More on Marketing

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.

Mark Shpuntov
3 years ago
How to Produce a Month's Worth of Content for Social Media in a Day
New social media producers' biggest error
The Treadmill of Social Media Content
New creators focus on the wrong platforms.
They post to Instagram, Twitter, TikTok, etc.
They create daily material, but it's never enough for social media algorithms.
Creators recognize they're on a content creation treadmill.
They have to keep publishing content daily just to stay on the algorithm’s good side and avoid losing the audience they’ve built on the platform.
This is exhausting and unsustainable, causing creator burnout.
They focus on short-lived platforms, which is an issue.
Comparing low- and high-return social media platforms
Social media networks are great for reaching new audiences.
Their algorithm is meant to viralize material.
Social media can use you for their aims if you're not careful.
To master social media, focus on the right platforms.
To do this, we must differentiate low-ROI and high-ROI platforms:
Low ROI platforms are ones where content has a short lifespan. High ROI platforms are ones where content has a longer lifespan.
A tweet may be shown for 12 days. If you write an article or blog post, it could get visitors for 23 years.
ROI is drastically different.
New creators have limited time and high learning curves.
Nothing is possible.
First create content for high-return platforms.
ROI for social media platforms
Here are high-return platforms:
Your Blog - A single blog article can rank and attract a ton of targeted traffic for a very long time thanks to the power of SEO.
YouTube - YouTube has a reputation for showing search results or sidebar recommendations for videos uploaded 23 years ago. A superb video you make may receive views for a number of years.
Medium - A platform dedicated to excellent writing is called Medium. When you write an article about a subject that never goes out of style, you're building a digital asset that can drive visitors indefinitely.
These high ROI platforms let you generate content once and get visitors for years.
This contrasts with low ROI platforms:
Twitter
Instagram
TikTok
LinkedIn
Facebook
The posts you publish on these networks have a 23-day lifetime. Instagram Reels and TikToks are exceptions since viral content can last months.
If you want to make content creation sustainable and enjoyable, you must focus the majority of your efforts on creating high ROI content first. You can then use the magic of repurposing content to publish content to the lower ROI platforms to increase your reach and exposure.
How To Use Your Content Again
So, you’ve decided to focus on the high ROI platforms.
Great!
You've published an article or a YouTube video.
You worked hard on it.
Now you have fresh stuff.
What now?
If you are not repurposing each piece of content for multiple platforms, you are throwing away your time and efforts.
You've created fantastic material, so why not distribute it across platforms?
Repurposing Content Step-by-Step
For me, it's writing a blog article, but you might start with a video or podcast.
The premise is the same regardless of the medium.
Start by creating content for a high ROI platform (YouTube, Blog Post, Medium). Then, repurpose, edit, and repost it to the lower ROI platforms.
Here's how to repurpose pillar material for other platforms:
Post the article on your blog.
Put your piece on Medium (use the canonical link to point to your blog as the source for SEO)
Create a video and upload it to YouTube using the talking points from the article.
Rewrite the piece a little, then post it to LinkedIn.
Change the article's format to a Thread and share it on Twitter.
Find a few quick quotes throughout the article, then use them in tweets or Instagram quote posts.
Create a carousel for Instagram and LinkedIn using screenshots from the Twitter Thread.
Go through your film and select a few valuable 30-second segments. Share them on LinkedIn, Facebook, Twitter, TikTok, YouTube Shorts, and Instagram Reels.
Your video's audio can be taken out and uploaded as a podcast episode.
If you (or your team) achieve all this, you'll have 20-30 pieces of social media content.
If you're just starting, I wouldn't advocate doing all of this at once.
Instead, focus on a few platforms with this method.
You can outsource this as your company expands. (If you'd want to learn more about content repurposing, contact me.)
You may focus on relevant work while someone else grows your social media on autopilot.
You develop high-ROI pillar content, and it's automatically chopped up and posted on social media.
This lets you use social media algorithms without getting sucked in.
Thanks for reading!

obimy.app
3 years ago
How TikTok helped us grow to 6 million users
This resulted to obimy's new audience.
Hi! obimy's official account. Here, we'll teach app developers and marketers. In 2022, our downloads increased dramatically, so we'll share what we learned.
obimy is what we call a ‘senseger’. It's a new method to communicate digitally. Instead of text, obimy users connect through senses and moods. Feeling playful? Flirt with your partner, pat a pal, or dump water on a classmate. Each feeling is an interactive animation with vibration. It's a wordless app. App Store and Google Play have obimy.
We had 20,000 users in 2022. Two to five thousand of them opened the app monthly. Our DAU metric was 500.
We have 6 million users after 6 months. 500,000 individuals use obimy daily. obimy was the top lifestyle app this week in the U.S.
And TikTok helped.
TikTok fuels obimys' growth. It's why our app exploded. How and what did we learn? Our Head of Marketing, Anastasia Avramenko, knows.
our actions prior to TikTok
We wanted to achieve product-market fit through organic expansion. Quora, Reddit, Facebook Groups, Facebook Ads, Google Ads, Apple Search Ads, and social media activity were tested. Nothing worked. Our CPI was sometimes $4, so unit economics didn't work.
We studied our markets and made audience hypotheses. We promoted our goods and studied our audience through social media quizzes. Our target demographic was Americans in long-distance relationships. I designed quizzes like Test the Strength of Your Relationship to better understand the user base. After each quiz, we encouraged users to download the app to enhance their connection and bridge the distance.
We got 1,000 responses for $50. This helped us comprehend the audience's grief and coping strategies (aka our rivals). I based action items on answers given. If you can't embrace a loved one, use obimy.
We also tried Facebook and Google ads. From the start, we knew it wouldn't work.
We were desperate to discover a free way to get more users.
Our journey to TikTok
TikTok is a great venue for emerging creators. It also helped reach people. Before obimy, my TikTok videos garnered 12 million views without sponsored promotion.
We had to act. TikTok was required.
I wasn't a TikTok user before obimy. Initially, I uploaded promotional content. Call-to-actions appear strange next to dancing challenges and my money don't jiggle jiggle. I learned TikTok. Watch TikTok for an hour was on my to-do list. What a dream job!
Our most popular movies presented the app alongside text outlining what it does. We started promoting them in Europe and the U.S. and got a 16% CTR and $1 CPI, an improvement over our previous efforts.
Somehow, we were expanding. So we came up with new hypotheses, calls to action, and content.
Four months passed, yet we saw no organic growth.
Russia attacked Ukraine.
Our app aimed to be helpful. For now, we're focusing on our Ukrainian audience. I posted sloppy TikToks illustrating how obimy can help during shelling or air raids.
In two hours, Kostia sent me our visitor count. Our servers crashed.
Initially, we had several thousand daily users. Over 200,000 users joined obimy in a week. They posted obimy videos on TikTok, drawing additional users. We've also resumed U.S. video promotion.
We gained 2,000,000 new members with less than $100 in ads, primarily in the U.S. and U.K.
TikTok helped.
The figures
We were confident we'd chosen the ideal tool for organic growth.
Over 45 million people have viewed our own videos plus a ton of user-generated content with the hashtag #obimy.
About 375 thousand people have liked all of our individual videos.
The number of downloads and the virality of videos are directly correlated.
Where are we now?
TikTok fuels our organic growth. We post 56 videos every week and pay to promote viral content.
We use UGC and influencers. We worked with Universal Music Italy on Eurovision. They offered to promote us through their million-follower TikTok influencers. We thought their followers would improve our audience, but it didn't matter. Integration didn't help us. Users that share obimy videos with their followers can reach several million views, which affects our download rate.
After the dust settled, we determined our key audience was 13-18-year-olds. They want to express themselves, but it's sometimes difficult. We're searching for methods to better engage with our users. We opened a Discord server to discuss anime and video games and gather app and content feedback.
TikTok helps us test product updates and hypotheses. Example: I once thought we might raise MAU by prompting users to add strangers as friends. Instead of asking our team to construct it, I made a TikTok urging users to share invite URLs. Users share links under every video we upload, embracing people worldwide.
Key lessons
Don't direct-sell. TikTok isn't for Instagram, Facebook, or YouTube promo videos. Conventional advertisements don't fit. Most users will swipe up and watch humorous doggos.
More product videos are better. Finally. So what?
Encourage interaction. Tagging friends in comments or making videos with the app promotes it more than any marketing spend.
Be odd and risqué. A user mistakenly sent a French kiss to their mom in one of our most popular videos.
TikTok helps test hypotheses and build your user base. It also helps develop apps. In our upcoming blog, we'll guide you through obimy's design revisions based on TikTok. Follow us on Twitter, Instagram, and TikTok.
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Ian Writes
3 years ago
Rich Dad, Poor Dad is a Giant Steaming Pile of Sh*t by Robert Kiyosaki.
Don't promote it.
I rarely read a post on how Rich Dad, Poor Dad motivated someone to grow rich or change their investing/finance attitude. Rich Dad, Poor Dad is a sham, though. This book isn't worth anyone's attention.
Robert Kiyosaki, the author of this garbage, doesn't deserve recognition or attention. This first finance guru wanted to build his own wealth at your expense. These charlatans only care about themselves.
The reason why Rich Dad, Poor Dad is a huge steaming piece of trash
The book's ideas are superficial, apparent, and unsurprising to entrepreneurs and investors. The book's themes may seem profound to first-time readers.
Apparently, starting a business will make you rich.
The book supports founding or buying a business, making it self-sufficient, and being rich through it. Starting a business is time-consuming, tough, and expensive. Entrepreneurship isn't for everyone. Rarely do enterprises succeed.
Robert says we should think like his mentor, a rich parent. Robert never said who or if this guy existed. He was apparently his own father. Robert proposes investing someone else's money in several enterprises and properties. The book proposes investing in:
“have returns of 100 percent to infinity. Investments that for $5,000 are soon turned into $1 million or more.”
In rare cases, a business may provide 200x returns, but 65% of US businesses fail within 10 years. Australia's first-year business failure rate is 60%. A business that lasts 10 years doesn't mean its owner is rich. These statistics only include businesses that survive and pay their owners.
Employees are depressed and broke.
The novel portrays employees as broke and sad. The author degrades workers.
I've owned and worked for a business. I was broke and miserable as a business owner, working 80 hours a week for absolutely little salary. I work 50 hours a week and make over $200,000 a year. My work is hard, intriguing, and I'm surrounded by educated individuals. Self-employed or employee?
Don't listen to a charlatan's tax advice.
From a bad advise perspective, Robert's tax methods were funny. Robert suggests forming a corporation to write off holidays as board meetings or health club costs as business expenses. These actions can land you in serious tax trouble.
Robert dismisses college and traditional schooling. Rich individuals learn by doing or living, while educated people are agitated and destitute, says Robert.
Rich dad says:
“All too often business schools train employees to become sophisticated bean-counters. Heaven forbid a bean counter takes over a business. All they do is look at the numbers, fire people, and kill the business.”
And then says:
“Accounting is possibly the most confusing, boring subject in the world, but if you want to be rich long-term, it could be the most important subject.”
Get rich by avoiding paying your debts to others.
While this book has plenty of bad advice, I'll end with this: Robert advocates paying yourself first. This man's work with Trump isn't surprising.
Rich Dad's book says:
“So you see, after paying myself, the pressure to pay my taxes and the other creditors is so great that it forces me to seek other forms of income. The pressure to pay becomes my motivation. I’ve worked extra jobs, started other companies, traded in the stock market, anything just to make sure those guys don’t start yelling at me […] If I had paid myself last, I would have felt no pressure, but I’d be broke.“
Paying yourself first shouldn't mean ignoring debt, damaging your credit score and reputation, or paying unneeded fees and interest. Good business owners pay employees, creditors, and other costs first. You can pay yourself after everyone else.
If you follow Robert Kiyosaki's financial and business advice, you might as well follow Donald Trump's, the most notoriously ineffective businessman and swindle artist.
This book's popularity is unfortunate. Robert utilized the book's fame to promote paid seminars. At these seminars, he sold more expensive seminars to the gullible. This strategy was utilized by several conmen and Trump University.
It's reasonable that many believed him. It sounded appealing because he was pushing to get rich by thinking like a rich person. Anyway. At a time when most persons addressing wealth development advised early sacrifices (such as eschewing luxury or buying expensive properties), Robert told people to act affluent now and utilize other people's money to construct their fantasy lifestyle. It's exciting and fast.
I often voice my skepticism and scorn for internet gurus now that social media and platforms like Medium make it easier to promote them. Robert Kiyosaki was a guru. Many people still preach his stuff because he was so good at pushing it.

Zuzanna Sieja
3 years ago
In 2022, each data scientist needs to read these 11 books.
Non-technical talents can benefit data scientists in addition to statistics and programming.
As our article 5 Most In-Demand Skills for Data Scientists shows, being business-minded is useful. How can you get such a diverse skill set? We've compiled a list of helpful resources.
Data science, data analysis, programming, and business are covered. Even a few of these books will make you a better data scientist.
Ready? Let’s dive in.
Best books for data scientists
1. The Black Swan
Author: Nassim Taleb
First, a less obvious title. Nassim Nicholas Taleb's seminal series examines uncertainty, probability, risk, and decision-making.
Three characteristics define a black swan event:
It is erratic.
It has a significant impact.
Many times, people try to come up with an explanation that makes it seem more predictable than it actually was.
People formerly believed all swans were white because they'd never seen otherwise. A black swan in Australia shattered their belief.
Taleb uses this incident to illustrate how human thinking mistakes affect decision-making. The book teaches readers to be aware of unpredictability in the ever-changing IT business.
Try multiple tactics and models because you may find the answer.
2. High Output Management
Author: Andrew Grove
Intel's former chairman and CEO provides his insights on developing a global firm in this business book. We think Grove would choose “management” to describe the talent needed to start and run a business.
That's a skill for CEOs, techies, and data scientists. Grove writes on developing productive teams, motivation, real-life business scenarios, and revolutionizing work.
Five lessons:
Every action is a procedure.
Meetings are a medium of work
Manage short-term goals in accordance with long-term strategies.
Mission-oriented teams accelerate while functional teams increase leverage.
Utilize performance evaluations to enhance output.
So — if the above captures your imagination, it’s well worth getting stuck in.
3. The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers
Author: Ben Horowitz
Few realize how difficult it is to run a business, even though many see it as a tremendous opportunity.
Business schools don't teach managers how to handle the toughest difficulties; they're usually on their own. So Ben Horowitz wrote this book.
It gives tips on creating and maintaining a new firm and analyzes the hurdles CEOs face.
Find suggestions on:
create software
Run a business.
Promote a product
Obtain resources
Smart investment
oversee daily operations
This book will help you cope with tough times.
4. Obviously Awesome: How to Nail Product Positioning
Author: April Dunford
Your job as a data scientist is a product. You should be able to sell what you do to clients. Even if your product is great, you must convince them.
How to? April Dunford's advice: Her book explains how to connect with customers by making your offering seem like a secret sauce.
You'll learn:
Select the ideal market for your products.
Connect an audience to the value of your goods right away.
Take use of three positioning philosophies.
Utilize market trends to aid purchasers
5. The Mom test
Author: Rob Fitzpatrick
The Mom Test improves communication. Client conversations are rarely predictable. The book emphasizes one of the most important communication rules: enquire about specific prior behaviors.
Both ways work. If a client has suggestions or demands, listen carefully and ensure everyone understands. The book is packed with client-speaking tips.
6. Introduction to Machine Learning with Python: A Guide for Data Scientists
Authors: Andreas C. Müller, Sarah Guido
Now, technical documents.
This book is for Python-savvy data scientists who wish to learn machine learning. Authors explain how to use algorithms instead of math theory.
Their technique is ideal for developers who wish to study machine learning basics and use cases. Sci-kit-learn, NumPy, SciPy, pandas, and Jupyter Notebook are covered beyond Python.
If you know machine learning or artificial neural networks, skip this.
7. Python Data Science Handbook: Essential Tools for Working with Data
Author: Jake VanderPlas
Data work isn't easy. Data manipulation, transformation, cleansing, and visualization must be exact.
Python is a popular tool. The Python Data Science Handbook explains everything. The book describes how to utilize Pandas, Numpy, Matplotlib, Scikit-Learn, and Jupyter for beginners.
The only thing missing is a way to apply your learnings.
8. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
Author: Wes McKinney
The author leads you through manipulating, processing, cleaning, and analyzing Python datasets using NumPy, Pandas, and IPython.
The book's realistic case studies make it a great resource for Python or scientific computing beginners. Once accomplished, you'll uncover online analytics, finance, social science, and economics solutions.
9. Data Science from Scratch
Author: Joel Grus
Here's a title for data scientists with Python, stats, maths, and algebra skills (alongside a grasp of algorithms and machine learning). You'll learn data science's essential libraries, frameworks, modules, and toolkits.
The author works through all the key principles, providing you with the practical abilities to develop simple code. The book is appropriate for intermediate programmers interested in data science and machine learning.
Not that prior knowledge is required. The writing style matches all experience levels, but understanding will help you absorb more.
10. Machine Learning Yearning
Author: Andrew Ng
Andrew Ng is a machine learning expert. Co-founded and teaches at Stanford. This free book shows you how to structure an ML project, including recognizing mistakes and building in complex contexts.
The book delivers knowledge and teaches how to apply it, so you'll know how to:
Determine the optimal course of action for your ML project.
Create software that is more effective than people.
Recognize when to use end-to-end, transfer, and multi-task learning, and how to do so.
Identifying machine learning system flaws
Ng writes easy-to-read books. No rigorous math theory; just a terrific approach to understanding how to make technical machine learning decisions.
11. Deep Learning with PyTorch Step-by-Step
Author: Daniel Voigt Godoy
The last title is also the most recent. The book was revised on 23 January 2022 to discuss Deep Learning and PyTorch, a Python coding tool.
It comprises four parts:
Fundamentals (gradient descent, training linear and logistic regressions in PyTorch)
Machine Learning (deeper models and activation functions, convolutions, transfer learning, initialization schemes)
Sequences (RNN, GRU, LSTM, seq2seq models, attention, self-attention, transformers)
Automatic Language Recognition (tokenization, embeddings, contextual word embeddings, ELMo, BERT, GPT-2)
We admire the book's readability. The author avoids difficult mathematical concepts, making the material feel like a conversation.
Is every data scientist a humanist?
Even as a technological professional, you can't escape human interaction, especially with clients.
We hope these books will help you develop interpersonal skills.

M.G. Siegler
3 years ago
G3nerative
Generative AI hype: some thoughts
The sudden surge in "generative AI" startups and projects feels like the inverse of the recent "web3" boom. Both came from hyped-up pots. But while web3 hyped idealistic tech and an easy way to make money, generative AI hypes unsettling tech and questions whether it can be used to make money.
Web3 is technology looking for problems to solve, while generative AI is technology creating almost too many solutions. Web3 has been evangelists trying to solve old problems with new technology. As Generative AI evolves, users are resolving old problems in stunning new ways.
It's a jab at web3, but it's true. Web3's hype, including crypto, was unhealthy. Always expected a tech crash and shakeout. Tech that won't look like "web3" but will enhance "web2"
But that doesn't mean AI hype is healthy. There'll be plenty of bullshit here, too. As moths to a flame, hype attracts charlatans. Again, the difference is the different starting point. People want to use it. Try it.
With the beta launch of Dall-E 2 earlier this year, a new class of consumer product took off. Midjourney followed suit (despite having to jump through the Discord server hoops). Twelve more generative art projects. Lensa, Prisma Labs' generative AI self-portrait project, may have topped the hype (a startup which has actually been going after this general space for quite a while). This week, ChatGPT went off-topic.
This has a "fake-it-till-you-make-it" vibe. We give these projects too much credit because they create easy illusions. This also unlocks new forms of creativity. And faith in new possibilities.
As a user, it's thrilling. We're just getting started. These projects are not only fun to play with, but each week brings a new breakthrough. As an investor, it's all happening so fast, with so much hype (and ethical and societal questions), that no one knows how it will turn out. Web3's demand won't be the issue. Too much demand may cause servers to melt down, sending costs soaring. Companies will try to mix rapidly evolving tech to meet user demand and create businesses. Frustratingly difficult.
Anyway, I wanted an excuse to post some Lensa selfies.
These are really weird. I recognize them as me or a version of me, but I have no memory of them being taken. It's surreal, out-of-body. Uncanny Valley.
