Machine Learning | Digital Fortress of Information

Cloud Computing and Social Networking: The Future 2020

The era of office workers is coming to a close end. According to researchers, the spread of social networks and cloud technologies can kill traditional offices.

According to research results, today many IT departments of various companies began to switch to mobile technologies, which reduce costs and increase labor productivity.

According to experts from the British branch of Microsoft, modern IT-specialists more and more often fulfill their duties not only at their workplaces, but also from home, in transport and even from specially equipped public offices. Social networks, video-conferencing services and cloud applications help employees cope with their tasks.

First of all, this means that now employers will not have to provide their subordinates with offices, and this, in turn, will allow enterprises to reduce rental costs.

“Companies will be more aggressive in resolving employee workplace issues,” said Dave Coplin of the Microsoft research team. – Indeed, in the best case, only 55% of the office space is used at a time. The remaining 45%, which are not used in any way, is just a waste of money. ”

The results of research by British experts also destroy the prevailing myths that the use of social networks reduces productivity. Thus, companies that restrict their employees access to services like Facebook or Twitter, only harm themselves.

“Organizations that block social networks through firewalls only limit the activity of their subordinates,” Koplin said. “They should definitely be given more freedom.”

The organizers of the study suggest that in the future, IT companies will abandon permanent jobs altogether, replacing them with offices in which employees will appear only when necessary – for example, to discuss business issues with customers or partners.

Moreover, these workrooms can be rented for use by several companies at once. According to Koplin, now in the largest cities in the UK there are offices that do not belong to any particular company. “They have everything you need for productive work — electricity, internet and coffee,” said a Microsoft spokesman.

Here is the future of online social network in cloud computing era 2020:

1. The social graph will become mobile.
Now the social graph of each of us (friends and key information about them like a mail address) is stored on Facebook. Public pressure caused by the desire to have more autonomous profiles is growing. Something will be done about this: I do not believe that users or the community will allow a single company to concentrate all the information about us in their hands.

After a while, it will be possible to join other social networks without having to re-register and spam friends. I know that now in 2010 this does not look so obvious, but this is my forecast. They will either make our profiles mobile, or we will leave for more accommodating competitors. I suppose that this clarity will come before the end of 2012.

2. We will gather in the right social networks: Quora, HackerNews, Namesake, StockTwits
Since 2006, I have been mourning what I call the “Facebook problem” – they are trying to lure me into one big social network. No one lives on just one network. I discuss drinking with friends in one place, and I really do not want to see these dialogs next to the photographs of my children that I post for relatives.

I would not want to mix either network with business communication. I want to maintain the image of a tough businessman, and student photos from a trip to Mexico are superfluous. I do not want to interfere with my “personal” networks with my “public” networks. Facebook just dumped everything and is trying to settle at the expense of groups. It seems to me that this problem cannot be solved.

And youth is not as naive as it seems to adults. They simply create additional Facebook accounts under pseudonyms for real discussions and more innocent ones under real names. I wonder what part of the 500 million accounts created for this purpose?

It seems to me that thematic social networks, such as HackerNews or Quora, are already being formed. We are witnessing an increase in social activity around topics of interest to society. So, StockTwits is intended for those who invest in securities. New social networks are created to meet narrower needs. Namesake is still called an experiment, but in the long term it will open a whole world of opportunities for those who want to communicate outside of Facebook.

3. Personal data issues will remain controversial: Diaspora
Facebook promised us a social network with a high degree of privacy. When its creators enviously watched the success of Twitter, they decided to make everything more open, but this is not what we agreed to initially. If I led Facebook, then I would simply divide the entire network into two parts – closed and open. The second could directly compete with Twitter.

Of course, we would have to choose who to follow, and there would not be that synergistic effect that is obtained now due to the collision of all users with each other. But if this were done, then Facebook would not have to deal with ethical issues, and we would all simply adore them instead of the current relationship on the verge of love and hate. Anyway, I go to Facebook every day to look at new photos of my nephews, but I don’t communicate with anyone from the business sphere there. Therefore, 95% of my time on social networks goes to Twitter.

For most, the issue of personal data is not so acute, but it seems to me that this is due to a lack of understanding of all the dangers. Working with a large number of companies that develop new technologies and create applications, I realized this: even if you do not personally give access to your data to a third-party application, the data can still be accessible to anyone if someone from your friends like – Inadvertently uses this application. And all these Facebook Connect buttons on websites are good for quick access, but for the convenience you have to pay website owners unlimited access to your personal information.

The leakage of such data will cause a public reaction in the long run, but now not many users understand the danger in order to somehow respond. The emergence of the Diaspora is a reaction to the growing number of complaints. No one knows if the Diaspora will become popular, but many users are ready for the emergence of similar projects.

4.Social networks penetrate all areas: Facebook Connect in the Pandora service and on the NY Times website.
As our graph becomes more mobile, social networks will penetrate all spheres of life. I already see their integration with services like Pandora, where all my friends appear by themselves and their musical preferences are displayed without any of my will. The NY Times website shows me articles recommended by friends, but in the meantime I didn’t even enable this option. This trend will continue to develop.

5. Toolkit from independent developers, allowing you to use social opportunities: Meebo
Despite the fact that many sites want to get a Facebook Connect button to learn more about you, at the same time they don’t understand at all what to do with this information. In most cases, everything is limited to showing targeted advertising, but this is not very interesting. Independent developers are beginning to offer site owners tools that will actually take advantage of social opportunities. A few more years should pass, but players like Meebo are already developing this direction with their toolbar.

6. Social networks (as well as the web) will be divided into segments: SimpleGeo, PlaceIQ
One of the most interesting trends of the last few years is Internet segmentation. One of the noteworthy new segments is geolocation services that have arisen in mobile social networks. If each startup had to independently find out the location of all the enterprises on the map, the scope of their activities and the exact addresses, then we would not have so many startups. SimpleGeo, for example, helps develop mobile products without having to re-create the functionality of cards every time. This pleasant trend will allow in the future to further reduce the cost of launching new services. I assume that SimpleGeo will succeed, but we must fear competition from even more innovative companies.

One of the recent companies I have seen is PlaceIQ. Their goal is to develop a platform that will allow marketers and developers to know everything about surrounding objects, not limited to certain enterprises. They collect data on the demographics of each segment on the map, the level of development of mobile services in these areas, specialization of geographical areas (for example, a romantic place, financial district) and provide everyone with access to these data.

7.Social chaos will create new business opportunities: Klout, Sprout Social, CoTweet, awe.sm, Buzzd
The rapid growth in the amount of information creates the need for new opportunities for managing this information. Since we receive data from people whom we do not know personally, we need evidence of their credibility. Use Klout – a service that determines the degree of user influence. The service can be imported into other products (for example, into the StockTwits securities network) – where authority and trust really mean a lot.

We know that Twitter provides businesses with additional opportunities to provide customer service and respond to complaints, but the opposite is also true. If you do not control what they say about you on social networks, this is dangerous. Sprout Social and CoTweet have emerged to help businesses track consumer sentiment. And awe.sm website (I invest in this project) and similar products – monitor the effectiveness of social media marketing campaigns.

One of the most exciting new services is being developed by Nihal Mehta, the founder of Buzzd, and promises to release it in 2011. I recently saw this new project, but vowed not to say anything until the official release. I can only say that it is connected with the fact that companies and consumers have become very mobile and social.

8. Facebook will not be the only dominant player.
Now Facebook is so much more popular than everyone else that it is amazing. We are back to the beginning, in which AOL replaced the entire Internet. Facebook has become the new AOL for our generation. If you are on Facebook, you are not on the Internet. This is a unique service, and I often use it myself (although less frequently than Twitter). But it’s funny to see how companies advertise their Facebook pages – just as they once did with AOL Keywords.

Here is a brief historical background that may affect your opinion.

In 1998, the Department of Justice launched a campaign against Microsoft. People were afraid that the company would monopolize the Internet using the Internet Explorer browser, which it equipped its operating system with. And now the public is more afraid of Apple than Microsoft.

In 2000, the merger of AOL and Time Warner made them the main potential Internet slaver in the eyes of the public. Now AOL is in the process of restructuring and it looks like they are doing fine, but dominating? Never.

In 2007, everyone expected Google to take over the Internet. The company controlled 2/3 of all searches in the United States, and as we all knew, a search was a prerequisite for obtaining information. Or wasn’t it? Now we see that social networks greatly affect the way we find and share content.

So, the end of 2010, Facebook has more than 500 million users. People on this social network browse more pages than on Google. They give her more than 10% of their time on the Internet. FB is a leader in online advertising, photo and video services, and games. Now the social network is aiming for email. But after 10 years, when we look back, I’m sure that the thought of Facebook’s monopoly will also seem ridiculous.

Artificial Intelligence in Telecom – From Hype to Reality – AI

Surprising Ways Telecom Companies Use Artificial Intelligence

AI is having enough hype through media, researchers and vendors. Innovative organizations are putting a lot of efforts in AI research to make full benefits of it.

We all know about Sophia a social humanoid robot developed by Hong Kong based company Hanson Robotics. She looks quite human like and has been in talk shows a lot. She has also been given citizen ship in Saudi Arabia as being first artificial intelligence based human robot. She is being consider as intelligent but in reality, she is thoughtless whose intelligence is very basic. She can read a manuscript, on stage can perform a speech and she can answer questions that are pre-programmed. But If we ask her question out of script she can’t answer. Why is it so? Why is the gap here?

Well there is a basic difference of implementation AI.

Artificial General Intelligence

Machines that almost same level of intelligence that humans have, are expected in AGI products. This is what we all are expecting.

Artificial Narrow Intelligence

Machines have ability to perform specific tasks extremely well. These are computers that are trained to do simple and basic level of tasks only more efficiently than that of humans. This ANI based products are more in utilization by industry now. i.e a machine that is trained to identify objects in images

A computer that can identify brain tumor cannot detect tiger in a picture because it has not been trained on that.

And certainly that’s the kind of AI, organizations like Telecom operators are trying to implement.5G , IoT and big data will be handled by Narrow AI models to perform small task efficiently and fast.

Operators can train AI models such that, input from big data and after processing give expected results about customers. Mobile operators are also training the network based on alarms to predict whether there will be a failure or not. We just need to in put this data to AI model to learn and give out put as per desired results. It will also learn the relationship that if a new related input is given then it can predict the answer. Similarly a new customer is added then machine will learn that client will churn or not.

This is very basic application of AI today in mobile telecom industry.

One more interesting and quite effective application of AI in telecom is dynamic carrier allocation.

Artificial Narrow Intelligence trained model can add or remove additional carrier based on learning from previous weeks trends using capacity. No more manual allocation and wastage of resources.

Another example of machine learning using AI is

Automatize Customer Care:

Machines are trained to identify patterns in the text and predict problems for better solution offers.

This is pure automation, quick and competent customer support application.

Challenges:

Challenges that mobile operators are facing at the moment is, they are not having enough samples of issues to predict more accurately.Only those queries are addressed well where model is having high volume data.

These are very concrete examples that are being used in Telecom companies today.We are seeing that AI will be a part of all domains in near future to automate tasks and improve productivity whether in Network, Customer care, Marketing, HR or Finance etc.

How to Adapt AI in Mobile industry:

First of all companies need to upgrade the technology stakes, upgrade the infrastructure and competence to work with AI. Especially need to fix the first mile and last mile of AI.

1^st mile means data readiness. To be able to collect, store, process to make available the data for training AI models.

Last mile is infrastructure on which AI based models work and utilization of predictions from AI models to operations.

So deploying AI in Telecom sector effectively, mobile operators needs to work on refine enough big data and then focus on applying outputs in business operations.

Key barriers that must be solved and must have things for AI readiness:

Agile data Access Processes.
Experimental platform with the right tool.
Culture for experimentation and failing.
Domain and AI expert collaboration / cross function operational model

Secret Methods of Applying Text Analytics ( AI and Machine Learning Application )

Findings of 007 Agent in Textual Analysis

According to Deloitte forecasts, 80 of the top 100 largest developers in the world will use cognitive technologies (text analysis of natural language, speech recognition, neural networks, etc.) already in 2019, which is 50% more than in 2018.
What if your company is not in the top 100? And what if you do not understand anything about text analytics and Big Data technologies? Communications in the Big Data market so far is more like a huge secret, where you need to be 007 agent to figure out who plays what role. Almost all market players talk about intelligent data analysis systems, convenient visualization, cloud solutions, machine learning, language definition, etc.

And what are the differences? What questions should you ask yourself first if you intend to implement text analytics Big Data and if you do not have a technical background? How exactly can these technologies be applied to your business? Let’s figure it out.

What tasks does text analytics solve using Big Data ?

The concept of “text analytics” is not as popular as the phrase “Big Data”. However, it is in the format of unstructured text that about 80% of all accumulated information is presented, according to a report by International Data Corporation. What to do with it and how?

Dmitry Torshin, IT Director for Investment and Vice President of Aplana, is sure:“The use of modern technologies based on text analytics is one of the most important tasks that heads of developing companies in Russia should set themselves. Their colleagues from developed countries have already done this, and we all are already using it, not even always realizing it. An x.ai virtual secretary has already been created to coordinate meetings (being a program, but it does not give out anything except a mail address – it perfectly answers questions and suggestions of people in correspondence). The App in the Air Chat on Facebook Messenger gives me the opportunity to learn in simple language what I can take with me on a plane in a particular country and what cannot, and find the flight I need. And the latest version of Apple’s desktop operating system, macOS, which came out just the other day, contains Siri and a search that lets you ask your computer to find “documents, which Petya sent me last week. ” People instantly get used to it, and if tomorrow your business is not able to communicate in human language with a client as well, then it will be seriously squeezed out with competitors ”.

Nevertheless, the most common cases of the applicability of text analytics can be found in the advertising market, in the banking industry, as well as in online retail (where this trend is only emerging, but the benefits of using it are already obvious).

What tasks can be solved by text analytics of unstructured data in advertising and customer service:

– Compilation of brand loyalty ratings,
– Increase in CTR by increasing the effectiveness of native advertising (matching content of the placed advertising),
– Content analysis (tagging and classification) to create the next sub-product or adjust the current one,
– Implementation of text analysis technologies in chat rooms for community management,
– Automatic identification of various kinds of entities and frequency analysis of words,
– Control of tonality of brand references as an indicator of the company’s health,
– Detection of trends at the time of their inception,
– Improving the effectiveness of loyalty programs (by monitoring not only the public space, but also the analytics of text data of chats, messages of call centers, email messages).

Banks are perhaps the leader in applying analytics to unstructured Big Data. Says Sergey Dobridnyuk, Director of Research and Innovation, Diasoft Systems, who are actively studying the banking sector:“My opinion is that trying to structure everything is a dead end. Up to 80% of daily information “digitized” by humanity is contained in an unstructured form. And the reason here is the complexity of both data and classifier systems. For example, to classify sales receipts for PFM systems, you will need to create a classifier with at least 1.5 million SKU headings. This is an unrealistically large dictionary in which it is easy to make a mistake: the great Pushkin had a vocabulary of about 30 thousand words. And IT successfully fights this complexity – there are hundreds of data management systems (DBMS) in NoSQL technologies – for which unstructured data is their native element. Algorithms are being greatly improved – for example, multilayer neural networks, Bayesian neural networks find connections and process texts, speech, images thousands of times faster than 10 years ago. Very high-quality and open source free software libraries have appeared – which make these technologies available to all comers. A breakthrough technology today is Machine Learning, when causal relationships are established by a computer based on statistical analysis, and even a person cannot explain logic – preferring to consider it an unknowable “black box”. All this is important in order to offer the client comprehensive services based on behavioral models, collected customer experience (CX). And the quality of the offer is constantly improving due to continuous monitoring of the client, all his “digital traces” in a structured and unstructured form. The intrigue also lies in the fact that this can be done not only by banks – but also by retailers, telecom operators, suppliers of services and goods, already knowing the client and offering him financial services no worse than the “average bank”. Therefore, classical banking is today in a zone of deep turbulence and a rethinking of its activities. ”

And the director of IBS Data Lab, Sergey Zablodsky, does not doubt the “real” analytics of unstructured data: “The question of the applicability of BigData analytics in business solutions today is no longer there. Rather, there is the task of doing this effectively. And for examples of effective solutions you do not need to go far – look at Uber, Airbnb, Netflix, Walmart. And these are only those names that are heard. All of them actively and successfully use BigData analytics in their business solutions, and for some, the entire business is based on BigData analytics. For example, the likelihood of commercial success of the series produced by Netflix reaches 70%, while the average market probability is only 35%. ”

Where to start and what is important to know for implementing text analytics ?

The most well-known companies in the field of Big Data and linguistics – mainly due to loud cases and the presence of visualization (interface) – have become social media and media monitoring companies (Brand Analytics, Brandwatch, Radian 6, Cribrum, etc.). However, the text analytics industry is not limited to this, but on the contrary, it becomes extremely difficult to understand the differences between the proposed solutions.

First of all, when choosing a text analytics solution, you should think for yourself what characteristics are important to you (provided that you have already decided that you will use text analysis technologies to solve a specific business problem).

Answer the questions below:

1. Do you really have big data or not? Are there really a lot of unstructured data among them?
2. What is more important for you: depth of analysis or speed?
3. Texts in what languages do you need to analyze? Each solution on the market has its own technical features of text analysis and language definition. All international corporate machine learning solutions work perfectly with the English language, but in the case of Russian there are many problems. Rich and powerful, so to speak!
4. Are you ready to export data?
5. In general, do you want a technology or a finished highly specialized product?
6. Do you need data collection or just text analysis of big data, or both?
7. Is it fundamentally a solution to your internal circuit or a cloud-based solution through the REST API?
8. Do you have the resources to visualize the analyzed data?
9. Which of the main areas of text analytics do you need: search (information search methods) or descriptive / predictive analytics (text mining and tonality determination)?
10. Do you need to extract commercially useful knowledge from text online?
11. Do you have professionals in the team who are able to correctly interpret the result of the analysis, introduce the technology, create a product, or do you expect this from the technology supplier?
12. Finally, what budget are you willing to invest in such decisions? It must be understood that the maximum benefit from the analysis of big data can be obtained with a long-term analysis (that is, evaluate the results of analysis in time), and this is a subscription model, and not a one-time project.

Who has what method?

So, you were more or less able to answer the questions listed above. The next step is choosing a partner. Unstructured information analysis solutions can be conditionally divided into 3 types:

– Finished products based on text analytics technologies: not for a mass audience, and therefore quite expensive and “tailored” for a specific segment of B2B clients.
– Point solutions-products at the junction of text analytics and big data for the mass-market segment, if I may say so in B2B: simpler to implement, designed for different B2B segments.
– Modular text analytics technologies: perhaps the most flexible in implementation, suitable for a wide range of tasks – such a cube in the Lego text analytics constructor for business.

The first group includes solutions really from the field of artificial intelligence, which can perform not only the tasks of text analytics, but also in general, provide cognitive services and their mix. For example, IBM Watson, officially launched in 2007, operates big data regardless of the type and format of data, has the ability to self-learn, and is suitable for quickly finding answers to questions. On their website they provide a demo for subscription.

Both startups and very targeted products of well-known corporations fall into the second category. For example, in the summer of 2016, ABBYY announced the launch of Findo, a search assistant for mail messages, files and documents in the clouds. And in 2014, ABBYY launched Compreno – an intelligent search and identification of “essence” in texts. Of the non-corporate solutions on the market, there are innovative companies / startups such as Textocat (also offering smart search) and the product “chat bot”. SAS also released two key solutions for text mining and tonality analysis: SAS Text Miner and SAS Sentiment Analysis.

Among modular technologies, players such as Yandex Data Factory and EurekaEngine are actively present on the market. Both help companies make commercial use of the accumulated data: create end services in existing business processes of companies instead of implementing software and visualizations. YDF uses corporate experience and machine learning technologies, EurekaEngine uses high-speed text analytics, especially for the Russian-speaking space, because the company has its roots in Russia (which, by the way, is used by Brand Analytics, one of the leaders in the market for social media and media monitoring services, which took 1st place by quality among social media monitoring systems in the TECH INDEX 2016 ranking by AdIndex).

Advertisers, especially DMP systems and advertising auditors, also have their own developments in the field of text analysis, but they are mainly used for their own internal tasks: segmentation, more targeted targeting, semantic comparisons of audiences (for example, audiences of mobile applications), etc. d. As you know, the devil is in the details: almost everyone has problems with the accuracy of the analysis and the inability to separate the advertising content of the text block from the text of the article in the media, as well as the further output of the product.

Conclusions

What does client think about the usefulness of text analytics in solving business problems? Ivan Tretyakov, managing partner of the Association A.R.Z.A.M.A. and POSonline service:

“In an era of growing consumption, as well as demand for the quality of services, business (in particular the banking and retail segments) began to look more deeply at the root of how to be closer to the client and make him more loyal. Big Data tools – analytics and, in particular, analysis of text arrays already today show amazing results: you can adjust your service based on the feedback of people in the media, chats, forums; You can offer people interesting promotions / discounts by studying their factors of demand and interest in specific product groups / brands; you can expand your own list of services offered or lower the loan rate by studying the behavior of your customers in the Internet.

Text analytics can be applicable not only for a business concentrated in the Internet space, but also for offline players, for example: by analyzing the behavior / user reviews on the Internet for certain goods / services and armed with geolocation services to work with a potential audience – you can offer them interesting Products / services / solutions are already in offline space. For example: courses, travels, workshops, etc. And thanks to the availability of ready-made SAAS services for text analytics, the business will receive a strong tool to grow its profits and increase satisfied customers. ”

Must Have Marketing Skills to Survive in The Age of AI

10 Skills Without Which A Marketer Cannot Survive in The Age of AI

It happened. We live in an age of artificial intelligence. I can’t believe it, right?

It is high time for marketers to accept this fact and begin to prepare for the inevitable changes in the technology era.

Already, machines are actively learning to recognize images and speech, to predict the likelihood of the development of certain events and make decisions. That is to do our work.

Today, the most effective brands are more than twice as likely as competitors to use AI in their marketing processes. Artificial intelligence helps companies to increase sales, indicators are growing due to the personalization of experience .

Over the past 5 years, the number of jobs requiring AI knowledge has grown by 450%.

And artificial intelligence will continue to conquer the field of marketing. Are you ready for this?

In today’s article, we’ll talk about 12 skills without which a marketer cannot survive in the AI age.

1. Flexibility
If you don’t start to adapt today, you will soon be behind your competitors. Just look at how many companies are already using AI, and how many plan to implement this technology in the future: AI is the fastest growing marketing technology. It is expected that over the year it will grow by 53%.

If you want to succeed, you need to adapt. Do not rely too much on time-tested strategies. Feel free to experiment and test new technologies.

2. Sociability
It’s not new to marketers that developed communication skills make a significant contribution to business success. It is important to be able to convey your thoughts to employees, customers and other people with whom you have to communicate every day.

In the age of AI, communications are becoming an even more significant element of business. After all, not one, even the most advanced artificial intelligence, is capable of replacing live communication.

Do not delegate communication with clients to robots at 100%. In the age of high technology, the human face of the brand will become a major competitive advantage.

3. Budget allocation
The introduction of artificial intelligence is not cheap. For this reason, most brands do not use solutions in AI marketing:

For what reason you are not interested in implementing AI solutions ?
If you decide to incorporate new technology into your strategy, you cannot do without planning and budget allocation skills.

Try to find ways to cut costs in other areas to enter the new century before the competition.

4. The ability to analyze big data
AI will open up access to huge amounts of data that are important to be able to analyze.

According to research, 29% of brands use artificial intelligence to automate data analysis. 26% use AI to analyze operational effectiveness. As a result, business owners receive large amounts of information, on the basis of which it is necessary to draw conclusions and make decisions. Are you ready for this?

5. Programming Skills
To use artificial intelligence, you do not have to be a programmer. However, knowledge in this area will not be superfluous, for sure. For example, they will help to save on the call to a specialist.

You will have enough basic skills to configure the collection of data that you need.

Often AI is used to identify patterns. If you are good at programming, it will be much easier for you to understand the features of this field of application.

Far from all this? You can easily find basic information on the Internet, for example, on Codecademy . Both courses for beginners in programming basics and specialized training materials in data science will come in handy.

6. Content creation
Content is king, right? The main goal of modern business is to create effective content both from the point of view of users and search engines. Any marketing strategy is based on the generation of content.

The competent use of artificial intelligence will allow you to make your articles, posts, videos, photos, audio, email messages even better. For example, some brands due to AI make Facebook ads even more relevant for different user groups. And this is only one of hundreds of areas of application of artificial intelligence for creating and promoting content.

7. Security
Over the past few years, we have only heard about constant leaks of information in large corporations. These messages significantly damage the reputation of brands.

Do you want your customers not to worry about the safety of their personal data? Use AI with caution.

Consumers believe that artificial intelligence can make it harder for a business to secure online. Develop this myth by conducting thematic campaigns, and always responsibly treat user data.

8. The spirit of competition
Marketing is a high stakes game. You constantly have to fight with other companies for users.

After the massive introduction of artificial intelligence, competition will only intensify. Without the spirit of competition, one cannot survive.

84% of marketers are confident that AI will help them outperform competitors. Find out, and your rivals are already introducing new technology?

9. Delegation and time management

The community is hotly debating the possibility of replacing people with robots in most jobs. But this does not mean that AI should be considered as a threat. Rather, it is a dream assistant for any marketer. After all, with its help you can automate many tasks.

You no longer have to load workers with the work that a computer can easily do. They will have more time to solve creative problems.

10. Thirst for knowledge
To survive in the age of AI, it is important to be able to learn. The benefit for this today is not necessary to leave the house. There are many training courses and webinars available online.

Technologies are constantly evolving, so you should closely monitor the news, expand your knowledge and listen to the opinions of experts.

Does your business need artificial intelligence to survive?

Naturally, it is not so necessary as a presence in social networks, your website and the ability to accept online payments. From this point of view, it will not be easy to convince yourself of the need for such a serious step. But in this case, it is important to have a broad outlook and look at things in the future.

If even now you can’t afford the introduction of technology, you need to start closely monitoring it today. After all, artificial intelligence is the future, and not just marketing.

Cutting Edge Technologies That Will Change Marketing Industry Forever

It is difficult to imagine a marketing field that modern technologies would not significantly change. Companies that rely on artificial intelligence, virtual reality and voice search, gain an advantage over competitors and let them create future promotions with extra ordinary results.

We have listes 10 leading marketing technologies and the possibility of their application in companies of various sizes. Which of them will you choose to transform your strategy?

10 Cutting Edge Technologies Changing Internet Marketing

1. Big data

• Improves the quality of customer data collection for fine-tuning advertising campaigns.
• Helps evaluate campaign performance.
• In the near future, big data will allow creating attribution models to assess the impact of each channel on conversion rates, customize programmatic ads and optimize video marketing.

2. Artificial Intelligence

• Finds valuable patterns for more effective targeting and prediction of consumer behavior.
• Used by search engines to analyze queries and select the appropriate content.
• Based on artificial intelligence, platforms for online chat are created that help to automatically collect customer information and solve problems on demand.
• AI-based technologies deeply analyze trends, create detailed customer profiles, and help develop successful personalization strategies for better customer focus.

3. Machine Learning ( ML )

• It is used in audience segmentation and is embedded in analytics systems to track anomalies and analyze large volumes of data in real time.
• Robots have learned to create content. Banner advertising, email campaigns, posts on social networks are generated in different formats for different channels. After analyzing enough data, machines can create and change headers to increase efficiency.

4. Bots

• Not only an effective tool for communication, but also a channel for round-the-clock interaction with the brand.
• Often used in sales and support, help find and recommend products.
• Soon they will be able to remind of repeated purchases through voice assistants.
• Communication with the chat bot can occur on several devices, be omnichannel.

5. Voice Search

• Marketers use voice search to collect information about device users through search queries, keywords, applications, or voice dialing.
• Soon, voice search will be integrated with SEO. Marketers need to learn how to optimize content for conversational queries.
• The technology has every chance to change the approach to advertising on the search and organic promotion of content.

6. Virtual and Augmented Reality

• Both technologies create an impressive experience that affects feelings and emotions.
• They expand the experience of product testing, brand engagement, and shopping.
• They bring offline stores and ecommerce closer, gradually blurring the line between real and virtual interaction.
• Can be used for storytelling and creating interactive brand content.

7. Internet of things ( IoT ) and wearable devices

• Used to collect information about users: their habits or preferences. The more connected devices a person uses, the more marketers have more opportunities to contact him with an actual offer.
• Wearable devices transmit information on the biological state of consumers to the Internet.
• Biometric data can be used to analyze consumer interactions with the brand.

8. Blockchain

• Using blockchain technology, marketers can motivate consumers to view ads and interact with content.
• Decentralized applications based on blockchain technology can compete with Apple and Android platforms and support a new cooperative economy around the world.

9. Beacons

• Gathers detailed information about the visitor to optimize the shopping experience and helps create personalized campaigns based on movement data.
• Ecommerce companies can use localization to target potential customers within a certain radius of the sensors.
• Combines online and offline presence and provides a consistent experience.
• It helps to determine which campaigns attract attention and show only relevant ads to each client.

10. 5G

• A faster connection allows you to load pages faster, reduce bounce rates, and increase CTR and ROI.
• Enhances display capabilities using VR and AR for an engaging demonstration of offers.
• Allows marketers to collect data in real time to optimize campaigns and local promotion.
These technologies significantly affect marketing and business, including:

• Data collection
• Data analysis
• Content Creation
• Content distribution
• Personalization
• Targeting and placement
• Customer service

Over All Digital or Internet Marketing is going to have huge exponential positive impact with the deployment of these amazing latest technologies.

Technology is evolving and becoming more accessible. Changing the industry under the influence of technology is happening now, you need to have time to master promising areas.