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<Img
img="/uploads/marketing_trends_with_data_analysis_and_machine_learning_0e6843230d.png"
alt="Forecasting Marketing Trends with ML"
/>

The volumes of information in the world are enormous, and trends in digital marketing change at a staggering pace. Just as marketers finish studying the market and digital environment, they find themselves having to start their research anew.

It's crucial to think about the future in advance: how consumer behavior, fashion, and promotional tools will change. The first option is to "guess" and rely on vision, intuition, and experience, making marketing management unpredictable.

The second path is [**to use a data-driven approach**](https://altcraft.com/blog/data-driven-marketing) that provides accurate forecasts. For example, choosing data analysis in marketing through machine learning to "predict" trends.

The article will explore why forecasting marketing trends is important, the role of it, and how machine learning works in this context.

## Why forecast marketing trends

Audience preferences change rapidly, so marketers need to "catch the wave" before customer interests shift. This applies to both global trends and local changes. Lagging brands won't gain anything if they miss a trend. Knowing in advance what will be relevant allows for preparation. Then the company's marketing strategy can adapt to changes.

Forecasting trends is a path to precise planning and risk reduction. Marketing analysis will indicate where to direct resources and how to gain benefits. Trend forecasting is useful not only for creating advertising campaigns but also for the brand's products themselves. This approach simplifies promotion because the product already has an advantage. For example, a popular color, features, and the right values that meet society's needs.

"Looking" into the future provides insights into which creative marketing campaigns and promotion formats yield results. There's still time to come up with new ideas and explore new tools and communication channels.

Tracking trends in marketing is crucial for businesses to avoid becoming outdated. The competition for attention continues constantly, and those who can adapt to changes and offer something new emerge victorious.

## Data analysis for marketing

When marketing is based on data analysis, forecasting becomes more accurate, and marketing becomes more manageable, reducing guesswork. Predictive analytics is a reliable way to plan marketing actions and advertising budgets.

A sufficient amount of information about past campaigns will also indicate weaknesses and guide efforts to work on mistakes. Every marketer should conduct data analysis before launching advertising, sending out campaigns, or creating a content plan to properly [**segment the audience**](https://altcraft.com/blog/how-and-why-to-segment-target-audience).

This way, the development of the marketing strategy will be tailored to a specific user group, enhancing [**personalization**](https://altcraft.com/glossary/personalization-what-it-is-and-why-personalized-marketing-matters), ultimately leading to greater predictability of results.

## Machine learning for marketing

The volume of data is growing, and a human cannot manually process such vast information. The problem is solved by [**marketing automation**](https://altcraft.com/blog/what-is-marketing-automation-and-how-it-affects-business-development), which includes machine learning — a method of artificial intelligence. Robots collect and analyze large datasets, and machine learning transforms the information into something useful for marketing purposes. Marketers begin to:

- **Properly understand and interpret the gathered information.** The application of machine learning eliminates human factors and subjective assessments. Information about orders, purchases, feedback, and preferences is not lost and is considered in data analysis. <p>
</p>
- **Explore the customer in 360 degrees.** AI technologies can process terabytes of internal (customer database, email campaign results) and external (social media comments, likes, reposts, etc.) data to identify patterns. The result of such analysis is precise personalization of offerings. <p>
</p>
- **Predict trends.** Machine learning in marketing is essential for identifying future trends in customer behavior and user preferences. This approach is valuable for refining products, services, and content.

Predicting trends through machine learning differs from trend watching, which is the method of finding trends here and now because ML forecasts trends are based on historical data and "looks" into the future.

## How machine learning predicts trends

To apply machine learning in business, researchers go through the following stages:

1. Gather information. Sources include internal databases from CDP, data from external third-party resources, and so on. <p>
</p>
2. Cleanse and enhance the information. It is crucial to minimize errors and collect comprehensive data to enable the AI to learn correctly. This stage involves adjusting the data to the required format. <p>
</p>
3. Determine which machine learning model to use for forecasting.

<Table>
| Learning model | What it means | What kind of forecasting is useful for |
| ------ | ------ | ------ |
| With a trainer | A person provides the system with data labeled according to specific rules. | When results are limited in number; if categorization of data is needed. |
| Without a trainer | The algorithm retrieves the data without partitioning. | To predict future purchases, and to clean up information for the next steps. |
| Involving trainers in part | A small fraction of the data is labeled, but most of it is unlabeled. | When you need to process documents where there is a lot of information. |
</Table>

4. Initiate model training and monitor its success: check the results it produces. If the forecasting is successful, the model is potentially used for other predictions with new data.

## Examples of trend forecasting

Since 2018, the [**Pyaterochka**](https://www.retail.ru/news/x5-primenit-mashinnoe-obuchenie-v-marketinge/) retail chain has been using machine learning to customize special offers and promotions in the future. The system relies on customer reactions and sales volumes, with the data anonymized. As a result, the company achieves a personalized approach.

[**Walmart**](https://www.clickz.com/5-businesses-using-ai-to-predict-the-future-and-profit/112336/) predicts the likelihood of customers purchasing a product and personalizes product offerings on the website. Additionally, predictive analytics manages delivery times and other processes to ensure customers receive their products on time.

Platforms dealing with content and advertising also utilize machine learning. For example, on [**VKontakte**](https://vk.com/@smm_pub-neiroseti-za-kulisami-vk-kak-socset-primenyaet-algoritmy), algorithms are essential for optimizing advertising campaigns, particularly for suggesting an audience similar to the advertiser's customers. In other words, the algorithm predicts who else might be interested in the brand's offer.

[**IBM**](https://www.ibm.com/products/weather-company-advertising-accelerator)'s service generates personalized creatives for advertising campaigns and adapts variations for different displays to appeal to users and display correctly. User engagement data is used in this process, and brands like Chevrolet and Mastercard adopt this approach.

[**Netflix**](https://www.argoid.ai/blog/netflix-ai#:~:text=Machine%20learning%20technologies%20are%20at,their%20rating%20and%20watching%20history.)'s recommendation algorithm is based on machine learning, considering user preferences and other factors. Content views, time, ratings, and other factors are taken into account. The [**Rive Gauche**](http://www.mskit.ru/news/n207949/) company also achieves personalization through machine learning tools, predicting customer behavior based on data and creating campaigns that [**enhance loyalty**](https://altcraft.com/blog/customer-loyalty) and sales.

## Challenges of machine learning and data analysis

**Dependency on data quality.** Predictions about the future are based on existing information. If data is insufficient, incomplete, or incorrect, there is no way to correct it in real-time.

**Limited coverage of offline business.** Machine learning may not fully capture user actions in the real world, especially in offline scenarios. While tracking all orders, user actions, and reactions to content is feasible in the digital realm, it becomes more complex in offline stores. However, AI can still be applied to some extent.

**Need for significant data volumes.** Machine learning requires substantial datasets, often in the thousands, and insufficient sample sizes may lead to unreliable results.

**Cost.** The task of forecasting requires a trained specialist, and resources are also spent on the system itself, configuration, and integrations. Implementing ML is feasible only for businesses with a sufficient budget for these purposes.

## The future of data analysis in marketing

Marketing is undergoing a transformation, integrating technologies as the average user engages in [**20-500 interactions with a brand**](https://www.invoca.com/blog/state-of-data-driven-marketing-update-your-strategy) before making a purchase. This generates vast amounts of information that need to be tracked and processed accurately. Additionally, users expect a personalized approach and recommendations for suitable products ([**91% of consumers**](https://www.wunderkind.co/blog/article/smarterhq-wunderkind-audiences/)). Without IT tools, marketers cannot handle such tasks, so the use of machine learning, artificial intelligence, [**neural networks**](https://altcraft.com/blog/neural-networks-in-business-marketing-and-life), and Big Data will continue to be implemented in marketing practices.

## Summary

It is crucial for brands to stay on trend, tracking global trends, and anticipating customer behavior for budget planning, creating advertising campaigns, and generating ideas. Data analysis becomes a reliable way to "see" into the future, eliminating guesswork.

To predict trends, machine learning algorithms are employed, providing a comprehensive view of the customer. They guide what offers to make to encourage user purchases.

For trend prediction through ML, information is collected and processed (large datasets), a model is selected, and the algorithm's performance is launched and monitored.

Machine learning is a reliable method for prediction but comes at a cost. Significant data volumes are required for ML to function properly. There are also limitations for predictions in offline business. Marketing is already intertwined with IT and will not thrive in the future without AI, ML, Big Data, and other information processing methods.


Brands must track trends with data analysis, using machine learning for customer behavior prediction and future-proofing marketing with AI and Big Data.

medium_marketing-trends-with-data-analysis-and-machine-learning.png

small_marketing-trends-with-data-analysis-and-machine-learning.png

thumbnail_marketing-trends-with-data-analysis-and-machine-learning.png

marketing-trends-with-data-analysis-and-machine-learning.png

What is trend forecasting in marketing and how to use ML effectively.

How to Predict Marketing Trends via Data Analysis & ML

Forecasting Marketing Trends with Data Analysis and Machine Learning

<Img
img="/uploads/3_nejroseti_konkurenta_7e54f78322.png"
alt="What Distinguishes ChatGPT, Bard, and Bing in Marketing"
/> 

The first AI-powered conversational service, ChatGPT by OpenAI, was introduced in November 2022 and immediately gained popularity. Within just 5 days, it had attracted over a million users to the platform. Similar figures [**were achieved by Facebook* in 10 months**](https://www.britannica.com/topic/Facebook).

At that time, other AI-based projects were also under development. The success of ChatGPT demonstrated the market demand for such a product and inspired other players.

Three months later, [**Google introduced Bard to the world**](https://blog.google/technology/ai/bard-google-ai-search-updates/), followed by Microsoft releasing [**its counterpart, Bing**](https://blogs.microsoft.com/blog/2023/02/07/reinventing-search-with-a-new-ai-powered-microsoft-bing-and-edge-your-copilot-for-the-web/), exactly one day later.

The interest of ordinary users in AI-based technologies is quite understandable. Chatbots, in addition to their functional purposes, also serve an entertaining function, for example, they can tell jokes.

<Img
img="/uploads/1_073326c7be.png"
alt="ChatGPT tells a joke"
/>

The content generated by AI technologies is often catchy and appealing. Each of the three projects undoubtedly deserves attention. In this article, we will explore the features, advantages, and disadvantages of ChatGPT, Bing, and Bard.

## ChatGPT by OpenAI: advantages and disadvantages

The paid version, ChatGPT Plus, was released on February 1st, while the public free version was available earlier.

The chatbot is capable of recognizing and understanding natural language questions and finding relevant answers on the internet. However, it's not simply copying information; ChatGPT processes the retrieved information and generates it as unique content.

The tool excels not only in search tasks but also in handling simple requests, such as "Write a message to my manager informing them that I won't be coming to work on Friday due to family circumstances."

A significant drawback of the system is that the bot doesn't verify the accuracy and correctness of the data. The creators of ChatGPT acknowledge this issue: "The output generated by the model needs to be checked, as it may be plausible but incorrect." The question of data relevance arises because the chatbot is limited to searching information up to the year 2021.

Despite this limitation, ChatGPT remains a powerful marketing tool, a source of inspiration, and an invaluable assistant for many marketers. For example, if an employee needs to write a post about the strengths and weaknesses of using chatbots in business, they can assign the task to the system: "Write a post about the advantages and disadvantages of using chatbots in business." The generated result can then be used as a draft for their work.

Marketers should always verify the correctness of the data, edit the text, and optimize it according to the desired tone of voice.

<Table>
| Pros of ChatGPT | Cons of ChatGPT |
| ------ | ------ |
| It simplifies the work of marketers by generating draft emails, posts, and descriptions. | The information can be sourced from anywhere, including outdated and unreliable sources. |
| It provides starting material for blog authors who struggle to find inspiration. | It cannot ask clarifying questions to provide the most accurate response to user queries. |
| It curates a list of internet sources for conducting marketing research. | It relies on internet data up to 2021. All information generated by ChatGPT needs to be verified. Additionally, the results may not always meet expectations, as the robot may provide simplistic and cliché answers. |
</Table>

## Bard by Google: advantages and disadvantages

Bard is currently being presented as an AI-powered dialogue system experiment. It operates based on LaMDA and is currently available only in beta version, with no general access yet.

It represents a breakthrough in search engine technology. Like many other search engines, Bard searches for answers to queries by leveraging the vast resources of the internet. The difference lies in the quality of information processing and the resulting output.

When composing a response to a user's question, the chatbot provides a summary from various perspectives. This allows specialists, including marketers, to familiarize themselves with Bard's output instead of having to read through thousands of sources to delve into the issue.

The most significant distinguishing feature of Bard is its ability to engage in conversation with humans. Thanks to AI technology, the chatbot goes beyond simply copying and pasting text snippets from the internet and instead captures patterns in human speech. Google announces that future updates will enable Bard to respond to complex, ambiguous questions and those without a definitive answer.

Currently, if you were to ask the robot a question like, "Is the piano or the guitar easier to learn, and how much practice does each need?" Bard would provide a response along the lines of:

<Img
img="/uploads/2_34be1b70f7.png"
alt="Bard figures out about playing the instruments 1"
/>

In another variant, the response may look like this: "Some say the piano is easier to learn, as the finger and hand movements are more natural, and learning and memorizing notes can be easier. Others say that it’s easier to learn chords on the guitar and you could pick up a strumming pattern in a couple of hours."

<Img
img="/uploads/3_5f4add1040.png"
alt="Bard figures out about playing the instruments 2"
/>

Bard from Google has undoubtedly turned out to be more advanced than ChatGPT. However, it is important not to place too much trust in the chatbot. Once, it made a mistake in a product presentation, resulting in Google losing $100 billion in stocks.

<Table>
| Pros of Bard | Cons of Bard |
| ------ | ------ |
| Engages in a dialogue with the user and can ask clarifying questions. | Occasionally provides false, outdated, and biased information. |
| Takes into account different perspectives on the issue and offers the user to explore the problem from various angles. |   | 
| Utilizes more recent and up-to-date information compared to ChatGPT for answering questions. |   | 

</Table>

## Bing by Microsoft: advantages and disadvantages

Bing, developed by Microsoft, is not a dialogue service but a full-fledged search engine. It demonstrates high performance as it operates on AI technology. Therefore, Bing successfully provides answers to users' complex questions.

In response to search results, users can engage in a dialogue with the AI by asking follow-up questions. This allows for a comprehensive interaction between the user and the AI, and [**Microsoft proudly refers to this feature**](https://blogs.microsoft.com/blog/2023/02/07/reinventing-search-with-a-new-ai-powered-microsoft-bing-and-edge-your-copilot-for-the-web/) as "AI for the web."

Previously, the company invested significant resources in OpenAI. However, after the emergence of Bing, Microsoft stated that this new product is more powerful and intelligent than ChatGPT. In an interview, Microsoft expressed the following about Bing: "We’re excited to announce the new Bing is running on a new, next-generation OpenAI large language model that is more powerful than ChatGPT and customized specifically for search. It takes key learnings and advancements from ChatGPT and GPT-3.5 – and it is even faster, more accurate and more capable."

If you ask Bing, "I am planning a trip for our anniversary in September. What are some places we can go that are within a 3 hour flight from London Heathrow?" you will receive an answer similar to this:


<Gallery>
<GalleryItem
original="/uploads/4_3bac2236f1.png"
thumbnail="/uploads/4_3bac2236f1.png"
/>
<GalleryItem
original="/uploads/5_438612d5d0.png"
thumbnail="/uploads/5_438612d5d0.png"
/>
</Gallery>



Did you evaluate the amount of information provided in response to the query? Bing even divided the data into categories. Here you will find activities for every taste. Below, the system offers you several phrases to choose from to continue or end the dialogue.

And that’s what ChatGPT responded to the same query:



<Img
img="/uploads/6_f998b6bbe7.png"
alt="ChatGPT gives a piece of advice"
/>

This is also a fairly comprehensive answer, but it lacks a human touch. Well, and you won't be able to continue the conversation with the robot.

<Table>
| Pros of Bing | Cons of Bing |
| ------ | ------ |
| Carefully selects and organizes information, providing deep answers to questions. | Works only with the Edge browser on MacOS and Windows. |
| Can communicate with users, allowing for query clarification through dialogue. | May provide false, unreliable, and outdated information. |
| Generates unique content, assisting marketers in saving significant time and effort in writing [**emails**](https://altcraft.com/ru/blog/tipy-rassylok-po-email), posting, and creating product descriptions. |   |
| Responds to unrealistic and dangerous queries. For example, Bing will indicate that rapid weight gain is harmful to health. |   |
</Table>

Microsoft warns users: "Always verify the information obtained from Bing. Sometimes the system distorts information. Its response may appear convincing and reliable, but in reality, it is not."

## Conclusion

Each of the three digital products has the potential to greatly enhance the efficiency of marketers and other professionals. It is essential to objectively evaluate the capabilities of the robot and diligently verify the data provided. Moreover, it is crucial to adapt the information to the intended tone of voice and refrain from utilizing it in its raw, unprocessed state.

**The products of the organization Meta are recognized as extremist in the territory of the Russian Federation.*


Each of AIs has its potential to greatly enhance the efficiency of marketers and other professionals if its capabilities are objectively evaluated.

medium_3-nejroseti-konkurenta.png

small_3-nejroseti-konkurenta.png

thumbnail_3-nejroseti-konkurenta.png

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Who wins the race between ChatGPT, Bard, and Bing when it comes to AI-involved marketing?


What Distinguishes ChatGPT, Bard, and Bing in Marketing

What Distinguishes ChatGPT, Bard, and Bing in the World of Marketing

<Img
img="/uploads/web3_95dcd31dca.png"
alt="Web 3.0: What It Is and How It Will Affect Marketing"
/>

Progress does not stand still, and Web3 has already appeared on the horizon. There are many rumors surrounding this concept and almost no specifics. However, it’s clear that marketing will have to face new realities. In this post, we will talk about what Web3 is, when to expect it and what marketers should prepare for.

## Third Generation Internet

The third generation of the World Wide Web, or the next generation of the Internet. This is how Web3 stands for. 

Web3 is the concept of a decentralized Internet space where power does not belong to giant companies such as Amazon, Google and Netflix, but to ordinary users. Web3 is based on blockchain technology, machine learning, big data and artificial intelligence. It is predicted that all this will make the Internet more accessible, and at the same time private and secure.

The first version of the Internet was introduced in the late 90s. It was a primitive web: simple fonts, inconspicuous buttons and blue hyperlinks. If you want to visualize the old version of the Internet, you just need to open any site using only HTML files. In fact, it was even worse.

Significant changes took place in 2005. Web2 users got the opportunity to watch new content, hang out on blogs and social networks. Everything would be fine, but a new problem has emerged in the process of evolution of the Internet. New marketing methods used by companies to work with customers have created [**a threat to the security of user data**](customer-data-privacy-issues-in-digital-marketing).

People began to distrust brands, despite efforts to protect Internet users and prevent confidential information from being shared with third parties. For example, in 2018 comedian Hasan Minaj stated on his Netflix show “The Patriot Act” that Amazon has control over the most important 21st-century commodity — data. The marketplace knows how much and where we spend money, and what we prefer to do in the digital space.

<Img
img="/uploads/glavnaya_stranica_amazon_ab73372337.jpg"
alt="Amazon website"
/>

It's not a joke at all. Amazon has grown from a bookstore to a tech giant. Now the scope of the corporation's interests includes e-commerce, streaming, cloud products and developments in the field of AI.

Web3 is supposed to solve the problem. The new generation of the Internet will allow users to independently control technical platforms. At the same time, they will no longer be in the role of “sheep” that campaigns shear for data. This can be done using the technology of tokens (cryptocurrencies) and blockchain. Blockchain will be owned by the one who owns the token. The more tokens you have, the more power you have over the World Wide Web. 

Critics of this approach agree that the attempt to decentralize the Internet looks too veiled, and in fact, people who have more money will continue to control the digital space.

<Img
img="/uploads/nft_kartina_382d17aed2.jpg"
alt="NFT picture"
/>

Anyway, tokens will soon take part in all digital processes: social networks, games, [**virtual art**](what-is-nft) and digital events.

## When to expect Web3

No one knows. Web3 has been a topic of discussion for several years, but the idea is still in its infancy. While the infrastructure required for implementation is evolving, there is no timeline for completion. Then what's all this noise about?

It is all about cryptocurrencies. They have become so popular that venture investors have invested $27 billion in cryptocurrency development projects in 2021 alone (according to [**The New York Times**](https://www.nytimes.com/interactive/2022/03/18/technology/web3-definition-internet.html?hubs_post-cta=blognavcard-marketing)). Therefore, everyone around is talking about the transition of the Internet to crypto technologies.

## What Web3 Means for Marketers

When Web3 appears, its arrival will greatly shake the world of marketing. 

### User data will become inaccessible

Web3 is characterized by high data privacy. Nowadays, all marketing is based on [**customer data**](first-second-and-third-party-data). Marketers collect all available information into a single client profile: contact details, socio-demographic status, behavioral characteristics.

All marketing campaigns are based on the analysis of behavioral data, for example, which places and sites the user visits, what products they buy. If companies know how much money customers spend, they can guess their income level and offer more expensive products.

Web3 assumes that users will be able to decide what information about themselves to share, and clearly control the scope of its application. This means that companies will have to bring transparency to the processes of collecting and using data. And also find more creative approaches to attract and retain customers.

### Communities will play an important role

Communities as a collection of users united by common ideas will be of particular value. Since the power in Web3 is concentrated in the hands of the “average” consumer, many such people together will have weight in determining the direction for the development of the digital space. The stronger the distrust of brands, the more interesting the idea of creating strong communities.

### Content will get more attention

How to attract potential customers if there are so many restrictions around? Use high-quality content. This is the content that the user will see and go to the seller himself.

Currently, content makers have to comply with the requirements of various platforms for posting materials, which seriously limits them. Web3 will give creators autonomy and remove the ceiling on potential earnings.

Charlie Neer, chief revenue officer at MIQ, stated in an interview for [**CMSWire**](https://www.cmswire.com/digital-marketing/what-does-web3-mean-for-marketing-and-customer-experience/?hubs_post-cta=blognavcard-marketing): “What does this look like in our current environment? Currently, when an individual downloads a song, the creator gets a fraction of the total revenue and the host (think Spotify or Apple Music) makes out like a bandit. The same goes for creators on YouTube, Twitch, etc”.

There is supposed to be more fairness in the age of Web3.

Most likely, we won’t see Web3 soon. However, those who keep abreast of the latest developments will win.

Web3 is the new generation of the internet. Read about when it will launch and what marketers should prepare for.

medium_web3.png

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web3.png

Web3.0 is the next generation of the Internet. Let's break down what this means for the marketer.

Web 3.0: What It Is and How It Will Affect Marketing

How Web3 Will Change Digital Marketing

<Img
img="/uploads/NFT_4dbbc2853c.png"
alt="NFT: What is It and Why is It So Popular"
/>

Today, there's a lot of buzz going around NFT. It's the [**word of 2021**](https://blog.collinsdictionary.com/language-lovers/get-your-crypto-at-the-ready-nfts-are-big-in-2021/) according to Collins dictionary. And the popularity of the technology will continue to grow. The NFT market size reached $25 billion in 2021. According to forecasts, this number will reach $35 billion in 2022 and will increase to $80 billion by 2025. 
 
NFT allows one to sell and buy digital objects for cryptocurrency. Digital property prices reach thousands and millions of dollars. The core [**target audience**](creating-a-customer-profile) of NFTs are gamers, collectors and advanced investors. They tend to invest in NFTs rather than in stocks. The value of digital objects is growing, and NFT may soon replace documents in the real world. 
 
In this piece you will learn what NFTs are, how they work, what they are for, where to create, sell and buy a digital work of art or a digital object.

## What is NFT
 
**NFT (a non-fungible token)** is a technology that represents an entitlement its owner has to a digital object and confirms the uniqueness of a digital property. The concept came from the world of cryptocurrencies. Each NFT exists on a blockchain: a technology that records data in digital blocks in a certain order. Information on a blockchain can't be deleted or changed. Blocks are stored on multiple servers all over the world. It's almost impossible to hack a digital object on a blockchain. 
 
A **token** is a blockchain element or a digital record that can be compared to securities and stocks in the real world. There are fungible, partially-fungible and non-fungible tokens (NFTs). 
 
Let's look at examples.
 
### Fungible token

If you borrow the US one-hundred-dollar bill from someone, and then recover your debt with another one of the same value, there will be no difference for the person from whom you borrowed. Although the bills are different (i.e. each one has a unique number), they are of equal value and can replace each other. Cryptocurrency works the same way in the digital world. Any bitcoin is equal to the same one because each has a fungible token. 
 
### Partially-fungible token

A train ticket you buy is not unique because other passengers have the same tickets that can be exchanged. However, each passenger has a seat number specified in their ticket. It distinguishes one ticket from another. In the digital world, this ticket would combine the characteristics of a fungible token (the passengers of this train can exchange their tickets with each other and still get to their destination) and a non-fungible one because each ticket has a unique seat number. Therefore, a train ticket with a seat number can be viewed as a partially-fungible token. 
 
### Non-fungible token (NFT)

If you buy a painting that is sold in a single copy, you can't replace it with a reproduction because it has its own characteristics. When a unique object exists only in the digital world, it is assigned a non-fungible token (NFT). 

*An example of an NFT that is adored by many people around the world is a game called [**CryptoKitties**](https://www.cryptokitties.co/). There people buy digital pets with unique tokens. People breed NFT crypto cats and get new kittens. The blockchain code here functions as a genetic one: all new cats will be unique.*

<Img
img="/uploads/Crypto_Kitties_33c6faf574.jpg"
alt="CryptoKitties"
/>

## How the NFT Technology Appeared

The technology appeared in 2017 on the basis of the Ethereum cryptocurrency smart contracts. Smart contracts are agreement codes between a buyer and a seller and a way of using an object. In the digital world, a token performs the function of a signature. 
 
Initially, the NFT technology supported blockchain art: it protected the copyright of unique content. It is difficult to find out who the real author is in the digital world. For example, a JPG image of a cat doesn't differ from its copy. When you copy an image, it loses its uniqueness and the author remains unknown unless users don't specify their name under each post. If an image has an NFT, the copying history is saved and each user knows its author and owner. 
 
The first transition of a real work of art into the digital world became a performance. Injective Protocol bought Banksy's stencil «Morons (White)» created in 2007 for 95 thousand dollars. The work was burned, and only the virtual version in the form of an NFT was left.

<Img
img="/uploads/Morons_a3a09f84f4.jpg"
alt="Morons"
/>

Now, not only paintings, but also author's images, GIFs, music, photos and videos, game items can have an NFT. Even real-world objects can have it: cars, real estate. Perhaps in the future there will be no need for paper documents because NFTs will replace even passports.  

## How to Create, Sell and Buy NFTs

### How to Buy an NFT
 
First, you need to choose a platform. NFT platforms trade digital objects in cryptocurrency, sometimes in dollars. Examples of platforms: Juggerworld, Treasureland, Blockparty, Nfty Gateway, Rarible, OpenSea, NFT STARS, NFT-X and others.  
 
A buyer receives a digital certificate with unique blockchain data and stores an object on any device: smartphone, computer, flash drive. The object itself remains in IPFS (Inter-Planetary File System). Other users will be able to download and view the object, but only one user will have the private key (certificate). The owner has the right to issue public keys to users when copying to confirm the authenticity of the object.

### How to Create an NFT and Sell It 
 
You can use one platform for creation and sale. The user needs a crypto wallet to pay the platform commission (sometimes there's no commission) and the object itself. The owner uploads the content to the platform and sets the price.
 
NFT is created in one of the blockchain formats: ERC-721, ERC-1155, ERC-998, EIP-2309 and others that NFT platforms have. 
 
**An NFT author has the right:**

- To limit the number of copies. 
- To receive royalties from each sale (sometimes this process is automated). 
- Not to prove copyright, which is registered in the blockchain. 

## What are NFTs for

### Authors can earn money from their content

Usually authors promote the platforms with their content. In return, they get advertising and virality, but not money directly. With NFT, the author will receive royalties when someone uses their content. 
 
### Copyright protection

Before NFTs, it was necessary to specify the author's name on their creations. The method worked poorly, the author's name was often lost. The creator of the object, the current owner and the resale history are recorded in the blockchain.
 
### Replacement of digital documents and tickets

With NFTs, ownership of real estate or a car is confirmed with a token instead of a paper document. The technology is also used to sell tickets to events. The difference between ordinary e-tickets and documents and NFTs is in the degree of protection: NFTs can't be forged and stolen.
 
### Content interactivity

NFTs make media content interactive allowing the user to take part in its creation. 
 
Example. Creators of comedy series The Gimmicks distributed free tokens that users use to [**vote for plot development options**](https://www.sammobile.com/news/samsung-tv-buy-sell-hold-nfts/). Also, users receive a unique NFT character from the series and even become assistants in the production team. 
 
### Investment

Buying digital objects is a profitable investment. NFTs are getting more expensive, digital objects are being resold for impressive amounts of money, but still it's impossible to say for sure the price of which NFT will skyrocket in the future. Not all NFTs are valuable: it depends on the author and characteristics. For example, [**Elon Musk put up for sale his tweet**](https://www.cnbc.com/2021/03/16/elon-musk-is-offering-to-sell-his-tweet-as-an-nft.html) in the form of an NFT. The price of the item at auction exceeded one million dollars.

<Img
img="/uploads/tvit_ilona_maska_4917169831.jpg"
alt="Elon Musk put up for sale his tweet"
/>

## Examples of NFTs 

Some NFTs become famous all over the world, not just among collectors. Such objects are sold at famous auctions Christie's and Sotheby's. Sometimes NFT art seems primitive, but even simple images can cost millions of dollars. Below you will see a few examples of digital objects that cost like millionaires' yachts.

### CryptoPunks

This is an example of a very simple but expensive NFT. Only rich collectors can afford these [**unique pixel avatars**](https://www.larvalabs.com/cryptopunks).

<Img
img="/uploads/Crypto_Punks_55a6ec26df.jpg"
alt="CryptoPunks"
/>

A collection of nine rare CryptoPunks images was sold for almost [**$17 million**](https://www.christies.com/lot/lot-6316969) at Christie's.

<Img
img="/uploads/Crypto_Punks2_a3ab63d3f4.jpg"
alt="CryptoPunks"
/>

### The First 5000 Days

Artist Beeple published a new work every day for 13 years and then combined all the images into a collage of 50000 thousand elements and sold as NFT at Christie's. The image is called The First 5000 Days because the author decided to create a new picture every day for the rest of his life. The collage with the first days costs $69 million.

<Img
img="/uploads/pervye_pyat_tysyach_dnej_3eec316268.jpg"
alt="The First 5000 Days"
/>

### World Wide Web source code

English scientist Tim Berners-Lee created a token for the [**source code of the Internet**](https://www.sothebys.com/en/buy/auction/2021/this-changed-everything-source-code-for-www-x-tim-berners-lee-an-nft/source-code-for-the-www), which he invented in 1989. The cost of this NFT at Sotheby's is $5.4 million.

<Img
img="/uploads/iskhodnyj_kod_interneta_aac87ed64d.jpg"
alt="World Wide Web source code"
/>

### Campbell's Soup Can
 
Andy Warhol's famous painting of Campbell's soup cans also turned into an NFT. The work called «Untitled (Campbell's Soup Can)» was sold at Christie's for $1.1 million.

<Img
img="/uploads/banka_supa_campbell_s_73d98ef1bc.png"
alt="Campbell's Soup Can"
/>

### Transition by Pokras Lampas

Calligrapher Pokras Lampas digitized and sold for [**$29,000**](https://foundation.app/@pokraslampas/foundation/5441) an NFT photo depicting a projection of his work at the Chirkeyskaya hydropower plant.

<Img
img="/uploads/Transition_pokrasa_lampasa_e67041ca23.jpg"
alt="Transition by Pokras Lampas"
/>

### Nyan Cat

Creator of Nyan Cat meme Chris Torres made a token out of the [**Internet-famous cat**](https://foundation.app/@NyanCat/foundation/219) and sold it for more than $560 thousand dollars.

<Img
img="/uploads/Nyan_Cat_afdc9a304c.jpg"
alt="Nyan Cat"
/>

## Conclusion

NFT (a non-fungible token) is a blockchain-based technology that confirms the uniqueness of a digital object, protects copyright and keeps the history of changes and resales. 
 
It's impossible to support NFT, but it's easy to create one. A digital object is uploaded to one of the NFT platforms and the price is indicated in cryptocurrency (sometimes in dollars). With the technology, people sell works of art, images, music, GIFs and even game items. NFTs even replace paper documents when buying real estate or a car. 
 
This technology allows content creators to receive royalties. NFTs are also an alternative to conventional investment. Digital objects are growing in price and are often sold at auctions for thousands and millions of dollars.

In this piece, we will tell you what NFTs are, how they work and what they are for, where to create, sell or buy a digital work of art or a digital object.

medium_NFT.png

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NFT.png

NFT allows one to sell and buy digital objects for cryptocurrency. It may soon replace documents in the real world. 

NFT: What It Is, How It Appeared, What It Is For

NFT: What is It and Why is It So Popular

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