More on Marketing

Francesca Furchtgott
3 years ago
Giving customers what they want or betraying the values of the brand?
A J.Crew collaboration for fashion label Eveliina Vintage is not a paradox; it is a solution.
Eveliina Vintage's capsule collection debuted yesterday at J.Crew. This J.Crew partnership stopped me in my tracks.
Eveliina Vintage sells vintage goods. Eeva Musacchia founded the shop in Finland in the 1970s. It's recognized for its one-of-a-kind slip dresses from the 1930s and 1940s.
I wondered why a vintage brand would partner with a mass shop. Fast fashion against vintage shopping? Will Eveliina Vintages customers be turned off?
But Eveliina Vintages customers don't care about sustainability. They want Eveliina's Instagram look. Eveliina Vintage collaborated with J.Crew to give customers what they wanted: more Eveliina at a lower price.
Vintage: A Fashion Option That Is Eco-Conscious
Secondhand shopping is a trendy response to quick fashion. J.Crew releases hundreds of styles annually. Waste and environmental damage have been criticized. A pair of jeans requires 1,800 gallons of water. J.Crew's limited-time deals promote more purchases. J.Crew items are likely among those Americans wear 7 times before discarding.
Consumers and designers have emphasized sustainability in recent years. Stella McCartney and Eileen Fisher are popular eco-friendly brands. They've also flocked to ThredUp and similar sites.
Gap, Levis, and Allbirds have listened to consumer requests. They promote recycling, ethical sourcing, and secondhand shopping.
Secondhand shoppers feel good about reusing and recycling clothing that might have ended up in a landfill.
Eco-conscious fashionistas shop vintage. These shoppers enjoy the thrill of the hunt (that limited-edition Chanel bag!) and showing off a unique piece (nobody will have my look!). They also reduce their environmental impact.
Is Eveliina Vintage capitalizing on an aesthetic or is it a sustainable brand?
Eveliina Vintage emphasizes environmental responsibility. Vogue's Amanda Musacchia emphasized sustainability. Amanda, founder Eeva's daughter, is a company leader.
But Eveliina's press message doesn't address sustainability, unlike Instagram. Scarcity and fame rule.
Eveliina Vintages Instagram has see-through dresses and lace-trimmed slip dresses. Celebrities and influencers are often photographed in Eveliina's apparel, which has 53,000+ followers. Vogue appreciates Eveliina's style. Multiple publications discuss Alexa Chung's Eveliina dress.
Eveliina Vintage markets its one-of-a-kind goods. It teases future content, encouraging visitors to return. Scarcity drives demand and raises clothing prices. One dress is $1,600+, but most are $500-$1,000.
The catch: Eveliina can't monetize its expanding popularity due to exorbitant prices and limited quantity. Why?
Most people struggle to pay for their clothing. But Eveliina Vintage lacks those more affordable entry-level products, in contrast to other luxury labels that sell accessories or perfume.
Many people have trouble fitting into their clothing. The bodies of most women in the past were different from those for which vintage clothing was designed. Each Eveliina dress's specific measurements are mentioned alongside it. Be careful, you can fall in love with an ill-fitting dress.
No matter how many people can afford it and fit into it, there is only one item to sell. To get the item before someone else does, those people must be on the Eveliina Vintage website as soon as it becomes available.
A Way for Eveliina Vintage to Make Money (and Expand) with J.Crew Its following
Eveliina Vintages' cooperation with J.Crew makes commercial sense.
This partnership spreads Eveliina's style. Slightly better pricing The $390 outfits have multicolored slips and gauzy cotton gowns. Sizes range from 00 to 24, which is wider than vintage racks.
Eveliina Vintage customers like the combination. Excited comments flood the brand's Instagram launch post. Nobody is mocking the 50-year-old vintage brand's fast-fashion partnership.
Vintage may be a sustainable fashion trend, but that's not why Eveliina's clients love the brand. They only care about the old look.
And that is a tale as old as fashion.

Jon Brosio
3 years ago
This Landing Page is a (Legal) Money-Printing Machine
and it’s easy to build.
A landing page with good copy is a money-maker.
Let's be honest, page-builder templates are garbage.
They can help you create a nice-looking landing page, but not persuasive writing.
Over the previous 90 days, I've examined 200+ landing pages.
What's crazy?
Top digital entrepreneurs use a 7-part strategy to bring in email subscribers, generate prospects, and (passively) sell their digital courses.
Steal this 7-part landing page architecture to maximize digital product sales.
The offer
Landing pages require offers.
Newsletter, cohort, or course offer.
Your reader should see this offer first. Includind:
Headline
Imagery
Call-to-action
Clear, persuasive, and simplicity are key. Example: the Linkedin OS course home page of digital entrepreneur Justin Welsh offers:
A distinctly defined problem
Everyone needs an enemy.
You need an opponent on your landing page. Problematic.
Next, employ psychology to create a struggle in your visitor's thoughts.
Don't be clever here; label your customer's problem. The more particular you are, the bigger the situation will seem.
When you build a clear monster, you invite defeat. I appreciate Theo Ohene's Growth Roadmaps landing page.
Exacerbation of the effects
Problem identification doesn't motivate action.
What would an unresolved problem mean?
This is landing page copy. When you describe the unsolved problem's repercussions, you accomplish several things:
You write a narrative (and stories are remembered better than stats)
You cause the reader to feel something.
You help the reader relate to the issue
Important!
My favorite script is:
"Sure, you can let [problem] go untreated. But what will happen if you do? Soon, you'll begin to notice [new problem 1] will start to arise. That might bring up [problem 2], etc."
Take the copywriting course, digital writer and entrepreneur Dickie Bush illustrates below when he labels the problem (see: "poor habit") and then illustrates the repercussions.
The tale of transformation
Every landing page needs that "ah-ha!" moment.
Transformation stories do this.
Did you find a solution? Someone else made the discovery? Have you tested your theory?
Next, describe your (or your subject's) metamorphosis.
Kieran Drew nails his narrative (and revelation) here. Right before the disclosure, he introduces his "ah-ha!" moment:
Testimonials
Social proof completes any landing page.
Social proof tells the reader, "If others do it, it must be worthwhile."
This is your argument.
Positive social proof helps (obviously).
Offer "free" training in exchange for a testimonial if you need social evidence. This builds social proof.
Most social proof is testimonies (recommended). Kurtis Hanni's creative take on social proof (using a screenshot of his colleague) is entertaining.
Bravo.
Reveal your offer
Now's the moment to act.
Describe the "bundle" that provides the transformation.
Here's:
Course
Cohort
Ebook
Whatever you're selling.
Include a product or service image, what the consumer is getting ("how it works"), the price, any "free" bonuses (preferred), and a CTA ("buy now").
Clarity is key. Don't make a cunning offer. Make sure your presentation emphasizes customer change (benefits). Dan Koe's Modern Mastery landing page makes an offer. Consider:
An ultimatum
Offering isn't enough.
You must give your prospect an ultimatum.
They can buy your merchandise from you.
They may exit the webpage.
That’s it.
It's crucial to show what happens if the reader does either. Stress the consequences of not buying (again, a little consequence amplification). Remind them of the benefits of buying.
I appreciate Charles Miller's product offer ending:
The top online creators use a 7-part landing page structure:
Offer the service
Describe the problem
Amplify the consequences
Tell the transformational story
Include testimonials and social proof.
Reveal the offer (with any bonuses if applicable)
Finally, give the reader a deadline to encourage them to take action.
Sequence these sections to develop a landing page that (essentially) prints money.

Jano le Roux
3 years ago
Here's What I Learned After 30 Days Analyzing Apple's Microcopy
Move people with tiny words.

Apple fanboy here.
Macs are awesome.
Their iPhones rock.
$19 cloths are great.
$999 stands are amazing.
I love Apple's microcopy even more.
It's like the marketing goddess bit into the Apple logo and blessed the world with microcopy.
I took on a 30-day micro-stalking mission.
Every time I caught myself wasting time on YouTube, I had to visit Apple’s website to learn the secrets of the marketing goddess herself.
We've learned. Golden apples are calling.
Cut the friction
Benefit-first, not commitment-first.
Brands lose customers through friction.
Most brands don't think like customers.
Brands want sales.
Brands want newsletter signups.
Here's their microcopy:
“Buy it now.”
“Sign up for our newsletter.”
Both are difficult. They ask for big commitments.
People are simple creatures. Want pleasure without commitment.
Apple nails this.
So, instead of highlighting the commitment, they highlight the benefit of the commitment.

Saving on the latest iPhone sounds easier than buying it. Everyone saves, but not everyone buys.
A subtle change in framing reduces friction.
Apple eliminates customer objections to reduce friction.

Less customer friction means simpler processes.
Apple's copy expertly reassures customers about shipping fees and not being home. Apple assures customers that returning faulty products is easy.
Apple knows that talking to a real person is the best way to reduce friction and improve their copy.
Always rhyme
Learn about fine rhyme.
Poets make things beautiful with rhyme.
Copywriters use rhyme to stand out.
Apple’s copywriters have mastered the art of corporate rhyme.
Two techniques are used.
1. Perfect rhyme
Here, rhymes are identical.

2. Imperfect rhyme
Here, rhyming sounds vary.

Apple prioritizes meaning over rhyme.
Apple never forces rhymes that don't fit.
It fits so well that the copy seems accidental.
Add alliteration
Alliteration always entertains.
Alliteration repeats initial sounds in nearby words.
Apple's copy uses alliteration like no other brand I've seen to create a rhyming effect or make the text more fun to read.
For example, in the sentence "Sam saw seven swans swimming," the initial "s" sound is repeated five times. This creates a pleasing rhythm.
Microcopy overuse is like pouring ketchup on a Michelin-star meal.
Alliteration creates a memorable phrase in copywriting. It's subtler than rhyme, and most people wouldn't notice; it simply resonates.

I love how Apple uses alliteration and contrast between "wonders" and "ease".
Assonance, or repeating vowels, isn't Apple's thing.
You ≠ Hero, Customer = Hero
Your brand shouldn't be the hero.
Because they'll be using your product or service, your customer should be the hero of your copywriting. With your help, they should feel like they can achieve their goals.
I love how Apple emphasizes what you can do with the machine in this microcopy.

It's divine how they position their tools as sidekicks to help below.

This one takes the cake:

Dialogue-style writing
Conversational copy engages.
Excellent copy Like sharing gum with a friend.
This helps build audience trust.

Apple does this by using natural connecting words like "so" and phrases like "But that's not all."
Snowclone-proof
The mother of all microcopy techniques.
A snowclone uses an existing phrase or sentence to create a new one. The new phrase or sentence uses the same structure but different words.
It’s usually a well know saying like:
To be or not to be.
This becomes a formula:
To _ or not to _.
Copywriters fill in the blanks with cause-related words. Example:
To click or not to click.

Apple turns "survival of the fittest" into "arrival of the fittest."
It's unexpected and surprises the reader.
So this was fun.
But my fun has just begun.
Microcopy is 21st-century poetry.
I came as an Apple fanboy.
I leave as an Apple fanatic.
Now I’m off to find an apple tree.
Cause you know how it goes.
(Apples, trees, etc.)
This post is a summary. Original post available here.
You might also like

Ashraful Islam
4 years ago
Clean API Call With React Hooks
| Photo by Juanjo Jaramillo on Unsplash |
Calling APIs is the most common thing to do in any modern web application. When it comes to talking with an API then most of the time we need to do a lot of repetitive things like getting data from an API call, handling the success or error case, and so on.
When calling tens of hundreds of API calls we always have to do those tedious tasks. We can handle those things efficiently by putting a higher level of abstraction over those barebone API calls, whereas in some small applications, sometimes we don’t even care.
The problem comes when we start adding new features on top of the existing features without handling the API calls in an efficient and reusable manner. In that case for all of those API calls related repetitions, we end up with a lot of repetitive code across the whole application.
In React, we have different approaches for calling an API. Nowadays mostly we use React hooks. With React hooks, it’s possible to handle API calls in a very clean and consistent way throughout the application in spite of whatever the application size is. So let’s see how we can make a clean and reusable API calling layer using React hooks for a simple web application.
I’m using a code sandbox for this blog which you can get here.
import "./styles.css";
import React, { useEffect, useState } from "react";
import axios from "axios";
export default function App() {
const [posts, setPosts] = useState(null);
const [error, setError] = useState("");
const [loading, setLoading] = useState(false);
useEffect(() => {
handlePosts();
}, []);
const handlePosts = async () => {
setLoading(true);
try {
const result = await axios.get(
"https://jsonplaceholder.typicode.com/posts"
);
setPosts(result.data);
} catch (err) {
setError(err.message || "Unexpected Error!");
} finally {
setLoading(false);
}
};
return (
<div className="App">
<div>
<h1>Posts</h1>
{loading && <p>Posts are loading!</p>}
{error && <p>{error}</p>}
<ul>
{posts?.map((post) => (
<li key={post.id}>{post.title}</li>
))}
</ul>
</div>
</div>
);
}
I know the example above isn’t the best code but at least it’s working and it’s valid code. I will try to improve that later. For now, we can just focus on the bare minimum things for calling an API.
Here, you can try to get posts data from JsonPlaceholer. Those are the most common steps we follow for calling an API like requesting data, handling loading, success, and error cases.
If we try to call another API from the same component then how that would gonna look? Let’s see.
500: Internal Server Error
Now it’s going insane! For calling two simple APIs we’ve done a lot of duplication. On a top-level view, the component is doing nothing but just making two GET requests and handling the success and error cases. For each request, it’s maintaining three states which will periodically increase later if we’ve more calls.
Let’s refactor to make the code more reusable with fewer repetitions.
Step 1: Create a Hook for the Redundant API Request Codes
Most of the repetitions we have done so far are about requesting data, handing the async things, handling errors, success, and loading states. How about encapsulating those things inside a hook?
The only unique things we are doing inside handleComments and handlePosts are calling different endpoints. The rest of the things are pretty much the same. So we can create a hook that will handle the redundant works for us and from outside we’ll let it know which API to call.
500: Internal Server Error
Here, this request function is identical to what we were doing on the handlePosts and handleComments. The only difference is, it’s calling an async function apiFunc which we will provide as a parameter with this hook. This apiFunc is the only independent thing among any of the API calls we need.
With hooks in action, let’s change our old codes in App component, like this:
500: Internal Server Error
How about the current code? Isn’t it beautiful without any repetitions and duplicate API call handling things?
Let’s continue our journey from the current code. We can make App component more elegant. Now it knows a lot of details about the underlying library for the API call. It shouldn’t know that. So, here’s the next step…
Step 2: One Component Should Take Just One Responsibility
Our App component knows too much about the API calling mechanism. Its responsibility should just request the data. How the data will be requested under the hood, it shouldn’t care about that.
We will extract the API client-related codes from the App component. Also, we will group all the API request-related codes based on the API resource. Now, this is our API client:
import axios from "axios";
const apiClient = axios.create({
// Later read this URL from an environment variable
baseURL: "https://jsonplaceholder.typicode.com"
});
export default apiClient;
All API calls for comments resource will be in the following file:
import client from "./client";
const getComments = () => client.get("/comments");
export default {
getComments
};
All API calls for posts resource are placed in the following file:
import client from "./client";
const getPosts = () => client.get("/posts");
export default {
getPosts
};
Finally, the App component looks like the following:
import "./styles.css";
import React, { useEffect } from "react";
import commentsApi from "./api/comments";
import postsApi from "./api/posts";
import useApi from "./hooks/useApi";
export default function App() {
const getPostsApi = useApi(postsApi.getPosts);
const getCommentsApi = useApi(commentsApi.getComments);
useEffect(() => {
getPostsApi.request();
getCommentsApi.request();
}, []);
return (
<div className="App">
{/* Post List */}
<div>
<h1>Posts</h1>
{getPostsApi.loading && <p>Posts are loading!</p>}
{getPostsApi.error && <p>{getPostsApi.error}</p>}
<ul>
{getPostsApi.data?.map((post) => (
<li key={post.id}>{post.title}</li>
))}
</ul>
</div>
{/* Comment List */}
<div>
<h1>Comments</h1>
{getCommentsApi.loading && <p>Comments are loading!</p>}
{getCommentsApi.error && <p>{getCommentsApi.error}</p>}
<ul>
{getCommentsApi.data?.map((comment) => (
<li key={comment.id}>{comment.name}</li>
))}
</ul>
</div>
</div>
);
}
Now it doesn’t know anything about how the APIs get called. Tomorrow if we want to change the API calling library from axios to fetch or anything else, our App component code will not get affected. We can just change the codes form client.js This is the beauty of abstraction.
Apart from the abstraction of API calls, Appcomponent isn’t right the place to show the list of the posts and comments. It’s a high-level component. It shouldn’t handle such low-level data interpolation things.
So we should move this data display-related things to another low-level component. Here I placed those directly in the App component just for the demonstration purpose and not to distract with component composition-related things.
Final Thoughts
The React library gives the flexibility for using any kind of third-party library based on the application’s needs. As it doesn’t have any predefined architecture so different teams/developers adopted different approaches to developing applications with React. There’s nothing good or bad. We choose the development practice based on our needs/choices. One thing that is there beyond any choices is writing clean and maintainable codes.

Amelia Winger-Bearskin
3 years ago
Reasons Why AI-Generated Images Remind Me of Nightmares
AI images are like funhouse mirrors.
Google's AI Blog introduced the puppy-slug in the summer of 2015.
Puppy-slug isn't a single image or character. "Puppy-slug" refers to Google's DeepDream's unsettling psychedelia. This tool uses convolutional neural networks to train models to recognize dataset entities. If researchers feed the model millions of dog pictures, the network will learn to recognize a dog.
DeepDream used neural networks to analyze and classify image data as well as generate its own images. DeepDream's early examples were created by training a convolutional network on dog images and asking it to add "dog-ness" to other images. The models analyzed images to find dog-like pixels and modified surrounding pixels to highlight them.
Puppy-slugs and other DeepDream images are ugly. Even when they don't trigger my trypophobia, they give me vertigo when my mind tries to reconcile familiar features and forms in unnatural, physically impossible arrangements. I feel like I've been poisoned by a forbidden mushroom or a noxious toad. I'm a Lovecraft character going mad from extradimensional exposure. They're gross!
Is this really how AIs see the world? This is possibly an even more unsettling topic that DeepDream raises than the blatant abjection of the images.
When these photographs originally circulated online, many friends were startled and scandalized. People imagined a computer's imagination would be literal, accurate, and boring. We didn't expect vivid hallucinations and organic-looking formations.
DeepDream's images didn't really show the machines' imaginations, at least not in the way that scared some people. DeepDream displays data visualizations. DeepDream reveals the "black box" of convolutional network training.
Some of these images look scary because the models don't "know" anything, at least not in the way we do.
These images are the result of advanced algorithms and calculators that compare pixel values. They can spot and reproduce trends from training data, but can't interpret it. If so, they'd know dogs have two eyes and one face per head. If machines can think creatively, they're keeping it quiet.
You could be forgiven for thinking otherwise, given OpenAI's Dall-impressive E's results. From a technological perspective, it's incredible.
Arthur C. Clarke once said, "Any sufficiently advanced technology is indistinguishable from magic." Dall-magic E's requires a lot of math, computer science, processing power, and research. OpenAI did a great job, and we should applaud them.
Dall-E and similar tools match words and phrases to image data to train generative models. Matching text to images requires sorting and defining the images. Untold millions of low-wage data entry workers, content creators optimizing images for SEO, and anyone who has used a Captcha to access a website make these decisions. These people could live and die without receiving credit for their work, even though the project wouldn't exist without them.
This technique produces images that are less like paintings and more like mirrors that reflect our own beliefs and ideals back at us, albeit via a very complex prism. Due to the limitations and biases that these models portray, we must exercise caution when viewing these images.
The issue was succinctly articulated by artist Mimi Onuoha in her piece "On Algorithmic Violence":
As we continue to see the rise of algorithms being used for civic, social, and cultural decision-making, it becomes that much more important that we name the reality that we are seeing. Not because it is exceptional, but because it is ubiquitous. Not because it creates new inequities, but because it has the power to cloak and amplify existing ones. Not because it is on the horizon, but because it is already here.

Jake Prins
3 years ago
What are NFTs 2.0 and what issues are they meant to address?
New standards help NFTs reach their full potential.
NFTs lack interoperability and functionality. They have great potential but are mostly speculative. To maximize NFTs, we need flexible smart contracts.
Current requirements are too restrictive.
Most NFTs are based on ERC-721, which makes exchanging them easy. CryptoKitties, a popular online game, used the 2017 standard to demonstrate NFTs' potential.
This simple standard includes a base URI and incremental IDs for tokens. Add the tokenID to the base URI to get the token's metadata.
This let creators collect NFTs. Many NFT projects store metadata on IPFS, a distributed storage network, but others use Google Drive. NFT buyers often don't realize that if the creators delete or move the files, their NFT is just a pointer.
This isn't the standard's biggest issue. There's no way to validate NFT projects.
Creators are one of the most important aspects of art, but nothing is stored on-chain.
ERC-721 contracts only have a name and symbol.
Most of the data on OpenSea's collection pages isn't from the NFT's smart contract. It was added through a platform input field, so it's in the marketplace's database. Other websites may have different NFT information.
In five years, your NFT will be just a name, symbol, and ID.
Your NFT doesn't mention its creators. Although the smart contract has a public key, it doesn't reveal who created it.
The NFT's creators and their reputation are crucial to its value. Think digital fashion and big brands working with well-known designers when more professionals use NFTs. Don't you want them in your NFT?
Would paintings be as valuable if their artists were unknown? Would you believe it's real?
Buying directly from an on-chain artist would reduce scams. Current standards don't allow this data.
Most creator profiles live on centralized marketplaces and could disappear. Current platforms have outpaced underlying standards. The industry's standards are lagging.
For NFTs to grow beyond pointers to a monkey picture file, we may need to use new Web3-based standards.
Introducing NFTs 2.0
Fabian Vogelsteller, creator of ERC-20, developed new web3 standards. He proposed LSP7 Digital Asset and LSP8 Identifiable Digital Asset, also called NFT 2.0.
NFT and token metadata inputs are extendable. Changes to on-chain metadata inputs allow NFTs to evolve. Instead of public keys, the contract can have Universal Profile addresses attached. These profiles show creators' faces and reputations. NFTs can notify asset receivers, automating smart contracts.
LSP7 and LSP8 use ERC725Y. Using a generic data key-value store gives contracts much-needed features:
The asset can be customized and made to stand out more by allowing for unlimited data attachment.
Recognizing changes to the metadata
using a hash reference for metadata rather than a URL reference
This base will allow more metadata customization and upgradeability. These guidelines are:
Genuine and Verifiable Now, the creation of an NFT by a specific Universal Profile can be confirmed by smart contracts.
Dynamic NFTs can update Flexible & Updatable Metadata, allowing certain things to evolve over time.
Protected metadata Now, secure metadata that is readable by smart contracts can be added indefinitely.
Better NFTS prevent the locking of NFTs by only being sent to Universal Profiles or a smart contract that can interact with them.
Summary
NFTS standards lack standardization and powering features, limiting the industry.
ERC-721 is the most popular NFT standard, but it only represents incremental tokenIDs without metadata or asset representation. No standard sender-receiver interaction or security measures ensure safe asset transfers.
NFT 2.0 refers to the new LSP7-DigitalAsset and LSP8-IdentifiableDigitalAsset standards.
They have new standards for flexible metadata, secure transfers, asset representation, and interactive transfer.
With NFTs 2.0 and Universal Profiles, creators could build on-chain reputations.
NFTs 2.0 could bring the industry's needed innovation if it wants to move beyond trading profile pictures for speculation.
