastic website, you want to make sure that as many customers as possible enter it. You have to be near the top of the list on a search engine page like Google to glean the maximum customer traffic.

When building and adding information to a website, you must think about search engine optimization and use keywords and phrases that customers are likely to type into a search engine. This is one of the ways that big data can be most helpful. You can use sophisticated data mining tools to get the keywords you need to create a successful campaign. When a specific word or group of words is entered into a search engine the same way it appears on your website, the viewer will be presented with your website as one of the top clickable options. Log file analysis and natural variations of that help company website builders better understand how search engines are working on their websites and gather ideas on ways to improve their SEO performance.

Create a Quality Website

Big data has also been very important in developing websites. You can read our previous article on using big data for website development.

Online shopping has been more popular than ever since the unwelcome appearance of COVID 19 across the world, forcing society into periods of home quarantine. People have turned to the internet to buy goods and hunt for service providers, so it is crucial that you have a website for your business.

A top-notch website is one that is easy to navigate, interesting, informative, and easy on the eye. If your website is crammed with unnecessary literature and it is confusing or awkward to locate specific information, the potential customer will rapidly lose heart and turn to another website. You can use data-driven analytics tools like Crazy Egg to help optimize the site.

Use clear photographs depicting every angle of your product. List the dimensions, colors available, and any other relevant details, but keep the description short. Ensure it is easy for the client to check out items in their cart and offer various payment options. Publish precise contact details of your company so that customers can contact you quickly should they have any issues.

Boost Sales with a Brand and Logo

Some of the world’s most successful companies have a logo and branding that is instantly recognizable such as McDonald’s Golden Arches or the half-eaten fruit of Apple. Often people will remember a symbol but not a name, so it makes sense to develop a visual identity for your company that customers will instantly think of when they are looking for a particular product or service.

This is an overlooked area where big data can be highly useful. You can use data-driven design platforms like Canva to create great website content.

Be a Social Butterfly

These days it is imperative you have a social media presence as around 70% of US inhabitants have a social media account, whether it be with platforms such as Facebook, LinkedIn, or Instagram. You can’t afford to be an effective social media marketer without using big data these days.

On sites such as Facebook, you can advertise, open a store, and communicate with customers all over the world for free. Your Facebook site can display photos of your products and links to your website or YouTube channel – another essential accessory for a successful business. A YouTube channel devoted to your company allows you to be creative with your advertising while reaching out to customers in all corners of the world.

You will need to use data analytics tools like Google Analytics or Hootsuite to optimize, automate and improve your social media strategy.

Develop an App

Rather than scouring through web pages, many people like to use an app on their phone or tablet. Big data is also proving to be useful for app development.

Create an app for your customers that is simple and speedy to use, and you will find that they keep coming back for more. Apps help customers feel more engaged with your company and make your business more visible.

Write a Blog

Including a blog on your website can help you attract traffic. A well-constructed and entertaining blog can engage people and make them want to come back to read subsequent blogs. Some fans of your writing may share the blog on their social media pages or email links to friends and family. Get blogging as it may just expand your customer base.

Ask Affiliates For Assistance

Bloggers and YouTube influencers can do wonders for the sale of your product.

Look on social media platforms such as YouTube for people who use products similar to those you produce and ask them if they will include your wares in one of their videos. For example, suppose you manufacture paints and art supplies. In that case, you could ask a popular artistic YouTuber such as Moriah Elizabeth to use and promote your products on some of her videos. Followers of the influencer will be keen to buy the products their idol uses, and the influencer will be content as they will receive a percentage commission from sales made through the link to your products on their site.

Many of the top influencers have hundreds of thousands of fans from nations across the globe. Brands used on YouTube videos by these people have been known to sell out in minutes.

You can use big data to help with your affiliate marketing strategy as well. You will be able to monitor the ROI of different affiliate traffic sources and rule out affiliate fraudsters if you use analytics properly.

Be Seen Everywhere

You need to be seen in order to be successful, so get your company out there. Invest a decent amount of money on advertising in local and national newspapers, billboards, radio, and television.

Initially, it may seem like you are emptying your wallet, but widespread quality advertising will do wonders for your sales. Consult a professional marketing company about how to advertise your product best, visually, verbally, and aurally. They can help you compose a catchy jingle for your radio and television advertisements or an eye-catching full-page spread for the local rag.

Make Useful Merchandise and Be Generous with Freebies

Everyone loves a freebie, so devote some of your budget to creating innovative merchandise or handing out free samples of your products.

If your business sells food or drink products, you could set up a stall at the local market and hand out free samples of the goods. Once people taste your cuisine, they will be desperate to buy more.

Pass out merchandise such as pens or clothing around local businesses or at business expos. Wear branded clothes yourself when you are out and about or have business livery printed onto your vehicle.

There are thousands of ways you can promote your business – just make sure your method grabs the public’s attention. Above all, ensure your goods or services live up to the hype!

Big Data is Vital to Modern Marketing

You can’t overlook the importance of big data in the marketing field. Make sure that you use it wisely, so you can get the most bang for your buck.

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Why Investing in Data Is Crucial for Business Growth In 2022

Why Investing in Data Is Crucial for Business Growth In 2022

There’s no denying that data is everywhere in life. The rate at which information is being collected is growing exponentially, with approximately 2.5 quintillion bytes (that’s 2,5000, 000, 000, 000, 000, 000!) of data being produced every day.

As technology continues to advance data generation across the world, it’s safe to say that investing in data solutions will be crucial to seeing business growth and success in 2022 and beyond.

How can data help my business?

There are many ways you can use data to your business’s advantage. Ultimately, data helps firms understand and improve their processes, reducing money and time spent on wasted resources. It has been very useful in countless industries, including financial trading.

IBM estimates that 90% of all data generated by the Internet of Things (IOT) is not analyzed, or utilized in business decision processes. Despite this, there are four key areaswhere data can help to shape better understanding of how your business is running – and plenty of tools to help you get there!

Understanding performance

As a starting point, there are a number of tools that utilize data visualization for businesses. It’s important to regularly implement performance mapping, to ensure your company is continually making improvements to be the best it can.

Sometimes, it can be hard to spot aspects of a business that aren’t running as smoothly as they could be. For this reason, exploring data visualization can come in handy. From

Google Charts to Tableau, there are so many tools and analytics software options available for your business to thrive.

Understanding employees

Business owners can leverage data to understand their workforce better. By gaining deeper insights into the needs of your employees, you can help to provide a better overall experience and workplace environment.

Surveys and email communications can be used to gain insight into employee satisfaction levels. By asking for feedback, employers will gain greater respect from their staff, who will feel as though their voices are being heard.

Often, smaller companies don’t have structured Human Resource (HR) processes in place, and cross-department communications are under strain. Cross-sharing of data can aid this, with platforms like ScreenCloud helping to ensure teams are being heard.

Understanding customers

Providing a good customer experience is becoming more and more important. Consumer expectations are rising, and without tracking behaviors at various points in the customer journey, you won’t be able to make improvements to the experience you’re providing. There are so many ways that online data can be leveraged through analytics and software to improve your offering.

Data is important in all aspects of online marketing and advertising, helping businesses find new potential customers, improve conversions and ensure loyal customers are being nurtured. The bottom line is, in a world that now values speed, ease and efficiency, if you don’t ensure you’re providing these factors, it’s likely you’ll find customer retention difficult.

By better understanding your customers better, you will be able to leverage your data and boost company sales moving forward.

Understanding competitors

Competitor analysis is crucial to understanding your market share position. In order to gain a competitive advantage, you need to fully understand what you’re up against. Data can be used to show your competitors’ strengths and weaknesses, helping you to realize how your own business strategy can be enhanced for optimal performance.

Investing in data solutions

If investing in data solutions hasn’t been a top priority for your business so far, now is the time to make it one! In order to remain ahead of the game, data solutions should be integrated to your business processes to ensure optimum performance.

When thinking about your budget for the next quarter, it’s a good idea to leave some money aside for data. Alternatively, you could consider low cost unsecured funding as a short-term solution that will have long term results. Though data can be expensive, it offers one of the greatest return on investment (ROI) for businesses.

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Biggest Trends in Data Visualization Taking Shape in 2022

Biggest Trends in Data Visualization Taking Shape in 2022

There are countless examples of big data transforming many different industries. It can be used for something as visual as reducing traffic jams, to personalizing products and services, to improving the experience in multiplayer video games.

There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. This is something that you can learn more about in just about any technology blog. We would like to talk about data visualization and its role in the big data movement.

Data is useless without the opportunity to visualize what we are looking for. As we have already said, the challenge for companies is to extract value from data, and to do so it is necessary to have the best visualization tools. Over time, it is true that artificial intelligence and deep learning models will be help process these massive amounts of data (in fact, this is already being done in some fields). However, there will always be a decisive human factor, at least for a few decades yet.

What is data virtualization?

Data visualization is going to grow in importance in the short term. Data visualization is a concept that describes any effort to help people understand the significance of data by placing it in a visual context. Patterns, trends and correlations that may go unnoticed in text-based data can be more easily exposed and recognized with data visualization software.

Data virtualization is becoming more popular due to its huge benefits. Companies are expected to spend nearly $4.9 billion on data virtualization services by 2026.

This is of great importance to remove the barrier between the stored data and the use of the data by every employee in a company. If we talk about Big Data, data visualization is crucial to more successfully drive high-level decision making. Big Data analytics has immense potential to help companies in decision making and position the company for a realistic future.

There is little use for data analytics without the right visualization tool. What benefits does it bring to businesses?

In the era of Big Data, the Web, the Cloud and the huge explosion in data volume and diversity, companies cannot afford to store and replicate all the information they need for their business.

Data Virtualization is a technology that allows combining information from different data sources and transforming them into a single virtual data source that can be accessed in real time by different applications.

In this way, it is possible to exploit the business value of all data, of any type and from any source. It also generates integrated and standardized data services that help you get more agile performance from your data without the need for constant replication.

Why is Data Virtualization the cheapest and fastest option?

Physically moving and storing the same data in different repositories multiplies costs and slows down processes when IT changes need to be made. Data Virtualization allows accessing them from a single point, replicating them only when strictly necessary.

In which projects or use cases is Data Virtualization ideal?

Data virtualization is ideal in any situation where the is necessary:

Information coming from diverse data sources.Real-time information.Agile requirements and fast deployment times.Multi-channel publishing of data services.

Agile BI and Reporting, Single Customer View, Data Services, Web and Cloud Computing Integration are scenarios where Data Virtualization offers feasible and more efficient alternatives to traditional solutions.

Does Data Virtualization support web data integration?

The web is inherently large, dynamic, heterogeneous, and the fastest growing source of information. Data Virtualization can include web process automation tools and semantic tools that help easily and reliably extract information from the web, and combine it with corporate information, to produce immediate results.

How does Data Virtualization manage data quality requirements?

Data Virtualization includes capabilities for integrating, transforming and enriching information, based on rules and extensible with specific third-party products. It can control changes in the sources from which it extracts data and includes Data Lineage capabilities, which means confidence for the user.

How is Data Virtualization performance optimized?

The best Data Virtualization platforms employ performance optimization techniques such as intelligent caches, task scheduling, delegation to sources, query optimization, asynchronous and parallel execution, etc., for scalable performance in demanding environments.

How do Data Federation tools differ from Data Virtualization tools?

Virtualization goes beyond query federation. Some solutions provide read and write access to any type of source and information, advanced integration, security capabilities and metadata management that help achieve virtual and high-performance Data Services in real-time, cache or batch mode.

How does Data Virtualization complement Data Warehousing and SOA Architectures?

Data Virtualization can be used as an extension to Data Warehouse and other data migration solutions, federating multiple sources to create virtual Data Marts. Data Virtualization integrates with ESBs and enables real-time deployment of Data Services in SOA implementations.

What is the cost and ROI of Data Virtualization?

The investment in a standard Data Virtualization project is recovered in less than six months and its cost is one third of data replication solutions or custom developments. The ROI is obtained by savings in the cost of hardware, software, storage, development and maintenance.

How can data visualization benefit companies?

Maximizing customer engagement. Customer service is one of the most benefited from a good use of big data. Having visualization tools available has a positive impact on how companies serve their customers and solve their problems, and makes it possible to detect trends and develop strategies that better connect with those customers and potential customers.

In improving operational processes. The study and analysis of data allows to improve the automation of processes, optimizing sales strategies and improving business efficiency.

In forecasting future events. Predictive analytics is an area of big data analysis that facilitates the identification of trends, exceptions and clusters of events, and all this allows forecasting future trends that affect the business.

Prescriptive analytics. This type of analysis is primarily aimed at prescribing actions to be taken to address an anticipated future challenge. It is the next phase after predictive analytics, and can help managers understand the underlying reasons for problems and find the best possible course of action.

There are many tools available to companies to improve data visualization. From applications such as Infogram, for making infographics at all levels, to others such as Domo, an artificial intelligence-based application that allows an organization’s employees to create and share data, all of them are of great practical use in making more effective use of data, and improving decision making.

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Important Steps to Take to Address the Bias in AI

Important Steps to Take to Address the Bias in AI

We mentioned previously that bias is a big problem in machine learning that has to be mitigated. People need to take important steps to help mitigate it for the future.

Regardless of how culturally, socially, or environmentally aware people consider themselves to be, bias is an inherent trait that everyone has. We are naturally attracted to facts that confirm our own beliefs. Most of us tend to believe that younger people will perform certain tasks better than their older colleagues, or vice versa. Countless studies reveal that physically attractive candidates have a better shot at getting hired than unattractive ones. The list goes on.

We, as humans, can’t confidently say that our decision-making is bias-free. The root cause of this problem is that bias creeps in unconsciously, making us helpless in figuring out if the decisions we took were biased or not.

This is why the notion of biased artificial intelligence algorithms shouldn’t be surprising as the whole point of AI systems is to replicate human decision-making patterns. To make a functional AI system, developers train it with countless examples of how real people solved that particular problem.

For example, to build an AI system that can help sort job applications, engineers would show the algorithm many examples of accepted and rejected CVs. The AI system then would figure out the main factors that impact decisions, developers would test the system accuracy, and deploy it. In this simplified example, two problems can emerge: HR specialists can be biased in their decision-making to begin with, and the training dataset can appear unrepresentative of a certain gender, age, race, etc. For example, it can be that, historically, a company have been unintentionally hiring only men for the frontend developer position, prompting the AI to rule out women from even getting a chance to be interviewed. This leads us to the first method of eliminating bias from AI.

Data Fairness

AI has been important in solving many challenges. However, the data behind it must be well structured and as free of bias as possible.

In the majority of cases the biggest reason for AI unfairness, especially when it comes to inexperienced developers or small companies, lies in the training data. Getting a diverse enough dataset, which takes into account every demographic or any other critical attribute is what data scientists can only dream of. That’s why you should approach AI development as if your training data is inherently biased and account for this at every stage of the process.

The Alan Turing Institute has introduced a method called ‘Counterfactual fairness’, which is aimed to reveal dataset problems. Let’s get back to our example of a company that hires a frontend developer using AI. In this case, to ensure that the algorithm is fair, developers need to conduct a simple test, letting the AI system evaluate two candidates with identical skillset and experience, with the only difference being gender or any other non-essential variable. Unbiased AI would rate both of those candidates equally, while unfair AI would assign a higher score to men, indicating that readjustments need to be made.

The Institute produced a set of guidelines posed to help AI developers ensure model fairness. Here, at Itransition, we believe that such initiatives will play an increasingly important role in tackling bias in AI.

Adversarial Learning

Besides flawed datasets, bias can also creep in during the model learning stage. To mitigate this, many developers now opt for the adversarial training method. This implies that besides your main model (e.g., the one that sorts applications), you apply another model, which tries to figure out the sensitive variable (age, gender, race, etc.) based upon the results of the main model. If the main model is bias-free, the adversarial model won’t be able to determine the sensitive attribute. Data scientists cite this technique as one of the most effective and easy-to-use, as unlike conventional reweighing, adversarial learning can be applied to the majority of modeling approaches.

Reject Option-based Classification

Lastly, there is also a number of post-processing techniques that can help mitigate bias. The appeal of such methods is that neither engineers nor data scientists need to be bothered with tweaking the model or changing datasets, as only the model outputs need to be modified.

Reject option-based classification is among the most popular post-processing techniques. In essence, the bias is reduced by rejecting predictions that the model is least confident in. For example, we can set a confidence threshold of 0.4. If the prediction certainty is 0.39 or below, the system will flag the output as biased.

Team Diversity

Navigating the AI landscape depends on understanding the business context more than it’s generally perceived. No doubt, data science is closely associated with number crunching, but realizing what’s behind those numbers is equally important. And even then, data scientists’ unconscious prejudices can play a critical role in how bias takes over their algorithms. This is why, more often than not, combating bias in AI is closely tied to hiring people of different race, gender and background.

To enable more thoughtful hiring, companies need to incorporate more objective interviewing techniques. Especially when it comes to large enterprises, too many interviews are limited to traditional CV screening. Forward-looking and innovative companies now make real-world project-based data analysis a centerpiece of their interview process. Not only do they assess how well a candidate performs data analysis science-wise, but they also ensure that he or she can explain findings in the business context.

With AI being a driving force behind many business transformations, it’s imperative that we establish definitive frameworks that tackle bias in AI. It’s also important to realize that we can’t mitigate bias completely. However, it’s far more attainable to control prejudices in algorithms than in humans.

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Cyber Insurance Could Keep Your SMB Afloat Post Cyber Attack

Cyber Insurance Could Keep Your SMB Afloat Post Cyber Attack

In the wake of the COVID pandemic, cybercrime is skyrocketing to unprecedented levels and daily ransomware attacks increased by 50% in 2020.

The cause of this rise is largely due to the massive increase in American employees working from home. Where employees used to be under the umbrella of their organization’s security networks and using their business’ secured devices, today the majority of employees are remote. Remote work has many benefits and isn’t likely to go away any time soon, however it poses new security issues as personal devices, and personal or public networks simply do not provide the same cyber security covering as employee’s experienced while working in the office.

Many remote employees are unaware of what security measures they have in place on their devices and networks, and IT departments are unable to personally secure every network and device that employees are now connecting from. All of these factors bring a wide variety of new security vulnerabilities, and cyber criminals have been taking full advantage of these new open doors.

Another aspect of the expansion of cybercrime is the inherent danger that comes with the expansion of internet access across the globe. The number of individuals with internet access is expected to reach 5.3 billion, and 3.6 connected devices per person worldwide, by 2023.

Ransomware attacks are among the top cyber security concerns for individuals and the companies that employ them. Ransomware attacks are often undetected and they happen to a person or business every 10 seconds. These attacks can come in the form of emails that seem harmless. They are often even branded emails that look like they’re coming from a trusted company. One individual falling prey to ransomware can actually be the catalyst for a much bigger, more sophisticated attack on an entire company through phishing and other kinds of theft.

For small to midsize businesses, a single ransomware attack can be absolutely devastating, and sadly, 45% of SMBs say their cyber security is not nearly enough to protect them. In 2020, 66% of SMBs experienced a minimum of one cyber-attack. The most unfortunate effect being that 60% of SMBs will go out of business within 6 months of a data breach.

It’s no wonder that these businesses are so vulnerable. The most common security measures are easily circumvented. Two factor authentication, “strong” passwords, and password manager apps are ultimately just a minor delay for a cyber-attack. They often do not do the job of actual prevention. Just one cyber-attack can mean the loss of money, the loss of privacy and productivity, the loss of reputation, and ultimately the loss of the entire business.

Cyber insurance may be the best solution for SMBs to protect themselves if and when they fall victim to a cyber-attack. Most cyber insurance policies for SMBs will cover up to one million dollars of damages, which includes coverage for profit losses, liabilities, and lawsuits. Cyber insurance can help SMBs recover their reputation, cover penalties and fines, and the cost of class-action lawsuits and regulatory investigations.

Cyber insurance does not cover the loss of physical property, such as “bricked” devices. It does not cover future loss of profits or long-term effects of cyber-attacks on profits. It also does not cover the loss of intellectual property, such as loss of company value after a breach. Ransom payments themselves also may not be covered as the demand is simply outgrowing the supply. However, with cyber insurance, companies can potentially rebuild and recover their losses to the extent that they can still stay in business and have a leg to stand on for future growth.

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Importance of Licenses for Data-Driven Fintech Companies Offering AISP

Importance of Licenses for Data-Driven Fintech Companies Offering AISP

Big data technology has been the basis for the Fintech industry. There is no disputing the major benefits that big data has created for the financial sector.

However, there are also new challenges that have arisen as big data has become more widely available in Fintech. One of the biggest changes is new regulations. Fintech businesses must make sure that any data scientists working for them are licensed and trained to handle tasks with the utmost sensitivity.

One of the most regulated aspects of the Fintech industry is AISP, due to the vulnerability of people that might have their data exposed by people working in this field. You need to make sure that you are properly licsensed if you intend to offer AISP services as a data-driven financial company.

Getting an AISP License as a Fintech Company Relying on Big Data

It goes without saying, Payment Services Directive (PSD2) opened the way for new Fin-Techs to launch. Unfortunately, PSD2 regulations are applied only in the European Union and the European Economic Area. Account Information Service Provider (AISP) is authorized to send and receive account data from banks and other financial institutions. This data can be used for various purposes and could be extremely beneficial for end users. At the same time, online service providers who have AISP licenses can stand out and amaze with better customer experience.

Not only Fin-Techs can apply for AISP license, in some cases banks, insurance companies and other organizations use it for several reasons. Institutions can have both AISP and PISP (Payment Initiation Service Provider) licenses at the same time and carry out related activity.

Typically, authorized AISP license holders with the permission of users can get private information on other platforms. This solution works for safer banking and financial transfers as much as registering and signing to other platforms in a few times faster way. AISP technology allows to receive user data but doesn’t allow to make any financial transaction. Received information is mainly used for analyzing separate service providers and monitoring all of them on one dashboard. Anyway, the AISP licensing process is strict and time-consuming.

To get AISP license, organizations must hold Professional Indemnity (PI) insurance. It can be applied for business or self-employed freelancers. This type of insurance covers any cases where any financial loss is made by the customer‘s or organization‘s fault. So it‘s good to know that even if something may go wrong, there will always be a third party who will compensate for the loss of money or data.  

As mentioned before, PS Directive is a great opportunity to start a Fin-Tech business by creating and representing a brand new, never-before-seen service or by improving one that exists but could be provided in a transformed format.

The AISP license is not easy to get. First, you must fill in an application form. It involves the business plan, all the legal information about the company, and why AISP is necessary in your business. All the documents and agreements must be provided to meet strict requirements. Also, you must ensure that your system is safe enough and use the required safety protocols. Funds and personal information are too valuable to be lost. The only way to do it – a compliance demonstration.

Your idea of an AISP-based system must be fulfilled and prepared without skipping any step. AISP technology is being developed, but there are still many undiscovered methods of use that must succeed.

PSD2 opened the new page of EU/EEA online services. To regulate this sector was a great idea, and the most benefits are felt by end users. Traditional banks now have new-age competitors who correct the prices of some services and make traditional banking come along with the latest trends. Glad that in this situation the maximum benefit is to the end user.

Data-Driven Fintech Companies Must Get a License Before Offering AISP

Big data has been highly useful in the Fintech sector. More companies are using sophisticated big data tools to offer services like AISP. However, you need to make sure that your company is properly licensed first.

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Starting a Career as an Analytics-Driven Video Game Coach

Starting a Career as an Analytics-Driven Video Game Coach

There are tremendous career opportunities for people that are knowledgeable about analytics. You will need to know what steps to take if you are interested in using your analytics knowledge to find a new career.

Some of the career opportunities for people with a background in analytics are pretty obvious. You will be able to become a data scientist, data-driven marketing consultant, information systems experts using big data or a variety of other technology focused jobs.

However, there are a lot of other careers that people with a background in analytics might want to consider. One of these options is becoming a video game coach.

How can a video game coach be a good career choice for someone with a background in analytics? The truth is that analytics has become more important in video games than ever. You can use analytics tools to better understand the mistakes and habits of your customers. You can also learn more insights about some of the games you are reaching people.

Pursuing a Career as a Video Game Developer with a Background in Analytics

There is no secret that analytics and big data are becoming more important in video game development. However, fewer people consider the merits of using analytics in playing video games. Video game coaches that know how to use analytics technology can help people become better players.

Playing video games has been a mainstream form of entertainment. It is no longer just for kids. More adults are picking up controllers and playing video games in their spare time. In fact, playing video games has become a sport. eSports pits teams of gamers in competitions watched by millions of people from all over the world. At the end of it, the winner gets millions of dollars in prizes.

Gaming developers have started using analytics to understand user behavior. However, customers can use analytics to play more effectively themselves.

The demand for analytics in gaming will increase as the hobby becomes more popular. Gaming has become a lucrative way to earn money and turn regular people into celebrities. The biggest gamers in the world earn eight figures a year. Tyler Blevins, more popularly known as Ninja, is the most successful, earning $17 million in 2019 alone. He even played Fortnite with rapper Drake. Felix Kjellberg, also known as PewDiePie, reportedly made $15 million in 2019. Preston Arsement or Preston Playz made $14 million.

It is no wonder that plenty of people want to be involved in it and are using analytics to get an edge. However, not everyone has what it takes to become a star in the world of video games. A player must be outstanding to compete in eSports or entertaining to stream on Twitch or YouTube.

The Rise of Analytics-Driven Video Game Coaches

Playing video games for some people has stopped being a casual hobby. They want to be good at it so that they can stream, compete professionally, or increase their enjoyment of the activity.

Thus, video game coaches emerged. People who have extensive experience in video games are now offering their services to amateurs who want to gain new skills and improve their performances. The pandemic seems to have boosted the demand for their expertise. They are also leveraging data analytics tools to offer more reliable services to their users.

Fiverr, a platform where freelancers offer services for a fee, had a 43 percent increase in the number of video game coaching sessions booked between January and March 2020. The most popular games on the platform are Fortnite, a massive multiplayer online game, and Rainbow Six Siege, a tactical shooting game. Both are very competitive.

Meanwhile, GamerCoach, a platform specifically for video game coaching, sold more than a thousand hours of sessions in March 2020, up from just 650 hours from the month prior.

Everyone is a Gamer

The video game industry thrived massively during the pandemic. While other markets suffered losses, video game companies saw their revenue increase. The use of analytics in the design process has played a huge role.

By August 2020, the sale of video games increased to $3.3 billion — a 37 percent growth compared to the same period in 2019. Part of the surge was caused by the imposition of restrictions to stop COVID-19. People stuck at home were looking for ways to be entertained while they waited out the public health crisis. Many people purchased a video game console to start playing. In fact, Nintendo Switch was sold out in many places during the first weeks of the pandemic.

But video game consoles were not the only ones that were in high demand. Mobile games sales on iPhones also increased in Japan and the European Union. Meanwhile, the PC market saw sales grow, particularly for gaming, for the first time in 10 years. Consumers were building gaming computers.

The renowned soccer video game franchise added 7 million new players during the second quarter of 2020. NBA 2K20 had an 82 percent increase in active players during the same period.

And, despite the restrictions being lifted, the outlook for the entire industry is still very positive, making analysts confident that the attention will not be temporary.

What Video Game Coaches Do

Many of these people are taking playing video games more seriously or taking the opportunity to be good at the video games they play. They need a coach to help them gain skills in the shortest time possible.

A video game coach can provide advice on how a player can make better decisions, for example. They may play against the client online and then record it to point out what can be improved or where the client went wrong. It is different from a professional sporting coach who may give instructions on how to win the game. The goal of a video game coach is to teach the client how to become a better player and show them a different way to enjoy the video game.

The fee depends on the level of expertise of the coach. An hour can cost about $15 to over $90. The business of coaching video games in-person or via streaming is estimated to have already exceeded $1 billion.

Playing video games has become a popular hobby across all age groups. More people are also now earning money from it via creating content online or competing in professional tournaments. Naturally, more people want to become good at it. Coaches can help them become better video game players.

Meta title: How People Are Earning Money as Video Game Coaches
meta desc: Playing video games can be a lucrative career. Therefore, more people want to explore the industry and are hiring coaches to become better gamers.

Analytics is Driving the Future of Video Game Coaching

Analytics technology has become very common in the video game profession. Most of the discussions have centered on the benefits of using analytics in game design. However, it can also be very useful for video game coaches trying to help their users improve their skills.

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How Can You Use Machine Learning to Optimize Pricing in FinTech?

How Can You Use Machine Learning to Optimize Pricing in FinTech?

FinTech is about connecting with customers. They expect something different from classically understood banking. The more you know about your audience, the more you can offer them. It’s similar to prices – price optimization through machine learning is a great tool to grow your revenue. What can you learn from real-market examples?

Figuring out the best pricing model can be tricky. Especially with a newly developed product, when you have to convince people to set up accounts and trust you with both: data and money. That’s where machine learning algorithms come into place. By processing and analyzing big amounts of data, they can help you establish optimized pricing plans. How exactly?

Hire machine learning to make optimal pricing decisions

Solutions mentioned below will boost your product in real-time. They can help both: established companies and startups. Think of them as a multiple-step guide to designing your app with specific features and customer-centric solutions in mind.

This is how you can improve a pricing model:

Use machine learning to process data and discover services that need a boost. There are highly specialized FinTech applications that offer only one product; loans for example. There are, however, applications that are very popular and sell multiple solutions to the same audience. What product generates more money? Which solution is better? Do an A/B testing and find out. By going through data, you can figure out what works and what doesn’t. This solution can free up resources (money, employees’ time) to pursue more profitable features.Use automated pricing models to drive up revenue. The Boston Consulting Group created a study and it seems that revenue can be boosted up by 5% with this. The BCG believes that machine learning offers optimal pricing rules in revenue management systems. It also enforces contractual pricing.Generate insight on changing user’s behaviors through automated pricing solutions. It gives a highly valuable context on transactional data, providing the necessary perspective. One of the companies that offer interesting solutions is Vendavo. Their model and industry integrations work great with custom software development, powering your app. This combo of data and development solutions will help you make pricing decisions. Especially based on cross-border parameters.Use machine learning to figure out which customers are willing to pay for a product or a specific feature. You can pull information by linking spending or monthly fees in a software-as-a-service (SaaS) model with discounts, promo codes, etc. It’s especially valuable in the case of VIP pricing plans.Predict pricing impact with AI-powered user personas. Try to predict whether a first-time user or a paying customer will perform a certain and desirable action. Thanks to artificial intelligence propensity models, you can increase the customer retention and reduce churn.Use rule-based artificial intelligence (AI) models to establish the risk-to-revenue. Software development, specially dedicated to the B2C market, isn’t always fully predictable. Customers’ needs and the market itself change rapidly. Friction in user experience can be managed but what about mobile app development? You can use the customer even before you know about the issue. The price is not acceptable. The solution is brilliant, but underdeveloped. Microcopy inside the app doesn’t transmit the offers very well. User experience and user interface design are not attractive enough. Machine learning pricing algorithms won’t give you all the answers, but they can show you the right direction.

How to achieve your goals?

According to McKinsey, the estimated AI-based pricing solutions can have a global worth of $259.1B to $500B, globally. According to Mordor Intelligence, the AI market in the sector will grow from $7.27B in 2019 to over $35.4B by 2025. Those are, however, numbers you can’t use. As previously mentioned, 5% is something real. How to get to that? Use these factors to drive your decisions:

customers’ personasoperating costs and preferred marginsseasons and holidaysother, especially unforeseen, economic variables

Also, focus on something called a dynamic price. It’s adjusting prices, usually for a number of products, to react to the competition’s strategy. This model assumes frequent changes. It’s risky, unstable, and leads to churn. We have broken down the differences between price optimization, dynamic pricing, and price automation with machine learning.

Price optimization without machine learning is incomplete

Massive amounts of data and machine learning can generate pricing recommendations but you still have to base decisions on experience. Machine learning can and will give you a lot to think about, it can also free you from many mindless business operations. It can also be faulty.

As well as software development, which requires real specialists. Financial software development company can save you a lot of trouble and create a performing digital product worthy of your customers’ attention. Care to join the future?

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