The way: 5월 2018

New GSMA Study: Operators Must Look beyond Connectivity to Increase Share of $1.1 Trillion IoT Revenue Opportunity

By TheWAY - 5월 31, 2018

New GSMA Study: Operators Must Look beyond Connectivity to Increase Share of $1.1 Trillion IoT Revenue Opportunity

GSMA Intelligence Releases Global IoT Connections and Revenue Forecasts

COPY. GSMA

LONDON-- The global Internet of Things (IoT) market[1] will be worth $1.1 trillion in revenue by 2025 as market value shifts from connectivity to platforms, applications and services, according to new data from GSMA Intelligence. By that point, there will be more than 25 billion IoT connections (cellular[2] and non-cellular), driven largely by growth in the industrial IoT market. The Asia Pacific region is forecast to become the largest global IoT region in terms of both connections and revenue[3].

“As the number of connected consumer devices and industrial machines grow rapidly, the IoT ecosystem will evolve to become a trillion-dollar market over the course of the next decade,” said Sylwia Kechiche, Principal Analyst, IoT, GSMA Intelligence. “But the IoT revenue opportunity is shifting away from simply connecting devices to addressing specific sectors with tailored solutions, and successful ecosystem players will need to adapt their business models in line with these market trends.”

Revenue Opportunity Moving Beyond Connectivity

Although connectivity revenue will grow over the period, it will only account for 5 per cent of the total IoT revenue opportunity by 2025, underscoring the need for operators to expand their capabilities beyond connectivity in order to capture a greater share of market value. This is a challenge already being addressed by a number of operators, which are creating dedicated IoT business units and service lines.

Meanwhile, the platforms, applications and services segment will continue to increase as a share of overall IoT revenue, capturing two-thirds (68 per cent) of the total by 2025. This category spans multiple IoT layers such as platforms; application services; cloud; data analytics; and security. IoT professional services - which include system integration, managed services and consulting - will account for the remaining 27 per cent share of total IoT revenue by 2025.

Industrial IoT To Drive Connections Growth

GSMA Intelligence forecasts that the total number of IoT connections (cellular and non-cellular) globally will reach 25.2 billion in 2025, up from 6.3 billion in 2016. The industrial segment, which refers to IoT solutions deployed within enterprises or vertical-specific applications, will account for more than half of the connections total by that point (13.8 billion), while the number of IoT connections in the consumer segment will reach 11.4 billion, driven by developments in the smart home market.

“It’s well understood that connectivity will represent only a fraction of the total IoT opportunity. Complementing our IoT connections data with this major new dataset and analysis on IoT revenue provides a comprehensive and realistic view on where market opportunities exist for operators, vendors, integrators, and everyone else playing in the IoT ecosystem,” explained Peter Jarich, Head of GSMA Intelligence.

IoT connections and revenue forecasts are now available on the GSMA Intelligence platform for subscribers to the full service. The datasets provide forecasts for 2010-2025 for every region worldwide. Two accompanying reports provide commentary and further insight:

‘IoT: the $1 trillion revenue opportunity (May 2018)’

‘IoT: the next wave of connectivity and services (March 2018)’

About the GSMA

The GSMA represents the interests of mobile operators worldwide, uniting nearly 800 operators with more than 300 companies in the broader mobile ecosystem, including handset and device makers, software companies, equipment providers and internet companies, as well as organisations in adjacent industry sectors. The GSMA also produces industry-leading events such as Mobile World Congress, Mobile World Congress Shanghai, Mobile World Congress Americas and the Mobile 360 Series of conferences.

For more information, please visit the GSMA corporate website at www.gsma.com. Follow the GSMA on Twitter: @GSMA.

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HOW BIG DATA CAN TRANSFORM THE FINANCE INDUSTRY

By TheWAY - 5월 28, 2018

HOW BIG DATA CAN TRANSFORM THE FINANCE INDUSTRY

Big data in the finance industry will help overcome major challenges, gaining valuable insights to improve customer satisfaction and overall banking experience.

In today's digital world, organizations generate and collect data to improve transaction processing. Vast chunks of data get assimilated daily and it is essential to maintain them securely while meeting security constraints. Most banks fail to properly exploit the digital assets. It is crucial that the collected data must be put into good use as these bits of data can sometimes contain significant hidden information, which can drive to new opportunities. According to IBM, over 80% of data is dark data, expected to rise to 93% by 2020. However, every data that is generated and collected can be processed accurately with the use of big data analytics, which aim at analyzing, storing, querying, and updating substantial voluminous amounts of information. Big data in the finance industry has the potential to transform the finance industry by quickly assisting customers.

Challenges faced by the Finance Industry

The finance industry faces specific problems with the traditional data management models. One of the most significant challenges faced are the fraudulent activities that are increasingly growing. The conventional model lacked to maintain the security of digital assets, which enabled hackers to achieve vital customer or industry data. Hence, there is a need to overcome this challenge at the earliest, since there is a high risk that the finance industry could burn out. Another major problem faced is the analysis of customers' sentiments. Most clients represent real wealth for any organization, and every industry must keep fulfilling their ever-increasing demands. The traditional model, however, does not provide any technique to analyze their customers. Moreover, conventional model lacked in segmenting their customers based on their transactions and other internal and external processes. Furthermore, business users cannot target the right audience for their marketing purpose with the traditional model. The list is endless. There is an urgent need for an advanced technology that could help banks overcome these challenges that are impacting their financial results.

Big data in the Finance Industry

As we are aware of the challenges that the finance industry faces with the traditional data management models, it is high time to leverage big data analytics to overcome the biggest issues. A few years back, a survey said that 84% of enterprises see big data analytics changing their industries' competitive landscapes. This states that big data analytics can transform various industries, including the finance industry. Big data analytics help the finance industry to maintain security and privacy of the collected data by the use of predictive analytics.

Predictive analytics help in predicting any fraudulent activity in the future, thereby helping detect hackers. Additionally, predictive analytics could be used to predict a machine breakdown, if any. Furthermore, big data analytics could be used by the finance industry for marketing purpose. Through social media platforms with sentiment analysis researchers can gather sentiments, opinions, and feedbacks of customers that can help them alter a business if itscustomers are unhappy. This will help banks to analyze their customer better and alter their business if necessary.

Furthermore, big data analytics help in customer segmentation, which allows the industry to find the right target audience. Banks can, thereby, boost their marketing skills and make maximum profits if they are able to properly leverage big data analytics. According to a recent IBM survey, more than 25% financial institutions are using big data analytics to stay ahead of the curve. Big data in finance has the potential to quickly identify real-time customer sentiments, prevent fraud, improve marketing tactics, and accelerate business growth.

SOURCE: https://www.bbntimes.com/en/technology/big-data-is-transforming-the-finance-industry

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How airlines can leverage in-flight audiences with big data and personalisation

By TheWAY - 5월 27, 2018

How airlines can leverage in-flight audiences with big data and personalisation

With reliable connectivity, audiences becomes a valuable, brand engagement opportunity for both airlines and marketers

Until recently, 35,000 feet was a connectivity blackspot, unreliable at the best of times, and non-existent for the rest. But as full inflight connectivity (IFC) becomes ubiquitous, all this will change. Increasingly, airline passengers are opting to bring their own devices to watch and access the movies, Netflix series or e-books of their choice.

With reliable connectivity, this captive audience becomes a valuable, brand engagement opportunity for both airlines and marketers. Connectivity and data will enable greater personalisation of the passenger experience, increase passenger satisfaction and unlock an entirely new ancillary revenue stream. For marketers in Asia, it provides an untapped opportunity to engage a captive, mobile-first audience and deliver highly targeted, personalised campaigns.

Personalisation sells

A recent survey by Accenture found that 96% of leading airline executives are in favour of personalising the air travel experience using real-time data. According to Mark Brown, vice president for EMEA of UK-based Fusion, which aims to ‘optimise customer interactions’, the more personalised the offer, the higher the sales. His company typically drives 20-25% growth in traffic for its clients when it optimises the products they want to sell. We are already seeing examples of how this works on the ground, with some airlines and online travel agents using data and customer segmentation to deliver dynamic pricing.

Customer data is also beginning to change service in the air. Cathay Pacific, for example, leverages small data to predict the type of alcohol that first class passengers like to drink. Smartphones installed with airline branded apps become more valuable platforms for offers and tailored experiences, once inflight data is fed to them.

Flight time becomes prime time

Pervasive inflight connectivity will mean real-time data can open the controlled environment of the flight to the latest targeted digital messages that have become so familiar on the ground. Today’s passenger spends a significant portion of their time on their mobile devices, and this always-on connectivity on the ground is fast becoming an expectation in the air.

In our 2017 Global Passenger Survey, 91% of the passengers surveyed in Asia Pacific said they were willing to pay for Wi-Fi on long haul leisure flights and 79% on short haul leisure flights – some of the most willing globally to pay for inflight Wi-Fi. Each week, approximately 7,200 flights land or depart from Singapore’s Changi Airport – equating to more than 62.2mn passengers passing through the airport each year. With airlines like AirAsia and Singapore Airlines beginning to roll out in-flight connectivity options for passengers, the connected flight is set to become prime time for smart marketers.

With real-time data, offers could be made based on the passenger’s data throughout the whole journey experience. Passengers may get used to making onward travel plans in the air once robust Wi-Fi is business as usual. Would the passenger like to book a taxi to the airport now? The ad network could show real-time prices paid for by taxi brands at the destination. Would they prefer a train at their destination? The system could flash targeted offers on tickets. Messages can be tailored once the data indicates behaviours and preferences of passengers. If they chose a special meal, a destination restaurant’s campaign could be served in response to their selection. Last minute offers could fill open tables with passengers about to land in a new city.

Connectivity will bring the seat back screen, inflight digital display and airline portal messages up to speed with the world of online advertising and transform the value of the ad opportunities that airlines control. Adding detailed customer information to contextual real-time behaviour, even if anonymized, will make the airline’s connected ecosystem as valuable as a publisher.

Engaging a captive audience

With passengers increasingly being able to use their social media, messaging and shopping apps in the air, the opportunity for more targeted and relevant messaging is vast. Airlines host a captive audience over long journeys, effectively holding consumers on their platform for longer than many media outlets could manage. Because the airlines already have customer segmentation and data around the flight aggregated, they can offer the chance to optimise advertiser messaging. Automated combinations of destination, seat class, device usage, language and customer history information, could be combined with real-time data of passenger engagement to create precisely targeted sequences of messages. Connected airlines have the chance to become sophisticated media platforms and data sources.

The connected inflight ecosystem will also produce enticing affiliate deals as the data emerges to prove which passengers are most ready to buy. Entertainment brands may pay or provide content for free so that flyers can try their subscription services. Qantas, for example, offered a chance for Spotify and Netflix to trial subscription sampling with a free window. How the mix of advertising and sponsorship opportunities are displayed to the airline customer will depend hugely on the brand, but once passengers can be reached with this dynamic messaging, the more relevant and hyper-targeted it can become.

Taking flight

Data-driven air travel has enormous potential for digital marketers looking to create meaningful attribution. Sky High Economics, a comprehensive report developed by The London School of Economics (LSE) and Inmarsat, forecasted two key ancillary revenues areas for airlines: e-commerce and digital advertising, with broadband in the sky set to create a $52bn market in Asia Pacific by 2035. While there will always be passengers who prefer an unconnected experience in the air, consumers in this region are largely early adopters and purveyors of the BYOD phenomenon.

Providing the option for passengers to purchase reliable WiFi, should they choose, is fast becoming a growing necessity of today’s connected world. The question now is how marketers in Asia will leverage this new, golden era of travel to their advantage.

Ben Griffin is vice president of aviation for IMEA and Asia Pacific at Inmarsat.

This article is about: Singapore, Airline, Thought Leadership, Digital, Digital Advertising, Events, Marketing, Media, Mobile, Social Media, Advertising, B2B, Marketing Services, Technology, Transport & Logistics, Brand

SOURCE: http://www.thedrum.com/opinion/2018/05/21/how-airlines-can-leverage-flight-audiences-with-big-data-and-personalisation

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Artificial Intelligence To Add $182 Billion To U.A.E.’s Economy By 2035

By TheWAY - 5월 26, 2018

Artificial Intelligence To Add $182 Billion To U.A.E.’s Economy By 2035

rtificial intelligence or AI as it is more commonly referred to will have a strong economic impact in the U.A.E., a new study has found.

According to a report by Accenture, AI will boost economic growth within the U.A.E. by 1.6 percentage points, adding $182 billion to the national economy by 2035. The report examined the impact of using AI on 15 industries in the U.A.E. and 13 in Saudi Arabia.

As per the findings, AI was found to have the maximum impact on the financial services, healthcare, transport and storage industries with increases of $37 billion, $22 billion and $19 billion, respectively, in their annual gross value added (GVA), which measures the output value of all goods and services in a sector.

AI is also set to lead to an increase of $6 billion and $8 billion in GVA within labor intensive industries such as education and construction respectively, the report found. Meanwhile in Saudi Arabia, AI will increase GVA by $215 billion.

The findings come as the Middle East and specifically the U.A.E. look to AI to diversify away from its dependence on oil revenues.

Last year, the U.A.E. revealed an artificial intelligence strategy that largely aims to speed up the government’s productivity and improve the performance of all official departments. The country also appointed a minister for artificial intelligence to spearhead the development of its AI strategy.

Within the U.A.E., the emirate of Dubai has been at the forefront of automating processes. Dubai has introduced robo-cops, aiming to transform nearly 25% of its patrolling taskforce to robots by 2030. The emirate has also started testing the world’s first autonomous taxi-pods.

Meanwhile Saudi Arabia recently awarded a robot its citizenship, signaling its willingness to embrace AI as it develops its non-oil economy.

“The level of growth that AI stands to bring to the U.A.E.’s economy is unparalleled,” said Amr El Saadani, managing director of Accenture’s Financial Services practice in the Middle East and Turkey. “The nation’s leaders already understand the impact of this powerful technology, evidenced by the appointment of the first Minister of AI last year.

“While AI-led growth will be felt across a wide variety of industries, the financial services sector has the most to gain — which isn’t surprising, given that many of its jobs can be significantly augmented with AI and machine learning. In addition, Accenture reports have already shown that banking executives globally are taking action to transform their businesses through the use of AI.”

SOURCE: https://www.forbesmiddleeast.com/en/naguib-sawiris-beltone-financial-to-acquire-significant-stake-in-oragroup/

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Artificial intelligence: The reality beyond the movies

By TheWAY - 5월 25, 2018

Artificial intelligence: The reality beyond the movies

“Artificial intelligence (AI) is coming to get us” and it’s just a small step from a self-driving car to AIs taking over our world and the “end of days” dystopias that Hollywood has popularised in a number of recent films. Or so some would have us believe.

The reality is far less dramatic, and AI will need to go through a number of stages of development before it reaches the most extreme scenarios – if ever. In our recent book Beyond Genuine Stupidity – Ensuring AI Serves Humanity, we explore the possibilities and challenges presented by this game changing technology. In this article we draw on key concepts from the book to demystify the fundamentals of AI.

What is Artificial Intelligence and why now?

At the core of the concept of AI is the idea of developing intelligent machines - e.g. computer algorithms that work and react like humans. Applications include performing speech recognition, natural language processing and translation, visual perception, learning, reasoning, inference, strategising, planning, intuition, and decision-making. People have been working on these concepts since the 1940’s and AI has experienced many false dawns or “winters” as the AI community likes to describe them.

This time round, the feeling is that AI is here to stay. There are five main factors that have made AI the hot topic on the agenda for companies, investors, politicians, and citizens alike.

Firstly, we are seeing the development of far more efficient and smarter machine learning tools – the core algorithms through which AI systems develop their intelligence. 2) In parallel, computer hardware processing power and transaction speeds have accelerated, and 3) cloud computing allows us to share and combine data and processing power across the globe. 4) At the same time companies such as Google and Amazon have amassed vast amounts of data that require AI to process it – giving rise to 5) money. The scale of the opportunity presented by AI has seen billions of dollars being invested by these new technology companies, corporates in other sectors, and venture funded start-ups – so the game is well and truly on.

Core Fields of Artificial Intelligence

There are a number of different fields which fall under the broad umbrella of AI, the main ones are described below. The most common are rule based or “expert” systems which can apply vast number of rules on a consistent basis. These have been around for over 30 years with common applications including the processing of loans and mortgage applications and basic medical diagnosis.

Robotic Process Automation (RPA) is the next stage on, with machines performing complete processes that in the past required a combination of rule based decision making and an element of human judgement – common in tasks such as handling calls to service centre, processing an insurance claim, or checking the calculations in an architectural design.

Tasks considered closer to true human intelligence include voice recognition, interpretation of human conversations conducted in “natural” languages, and speech generation. Similarly, considerable progress has been made with computer vision – enabling the ever-more accurate recognition of images – with application as diverse as spotting misshapen pies on a production line through to facial recognition for airport security purposes. Other increasingly deployed AI applications include tools that can undertake sophisticated planning, scheduling, and optimisation of tasks - encompassing everything from manufacturing to crew rostering.

The hottest field of AI at present is Machine Learning - the notion of using statistical techniques to help systems learn from data. This is the area gaining most attention at present because of its potential – namely the use of neural networks and deep learning algorithms to develop systems with learning capabilities closer to those of the human brain. These tools are being used across a range of applications, with the most common being chatbots to perform increasingly sophisticated customer interaction tasks by combining machine learning, natural language processing, and speech generation.

Finally, robotics is being put to widespread use in everything from warehouse management and surgery to cooking burgers in restaurants. Robots typically combine a number of the other Ai fields to provide smart mechanoids.

As we said time round, the feeling is that AI is here to stay. It could become central to every aspect of human existence from detecting and treating heart failure through to running companies, economies, and legal systems.

Rohit Talwar, Steve Wells, Alexandra Whittington, April Koury, and Helen Calle, of Fast Future

SOURCE: https://www.gigabitmagazine.com/ai/artificial-intelligence-reality-beyond-movies

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5 WAYS BIG DATA GETS MISUSED

By TheWAY - 5월 24, 2018

5 WAYS BIG DATA GETS MISUSED

Let’s get this out of the way right now: data of any kind can simultaneously be both incredibly beneficial and damaging. Not all data has the capacity to be harmful on its own, yet the ways in which you choose to collect and leverage it can change that.

A simple email address, for instance, can be a great example. When you provide your address to a company for future communications, you’re aware they will be using your email address to contact you. While it’s likely many who collect your email will send you promotional content, you consent to this and know it’s going to happen.

But when a company gets your email address without your consent, the concerns become more potent. The party involved never gave you the option to avoid communications and mined your information without your express consent or knowledge.

The scenario is even worse in the case of more sensitive data, such as your phone number, your home address, family information or even your Social Security number or other personal identifiers.

The danger isn’t always because a company has hidden motives, either. Many mobile apps and analytics tools, for instance, can do things like track the time you spend at work, improve your efficiency and performance and help you make better decisions.

These apps and platforms aren’t an issue, but the vulnerability of the data they collect is. In the event of a data breach or cyber attack, the inherent risks can come to fruition.

How Big Data gets misused

In today’s hyper-digital landscape, data is necessary to partake in so many experiences. Shop online via retailers like Amazon, and the website tracks your order history and purchase data.

When you browse social media, your favorite platforms mine your interactions and interests for future targeted promotions and ads. Visit a chain restaurant’s website, and it collects your location data to better provide local and relevant information.

Data makes the online world go around, and, believe it or not, it now also helps facilitate real-world experiences too. However, even though it’s necessary, that doesn’t mean it’s always safe.

The moral implications of improper profiling

One common form of big data and analytics businesses use to understand their consumers relies on a technique called algorithmic profiling. Through a variety of collected datasets and information, an analyst can merge and study the details to find more complex targets.

To create the datasets, automated algorithms sort data based on a variety of meta-information. However, much of the sorting flies under the radar, and as a result, remains proprietary and private. At any given time, people visiting a site or using an app have no idea the technology is categorizing them based on their actions.

Data profiling can lead to some extremely dangerous and morally concerning habits. For example, it is possible to compile lists with the names and contact information of rape victims, the addresses and locations of domestic violence shelters, people with specific illnesses and more. People called data brokers can then get their hands on these lists and sell them to interested businesses.

Pam Dixon from the World Privacy Forum testified to the U.S. Congressabout these exact things happening.

Discrimination

Similar to the problem with algorithmic profiling, big data can be — and currently is — a source of both intentional and unintentional discrimination in all forms, not just race and nationality.

A Google study, for instance, revealed men and women see separate online job ads, resulting in men being exposed to ads for higher-paying jobs and better opportunities, more often.

It’s not always due to direct targeting from a specific individual or group, however. Facial recognition has a tough time identifying those who are not white or fair-skinned. On personal devices like a smartphone, it’s frustrating. Yet, when companies or law enforcement agencies use the technology on a greater scale for activities like criminal identification and profiling, it’s not only unethical but puts vulnerable people at risk.

Data, system and collection errors

With the sheer amount of data being collected, and how it gets collected, there is certainly room for error. How does the system or business know, for example, that you prefer strawberry over vanilla?

With smaller details that are less consequential, this isn’t an issue, nor is it scary. In fact, it can be silly to see how many odd things advertisers suggest for you based on something like your past browsing habits or recent purchases.

But what about when the information is much more crucial to your life or opportunities? What about when it involves your identity entirely? Australia’s automated debt recovery system has been the target of complaints, many of which purport the system inaccurately targets improper or vulnerable people.

Welfare cuts in the U.S. powered by big data systems have also come under fire for harming the lives of many innocents in Indiana, Florida and Texas due to inaccuracies.

Misinformation visualization — the improper visualization of data — is also possible through collection or processing errors. This can lead to distorted or corrupted data that has unintended consequences for both your audience and organization.

This brings us to the question: how do we know a system is truly accurate and that an algorithm is working properly? What happens when there are errors or bugs, and how do we address them?

Data breaches or cyber attacks

Massive troves of data must have a home somewhere. Companies tend to deploy their own local or in-house data centers to this end, or they outsource the systems and handling to a third-party provider. In any case, the collected information gets stored on remote servers often not far from an open connection. It is exposed, especially to outside and unscrupulous groups.

In the event of a large data breach, which happens often these days, that information and data can quickly become compromised. Sometimes the root cause is lax security, while other times, it’s through no fault of the company that was collecting said data — though they are certainly still responsible for it. Yet the compromised data is affecting thousands, maybe even millions, of people.

A widescale data breach comes with many consequences and repercussions. It can lead to identity theft, blackmail, reputation or social damage, and even financial or personal issues. The companies that owned the data can face legal and financial punishment, as well.

Political or social manipulation

It’s crazy to think about, but the more people and organizations know about you, the more influence they can have on your life choices. For example, the rise of bots that circulate false information online has been a frequent topic of recent media coverage concerning the effect they can have on political polarization.

In these circumstances, the disseminated information often gets manipulated based on hidden motives. This spread of misinformation causes both social and political harm. In this way, propaganda has taken on a new form in the modern digital age.

The Oxford Internet Institute revealed the results of a study on this problem, exploring how misinformation via social media can be weaponized to manipulate public opinion. You might also be surprised to learn these tactics are in use in at least nine countries, likely more.

How do we prevent data harm?

Luckily, there are already groups focused on developing ideas and solutionsto scenarios involving misuse of data.

Everyone should strive for greater transparency, better security and protections, accountability and due process for modern digital data and its handling. Public and political pressure is the best way to get things done, and put standards, regulations and limitations in place to protect the public.

SOURCE: https://irishtechnews.ie/5-ways-big-data-gets-misused/

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The Art Of Being Heard: Are Big Data And Analytics The Future Of Music Marketing?

By TheWAY - 5월 23, 2018

The Art Of Being Heard: Are Big Data And Analytics The Future Of Music Marketing?

As the use of big data as a marketing tool gains speed in music industry, Natasha Lane here explores in depth the definition of big data, and how it applies to music itself, and the marketing strategy implemented for said music.

Guest post by Natasha Lane

We live in an age of information overload. Every time you go on the internet, your devices produce huge amounts of data that contain your actions, locations, preferences, etc. It is said that users create around 2.5 quintillion (that’s 1 followed by 18 zeros) bytes of data in total on a daily basis. This constitutes what people refer to as big data. Analyzing this type of data can help companies create more effective ads and make better campaigns. This marketing concept is slowly entering the world of music, as well, and many successful companies and artists actually rely on big data and analytics. In case you want to get in on it, we’re going to show you just how it works and what are the benefits.

The Definition of Big Data

Source: freepik.com

One of the main problems with big data is its definition. Some people believe that it is a rather arbitrary and loose term, but no one dares deny its importance. Gartner technically defines this term as:

Big data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.

The most important distinction between big and regular data is that the former can’t be analyzed with normal processors because of the sheer volume and complexity.

Big Data and Music

OK, so what does big data have to do with music and how can it be applied in the music industry? Well, it seems that big data analysis might be the most reliable way to assess the popularity of songs and artists.

Source: unsplash.com

Well, back in the 1950s, charts relied mainly on the number of sold albums and these stats weren’t actually that reliable. Radio DJs basically chose the tracks on their own accord and these tracks became the most played ones. The things changed at the start of the 1990s thanks to Billboard’s use of a new technology called Soundscan. An article by Emmanuel Legrand notes:

Based on purchases scanned at till level, the system could for the first time measure actual sales. It transformed the music landscape in the USA by showing that music genres such country, R&B or rap were far more popular than previous charts showed, to the detriment of “heritage” acts whose performances dwindled.

Now, however, big data offers an even better insight into people’s music choices. Companies can now collect precise information about user’s listening habits and calculate the true popularity of songs.

Source: unsplash.com

Take Shazam, for example, a popular app that helps you identify the song from a recording. According to its owner, this was one of the 10 most popular apps in the world in 2013. However, this is not the only thing it does. The app also tracks all the songs that are being searched for and compares them to various reviews in order to monitor the popularity and predict the next great hit. This is just one example of how this new technology can be used in music.

Then there’s Pandora, a music-streaming service that tracks the user’s preferences and suggests similar songs he might like. This involves a complex process of analyzing each song to find its “DNA” and comparing their numerous attributes.

Because Pandora is available on everything from car stereos to mobile phones, the music people choose to listen to at different times of the day and on different devices can be radically different from each other. [...] It’s Pandora’s job to incorporate things like the time of day to a user’s listening preferences and ensure that the next song on the playlist is one they’ll love.

Pandora is yet another example of the potential big data has in the music industry.

Big Data and Marketing

Source: freepik.com

The question, you’re probably asking yourself, though, is - what is the point of it? Why would you even need to waste your time with this heap of data? How can it improve your marketing ventures?

Well, based on your needs, we can recognize different types of big data analyses. A well-known website that deals with simple explanations of complex concepts, Dummies, states there are 4 main types:

Basic analytics that allows you to check the state of things and visualize your marketing efforts.
Advanced analytics that offers some predictions and might help you streamline your campaigns.
Operationalized analytics that becomes a part of your business plan.
Monetized analytics that is supposed to help increase your revenues.

Of course, in order to be successful, you need to make sure that the analysis is done properly. Thanks to the sudden popularity of this technology, there are now numerous specialized big data marketing agencies that will do the heavy lifting for you and present you with the results. You can use their findings to work on improving your campaigns, or perhaps finding new target audience.

The Future of Big Data Analytics

Source: freepik.com

So, all this being said, what is the future of big data analytics? Well, the fact is that the amount of data people produce on a daily basis keeps increasing every year. This means that the music marketing will be able to personalize music experience even more and focus on the right target audience. This will help both old and new artists reach their fans.

Up and coming artists have always had a difficult job finding their target audience. But now, with the use of data and analytics, it will be much easier to pinpoint how to reach those audiences, which ones to avoid entirely, and the most effective route to get there. Big Data provides similar advantages to established artists but more importantly, it helps these well-known musicians stay relevant to their demographic and, possibly, build new audiences they would have never been aware of before.

Source: unsplash.com

The same can be applied to marketing. If the artist knows who his target audience is and if he is able to single them out from the crowd, his promotion will go a lot smoother and be a lot more successful. Besides that, big data research will help recognize the current and upcoming music trends so the artist can adapt his tunes accordingly. Although we have yet to see everything that big data has in store for us, it’s potential is undeniable and quite mesmerizing. There is no doubt that you’ll find a way to employ this technique in the future.

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New GSMA Study: Operators Must Look beyond Connectivity to Increase Share of $1.1 Trillion IoT Revenue Opportunity

New GSMA Study: Operators Must Look beyond Connectivity to Increase Share of $1.1 Trillion IoT Revenue Opportunity

HOW BIG DATA CAN TRANSFORM THE FINANCE INDUSTRY

Challenges faced by the Finance Industry

Big data in the Finance Industry

How airlines can leverage in-flight audiences with big data and personalisation

Artificial Intelligence To Add $182 Billion To U.A.E.’s Economy By 2035

Artificial intelligence: The reality beyond the movies

5 WAYS BIG DATA GETS MISUSED

The Art Of Being Heard: Are Big Data And Analytics The Future Of Music Marketing?

The Definition of Big Data

Big Data and Music

Big Data and Marketing

The Future of Big Data Analytics

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