Sectors – Big Data Made Simple https://bigdata-madesimple.com One source. Many perspectives. Wed, 21 Aug 2019 10:49:33 +0000 en-US hourly 1 https://wordpress.org/?v=4.9.7 https://bigdata-madesimple.com/wp-content/uploads/2018/10/bdms-favicon.jpg Sectors – Big Data Made Simple https://bigdata-madesimple.com 32 32 Digital marketing: can data improve creativity? https://bigdata-madesimple.com/digital-marketing-can-data-improve-creativity/ https://bigdata-madesimple.com/digital-marketing-can-data-improve-creativity/#respond Wed, 21 Aug 2019 10:49:33 +0000 https://bigdata-madesimple.com/?p=35437 There are all sorts of data flowing through your network. From customer data that includes contact information as well as purchase activity to the daily hits on your website to posts on your blog that generate a lot of attention. If it hasn’t sunk in yet, that data can be used to create a powerful … Continue reading Digital marketing: can data improve creativity?

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There are all sorts of data flowing through your network. From customer data that includes contact information as well as purchase activity to the daily hits on your website to posts on your blog that generate a lot of attention.

If it hasn’t sunk in yet, that data can be used to create a powerful digital marketing campaign. All you have to do is take a fresh look and relate it back to the sales and marketing process. Here are some examples of how to use data to generate more revenue and improve your brand’s reputation at the same time.

Spot trends and know where they’re going

The combination of the data you collect in-house coupled with external data about industry trends offers insight of historic proportions into what consumers want now. You also have access to information that gives you a good idea of what they wanted yesterday. Combined, the historical and present data create a foundation for projecting what consumers will want next week, next month, and next year.

Projecting those market movements is simpler today than at any time in the past. Thanks to Artificial Intelligence and the ability to assimilate and analyze data, it’s possible to create a scheme for predictive analytics that’s highly accurate. Think of how you can use this type of knowledge to structure a digital marketing plan that remains fresh for more than a couple of months.

Refining your ideal customer profile

If you’ve never heard of an ICP, don’t think it’s some complicated novelty. The term is short for “ideal customer profile.” It’s a way of identifying the type of consumer who is most likely to be interested in the products that you offer for sale.

Current and past customer interactions will help you refine the ICP and possibly uncover ideas that you’ve overlooked in the past. That includes data that’s landed on your business network and been forgotten. Along with creating a clearer image of your primary customer demographic, you may identify a couple of secondary consumer markets that would also be a good fit for your products.

Adjusting website content to attract more visitors

Content is a major resource in terms of attracting and retaining consumers. The content found on your website must speak to the needs of those who find their way to those pages. That means you need to know what’s motivating them to visit your website.  And which pages that keep them engaged over a few seconds. And how those pages perform from month to month.

Monitoring the data related to page hits helps you understand what topics hold the interest of visitors. That in turn makes it possible to structure the digital marketing campaign to focus more attention on those topics. Along the way, you may need to tweak the content in order to keep it up to date. Doing so will ensure new visitors are not disappointed when they make a first appearance on your pages.

Gauging the success of your social media efforts

Social media is not going away. If anything, it will figure more prominently in your digital marketing campaigns moving forward. That means you need to pay attention to how well your posts are attracting readers and getting them to go where you want them to go.

The right social media posts will encourage readers to engage with your company, visit the website and blog, and even click over to an order page. By setting up and responsibly using those social media accounts to engage with your targeted client base, you bring another layer to your digital campaign, one that’s relatively inexpensive but has the potential to produce a significant return on your investment.

The eCommerce juggernaut runs on big data

For many online entrepreneurs, about half a million and counting, Shopify is a popular eCommerce platform for building and monetizing a retail audience, and it’s proven to be an excellent way to integrate the power of Big Data into a marketing plan for small business practitioners. Take a look at this list of strategies for a sense of the possibilities.

Does the data indicate there’s a problem with acquisition or retention? Could be trouble with your marketing content or even bad site design. A deep dig into data might be the tool needed to help you pinpoint the exact issue and rectify it. The good news is you don’t need a degree in computer science. What you may find is that a few simple changes to the site is all it takes to make visitors stay longer and spend more.

Making your blog more relevant

Any digital marketing campaign must address the use of a blog. You want the content to be informative and helpful to the readers. At the same time, there must be an obvious connection to what your company has to offer. This makes it easier to include backlinks designed to drive traffic to your website.

What does data have to do with this process? It helps you identify the posts that are consistently getting attention. And the links that redirect readers to your website. Analyze that data and use it to plan future blog posts and the choice of links. The result will be more revenue and probably more social media shares by your readers.

Include options to opt into a mailing list or get notifications about new blog posts. Remember you also want to include a way for readers to remove themselves when and if they like. That keeps you in compliance with current regulations and trending public sentiment in regard to data handling and makes it clear you’re not trying to run some sort of scam involving unwanted contacts.

As well as making the most of guest blog opportunities

(Image: https://i.pinimg.com/originals/df/f1/62/dff162017c7360cb01c556575f3a9599.png)

Does guest blogging help your marketing efforts? Many site owners find that it does. You generate interest by posting on an authoritative blog. Include links to relevant pages on your site. Monitor the traffic from those links and get an idea of how much is coming from the guest post.

Enhancing your text, email, and video marketing campaigns

The data you collect from website visits, social media comments, and responses to blog posts provides fodder for creating the email, video, and text components of your digital marketing campaign. They provide inspiration for creating unity between each of those components without necessarily falling into the habit of dull uniformity. The thrust doesn’t change, even if the message is differently worded.

Final thoughts

Have you fully explored all the data that’s at your fingertips? If you have a sneaking suspicion that you aren’t taking full advantage of everything it can do for your marketing, you’re probably right. Big data has come a LONG way in recent years. And continuing advances make it more accessible than ever to businesses of any size. The thing is, a golden nugget of information could very well be hiding in plain sight, the kind of nugget that takes you to the next level, but you’ll never see it without the insight and processing power that only modern data analytics can provide.

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How eCommerce websites can take product pages to the next level https://bigdata-madesimple.com/how-ecommerce-websites-can-take-product-pages-to-the-next-level/ https://bigdata-madesimple.com/how-ecommerce-websites-can-take-product-pages-to-the-next-level/#respond Tue, 20 Aug 2019 12:31:23 +0000 https://bigdata-madesimple.com/?p=35431 Personalization on an eCommerce website is not unusual in today’s consumer-driven world. Customers want brands to know them; to offer products that fit in with their own needs and preferences. They want to have the same kind of experience as shopping at a store they’ve been going to for years. According to Gartner, 64% of … Continue reading How eCommerce websites can take product pages to the next level

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Personalization on an eCommerce website is not unusual in today’s consumer-driven world. Customers want brands to know them; to offer products that fit in with their own needs and preferences. They want to have the same kind of experience as shopping at a store they’ve been going to for years.

According to Gartner, 64% of all customers around the world would say that they find the “experience is more important than price.” In fact, by the year 2020, customer experience will overtake price completely, as the key brand differentiator.

Offline shopping experiences, online

Picture this: you walk into your local grocery store. You’ve known the shopkeeper for years. He knows what particular brand of coffee you like. So, when the new stock comes in, he makes sure to let you know. And even keeps some aside so that you can pick it up later. 

It’s little personal touches like these that makes shopping experiences for customers so much better. 

Of course, this kind of customer experience in brick and mortar stores is difficult to replicate in online stores. Online, the only thing the visitor interacts with is the webpage. The good news is that interaction data alone is enough to recommend the relevant products to visitors on your eCommerce product page. 

A study shows that about 43% of eCommerce traffic comes from organic Google searches. But most of those visitors leave without really buying anything. 

Why? The difficulty lies in retaining these customers and getting them to zero-in on products. And actually, buy them. 

Which is why, for online retailers, one of the most important pages on their website is the category page. Visitors to the website will spend most of their time on this page, browsing through the products displayed. So, it only makes sense to show visitors products you know they are going to buy. The product page on your website has ample opportunity to personalize according to your customers taste.

‘Picked just for you’ pages can go a long way

It’s important to make your visitors feel like your brand and products are truly for them. And with a little help, this is not exactly difficult to do. Provided you have access to enough customer-based behavioral data and machine learning algorithms.  

However, while a BAU category page can be reordered to prioritize products that match the visitors behavioral data, it can still be difficult for visitors to discover new products they’d like. Having a dedicated page for only the most relevant and personalized product recommendations for each visitor allows them to discover these products. 

Personal “boutique” pages also help visitors freely interact with the website. While at the same time allows them to provide instant feedback on each recommendation.With a machine learning model supporting the page, all of the new interaction data can be used to provide better product recommendations on the page. These recommendations can even be updated in real-time!

One such personalization engine for eCommerce websites is maya.ai. Created by Singapore-based AI and big data company, Crayon Data, the engine helps retailers recreate personal boutiques online. 

However, while personalization is a powerful tool that helps increase conversions, it shouldn’t be your only fall back. 

Don’t skimp on the little things

The design and layout of the product page itself is just as important as the products displayed on it. A website can have the best and most relevant products displayed on the page. But without a smooth user-friendly UI design, quick and easy checkout process as well as engaging and creative ad campaigns, visitors are more likely to abandon their shopping carts. 

On average, conversion rates for an eCommerce website ranges from 3%-4%. 

In order to increase this, it’s important to remember that simple details matter. Like high-quality product photos, which provide a 360° view of the product. In fact, eCommerce companies like Allbirds and Everlane actually have short video snippets to show their products from different perspectives. 

Another important detail that can be used to attract visitors is clear and concise product descriptions and content. Website content that’s not only quirky and interesting but also fulfills SEO standards to make your website more visible.

Optimizing your website is a given. Especially for mobile browsers. The main aim should be to create an effortless and personalized shopping experience for your customers. People who come to your website should get a clear understanding of what you’re offering them, with as little time or effort possible.

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AI provides the foundation for major breakthroughs in cancer treatments https://bigdata-madesimple.com/ai-provides-the-foundation-for-major-breakthroughs-in-cancer-treatments/ https://bigdata-madesimple.com/ai-provides-the-foundation-for-major-breakthroughs-in-cancer-treatments/#comments Mon, 19 Aug 2019 08:56:37 +0000 https://bigdata-madesimple.com/?p=35428 Cancer is a pervasive problem that is becoming more prevalent in the United States and abroad. Oncologists are investing in new technology to improve treatments for their growing number of patients. In recent years, healthcare experts have discovered that artificial intelligence is one of the most promising forms of technology in the field of oncology. … Continue reading AI provides the foundation for major breakthroughs in cancer treatments

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Cancer is a pervasive problem that is becoming more prevalent in the United States and abroad. Oncologists are investing in new technology to improve treatments for their growing number of patients. In recent years, healthcare experts have discovered that artificial intelligence is one of the most promising forms of technology in the field of oncology.

The number of benefits of AI in the field of oncology is almost too numerous to list. However, some of these benefits are so promising that they warrant discussion. Here are some of the top benefits of artificial intelligence for treating all types of cancer.

Personalized radiation treatments

Radiation has been one of the most common and effective forms of treating cancer for many years. However, oncologists have historically been unable to take all necessary patient variables into account when determining whether a patient should receive radiation treatments, duration of the treatment, the number of treatments they should undergo in a given interval of time and the ideal dose of radiation.

The Cleveland Clinic has recently started incorporating AI into its radiation treatments. Oncologists at the Cleveland clinic have been using electronic health records and medical imaging data to get a better understanding of patient at risk factors. They developed machine learning algorithms that rely on this data to develop radiation treatment plans for cancer patients.

This AI-driven approach to cancer treatment has proven to be remarkably effective. The success rate is reportedly over 95%.

These artificial intelligence models are likely to improve over time. According to the Lancet Digital Health publication, the original model relied on scans from 944 patients suffering from lung cancer. These models will eventually start to evaluate the outcomes of patients and offer more effective recommendations. They might also be able to evaluate the long-term health implications of radiation, so they can find a balance between providing clinically effective treatments and minimizing the risk of side effects.

Minimizing toxicity of radiation

Researchers from MIT have started developing new AI technology to improve outcomes for patients with cancer. While most oncologists are looking to use AI to more effectively eliminate tumors, these researchers are focusing on an equally important objective. They are trying to reduce the toxicity of cancer treatments to minimize the risk of devastating side effects.

The team of artificial intelligence scientists at MIT have taken a rather novel approach to their research. They borrowed a concept from the field of behavioral psychology known as reinforced learning. They developed a number of AI automatons that contribute to machine learning approaches. These AI bots are giving incentives to find better outcomes with available data.

Many experts believe that this approach will be useful in other fields as well. The admiration for this work is not limited to the field of AI development. Biologists with little training in AI are praising the research as well, including Nicholas Schork of J. Craig Venter Institute. MIT News contributor Rob Matheson reported on Schork’s opinion on the role of AI in healthcare.

“Schork adds that this work may particularly interest the U.S. Food and Drug Administration, which is now seeking ways to leverage data and artificial intelligence to develop health technologies. Regulations still need be established, he says, “but I don’t doubt, in a short amount of time, the FDA will figure out how to vet these [technologies] appropriately, so they can be used in everyday clinical programs.”

AI is the future of cancer treatment

Healthcare professionals should also be cognizant of AI technology helping radiologists. By definition, radiologists have always led the field by introducing the most advanced and innovative technologies. Many technology companies are developing solutions that will improve cancer patient treatment, as well as assist physicians and improve their efficiency. AI is one of the most promising forms of technology to treat nearly every type of cancer, and these will continue to be developed to address these growing risks.

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Big data and the insurance sector: the latest trends https://bigdata-madesimple.com/big-data-and-the-insurance-sector-the-latest-trends/ https://bigdata-madesimple.com/big-data-and-the-insurance-sector-the-latest-trends/#comments Fri, 16 Aug 2019 11:54:22 +0000 https://bigdata-madesimple.com/?p=35423 Actuarial scientists have made use of PCs ever since the first affordable microcomputers came on the market. This is one field where automation and AI are old news. What’s making headlines in the industry, though, is the fact that cloud-based infrastructure is now the norm for almost all insurance companies regardless of their size. Companies … Continue reading Big data and the insurance sector: the latest trends

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Actuarial scientists have made use of PCs ever since the first affordable microcomputers came on the market. This is one field where automation and AI are old news. What’s making headlines in the industry, though, is the fact that cloud-based infrastructure is now the norm for almost all insurance companies regardless of their size.

Companies that make the most efficient use of this information are often able to gain some leverage over the competition. Since they’re able to plan for the future much more easily. Data doesn’t have to be exclusively financial, however.

In fact, some of the more important applications of insurance information are more closely related to customer service records than investment portfolios. Use of big data in insurance continues to grow, so many companies are looking at more creative ways to revitalize their business operations. In turn, this is leading to the creation of an entire industry that develops technology solutions to help insurance companies keep track of information.

How much data does the insurance sector generate?

It’s hard to put hard numbers on how much data the insurance industry stores every single day. Some server farms have suggested that national insurers may generate several exabytes of information a week after you consider deduplication into the equation. Factor in backups and the number easily doubles.

Engineers have had to write new algorithms capable of dealing with this level of raw information. Predictably, risk management has seen the biggest use of this technology. Emerging threats have eaten into insurance companies’ profits. Which has reduced the chances that some firms can remain viable for long-term.

For instance, many companies only do business in North America or India. However, due to the wide-ranging reforms laid out under the General Data Protection Regulation (GDPR), these companies now have to worry about their customers’ data privacy. New technologies have been developed to automatically sort through huge databases and anonymize information to avoid falling afoul of these laws.

Document repositories usually have huge collections of worksheets. That aren’t ever touched by human hands. People fill them out when applying for an insurance policy. However, there’s only one purpose for storing them. And that’s for adhering to reporting regulations. Over time, these get lost in a sea of similar contracts. Even though they hold information that the GDPR or even domestic rules ban.

Algorithms can search the fields on these and find data that many technicians might not have even realized existed. When companies generate upwards of a petabyte of actual storage each day, this kind of technology is often what stands between profitably and problems.

Compliance isn’t the only field where big data algorithms are helping insurance companies rework their entire operations.

Big data predicts accidents

The most unpleasant aspect of the insurance industry is the requirement to figure out when someone is going to have to cash in on a policy. Underwriters have long debated different methods that can help calculate the odds of any single catastrophic event happening. These methods have been inexact at best for decades, which is why they’re in need of quite an overhaul.

Scientific data organized into tables may hold the secret to more accurate calculations. Sufficiently clean past data of any fields that easily identify a specific policyholder. Insurance companies can use it to build sophisticated databases full of accident statistics.

In the past, actuaries mostly looked at national data and used it to establish the odds of a particular accident happening anywhere. This system, however, considers information collected primarily from people who actually hold a company’s policies.

This focus on strategies that are individualized to each underwriter is slowly paving the way for a new type of insurance policy. One that’s based solely on the backgrounds of individual holders.

User-based insurance policies

User-based insurance (UBI) is a system that allows underwriters to personalize premium prices based on data collected from IoT devices. According to research, over a third of auto insurers will start to offer telematics-based packages by 2020. The health insurance industry has already taken to wearable fitness trackers.

Insurers are realizing that customer demands continue to outpace the plans that are provided to them. Empowered tech-savvy insurance consumers are spending more time shopping around for the best premium rates available. Offering individualized programs is a good way to retain customers. And ensure they’re not lost to progressive startup firms. Who are unafraid to try new things.

As a result, fitness wearables and dashboard cameras aren’t the only pieces of equipment that insurance companies are using to calculate premium rates these days. Fire insurance companies are expected to start using smart home automation devices to keep an eye on just how safe a property is. The same goes for those who insure against other types of property damage.

This kind of software will help to reduce the number of claims made by consumers. However, it’ll speed up the rate of processing existing claims.

Claims processing in a connected world

Analytics technology has helped insurance companies to predict the likelihood of a claim being made at any given time. As a result, most larger firms generally have enough on hand to cover claims when they happen. Predictive AI-based algorithms have also helped to sort out fraudulent claims, which in turn lead to faster processing times for consumers with legitimate problems.

This renewed focus on efficiency in the field of claims processing should help to drop premiums across the board. Especially for those who don’t normally file. If you’ve seen more companies offering accident forgiveness policies lately, then you’re already seeing the fruits of this kind of technology. Moving forward, it’s easy to believe that insurance will evolve into a self-service industry where consumers will no longer have to wait for sales representatives to help them out.

Right now it might look like big data has primarily benefited insurance underwriters. However, it’s really the consumer who will see the biggest positive changes.

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Are AI-powered security cameras better at protecting us than traditional ones? https://bigdata-madesimple.com/are-ai-powered-security-cameras-better-at-protecting-us-than-traditional-ones/ https://bigdata-madesimple.com/are-ai-powered-security-cameras-better-at-protecting-us-than-traditional-ones/#respond Sat, 10 Aug 2019 05:15:23 +0000 https://bigdata-madesimple.com/?p=35394 A new generation of AI-powered security cameras raises lots of questions. Especially for consumers looking for the best balance of protection, privacy, and cost. While new camera tech means more convenience, you should consider the privacy concerns before becoming an early adopter of the technology. The smarter security camera Traditional security cameras have been around … Continue reading Are AI-powered security cameras better at protecting us than traditional ones?

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A new generation of AI-powered security cameras raises lots of questions. Especially for consumers looking for the best balance of protection, privacy, and cost. While new camera tech means more convenience, you should consider the privacy concerns before becoming an early adopter of the technology.

The smarter security camera

Traditional security cameras have been around for decades. And there are hundreds of options for consumers looking for a baseline of added security. The latest traditional cameras are far from obsolete—most offer smart home integration, high-definition video, and smartphone controls that make them both convenient and simple to operate.

AI-powered cameras take security to a new level with the addition of facial recognition technology. Facial recognition is still in its infancy. But these cameras use the technology to expand the capabilities of a traditional security camera. The technology also raises some startling questions and implications for homeowners, and the disadvantages associated with the newer tech may not justify its cost.

How facial recognition technology works

Facial recognition algorithms use specific points on a person’s face (like your pupils, chin, or nose) to take incredibly precise measurements. Once the distances between your features are measured, the algorithm compares these measurements to millions of other saved data points to identify your unique features.

Earlier iterations of facial recognition were limited by things like glasses, hats, blurred images, and faces in profile, but the current generation of facial recognition algorithms boast an astounding 99.98% accuracy for both photos and video.

Facial recognition algorithms already permeate the lives of most Americans. Social media programs like Google, Facebook, and Snapchat have been using the technology for years. And most people’s photos are already part of massive stores of data. An AI-driven personal security camera uses only the data generated by locally recorded footage, but web-connected cameras in public spaces could potentially compare the data of millions of photos to accurately identify any individual.

Facial recognition technology in home security

Over the past several years, security cameras with facial recognition technology emerged on the consumer market. The first versions of these cameras used recorded footage to “learn” the faces of anyone who frequently visits your home. Unrecognized faces would be automatically flagged by the software, triggering an alert on a smartphone or at a monitoring facility.

Facial recognition technology is already becoming a mainstream feature on affordable security cameras. Known brands like Amazon’s Ring doorbells or Google’s Nest cameras. In fact, Amazon’s social network, Neighborhood, allows users to flag the faces of suspicious individuals and share the data with anyone on the network, as well as local law enforcement. Other apps like Citizen and Nextdoor are creating networked neighborhood watches in cities across the US.

AI-powered home security cameras that utilize a local sharing platform like Neighborhood provide law enforcement with the ability to identify and monitor any individuals that are flagged by users. This close relationship between companies like Amazon and law enforcement agencies is unprecedented, and law enforcement may not be required to protect the data gathered by these applications.

Amazon filed a patent in December 2018 that would allow Ring cameras to increase their facial recognition accuracy by building a database from the images collected by any Ring camera. It’s a significant leap from local sharing of images on Amazon’s Neighborhood. The patent has brought the company’s ambitions under intense scrutiny.

The ethics of facial recognition

Programs like Amazon’s facial recognition software, Rekognition, have sparked a backlash from prominent human rights organizations like the ACLU, who recognize the software’s potential for exacerbating racial biases while infringing on the privacy of American citizens. The negative press has done little to slow the adoption of the technology.

Message boards associated with these platforms are often a haven for racist language and racial profiling. An investigation by Motherboard found that the majority of individuals flagged on these platforms are people of color, and the descriptions by users often extend to racial profiling and hostility.

A legislative response

California, Massachusetts, New York, and Washington are all considering legislative action to limit the use of facial recognition technology in certain contexts. Regulations were also considered by Congress on July 2019, as bipartisan concerns grew over the unchecked use of the technology.

Advocacy groups like the ACLU, Fight for the Future, and Liberty is all drawing a hard line against facial recognition technology, citing a loss of privacy and the abuse of data by private corporations. Amazon’s combination of facial recognition and social networking creates a particularly dangerous environment. One of abuse of technology and increased harassment or profiling of people of color.

Facial recognition and you

Security cameras with facial recognition software are rapidly becoming more affordable. Since Amazon’s Ring cameras may soon use AI to process images over the web, the cameras themselves could gain facial recognition capabilities while remaining cheap and easy to install.

Facial recognition cameras offer other benefits for families or busy households. A camera with facial recognition technology can automatically alert you when your child comes home from school. Thereby affording them independence without risk. For business owners, the cameras could substantially decrease instances of shoplifting and hold would-be thieves responsible for lost property.

Public opinion of facial recognition technology is mixed. In September 2018, a survey found that roughly half of respondents were in favor of limitations on the use of facial recognition technology in law enforcement. Less than a year later, a new survey indicated that only one in four people favored these limits. Most individuals approve of the technology if it can be used to reduce crime.

Does facial recognition actually make you safer?

Ultimately, most consumers want to know whether this controversial technology can actually keep them safe. The technology has already been used in a substantial number of arrests; in 2018, 998 arrests were made in New York City using data from the FBI’s Facial Identification Section.

Proponents of the technology also cite the unreliability of human witnesses. Most false convictions stem from false IDs by humans. And the improved accuracy of an AI promises to limit these misidentifications.

There are, however, substantial trade-offs for the enhanced safety that facial recognition technology may provide. Facial recognition data is often stored on private servers with no legislative oversight. Your data could be at risk if those servers are compromised. And there’s nothing stopping major corporations from selling your facial recognition data to advertising agencies.

The bottom line

Ultimately, the adoption of facial recognition technology will be decided by the wallets of consumers. Privacy is being eroded every day by a number of technologies. And many consumers are becoming apathetic to the unrestricted use of their data. So-called neighborhood watch apps already have tens of thousands of users in cities all over the US.

As major corporations and governments prepare for the widespread implementation of facial recognition technology across a range of devices, individuals may soon lose their agency in deciding whether to opt-in or not. The technology is rapidly altering the way our society perceives security and privacy. And the benefits and harms are not yet clear.

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How will AI and data technology transform the insurance industry? https://bigdata-madesimple.com/how-will-ai-and-data-technology-transform-the-insurance-industry/ https://bigdata-madesimple.com/how-will-ai-and-data-technology-transform-the-insurance-industry/#respond Wed, 07 Aug 2019 08:24:44 +0000 https://bigdata-madesimple.com/?p=35374 When someone talks about artificial intelligence or innovation, the last thing that comes to our minds is the insurance industry. The reason for this is because most people can’t find a relation between insurance and high technology, yet it is one of the first industries to be affected by Al and data technology. The insurance … Continue reading How will AI and data technology transform the insurance industry?

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When someone talks about artificial intelligence or innovation, the last thing that comes to our minds is the insurance industry. The reason for this is because most people can’t find a relation between insurance and high technology, yet it is one of the first industries to be affected by Al and data technology. The insurance industry is based on a big bubble of risks, these companies immeasurably depend on their competence of predicting what risk a person, company, or organization depicts. For making accurate predictions, they need information and data, and the more data they have the chance of them analyzing the risk increases. It will also help them save and increase revenue.

Insurance companies can benefit from artificial intelligence and big data technology by enforcing them in their work and getting the upper hand over the competition. But, the question is how AI and Data Technology will transform the insurance industry? Here are some of the reasons how.

Behavioral premium pricing

One example of how technology has changed the way things are functioning in the insurance industry are telematics and wearable sensors, devices capable of collecting customer information. For example, if this device is installed in a vehicle, it will receive information about how the customer drives, at what speed they go on average, how they use the brakes if they do over speeding, etc. All this information helps the company to create a profile about the client as a driver, so they can predict how risk he is and how likely he is to cause an accident. This technology is not just limited to car insurance, but other areas of coverage as well.

Currently, financial models are built on the past performance and statistical samplings, insurance companies, go through and study their client’s records and then make predictions based on that. But, with this new technology, they can access real-time information and use it for their benefit, this way companies will not only get accurate information but will also be able to save tons of money spent on expensive assessments and audits. It will also be beneficial for customers, as careful drivers will not have to pay extra money for less-careful drives, as the company will have individual information about every customer.

Facial recognition

Did you know that the insurance industry is the first one to use facial recognition in their areas of work? Facial recognition is said not to have reached its full potential yet, but the applications it is offering currently are quite remarkable and impressive, and will only get better in the coming future. An insurance company named Lapetus offers its clients to buy life insurance by taking a selfie, an idea you must not have heard or thought of before. What the company does is run an analysis of the facial patterns submitted by the clients, and anticipates signs of life-threatening habits, like alcoholism or smoking. This technology behaves like an accurate predictor of a lifetime, and by making use of it, the company is saving their time and money spent on uncomfortable medical examinations.

AI interfaces and personalization

Modern business is all about giving customers an experience they will never forget, which includes customization. In the past, insurance companies use to offer their clients a limited set of options, which they had to choose from, but those days are now over. Like all other modern businesses, the insurance industry is also adopting the same techniques of customization. One example of this is Allianz1. It is a web interface where the insurance company has set their modules, and by that, the customers are allowed to build their insurance policies.

Faster claims settlement

The two main factors that determine how efficient an insurance company is are how fast it can manage to settle a claim, and how successfully it does it. Companies which are adequate in these two things’ are considered to be on top of their business.

Artificial intelligence technology is what advances both of these factors. As with its help, a company can achieve its goals in a week, which is impossible by even the best human specialist. According to a source, the United States is the largest insurance market in the world today. With China and Japan being the second and third largest markets, respectively. In the year 2017, Lemonade’s AI Jim broke the insurance industry record by settling a claim in less than three seconds, something only possible through AI.

Machine learning

A chatbot helps in building communication with their customers, without having to spend any money on employees. The insurance industry has been actively making use of such chatbots to improve the connections between the company and clients And save costs spent on operations, resulting in lower premium prices. Machine learning is also an ideal option for insurance companies that only work with their clients online. As it can help those counter frauds, and promise their customers a characterized experience.

Decreased fraud occurrence

According to insurance stats, every year, insurance companies report fraudulent activities of more than 80 billion dollars. With personal insurers, it is not physically possible to collect and alter all information about policyholders to help indicate a fraud. But, with artificial intelligence, this is very much possible and practical. Insurance companies that rely on AI can virtually process unlimited amounts of such information; this not only helps them in settling claims at a faster rate but also minimizes the chances of fraud. Furthermore, when companies use machine learning and other such technologies to determine fraud, they will have improved results over time. Which will help them perform in a much efficient manner as compared to the companies still relying on humans.

Conclusion

The introduction of artificial intelligence and data technology in the insurance industry is one great example of Digital Interruption. It has changed the entire course of the industry, and many believe it is going to reconstruct completely. With so much competition and modernization in the world, the insurance industry cannot be left behind and be conservative; they have to move ahead and grasp on to the changes as early as possible. The quicker they will accept these changes, the faster they will observe progress in their sectors of work.

The prediction for the next three years is, the insurance industry will experience a revolution with such technologies. And, this will only be a good thing for both the companies and the clients. As they will both benefit from its easiness and efficiency.

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Take 5! FinTech trends for 2019 that you can’t ignore https://bigdata-madesimple.com/take-5-fintech-trends-for-2019-that-you-cant-ignore/ https://bigdata-madesimple.com/take-5-fintech-trends-for-2019-that-you-cant-ignore/#respond Tue, 06 Aug 2019 11:55:42 +0000 https://bigdata-madesimple.com/?p=35364 Technology has played a crucial role in enhancing the life of a consumer. Various sectors are reaping benefits, but finance is still not quite there yet. When it comes to financial services, traditional banks are hesitant to adapt to newer technologies. This is mostly because of their legacy systems and compliance restrictions. On the bright side, … Continue reading Take 5! FinTech trends for 2019 that you can’t ignore

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Technology has played a crucial role in enhancing the life of a consumer. Various sectors are reaping benefits, but finance is still not quite there yet. When it comes to financial services, traditional banks are hesitant to adapt to newer technologies. This is mostly because of their legacy systems and compliance restrictions.

On the bright side, several FinTech startups are working with new-age technologies to create a more user-friendly platform.

From artificial intelligence, machine learning to the blockchain, various innovations will help streamline the financial sector. These five trends have shown the most promise in taking banking and finance to greater heights:

  • Blockchain
  • Robotics Process Automation
  • RegTech
  • Internet of Things
  • Artificial Intelligence

Let’s take a look at some of these trends.

Blockchain Technology

Blockchain is a distributed database that exists on multiple computers. It’s constantly growing in the form of new sets of data, also known as blocks. Each of these new blocks contains a timestamp with a link to the previous block. These blocks together form a chain. The blocks are preserved forever, making data manipulation or faking documents impossible. 

The blockchain-based technology is perfect for banks as it records transactions on a digital ledger. This ledger has limited access and will improve data security.

Blockchain technology is already helping banks with efficient transactions. By 2020, blockchain technology will power the production systems of 77% of the banks across the world 

RegTech

For the FinTech industry, regulatory compliance is essential. Regulatory Technology or RegTech will help businesses cover both compliance and risk management. The increasing number of regulations will have a direct impact on the costs associated with compliance. RegTech however, will help FinTech firms manage costs and meet requirements. 

RegTech will also provide opportunities in terms of competitive advantage, innovations, and technology integration. 

With banks spending more than $270 billion on compliance and regulatory obligations, it seems like the integration of RegTech will drive FinTech. Some of the more popular solutions in the RegTech sphere are risk management, transaction reporting, regulatory intelligence, and customer identification.

Robotic process automation

RPA will help the financial sector automate human labor and minimize any scope for errors. Considering the amount of data one has to deal with, there is always scope for errors. Robotics process automation will streamline a variety of back-office processes. Most importantly, it will drastically reduce human involvement in tedious tasks. 

RPA implementation will help banks reduce the processing cost by at least 30%. It will also free up the workforce to take up more critical tasks. Customer service, compliance, KYC, fraud detection, report automation are amongst the processes that can be automated.

The Robotics process automation industry is growing exponentially. According to the current RPA reports and trends, RPA is expected to be a $3 billion industry by 2021. By the end of 2019, 75% of financial institutions and banks will start using RPA software. 

Internet of things

IoT is as an ecosystem of connected objects which are accessible through the internet. If an object has an IP address and the ability to collect data, it fits into this ecosystem. 

This data from IoT will help financial companies gain a competitive edge over their peers. It will include user insights such as behavior preferences. Not only will this help bolster customer services but will help finance companies improve security on the whole. 

Among the other benefits of IoT in Fintech are quick customer support, queue management, and contextual services. 

By the end of 2020, more than 50 billion devices will be connected in an ecosystem. This will drive the IoT revenue to 3 trillion dollars. 

Artificial intelligence

As we all know, artificial intelligence or AI is a subset of computer science. AI engines enable computers to perform tasks that are done by people. Implementing AI models in routine tasks saves cost, effort, and time. 

Banks and FinTech companies have access to huge consumer data sets. Due to lack of IT setups, they’re unable to get the best out of it. Integrating an AI engine can help banks analyze every bit of data to provide unique insights for every user. With these insights, banks can create personalized campaigns and offers. 

For instance, Crayon Data, a Singapore based big data, and AI startup have been helping tier-1 banks world over. Their personalization engine maya.ai analyzes large data sets and engages customers with relevant campaigns. The AI engine with taste led personalization is consistently delivering a significant increase in spends across customer segments for various banks. 

AI in finance has led to other benefits and applications such as fraud detection, chatbots, crisis prevention, credit score generator, etc.

Keeping up with the latest FinTech trends is essential to stay relevant in the market. Big banks and FinTech companies are under a lot of pressure to innovate in this increasingly digital world. The only way to retain and attract new consumers is to adapt to modern technologies. With consumer expectations on the rise, implementing new features to their platforms can make the banking experience better. From automation to personalization, 2019 is turning out to be an exciting year for the global FinTech players 

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Cybersecurity: the motivation behind cyber-hacks [Infographic] https://bigdata-madesimple.com/cybersecurity-the-motivation-behind-cyber-hacks-infographic/ https://bigdata-madesimple.com/cybersecurity-the-motivation-behind-cyber-hacks-infographic/#comments Tue, 30 Jul 2019 09:15:04 +0000 https://bigdata-madesimple.com/?p=35338 Cyber-attacks are becoming more sophisticated all the time, with cyber hackers coming up with new and determined methods of threat that are increasingly difficult to detect, making attacks more dangerous than ever before. Statistics show that cybercrime is on the rise around the world. It’s estimated that by 2021 the annual cost of damages from … Continue reading Cybersecurity: the motivation behind cyber-hacks [Infographic]

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Cyber-attacks are becoming more sophisticated all the time, with cyber hackers coming up with new and determined methods of threat that are increasingly difficult to detect, making attacks more dangerous than ever before.

Statistics show that cybercrime is on the rise around the world. It’s estimated that by 2021 the annual cost of damages from cybercrime will cost the world $6 trillion. That’s a significant jump from $3 trillion in 2015, with cyber-attacks now one of the most serious threats to any business.

No matter the size of your organization, whether you’re a start-up business or have scaled to a million-dollar company, you need to be aware of the risk of a cyber-attack.

What’s the motivation behind all this cybercrime? The results of studies done on cyberhacking show that the motivation behind 90% of attacks is about financial gain and espionage. Here’s a closer look at the most-breached industries, who is doing the hacking, and what type of data is being hacked.

The most breached industries

All businesses are at risk for a cyber-attack, but there are some industries that are more at risk than others for hacking. What makes these industries more vulnerable is the type of data that’s at risk of being stolen, including financial, health, and personal information.

Healthcare

24% of all breaches occur in the healthcare industry, 79% of which is medical and personal data such as social security numbers, name and home addresses, information about income, and contact information. Stolen medical information can be used by hackers to gain unauthorized entry to some medical programs or to obtain prescription drugs for personal use or to sell for profit.

56% of the threat is internal, coming from within healthcare organizations, with another 34% being human error as employees leak information to other organizations without being aware of the infraction.

Food Services and Accommodation

Cyber-attacks in the food services and accommodation industries make up 15% of all breaches. These businesses are at high risk because they consistently collect information from their customers such as credit card numbers, name and address, and contact information. This stolen data can be used for identity theft and to gain access to financial accounts.

99% of the threat is external, with payment information accounting for 93% of the stolen data. Of equal concern is that in the food and accommodation industries, 96% of breaches aren’t discovered for a few months, at which time hackers have already used the information they stole.

Public administration

Close behind food and accommodation is public administration at 14% of industry breaches. With personal information amounting to 41% of the compromised data. Government data is at high risk for breaches due to a lack of cybersecurity funding, with 57% of government agencies hacked in 2018.

Both personal information and confidential government records are highly sought-after by cybercriminals at they can sell this data to foreign entities. Hackers who want to make a political statement are also a threat to public sector information.

Retail

The retail industry has always been vulnerable to cyber-attack, with at least 50% of retail businesses experiencing a security breach in 2018. 73% of the data compromised is payment information, with 93% of this data obtained as an external threat.

The payment information stolen by cyberhackers includes both financial and personal data. This can be used to make unauthorized purchases using credit card information as well as for identity theft.

Financial

Making up 7% of breached industries is the financial sector, where 36% of the data stolen is made up of personal and contact information as well as banking and credit card information.

79% of the threat is external, however, this threat doesn’t just compromise individuals, it also costs banking and financial institutions millions of dollars. The average cost per data breach was $7 million in 2017, compared to a lower liability cost for retail businesses.

Professional Services

Professional services, such as accountants and lawyers, are also at risk for cyber-attack, making up 8% of industry security breaches. 56% of this stolen data is the personal information that these services collect from their clients. This can include banking information, healthcare records, and personal contact and family data.

Who is hacking?

Threats to data can come from both internal and external sources. Internal hacking comes from within the organization, such as from employee error or a disgruntled employee. External threats are a malicious attack that comes from outside the organization. These external threats are often done by threat actors. Who attempt to impersonate the organization and lure unsuspecting targets into willingly providing them with personal information.

System administration (internal)

26% of internal hackers are based on system administration. These hackers have access to sensitive data and information and typically work in healthcare, financial, and public sector organizations.

System admin hackers will take advantage of the data they have access to, using it for their own monetary gain and sometimes to provide stolen confidential information to an external source.

End-user (internal)

22% of internal hackers are end-users. These are employees who click on an email link or attachment or who download software that contains malicious malware.

Malware is malicious software that’s made up of code developed by cyberhackers to cause damage or get unauthorized access into computing devices. Usually embedded in a website link or over email, hackers are just waiting for end-users to click on the link or open the email file in order to execute the malware.

Other (internal)

Internal hackers are also made up of about 22% “other” hackers. These fall into various categories. Such as those who want to break into computer systems just to prove they can or hackers who break into computer networks for a political or social cause.

Organized crime (external)

Organized crime makes up 62% of external hacking. The top threat from organized crime is ransomware, where cybercriminals exploit businesses and organizations by using malicious software to block access to computing networks until payment is made.

Other hacking threats include DDos (Distributed Denial of Service) and social engineering. Including phishing to hijack accounts and gain access to personal information.

Unaffiliated (external)

20% of external cyber-attacks come from unaffiliated hackers who are not part of organized crime or state-affiliated hacking. These hackers use sophisticated methods to steal information and make money.

Unaffiliated hackers are difficult to detect. They continue to come up with new malicious software to gain access to computing systems undetected as they bypass cybersecurity.

State-affiliated (external)

13% of cyber-attacks are done by state-affiliated hackers. These cybercriminals usually have a political or social motivation for hacking into computer networks. Often attempting to compromise the usage and accessibility of network traffic.

What data is hacked?

The data being hacked from businesses and organizations is specific and of value to cybercriminals. Hackers look for this data so they can make money, steal personal identities, and for blackmail. Still, other information is sold to external parties for malicious intent.

Most hacked assets

Hacking assets can be taken from information that can be directly stolen from computing devices and networks. This information can be directly used by hackers and includes both personal and financial information. The top data assets involved in security breaches include:

  • Databases: Network databases are involved in 18% of security breaches. One reason for this is that businesses typically use a database to store all their company and customer information. The infrastructure security of databases is constantly at risk. Making them vulnerable to the sophisticated software that hackers are continually creating.
  • POS terminals: Making up 16% of breaches, POS terminals are at risk. Especially from malware that can easily be installed, accessing the system and stealing data such as credit card information.
  • POS controllers: Another 16% security risk is POS controllers which are just as vulnerable to cyberhacking and malware attacks. The POS system is linked to business and customer information and the business payment process.

Most hacked data type

The most common types of data targeted by cybercriminals include personal, payment information, and medical records.

  • Personal: 36% of compromised data is personal information. Including name and address, social security number, and contact information such as email and phone. This data is often used in identity theft and can be used to apply for loans and open new credit cards.
  • Payment: Payment information compromises 27% of the data stolen in cyber-attacks and can include credit card numbers and other financial information. Once hackers have credit card information, they can make immediate online purchases.
  • Medical: Personal medical information can be used by hackers to buy medications or receive medical treatment. Medical data makes up 25% of security breaches.

Hackers are continually finding new ways to steal your data. Is your business at risk? It’s important that you know what types of businesses are most vulnerable and why. No matter how large or small your company, hackers are looking for a sensitive date to use to their advantage. By understanding the motivation of these cybercriminals, you can stay ahead by using preventive measures to keep your business data secure.

Learn more about how to protect your business and customers or clients by reading the full Hacker Motives: Red Flags and Prevention infographic by Varonis. You’ll find out what motivates hackers and what you can do to keep your confidential information safe.

 

 

 

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5 ways AI is changing content marketing https://bigdata-madesimple.com/5-ways-ai-is-changing-content-marketing/ https://bigdata-madesimple.com/5-ways-ai-is-changing-content-marketing/#comments Mon, 29 Jul 2019 05:00:21 +0000 https://bigdata-madesimple.com/?p=35330 For consumers, artificial intelligence conjures images of flying cars and personal robots who clean our homes. However, the fact is that AI is already here and has taken form in our modern, everyday lives. Consider the popularity of Siri and Cortana in electronic devices. Simply defined, AI is artificial intelligence or a computer program that … Continue reading 5 ways AI is changing content marketing

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For consumers, artificial intelligence conjures images of flying cars and personal robots who clean our homes. However, the fact is that AI is already here and has taken form in our modern, everyday lives. Consider the popularity of Siri and Cortana in electronic devices. Simply defined, AI is artificial intelligence or a computer program that mimics the way people behave and think. One huge benefit of AI is that it allows for machine learning.

Machine learning is essentially a computer program that enables machines to analyze patterns in human behavior. Social media behemoth Facebook uses both AI and machine learning to analyze text, recognize faces in photos, and target ads. Collecting and analyzing information about users allows artificial intelligence programs to gain more insight into how users work.

While marketers might be hesitant at first, AI points to better and more comprehensive user experience. Of course, content marketing will significantly change as AI grows and develops over time. Let’s look at five ways artificial intelligence is changing content marketing.

In-depth analysis

Gone are the days of stumbling around in the dark with customers. With more advanced technology and the help of AI, there’s plenty of data at your fingertips. Savvy businesses know that they can use this data to their benefit and give consumers what they want. Regardless of their sector or business model, they can deliver exactly what consumers crave with the help of AI.

Artificial intelligence uses algorithms to sort through data and create the best strategies to market content. By focusing on analyzing those consumer patterns and generating insight that way, a business can market the right content. If the analysis shows one type of content to be more popular than another, companies can pick up on how and why.

All of that comprehensive information points to better content marketing. A lot of the guesswork gets taken out of the process when business explicitly know what customers like. Furthermore, they can continue to provide content customers appreciate and thereby solidify customer loyalty. Beyond delivering great marketing, companies are guaranteed to benefit monetarily from AI content marketing.

Automation of content

AI won’t only help market great content to consumers, it will be able to create it, too!  Chances are you may have already read content generated by artificial intelligence. Short blurbs and news snippets are simple and fact-based content easy for AI to put together.

Marketers can save time and effort by allowing artificial intelligence to create content for them automatically. The key is a carefully crafted algorithm that will enable computers to craft human-like language. Since 2015, news outlets have been using AI to generate news stories. In 2017, the Washington Post used artificial intelligence to generate 850 news stories. Journalists, like many other professionals today, have begun to worry that they’ll be automated out of a job.

While artificial intelligence is more than capable of generating content, it is not yet likely to completely take over. At this stage, less than a quarter of content out there comes from AI and algorithms. Truthfully, that doesn’t seem like much but who knows what the future of AI holds?

More personalized content

Remember Netflix, the online streaming giant that put the movie rental company Blockbuster out of business?  Well, Netflix is a perfect example of AI providing personalized content. Their algorithm analyzes what people watch to provide them with suggestions of what to watch next. Similar companies like YouTube and Spotify are using comparable algorithms to generate suggestions.

Although it doesn’t stop at online streaming services. Companies collect information like age, personal interests, location, device, and surfing times to provide personalized content. Whether it’s an ad on Instagram or a suggested place Near You on Google Maps, AI helps offer better content. Artificial intelligence is making way for content marketing to become wholly personalized.

In fact, this personalization continues on into the world of newsfeeds, as well. Social media platforms use artificial intelligence to customize feeds to users’ preferences. After all, users who see content that interests them are far more likely to interact with it. Content marketers use this information to find out what content will be successful with specific demographics. Many writing services like Trust My Paper use AI to edit and analyze their text before sending it to customers.

AI marketing assistants

Content marketing would appear to be trending towards AI marketing assistants. Computing legends IBM already have a marketing assistant on the job, and her name is Lucy. Lucy goes beyond merely analyzing data and generating content, she can actually plan and segment. In fact, Lucy is so effective that she can do in one minute what a team of humans does in several months.

Marketers looking to take the lead will be keen to employ artificial intelligence marketing assistants on their team. The ability to receive instant answers on what regions to target or what content to include provides serious marketing power. Finding out the specific personality traits of your target audience will never be any more relaxed than with AI. These marketing assistants even can check up on your competitors for you.

The predictive abilities of artificial intelligence are really what give these marketing assistants their strength. Marketers will be able to plan and analyze a variety of hypothetical plans to select the ideal one. For now, artificial intelligence marketing assistants may be out of reach for most budgets. However, as they become more affordable, content marketing will begin to evolve completely.

Improved customer experience

Plenty of businesses already include chat boxes on their websites, which allow for more personalized customer experience. As AI develops this trend toward personalization will only continue. Chatbots and intelligent assistance will become the norm. In the world of content marketing, artificial intelligence will immensely transform the customer experience.

Sportswear brand Northface already uses AI in their online store to mimic the in-store experience. This AI service, powered by IBM, asks consumers about their preferences to help them find the ideal jacket for them. Hilton Hotels is also using artificial intelligence to improve customer experience. Their AI robot named Connie can help guests find their way around the hotel or select a place to dine.

Mass media campaigns are a thing of the past. Consumers of today expect a tailored experience. Artificial intelligence enables marketers to provide that experience quickly. However, the reality is that there are so many channels and campaigns out there, that marketers are falling behind. Attempting to do it all manually just isn’t realistic anymore. This is where the computing power and analysis of AI can really help content marketers improve.

Final thoughts

While most of the content marketing done today is still very much manual, things are changing. Marketers are letting algorithms and machine learning do more of the work for them. It’s only natural as artificial intelligence becomes more and more a part of our daily lives.

Consumers of today expect personalized experiences and relevant ads. They’ve signed away their rights to privacy for the comfort of better user experience. Artificial intelligence is giving them what they want. It will continue to do so as AI grows, expands, and takes over the marketing landscape.

 

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How streaming technology is educating every generation https://bigdata-madesimple.com/how-streaming-technology-is-educating-every-generation/ https://bigdata-madesimple.com/how-streaming-technology-is-educating-every-generation/#respond Fri, 26 Jul 2019 05:59:58 +0000 https://bigdata-madesimple.com/?p=35326 Streaming technology is disrupting how we learn in the same way it’s changed how we consume entertainment. As an analogy, think of Netflix’s evolution from DVD to streaming service. The humble beginnings of the media giant started with mailing customer’s DVDs. Customers would sort through a list of movies, choose titles that interested them, and … Continue reading How streaming technology is educating every generation

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Streaming technology is disrupting how we learn in the same way it’s changed how we consume entertainment. As an analogy, think of Netflix’s evolution from DVD to streaming service. The humble beginnings of the media giant started with mailing customer’s DVDs. Customers would sort through a list of movies, choose titles that interested them, and wait several days to receive content. If customers didn’t like their choices, they had to wait until the next title arrived.

Contrast that system with today’s Netflix streaming platform. It’s instantaneous. If customers don’t like a movie, they can stop and select another. Bad choices are immediately rectified. And today Netflix customers are guided more than ever in their choices. Since the early days of snail mail delivery, Netflix has perfected its recommendation algorithm to keep almost 150 million viewers engaged and subscribing. In short, Netflix’s DVD system is like the traditional classroom, with all its limitations with respect to time and interest.

In contrast, today’s streaming technology offers unlimited content, personalization, and targeted information delivered in real-time to learners. These characteristics are changing when, where, what, and how people of all ages learn. And learning online isn’t limited to online courses. Educational videos, podcasts, MOOCs (Massive Open Online Courses), and live streams are just a few tech platforms that bring information to people around the globe. Education is no longer a DVD in an envelope; it’s lightning in a bottle.

Streaming documentaries as voices of authority

Americans consume large amounts of news and information in a single day. Twitter and Facebook feeds are full of breaking news. And 24-hour cable news networks round out our evenings or serve as background noise to our workouts. But at least part of our daily information about the world comes from documentaries. These cinematic slices of real life are entertaining and educational. Nature documentary series like Our Planet are breaking new ground in the genre while crime dramas like Making a Murderer amass huge viewerships.

The documentary streaming service MagellanTV found in a survey that documentaries make up about 15% of their viewers’ total watch times. Millennials watch more than both Gen Xers (13%) and Baby Boomers (12%). While the total watch time may seem small compared to traditional news, the impact documentaries make on viewers is anything but. Among the survey’s respondents, 70% said they had shared something they learned in a documentary with others. For Millennials, that number hit 77%. The survey gets even more interesting when you consider personal impacts. Overall, 44% of survey respondents reported that watching documentaries inspired change in their lives. Again, that number spiked with Millennials, with 57% saying docs change their world view.

The survey data foregrounds an important point about streaming documentaries: while they’re a minority source of content, they’re viewed as credible voices of authority. Viewers trust their information enough to share with others. The power of a documentary comes from its deeper dive into a topic, an approach to facts that goes beyond thirty-second sound bite or a 280-character tweet. That’s a big differentiator in a world where perceptions of “fake news” and altered videos are threatening the credibility of traditional news sources.

Big data and recommendations

Streaming providers like Amazon, Google, and Spotify collect large amounts of data on their customers preferences to improve their experiences. These platforms track what you watch, what you listen to, and what you search for. All this data feeds algorithms for recommendations and “You might also like” suggestions. By personalizing content, these services keep customers watching longer and listening more.

Streaming video services like YouTube and Netflix track not only what you watch, but how you watch it. The data collected can include when you pause, rewind, or fast forward through a video. They can track what device you use for what content (e.g. iPads for children’s shows) and what time you like to watch. While some caution that recommendations limit our experiences or weaken our decision making, others point to the efficiency and personalization they bring.

And these same big data recommendations are making similar inroads to educational content. Whether you’re searching for the capital of Bangladesh or enrolling in an online coding class, learners want accurate information delivered fast.

Online learning platforms like Khan Academy and Lynda.com track user profiles to make suggestions on future courses. If students are working above their comprehension level, these platforms can suggest more basic lessons and vice versa. Students can find courses on related topics that can broaden their skills set or increase their knowledge. Recommendation lists help students stay engaged and on track. And big data and machine learning algorithms make this possible.

YouTube Search: targeted information

Everyone has searched for “How to do X”, only to be presented with an overly complex, 15-minute explanation by a YouTuber who’s more interested in marketing their own channel than answering a question. Or your question about “How to devein shrimp” may be buried somewhere in a video on “How to Cook Jambalaya”. Google’s search algorithm saves learners time by targeting the specific information they want. And since YouTube is now the second most popular search engine, the learning and time-saving potentials are significant.

When searching for something on Google, the results page often contains “featured snippets”. Snippets are usually a bulleted list of steps or a short definition presented. And they’re presented at the top of the search engine results page (SERP). Snippets often result from a user searching for something like “How to do X” or “What does X mean”. The idea is that a surfer need not click through to an article to have their query answered. Instead, Google presents the answer on the SERP.

Now, YouTube (owned by Google) is using the same strategy to expedite answers. Alongside featured snippets is a “suggested clip”. These are videos that answer specific questions. They can be entire videos or only sections. To save time, YouTube cues up the playhead for you right where the answer begins. No more watching lengthy intros or scanning through videos. Online education platforms also use this same strategy, pulling out a single video from a larger course that deals with a specific topic.

Future of streaming for education

These aspects of streaming content help students of every age learn faster and more effectively. And the future looks to be even brighter for teachers too. Educators of all levels are beginning to take advantage of tech like live streaming to make concepts more immediate and relevant for students. With live streaming platforms like Periscope or Facebook, educators can broadcast lectures or take kids on virtual field trips. Virtual reality is giving students first-hand experience in practicing skills or serving as flight simulators for surgeons. And mobile learning’s increased popularity is disrupting the traditional classroom — redefining when, where, and what kids of all ages can learn.

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