Instagram NFTs Are Here… How does this affect artists?
Instagram (IG) is officially joining NFT. With the debut of new in-app NFT functionalities, influential producers can interact with blockchain tech on the social media platform.
Meta unveiled intentions for an Instagram NFT marketplace in March, but these latest capabilities focus more on content sharing than commerce. And why shouldn’t they? IG's entry into the NFT market is overdue, given that Twitter and Discord are NFT hotspots.
The NFT marketplace/Web3 social media race has continued to expand, with the expected Coinbase NFT Beta now live and blazing a trail through the NFT ecosystem.
IG's focus is on visual art. It's unlike any NFT marketplace or platform. IG NFTs and artists: what's the deal? Let’s take a look.
What are Instagram’s NFT features anyways?
As said, not everyone has Instagram's new features. 16 artists, NFT makers, and collectors can now post NFTs on IG by integrating third-party digital wallets (like Rainbow or MetaMask) in-app. IG doesn't charge to publish or share digital collectibles.
NFTs displayed on the app have a "shimmer" aesthetic effect. NFT posts also have a "digital collectable" badge that lists metadata such as the creator and/or owner, the platform it was created on, a brief description, and a blockchain identification.
Meta's social media NFTs have launched on Instagram, but the company is also preparing to roll out digital collectibles on Facebook, with more on the way for IG. Currently, only Ethereum and Polygon are supported, but Flow and Solana will be added soon.
How will artists use these new features?
Artists are publishing NFTs they developed or own on IG by linking third-party digital wallets. These features have no NFT trading aspects built-in, but are aimed to let authors share NFTs with IG audiences.
Creators, like IG-native aerial/street photographer Natalie Amrossi (@misshattan), are discovering novel uses for IG NFTs.
Amrossi chose to not only upload his own NFTs but also encourage other artists in the field. "That's the beauty of connecting your wallet and sharing NFTs. It's not just what you make, but also what you accumulate."
Amrossi has been producing and posting Instagram art for years. With IG's NFT features, she can understand Instagram's importance in supporting artists.
Web2 offered Amrossi the tools to become an artist and make a life. "Before 'influencer' existed, I was just making art. Instagram helped me reach so many individuals and brands, giving me a living.
Even artists without millions of viewers are encouraged to share NFTs on IG. Wilson, a relatively new name in the NFT space, seems to have already gone above and beyond the scope of these new IG features. By releasing "Losing My Mind" via IG NFT posts, she has evaded the lack of IG NFT commerce by using her network to market her multi-piece collection.
"'Losing My Mind' is a long-running photo series. Wilson was preparing to release it as NFTs before IG approached him, so it was a perfect match.
Wilson says the series is about Black feminine figures and media depiction. Respectable effort, given POC artists have been underrepresented in NFT so far.
“Over the past year, I've had mental health concerns that made my emotions so severe it was impossible to function in daily life, therefore that prompted this photo series. Every Wednesday and Friday for three weeks, I'll release a new Meta photo for sale.
Wilson hopes these new IG capabilities will help develop a connection between the NFT community and other internet subcultures that thrive on Instagram.
“NFTs can look scary as an outsider, but seeing them on your daily IG feed makes it less foreign,” adds Wilson. I think Instagram might become a hub for NFT aficionados, making them more accessible to artists and collectors.
What does it all mean for the NFT space?
Meta's NFT and metaverse activities will continue to impact Instagram's NFT ecosystem. Many think it will be for the better, as IG NFT frauds are another problem hurting the NFT industry.
IG's new NFT features seem similar to Twitter's PFP NFT verifications, but Instagram's tools should help cut down on scams as users can now verify the creation and ownership of whole NFT collections included in IG posts.
Given the number of visual artists and NFT creators on IG, it might become another hub for NFT fans, as Wilson noted. If this happens, it raises questions about Instagram success. Will artists be incentivized to distribute NFTs? Or will those with a large fanbase dominate?
Elise Swopes (@swopes) believes these new features should benefit smaller artists. Swopes was one of the first profiles placed to Instagram's original suggested user list in 2012.
Swopes says she wants IG to be a magnet for discovery and understands the value of NFT artists and producers.
"I'd love to see IG become a focus of discovery for everyone, not just the Beeples and Apes and PFPs. That's terrific for them, but [IG NFT features] are more about using new technology to promote emerging artists, Swopes added.
“Especially music artists. It's everywhere. Dancers, writers, painters, sculptors, musicians. My element isn't just for digital artists; it can be anything. I'm delighted to witness people's creativity."
Swopes, Wilson, and Amrossi all believe IG's new features can help smaller artists. It remains to be seen how these new features will effect the NFT ecosystem once unlocked for the rest of the IG NFT community, but we will likely see more social media NFT integrations in the months and years ahead.
Read the full article here
More on NFTs & Art
Jim Clyde Monge
3 years ago
Can You Sell Images Created by AI?
Some AI-generated artworks sell for enormous sums of money.
But can you sell AI-Generated Artwork?
Simple answer: yes.
However, not all AI services enable allow usage and redistribution of images.
Let's check some of my favorite AI text-to-image generators:
Dall-E2 by OpenAI
The AI art generator Dall-E2 is powerful. Since it’s still in beta, you can join the waitlist here.
OpenAI DOES NOT allow the use and redistribution of any image for commercial purposes.
Here's the policy as of April 6, 2022.
Here are some images from Dall-E2’s webpage to show its art quality.
Several Reddit users reported receiving pricing surveys from OpenAI.
This suggests the company may bring out a subscription-based tier and a commercial license to sell images soon.
MidJourney
I like Midjourney's art generator. It makes great AI images. Here are some samples:
Standard Licenses are available for $10 per month.
Standard License allows you to use, copy, modify, merge, publish, distribute, and/or sell copies of the images, except for blockchain technologies.
If you utilize or distribute the Assets using blockchain technology, you must pay MidJourney 20% of revenue above $20,000 a month or engage in an alternative agreement.
Here's their copyright and trademark page.
Dream by Wombo
Dream is one of the first public AI art generators.
This AI program is free, easy to use, and Wombo gives a royalty-free license to copy or share artworks.
Users own all artworks generated by the tool. Including all related copyrights or intellectual property rights.
Here’s Wombos' intellectual property policy.
Final Reflections
AI is creating a new sort of art that's selling well. It’s becoming popular and valued, despite some skepticism.
Now that you know MidJourney and Wombo let you sell AI-generated art, you need to locate buyers. There are several ways to achieve this, but that’s for another story.
middlemarch.eth
3 years ago
ERC721R: A new ERC721 contract for random minting so people don’t snipe all the rares!
That is, how to snipe all the rares without using ERC721R!
Introduction: Blessed and Lucky
Mphers was the first mfers derivative, and as a Phunks derivative, I wanted one.
I wanted an alien. And there are only 8 in the 6,969 collection. I got one!
In case it wasn't clear from the tweet, I meant that I was lucky to have figured out how to 100% guarantee I'd get an alien without any extra luck.
Read on to find out how I did it, how you can too, and how developers can avoid it!
How to make rare NFTs without luck.
# How to mint rare NFTs without needing luck
The key to minting a rare NFT is knowing the token's id ahead of time.
For example, once I knew my alien was #4002, I simply refreshed the mint page until #3992 was minted, and then mint 10 mphers.
How did I know #4002 was extraterrestrial? Let's go back.
First, go to the mpher contract's Etherscan page and look up the tokenURI of a previously issued token, token #1:
As you can see, mphers creates metadata URIs by combining the token id and an IPFS hash.
This method gives you the collection's provenance in every URI, and while that URI can be changed, it affects everyone and is public.
Consider a token URI without a provenance hash, like https://mphers.art/api?tokenId=1.
As a collector, you couldn't be sure the devs weren't changing #1's metadata at will.
The API allows you to specify “if #4002 has not been minted, do not show any information about it”, whereas IPFS does not allow this.
It's possible to look up the metadata of any token, whether or not it's been minted.
Simply replace the trailing “1” with your desired id.
Mpher #4002
These files contain all the information about the mpher with the specified id. For my alien, we simply search all metadata files for the string “alien mpher.”
Take a look at the 6,969 meta-data files I'm using OpenSea's IPFS gateway, but you could use ipfs.io or something else.
Use curl to download ten files at once. Downloading thousands of files quickly can lead to duplicates or errors. But with a little tweaking, you should be able to get everything (and dupes are fine for our purposes).
Now that you have everything in one place, grep for aliens:
The numbers are the file names that contain “alien mpher” and thus the aliens' ids.
The entire process takes under ten minutes. This technique works on many NFTs currently minting.
In practice, manually minting at the right time to get the alien is difficult, especially when tokens mint quickly. Then write a bot to poll totalSupply() every second and submit the mint transaction at the exact right time.
You could even look for the token you need in the mempool before it is minted, and get your mint into the same block!
However, in my experience, the “big” approach wins 95% of the time—but not 100%.
“Am I being set up all along?”
Is a question you might ask yourself if you're new to this.
It's disheartening to think you had no chance of minting anything that someone else wanted.
But, did you have no opportunity? You had an equal chance as everyone else!
Take me, for instance: I figured this out using open-source tools and free public information. Anyone can do this, and not understanding how a contract works before minting will lead to much worse issues.
The mpher mint was fair.
While a fair game, “snipe the alien” may not have been everyone's cup of tea.
People may have had more fun playing the “mint lottery” where tokens were distributed at random and no one could gain an advantage over someone simply clicking the “mint” button.
How might we proceed?
Minting For Fashion Hats Punks, I wanted to create a random minting experience without sacrificing fairness. In my opinion, a predictable mint beats an unfair one. Above all, participants must be equal.
Sadly, the most common method of creating a random experience—the post-mint “reveal”—is deeply unfair. It works as follows:
- During the mint, token metadata is unavailable. Instead, tokenURI() returns a blank JSON file for each id.
- An IPFS hash is updated once all tokens are minted.
- You can't tell how the contract owner chose which token ids got which metadata, so it appears random.
Because they alone decide who gets what, the person setting the metadata clearly has a huge unfair advantage over the people minting. Unlike the mpher mint, you have no chance of winning here.
But what if it's a well-known, trusted, doxxed dev team? Are reveals okay here?
No! No one should be trusted with such power. Even if someone isn't consciously trying to cheat, they have unconscious biases. They might also make a mistake and not realize it until it's too late, for example.
You should also not trust yourself. Imagine doing a reveal, thinking you did it correctly (nothing is 100%! ), and getting the rarest NFT. Isn't that a tad odd Do you think you deserve it? An NFT developer like myself would hate to be in this situation.
Reveals are bad*
UNLESS they are done without trust, meaning everyone can verify their fairness without relying on the developers (which you should never do).
An on-chain reveal powered by randomness that is verifiably outside of anyone's control is the most common way to achieve a trustless reveal (e.g., through Chainlink).
Tubby Cats did an excellent job on this reveal, and I highly recommend their contract and launch reflections. Their reveal was also cool because it was progressive—you didn't have to wait until the end of the mint to find out.
In his post-launch reflections, @DefiLlama stated that he made the contract as trustless as possible, removing as much trust as possible from the team.
In my opinion, everyone should know the rules of the game and trust that they will not be changed mid-stream, while trust minimization is critical because smart contracts were designed to reduce trust (and it makes it impossible to hack even if the team is compromised). This was a huge mistake because it limited our flexibility and our ability to correct mistakes.
And @DefiLlama is a superstar developer. Imagine how much stress maximizing trustlessness will cause you!
That leaves me with a bad solution that works in 99 percent of cases and is much easier to implement: random token assignments.
Introducing ERC721R: A fully compliant IERC721 implementation that picks token ids at random.
ERC721R implements the opposite of a reveal: we mint token ids randomly and assign metadata deterministically.
This allows us to reveal all metadata prior to minting while reducing snipe chances.
Then import the contract and use this code:
What is ERC721R and how does it work
First, a disclaimer: ERC721R isn't truly random. In this sense, it creates the same “game” as the mpher situation, where minters compete to exploit the mint. However, ERC721R is a much more difficult game.
To game ERC721R, you need to be able to predict a hash value using these inputs:
This is impossible for a normal person because it requires knowledge of the block timestamp of your mint, which you do not have.
To do this, a miner must set the timestamp to a value in the future, and whatever they do is dependent on the previous block's hash, which expires in about ten seconds when the next block is mined.
This pseudo-randomness is “good enough,” but if big money is involved, it will be gamed. Of course, the system it replaces—predictable minting—can be manipulated.
The token id is chosen in a clever implementation of the Fisher–Yates shuffle algorithm that I copied from CryptoPhunksV2.
Consider first the naive solution: (a 10,000 item collection is assumed):
- Make an array with 0–9999.
- To create a token, pick a random item from the array and use that as the token's id.
- Remove that value from the array and shorten it by one so that every index corresponds to an available token id.
This works, but it uses too much gas because changing an array's length and storing a large array of non-zero values is expensive.
How do we avoid them both? What if we started with a cheap 10,000-zero array? Let's assign an id to each index in that array.
Assume we pick index #6500 at random—#6500 is our token id, and we replace the 0 with a 1.
But what if we chose #6500 again? A 1 would indicate #6500 was taken, but then what? We can't just "roll again" because gas will be unpredictable and high, especially later mints.
This allows us to pick a token id 100% of the time without having to keep a separate list. Here's how it works:
- Make a 10,000 0 array.
- Create a 10,000 uint numAvailableTokens.
- Pick a number between 0 and numAvailableTokens. -1
- Think of #6500—look at index #6500. If it's 0, the next token id is #6500. If not, the value at index #6500 is your next token id (weird!)
- Examine the array's last value, numAvailableTokens — 1. If it's 0, move the value at #6500 to the end of the array (#9999 if it's the first token). If the array's last value is not zero, update index #6500 to store it.
- numAvailableTokens is decreased by 1.
- Repeat 3–6 for the next token id.
So there you go! The array stays the same size, but we can choose an available id reliably. The Solidity code is as follows:
Unfortunately, this algorithm uses more gas than the leading sequential mint solution, ERC721A.
This is most noticeable when minting multiple tokens in one transaction—a 10 token mint on ERC721R costs 5x more than on ERC721A. That said, ERC721A has been optimized much further than ERC721R so there is probably room for improvement.
Conclusion
Listed below are your options:
- ERC721A: Minters pay lower gas but must spend time and energy devising and executing a competitive minting strategy or be comfortable with worse minting results.
- ERC721R: Higher gas, but the easy minting strategy of just clicking the button is optimal in all but the most extreme cases. If miners game ERC721R it’s the worst of both worlds: higher gas and a ton of work to compete.
- ERC721A + standard reveal: Low gas, but not verifiably fair. Please do not do this!
- ERC721A + trustless reveal: The best solution if done correctly, highly-challenging for dev, potential for difficult-to-correct errors.
Did I miss something? Comment or tweet me @dumbnamenumbers.
Check out the code on GitHub to learn more! Pull requests are welcome—I'm sure I've missed many gas-saving opportunities.
Thanks!
Read the original post here
Matt Nutsch
3 years ago
Most people are unaware of how artificial intelligence (A.I.) is changing the world.
Recently, I saw an interesting social media post. In an entrepreneurship forum. A blogger asked for help because he/she couldn't find customers. I now suspect that the writer’s occupation is being disrupted by A.I.
Introduction
Artificial Intelligence (A.I.) has been a hot topic since the 1950s. With recent advances in machine learning, A.I. will touch almost every aspect of our lives. This article will discuss A.I. technology and its social and economic implications.
What's AI?
A computer program or machine with A.I. can think and learn. In general, it's a way to make a computer smart. Able to understand and execute complex tasks. Machine learning, NLP, and robotics are common types of A.I.
AI's global impact
AI will change the world, but probably faster than you think. A.I. already affects our daily lives. It improves our decision-making, efficiency, and productivity.
A.I. is transforming our lives and the global economy. It will create new business and job opportunities but eliminate others. Affected workers may face financial hardship.
AI examples:
OpenAI's GPT-3 text-generation
Developers can train, deploy, and manage models on GPT-3. It handles data preparation, model training, deployment, and inference for machine learning workloads. GPT-3 is easy to use for both experienced and new data scientists.
My team conducted an experiment. We needed to generate some blog posts for a website. We hired a blogger on Upwork. OpenAI created a blog post. The A.I.-generated blog post was of higher quality and lower cost.
MidjourneyAI's Art Contests
AI already affects artists. Artists use A.I. to create realistic 3D images and videos for digital art. A.I. is also used to generate new art ideas and methods.
MidjourneyAI and GigapixelAI won a contest last month. It's AI. created a beautiful piece of art that captured the contest's spirit. AI triumphs. It could open future doors.
After the art contest win, I registered to try out these new image generating A.I.s. In the MidjourneyAI chat forum, I noticed an artist's plea. The artist begged others to stop flooding RedBubble with AI-generated art.
Shutterstock and Getty Images have halted user uploads. AI-generated images flooded online marketplaces.
Imagining Videos with Meta
Meta released Make-a-Video this week. It's an A.I. app that creates videos from text. What you type creates a video.
This technology will impact TV, movies, and video games greatly. Imagine a movie or game that's personalized to your tastes. It's closer than you think.
Uses and Abuses of Deepfakes
Deepfake videos are computer-generated images of people. AI creates realistic images and videos of people.
Deepfakes are entertaining but have social implications. Porn introduced deepfakes in 2017. People put famous faces on porn actors and actresses without permission.
Soon, deepfakes were used to show dead actors/actresses or make them look younger. Carrie Fischer was included in films after her death using deepfake technology.
Deepfakes can be used to create fake news or manipulate public opinion, according to an AI.
Voices for Darth Vader and Iceman
James Earl Jones, who voiced Darth Vader, sold his voice rights this week. Aged actor won't be in those movies. Respeecher will use AI to mimic Jones's voice. This technology could change the entertainment industry. One actor can now voice many characters.
AI can generate realistic voice audio from text. Top Gun 2 actor Val Kilmer can't speak for medical reasons. Sonantic created Kilmer's voice from the movie script. This entertaining technology has social implications. It blurs authentic recordings and fake media.
Medical A.I. fights viruses
A team of Chinese scientists used machine learning to predict effective antiviral drugs last year. They started with a large dataset of virus-drug interactions. Researchers combined that with medication and virus information. Finally, they used machine learning to predict effective anti-virus medicines. This technology could solve medical problems.
AI ideas AI-generated Itself
OpenAI's GPT-3 predicted future A.I. uses. Here's what it told me:
AI will affect the economy. Businesses can operate more efficiently and reinvest resources with A.I.-enabled automation. AI can automate customer service tasks, reducing costs and improving satisfaction.
A.I. makes better pricing, inventory, and marketing decisions. AI automates tasks and makes decisions. A.I.-powered robots could help the elderly or disabled. Self-driving cars could reduce accidents.
A.I. predictive analytics can predict stock market or consumer behavior trends and patterns. A.I. also personalizes recommendations. sways. A.I. recommends products and movies. AI can generate new ideas based on data analysis.
Conclusion
A.I. will change business as it becomes more common. It will change how we live and work by creating growth and prosperity.
Exciting times, but also one which should give us all pause. Technology can be good or evil. We must use new technologies ethically, fairly, and honestly.
“The author generated some sentences in this text in part with GPT-3, OpenAI’s large-scale language-generation model. Upon generating draft language, the author reviewed, edited, and revised the language to their own liking and takes ultimate responsibility for the content of this publication. The text of this post was further edited using HemingWayApp. Many of the images used were generated using A.I. as described in the captions.”
You might also like
Waleed Rikab, PhD
2 years ago
The Enablement of Fraud and Misinformation by Generative AI What You Should Understand
Recent investigations have shown that generative AI can boost hackers and misinformation spreaders.
Since its inception in late November 2022, OpenAI's ChatGPT has entertained and assisted many online users in writing, coding, task automation, and linguistic translation. Given this versatility, it is maybe unsurprising but nonetheless regrettable that fraudsters and mis-, dis-, and malinformation (MDM) spreaders are also considering ChatGPT and related AI models to streamline and improve their operations.
Malign actors may benefit from ChatGPT, according to a WithSecure research. ChatGPT promises to elevate unlawful operations across many attack channels. ChatGPT can automate spear phishing attacks that deceive corporate victims into reading emails from trusted parties. Malware, extortion, and illicit fund transfers can result from such access.
ChatGPT's ability to simulate a desired writing style makes spear phishing emails look more genuine, especially for international actors who don't speak English (or other languages like Spanish and French).
This technique could let Russian, North Korean, and Iranian state-backed hackers conduct more convincing social engineering and election intervention in the US. ChatGPT can also create several campaigns and various phony online personas to promote them, making such attacks successful through volume or variation. Additionally, image-generating AI algorithms and other developing techniques can help these efforts deceive potential victims.
Hackers are discussing using ChatGPT to install malware and steal data, according to a Check Point research. Though ChatGPT's scripts are well-known in the cyber security business, they can assist amateur actors with little technical understanding into the field and possibly develop their hacking and social engineering skills through repeated use.
Additionally, ChatGPT's hacking suggestions may change. As a writer recently indicated, ChatGPT's ability to blend textual and code-based writing might be a game-changer, allowing the injection of innocent content that would subsequently turn out to be a malicious script into targeted systems. These new AI-powered writing- and code-generation abilities allow for unique cyber attacks, regardless of viability.
OpenAI fears ChatGPT usage. OpenAI, Georgetown University's Center for Security and Emerging Technology, and Stanford's Internet Observatory wrote a paper on how AI language models could enhance nation state-backed influence operations. As a last resort, the authors consider polluting the internet with radioactive or misleading data to ensure that AI language models produce outputs that other language models can identify as AI-generated. However, the authors of this paper seem unaware that their "solution" might cause much worse MDM difficulties.
Literally False News
The public argument about ChatGPTs content-generation has focused on originality, bias, and academic honesty, but broader global issues are at stake. ChatGPT can influence public opinion, troll individuals, and interfere in local and national elections by creating and automating enormous amounts of social media material for specified audiences.
ChatGPT's capacity to generate textual and code output is crucial. ChatGPT can write Python scripts for social media bots and give diverse content for repeated posts. The tool's sophistication makes it irrelevant to one's language skills, especially English, when writing MDM propaganda.
I ordered ChatGPT to write a news piece in the style of big US publications declaring that Ukraine is on the verge of defeat in its fight against Russia due to corruption, desertion, and exhaustion in its army. I also gave it a fake reporter's byline and an unidentified NATO source's remark. The outcome appears convincing:
Worse, terrible performers can modify this piece to make it more credible. They can edit the general's name or add facts about current wars. Furthermore, such actors can create many versions of this report in different forms and distribute them separately, boosting its impact.
In this example, ChatGPT produced a news story regarding (fictional) greater moviegoer fatality rates:
Editing this example makes it more plausible. Dr. Jane Smith, the putative author of the medical report, might be replaced with a real-life medical person or a real victim of this supposed medical hazard.
Can deceptive texts be found? Detecting AI text is behind AI advancements. Minor AI-generated text alterations can upset these technologies.
Some OpenAI individuals have proposed covert methods to watermark AI-generated literature to prevent its abuse. AI models would create information that appears normal to humans but would follow a cryptographic formula that would warn other machines that it was AI-made. However, security experts are cautious since manually altering the content interrupts machine and human detection of AI-generated material.
How to Prepare
Cyber security and IT workers can research and use generative AI models to fight spear fishing and extortion. Governments may also launch MDM-defence projects.
In election cycles and global crises, regular people may be the most vulnerable to AI-produced deceit. Until regulation or subsequent technical advances, individuals must recognize exposure to AI-generated fraud, dating scams, other MDM activities.
A three-step verification method of new material in suspicious emails or social media posts can help identify AI content and manipulation. This three-step approach asks about the information's distribution platform (is it reliable? ), author (is the reader familiar with them? ), and plausibility given one's prior knowledge of the topic.
Consider a report by a trusted journalist that makes shocking statements in their typical manner. AI-powered fake news may be released on an unexpected platform, such as a newly created Facebook profile. However, if it links to a known media source, it is more likely to be real.
Though hard and subjective, this verification method may be the only barrier against manipulation for now.
AI language models:
How to Recognize an AI-Generated Article ChatGPT, the popular AI-powered chatbot, can and likely does generate medium.com-style articles.
AI-Generated Text Detectors Fail. Do This. Online tools claim to detect ChatGPT output. Even with superior programming, I tested some of these tools. pub
Why Original Writers Matter Despite AI Language Models Creative writers may never be threatened by AI language models.
Navdeep Yadav
3 years ago
31 startup company models (with examples)
Many people find the internet's various business models bewildering.
This article summarizes 31 startup e-books.
1. Using the freemium business model (free plus premium),
The freemium business model offers basic software, games, or services for free and charges for enhancements.
Examples include Slack, iCloud, and Google Drive
Provide a rudimentary, free version of your product or service to users.
Google Drive and Dropbox offer 15GB and 2GB of free space but charge for more.
Freemium business model details (Click here)
2. The Business Model of Subscription
Subscription business models sell a product or service for recurring monthly or yearly revenue.
Examples: Tinder, Netflix, Shopify, etc
It's the next step to Freemium if a customer wants to pay monthly for premium features.
Subscription Business Model (Click here)
3. A market-based business strategy
It's an e-commerce site or app where third-party sellers sell products or services.
Examples are Amazon and Fiverr.
On Amazon's marketplace, a third-party vendor sells a product.
Freelancers on Fiverr offer specialized skills like graphic design.
Marketplace's business concept is explained.
4. Business plans using aggregates
In the aggregator business model, the service is branded.
Uber, Airbnb, and other examples
Marketplace and Aggregator business models differ.
Amazon and Fiverr link merchants and customers and take a 10-20% revenue split.
Uber and Airbnb-style aggregator Join these businesses and provide their products.
5. The pay-as-you-go concept of business
This is a consumption-based pricing system. Cloud companies use it.
Example: Amazon Web Service and Google Cloud Platform (GCP) (AWS)
AWS, an Amazon subsidiary, offers over 200 pay-as-you-go cloud services.
“In short, the more you use the more you pay”
When it's difficult to divide clients into pricing levels, pay-as-you is employed.
6. The business model known as fee-for-service (FFS)
FFS charges fixed and variable fees for each successful payment.
For instance, PayU, Paypal, and Stripe
Stripe charges 2.9% + 30 per payment.
These firms offer a payment gateway to take consumer payments and deposit them to a business account.
Fintech business model
7. EdTech business strategy
In edtech, you generate money by selling material or teaching as a service.
edtech business models
Freemium When course content is free but certification isn't, e.g. Coursera
FREE TRIAL SkillShare offers free trials followed by monthly or annual subscriptions.
Self-serving marketplace approach where you pick what to learn.
Ad-revenue model The company makes money by showing adverts to its huge user base.
Lock-in business strategy
Lock in prevents customers from switching to a competitor's brand or offering.
It uses switching costs or effort to transmit (soft lock-in), improved brand experience, or incentives.
Apple, SAP, and other examples
Apple offers an iPhone and then locks you in with extra hardware (Watch, Airpod) and platform services (Apple Store, Apple Music, cloud, etc.).
9. Business Model for API Licensing
APIs let third-party apps communicate with your service.
Uber and Airbnb use Google Maps APIs for app navigation.
Examples are Google Map APIs (Map), Sendgrid (Email), and Twilio (SMS).
Business models for APIs
Free: The simplest API-driven business model that enables unrestricted API access for app developers. Google Translate and Facebook are two examples.
Developer Pays: Under this arrangement, service providers such as AWS, Twilio, Github, Stripe, and others must be paid by application developers.
The developer receives payment: These are the compensated content producers or developers who distribute the APIs utilizing their work. For example, Amazon affiliate programs
10. Open-source enterprise
Open-source software can be inspected, modified, and improved by anybody.
For instance, use Firefox, Java, or Android.
Google paid Mozilla $435,702 million to be their primary search engine in 2018.
Open-source software profits in six ways.
Paid assistance The Project Manager can charge for customization because he is quite knowledgeable about the codebase.
A full database solution is available as a Software as a Service (MongoDB Atlas), but there is a fee for the monitoring tool.
Open-core design R studio is a better GUI substitute for open-source applications.
sponsors of GitHub Sponsorships benefit the developers in full.
demands for paid features Earn Money By Developing Open Source Add-Ons for Current Products
Open-source business model
11. The business model for data
If the software or algorithm collects client data to improve or monetize the system.
Open AI GPT3 gets smarter with use.
Foursquare allows users to exchange check-in locations.
Later, they compiled large datasets to enable retailers like Starbucks launch new outlets.
12. Business Model Using Blockchain
Blockchain is a distributed ledger technology that allows firms to deploy smart contracts without a central authority.
Examples include Alchemy, Solana, and Ethereum.
Business models using blockchain
Economy of tokens or utility When a business uses a token business model, it issues some kind of token as one of the ways to compensate token holders or miners. For instance, Solana and Ethereum
Bitcoin Cash P2P Business Model Peer-to-peer (P2P) blockchain technology permits direct communication between end users. as in IPFS
Enterprise Blockchain as a Service (Baas) BaaS focuses on offering ecosystem services similar to those offered by Amazon (AWS) and Microsoft (Azure) in the web 3 sector. Example: Ethereum Blockchain as a Service with Bitcoin (EBaaS).
Blockchain-Based Aggregators With AWS for blockchain, you can use that service by making an API call to your preferred blockchain. As an illustration, Alchemy offers nodes for many blockchains.
13. The free-enterprise model
In the freeterprise business model, free professional accounts are led into the funnel by the free product and later become B2B/enterprise accounts.
For instance, Slack and Zoom
Freeterprise companies flourish through collaboration.
Start with a free professional account to build an enterprise.
14. Business plan for razor blades
It's employed in hardware where one piece is sold at a loss and profits are made through refills or add-ons.
Gillet razor & blades, coffee machine & beans, HP printer & cartridge, etc.
Sony sells the Playstation console at a loss but makes up for it by selling games and charging for online services.
Advantages of the Razor-Razorblade Method
lowers the risk a customer will try a product. enables buyers to test the goods and services without having to pay a high initial investment.
The product's ongoing revenue stream has the potential to generate sales that much outweigh the original investments.
Razor blade business model
15. The business model of direct-to-consumer (D2C)
In D2C, the company sells directly to the end consumer through its website using a third-party logistic partner.
Examples include GymShark and Kylie Cosmetics.
D2C brands can only expand via websites, marketplaces (Amazon, eBay), etc.
D2C benefits
Lower reliance on middlemen = greater profitability
You now have access to more precise demographic and geographic customer data.
Additional space for product testing
Increased customisation throughout your entire product line-Inventory Less
16. Business model: White Label vs. Private Label
Private label/White label products are made by a contract or third-party manufacturer.
Most amazon electronics are made in china and white-labeled.
Amazon supplements and electronics.
Contract manufacturers handle everything after brands select product quantities on design labels.
17. The franchise model
The franchisee uses the franchisor's trademark, branding, and business strategy (company).
For instance, KFC, Domino's, etc.
Subway, Domino, Burger King, etc. use this business strategy.
Many people pick a franchise because opening a restaurant is risky.
18. Ad-based business model
Social media and search engine giants exploit search and interest data to deliver adverts.
Google, Meta, TikTok, and Snapchat are some examples.
Users don't pay for the service or product given, e.g. Google users don't pay for searches.
In exchange, they collected data and hyper-personalized adverts to maximize revenue.
19. Business plan for octopuses
Each business unit functions separately but is connected to the main body.
Instance: Oyo
OYO is Asia's Airbnb, operating hotels, co-working, co-living, and vacation houses.
20, Transactional business model, number
Sales to customers produce revenue.
E-commerce sites and online purchases employ SSL.
Goli is an ex-GymShark.
21. The peer-to-peer (P2P) business model
In P2P, two people buy and sell goods and services without a third party or platform.
Consider OLX.
22. P2P lending as a manner of operation
In P2P lending, one private individual (P2P Lender) lends/invests or borrows money from another (P2P Borrower).
Instance: Kabbage
Social lending lets people lend and borrow money directly from each other without an intermediary financial institution.
23. A business model for brokers
Brokerages charge a commission or fee for their services.
Examples include eBay, Coinbase, and Robinhood.
Brokerage businesses are common in Real estate, finance, and online and operate on this model.
Buy/sell similar models Examples include financial brokers, insurance brokers, and others who match purchase and sell transactions and charge a commission.
These brokers charge an advertiser a fee based on the date, place, size, or type of an advertisement. This is known as the classified-advertiser model. For instance, Craiglist
24. Drop shipping as an industry
Dropshipping allows stores to sell things without holding physical inventories.
When a customer orders, use a third-party supplier and logistic partners.
Retailer product portfolio and customer experience Fulfiller The consumer places the order.
Dropshipping advantages
Less money is needed (Low overhead-No Inventory or warehousing)
Simple to start (costs under $100)
flexible work environment
New product testing is simpler
25. Business Model for Space as a Service
It's centered on a shared economy that lets millennials live or work in communal areas without ownership or lease.
Consider WeWork and Airbnb.
WeWork helps businesses with real estate, legal compliance, maintenance, and repair.
26. The business model for third-party logistics (3PL)
In 3PL, a business outsources product delivery, warehousing, and fulfillment to an external logistics company.
Examples include Ship Bob, Amazon Fulfillment, and more.
3PL partners warehouse, fulfill, and return inbound and outbound items for a charge.
Inbound logistics involves bringing products from suppliers to your warehouse.
Outbound logistics refers to a company's production line, warehouse, and customer.
27. The last-mile delivery paradigm as a commercial strategy
Last-mile delivery is the collection of supply chain actions that reach the end client.
Examples include Rappi, Gojek, and Postmates.
Last-mile is tied to on-demand and has a nighttime peak.
28. The use of affiliate marketing
Affiliate marketing involves promoting other companies' products and charging commissions.
Examples include Hubspot, Amazon, and Skillshare.
Your favorite youtube channel probably uses these short amazon links to get 5% of sales.
Affiliate marketing's benefits
In exchange for a success fee or commission, it enables numerous independent marketers to promote on its behalf.
Ensure system transparency by giving the influencers a specific tracking link and an online dashboard to view their profits.
Learn about the newest bargains and have access to promotional materials.
29. The business model for virtual goods
This is an in-app purchase for an intangible product.
Examples include PubG, Roblox, Candy Crush, etc.
Consumables are like gaming cash that runs out. Non-consumable products provide a permanent advantage without repeated purchases.
30. Business Models for Cloud Kitchens
Ghost, Dark, Black Box, etc.
Delivery-only restaurant.
These restaurants don't provide dine-in, only delivery.
For instance, NextBite and Faasos
31. Crowdsourcing as a Business Model
Crowdsourcing = Using the crowd as a platform's source.
In crowdsourcing, you get support from people around the world without hiring them.
Crowdsourcing sites
Open-Source Software gives access to the software's source code so that developers can edit or enhance it. Examples include Firefox browsers and Linux operating systems.
Crowdfunding The oculus headgear would be an example of crowdfunding in essence, with no expectations.
Sean Bloomfield
3 years ago
How Jeff Bezos wins meetings over
We've all been there: You propose a suggestion to your team at a meeting, and most people appear on board, but a handful or small minority aren't. How can we achieve collective buy-in when we need to go forward but don't know how to deal with some team members' perceived intransigence?
Steps:
Investigate the divergent opinions: Begin by sincerely attempting to comprehend the viewpoint of your disagreeing coworkers. Maybe it makes sense to switch horses in the middle of the race. Have you completely overlooked a blind spot, such as a political concern that could arise as an unexpected result of proceeding? This is crucial to ensure that the person or people feel heard as well as to advance the goals of the team. Sometimes all individuals need is a little affirmation before they fully accept your point of view.
It says a lot about you as a leader to be someone who always lets the perceived greatest idea win, regardless of the originating channel, if after studying and evaluating you see the necessity to align with the divergent position.
If, after investigation and assessment, you determine that you must adhere to the original strategy, we go to Step 2.
2. Disagree and Commit: Jeff Bezos, CEO of Amazon, has had this experience, and Julie Zhuo describes how he handles it in her book The Making of a Manager.
It's OK to disagree when the team is moving in the right direction, but it's not OK to accidentally or purposefully damage the team's efforts because you disagree. Let the team know your opinion, but then help them achieve company goals even if they disagree. Unknown. You could be wrong in today's ever-changing environment.
So next time you have a team member who seems to be dissenting and you've tried the previous tactics, you may ask the individual in the meeting I understand you but I don't want us to leave without you on board I need your permission to commit to this approach would you give us your commitment?