More on Marketing

Victoria Kurichenko
3 years ago
What Happened After I Posted an AI-Generated Post on My Website
This could cost you.
Content creators may have heard about Google's "Helpful content upgrade."
This change is another Google effort to remove low-quality, repetitive, and AI-generated content.
Why should content creators care?
Because too much content manipulates search results.
My experience includes the following.
Website admins seek high-quality guest posts from me. They send me AI-generated text after I say "yes." My readers are irrelevant. Backlinks are needed.
Companies copy high-ranking content to boost their Google rankings. Unfortunately, it's common.
What does this content offer?
Nothing.
Despite Google's updates and efforts to clean search results, webmasters create manipulative content.
As a marketer, I knew about AI-powered content generation tools. However, I've never tried them.
I use old-fashioned content creation methods to grow my website from 0 to 3,000 monthly views in one year.
Last year, I launched a niche website.
I do keyword research, analyze search intent and competitors' content, write an article, proofread it, and then optimize it.
This strategy is time-consuming.
But it yields results!
Here's proof from Google Analytics:
Proven strategies yield promising results.
To validate my assumptions and find new strategies, I run many experiments.
I tested an AI-powered content generator.
I used a tool to write this Google-optimized article about SEO for startups.
I wanted to analyze AI-generated content's Google performance.
Here are the outcomes of my test.
First, quality.
I dislike "meh" content. I expect articles to answer my questions. If not, I've wasted my time.
My essays usually include research, personal anecdotes, and what I accomplished and achieved.
AI-generated articles aren't as good because they lack individuality.
Read my AI-generated article about startup SEO to see what I mean.
It's dry and shallow, IMO.
It seems robotic.
I'd use quotes and personal experience to show how SEO for startups is different.
My article paraphrases top-ranked articles on a certain topic.
It's readable but useless. Similar articles abound online. Why read it?
AI-generated content is low-quality.
Let me show you how this content ranks on Google.
The Google Search Console report shows impressions, clicks, and average position.
Low numbers.
No one opens the 5th Google search result page to read the article. Too far!
You may say the new article will improve.
Marketing-wise, I doubt it.
This article is shorter and less comprehensive than top-ranking pages. It's unlikely to win because of this.
AI-generated content's terrible reality.
I'll compare how this content I wrote for readers and SEO performs.
Both the AI and my article are fresh, but trends are emerging.
My article's CTR and average position are higher.
I spent a week researching and producing that piece, unlike AI-generated content. My expert perspective and unique consequences make it interesting to read.
Human-made.
In summary
No content generator can duplicate a human's tone, writing style, or creativity. Artificial content is always inferior.
Not "bad," but inferior.
Demand for content production tools will rise despite Google's efforts to eradicate thin content.
Most won't spend hours producing link-building articles. Costly.
As guest and sponsored posts, artificial content will thrive.
Before accepting a new arrangement, content creators and website owners should consider this.

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!

Joseph Mavericks
3 years ago
You Don't Have to Spend $250 on TikTok Ads Because I Did
900K impressions, 8K clicks, and $$$ orders…
I recently started dropshipping. Now that I own my business and can charge it as a business expense, it feels less like money wasted if it doesn't work. I also made t-shirts to sell. I intended to open a t-shirt store and had many designs on a hard drive. I read that Tiktok advertising had a high conversion rate and low cost because they were new. According to many, the advertising' cost/efficiency ratio would plummet and become as bad as Google or Facebook Ads. Now felt like the moment to try Tiktok marketing and dropshipping. I work in marketing for a SaaS firm and have seen how poorly ads perform. I wanted to try it alone.
I set up $250 and ran advertising for a week. Before that, I made my own products, store, and marketing. In this post, I'll show you my process and results.
Setting up the store
Dropshipping is a sort of retail business in which the manufacturer ships the product directly to the client through an online platform maintained by a seller. The seller takes orders but has no stock. The manufacturer handles all orders. This no-stock concept increases profitability and flexibility.
In my situation, I used previous t-shirt designs to make my own product. I didn't want to handle order fulfillment logistics, so I looked for a way to print my designs on demand, ship them, and handle order tracking/returns automatically. So I found Printful.
I needed to connect my backend and supplier to a storefront so visitors could buy. 99% of dropshippers use Shopify, but I didn't want to master the difficult application. I wanted a one-day project. I'd previously worked with Big Cartel, so I chose them.
Big Cartel doesn't collect commissions on sales, simply a monthly flat price ($9.99 to $19.99 depending on your plan).
After opening a Big Cartel account, I uploaded 21 designs and product shots, then synced each product with Printful.
Developing the ads
I mocked up my designs on cool people photographs from placeit.net, a great tool for creating product visuals when you don't have a studio, camera gear, or models to wear your t-shirts.
I opened an account on the website and had advertising visuals within 2 hours.
Because my designs are simple (black design on white t-shirt), I chose happy, stylish people on plain-colored backdrops. After that, I had to develop an animated slideshow.
Because I'm a graphic designer, I chose to use Adobe Premiere to create animated Tiktok advertising.
Premiere is a fancy video editing application used for more than advertisements. Premiere is used to edit movies, not social media marketing. I wanted this experiment to be quick, so I got 3 social media ad templates from motionarray.com and threw my visuals in. All the transitions and animations were pre-made in the files, so it only took a few hours to compile. The result:
I downloaded 3 different soundtracks for the videos to determine which would convert best.
After that, I opened a Tiktok business account, uploaded my films, and inserted ad info. They went live within one hour.
The (poor) outcomes
As a European company, I couldn't deliver ads in the US. All of my advertisements' material (title, description, and call to action) was in English, hence they continued getting rejected in Europe for countries that didn't speak English. There are a lot of them:
I lost a lot of quality traffic, but I felt that if the images were engaging, people would check out the store and buy my t-shirts. I was wrong.
51,071 impressions on Day 1. 0 orders after 411 clicks
114,053 impressions on Day 2. 1.004 clicks and no orders
Day 3: 987 clicks, 103,685 impressions, and 0 orders
101,437 impressions on Day 4. 0 orders after 963 clicks
115,053 impressions on Day 5. 1,050 clicks and no purchases
125,799 impressions on day 6. 1,184 clicks, no purchases
115,547 impressions on Day 7. 1,050 clicks and no purchases
121,456 impressions on day 8. 1,083 clicks, no purchases
47,586 impressions on Day 9. 419 Clicks. No orders
My overall conversion rate for video advertisements was 0.9%. TikTok's paid ad formats all result in strong engagement rates (ads average 3% to 12% CTR to site), therefore a 1 to 2% CTR should have been doable.
My one-week experiment yielded 8,151 ad clicks but no sales. Even if 0.1% of those clicks converted, I should have made 8 sales. Even companies with horrible web marketing would get one download or trial sign-up for every 8,151 clicks. I knew that because my advertising were in English, I had no impressions in the main EU markets (France, Spain, Italy, Germany), and that this impacted my conversion potential. I still couldn't believe my numbers.
I dug into the statistics and found that Tiktok's stats didn't match my store traffic data.
Looking more closely at the numbers
My ads were approved on April 26 but didn't appear until April 27. My store dashboard showed 440 visitors but 1,004 clicks on Tiktok. This happens often while tracking campaign results since different platforms handle comparable user activities (click, view) differently. In online marketing, residual data won't always match across tools.
My data gap was too large. Even if half of the 1,004 persons who clicked closed their browser or left before the store site loaded, I would have gained 502 visitors. The significant difference between Tiktok clicks and Big Cartel store visits made me suspicious. It happened all week:
Day 1: 440 store visits and 1004 ad clicks
Day 2: 482 store visits, 987 ad clicks
3rd day: 963 hits on ads, 452 store visits
443 store visits and 1,050 ad clicks on day 4.
Day 5: 459 store visits and 1,184 ad clicks
Day 6: 430 store visits and 1,050 ad clicks
Day 7: 409 store visits and 1,031 ad clicks
Day 8: 166 store visits and 418 ad clicks
The disparity wasn't related to residual data or data processing. The disparity between visits and clicks looked regular, but I couldn't explain it.
After the campaign concluded, I discovered all my creative assets (the videos) had a 0% CTR and a $0 expenditure in a separate dashboard. Whether it's a dashboard reporting issue or a budget allocation bug, online marketers shouldn't see this.
Tiktok can present any stats they want on their dashboard, just like any other platform that runs advertisements to promote content to its users. I can't verify that 895,687 individuals saw and clicked on my ad. I invested $200 for what appears to be around 900K impressions, which is an excellent ROI. No one bought a t-shirt, even an unattractive one, out of 900K people?
Would I do it again?
Nope. Whether I didn't make sales because Tiktok inflated the dashboard numbers or because I'm horrible at producing advertising and items that sell, I’ll stick to writing content and making videos. If setting up a business and ads in a few days was all it took to make money online, everyone would do it.
Video advertisements and dropshipping aren't dead. As long as the internet exists, people will click ads and buy stuff. Converting ads and selling stuff takes a lot of work, and I want to focus on other things.
I had always wanted to try dropshipping and I’m happy I did, I just won’t stick to it because that’s not something I’m interested in getting better at.
If I want to sell t-shirts again, I'll avoid Tiktok advertisements and find another route.
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Vitalik
3 years ago
An approximate introduction to how zk-SNARKs are possible (part 1)
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has 2 very powerful applications: Perhaps the most powerful cryptographic technology to come out of the last decade is general-purpose succinct zero knowledge proofs, usually called zk-SNARKs ("zero knowledge succinct arguments of knowledge"). A zk-SNARK allows you to generate a proof that some computation has some particular output, in such a way that the proof can be verified extremely quickly even if the underlying computation takes a very long time to run. The "ZK" part adds an additional feature: the proof can keep some of the inputs to the computation hidden.
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has two very powerful applications:
- Scalability: if a block takes a long time to verify, one person can verify it and generate a proof, and everyone else can just quickly verify the proof instead
- Privacy: you can prove that you have the right to transfer some asset (you received it, and you didn't already transfer it) without revealing the link to which asset you received. This ensures security without unduly leaking information about who is transacting with whom to the public.
But zk-SNARKs are quite complex; indeed, as recently as in 2014-17 they were still frequently called "moon math". The good news is that since then, the protocols have become simpler and our understanding of them has become much better. This post will try to explain how ZK-SNARKs work, in a way that should be understandable to someone with a medium level of understanding of mathematics.
Why ZK-SNARKs "should" be hard
Let us take the example that we started with: we have a number (we can encode "cow" followed by the secret input as an integer), we take the SHA256 hash of that number, then we do that again another 99,999,999 times, we get the output, and we check what its starting digits are. This is a huge computation.
A "succinct" proof is one where both the size of the proof and the time required to verify it grow much more slowly than the computation to be verified. If we want a "succinct" proof, we cannot require the verifier to do some work per round of hashing (because then the verification time would be proportional to the computation). Instead, the verifier must somehow check the whole computation without peeking into each individual piece of the computation.
One natural technique is random sampling: how about we just have the verifier peek into the computation in 500 different places, check that those parts are correct, and if all 500 checks pass then assume that the rest of the computation must with high probability be fine, too?
Such a procedure could even be turned into a non-interactive proof using the Fiat-Shamir heuristic: the prover computes a Merkle root of the computation, uses the Merkle root to pseudorandomly choose 500 indices, and provides the 500 corresponding Merkle branches of the data. The key idea is that the prover does not know which branches they will need to reveal until they have already "committed to" the data. If a malicious prover tries to fudge the data after learning which indices are going to be checked, that would change the Merkle root, which would result in a new set of random indices, which would require fudging the data again... trapping the malicious prover in an endless cycle.
But unfortunately there is a fatal flaw in naively applying random sampling to spot-check a computation in this way: computation is inherently fragile. If a malicious prover flips one bit somewhere in the middle of a computation, they can make it give a completely different result, and a random sampling verifier would almost never find out.
It only takes one deliberately inserted error, that a random check would almost never catch, to make a computation give a completely incorrect result.
If tasked with the problem of coming up with a zk-SNARK protocol, many people would make their way to this point and then get stuck and give up. How can a verifier possibly check every single piece of the computation, without looking at each piece of the computation individually? There is a clever solution.
see part 2

Jon Brosio
3 years ago
Every time I use this 6-part email sequence, I almost always make four figures.
(And you can have it for free)
Master email to sell anything.
Most novice creators don't know how to begin.
Many use online templates. These are usually fluff-filled and niche-specific.
They're robotic and "salesy."
I've attended 3 courses, read 10 books, and sent 600,000 emails in the past five years.
Outcome?
This *proven* email sequence assures me a month's salary every time I send it.
What you will discover in this article is that:
A full 6-part email sales cycle
The essential elements you must incorporate
placeholders and text-filled images
(Applies to any niche)
This can be a product introduction, holiday, or welcome sequence. This works for email-saleable products.
Let's start
Email 1: Describe your issue
This email is crucial.
How to? We introduce a subscriber or prospect's problem. Later, we'll frame our offer as the solution.
Label the:
Problem
Why it still hasn't been fixed
Resulting implications for the customer
This puts our new subscriber in solve mode and queues our offer:
Email 2: Amplify the consequences
We're still causing problems.
We've created the problem, but now we must employ emotion and storytelling to make it real. We also want to forecast life if nothing changes.
Let's feel:
What occurs if it is not resolved?
Why is it crucial to fix it immediately?
Tell a tale of a person who was in their position. To emphasize the effects, use a true account of another person (or of yourself):
Email 3: Share a transformation story
Selling stories.
Whether in an email, landing page, article, or video. Humanize stories. They give information meaning.
This is where "issue" becomes "solution."
Let's reveal:
A tale of success
A new existence and result
tools and tactics employed
Start by transforming yourself.
Email 4: Prove with testimonials
No one buys what you say.
Emotionally stirred people buy and act. They believe in the product. They feel that if they buy, it will work.
Social proof shows prospects that your solution will help them.
Add:
Earlier and Later
Testimonials
Reviews
Proof this deal works:
Email 5: Reveal your offer
It's showtime.
This is it. Until now, describing the offer and offering links to a landing page have been sparse in the email pictures.
We've been tense. Gaining steam. Building suspense. Email 5 reveals all.
In this email:
a description of the deal
A word about a promise
recapitulation of the transformation
and make a reference to the urgency Everything should be spelled out clearly:
Email no. 6: Instill urgency
When there are stakes, humans act.
Creating and marketing with haste raises the stakes. Urgency makes a prospect act because they'll miss out or gain immensely.
Urgency converts. Use:
short time
Screening
Scarcity
Urgency and conversions. Limited-time offers are easy.
TL;DR
Use this proven 6-part email sequence (that turns subscribers into profit):
Introduce a problem
Amplify it with emotions
Share transformation story
Prove it works with testimonials
Value-stack and present your offer
Drive urgency and entice the purchase

Nick Babich
2 years ago
Is ChatGPT Capable of Generating a Complete Mobile App?
TL;DR: It'll be harder than you think.
Mobile app development is a complicated product design sector. You require broad expertise to create a mobile app. You must write Swift or Java code and consider mobile interactions.
When ChatGPT was released, many were amazed by its capabilities and wondered if it could replace designers and developers. This article will use ChatGPT to answer a specific query.
Can ChatGPT build an entire iOS app?
This post will use ChatGPT to construct an iOS meditation app. Video of the article is available.
App concepts for meditation
After deciding on an app, think about the user experience. What should the app offer?
Let's ask ChatGPT for the answer.
ChatGPT described a solid meditation app with various exercises. Use this list to plan product design. Our first product iteration will have few features. A simple, one-screen software will let users set the timeframe and play music during meditation.
Structure of information
Information architecture underpins product design. Our app's navigation mechanism should be founded on strong information architecture, so we need to identify our mobile's screens first.
ChatGPT can define our future app's information architecture since we already know it.
ChatGPT uses the more complicated product's structure. When adding features to future versions of our product, keep this information picture in mind.
Color palette
Meditation apps need colors. We want to employ relaxing colors in a meditation app because colors affect how we perceive items. ChatGPT can suggest product colors.
See the hues in person:
Neutral colors dominate the color scheme. Playing with color opacity makes this scheme useful.
Ambiance music
Meditation involves music. Well-chosen music calms the user.
Let ChatGPT make music for us.
ChatGPT can only generate text. It directs us to Spotify or YouTube to look for such stuff and makes precise recommendations.
Fonts
Fonts can impress app users. Round fonts are easier on the eyes and make a meditation app look friendlier.
ChatGPT can suggest app typefaces. I compare two font pairs when making a product. I'll ask ChatGPT for two font pairs.
See the hues in person:
Despite ChatGPT's convincing font pairing arguments, the output is unattractive. The initial combo (Open Sans + Playfair Display) doesn't seem to work well for a mediation app.
Content
Meditation requires the script. Find the correct words and read them calmly and soothingly to help listeners relax and focus on each region of their body to enhance the exercise's effect.
ChatGPT's offerings:
ChatGPT outputs code. My prompt's word script may cause it.
Timer
After fonts, colors, and content, construct functional pieces. Timer is our first functional piece. The meditation will be timed.
Let ChatGPT write Swift timer code (since were building an iOS app, we need to do it using Swift language).
ChatGPT supplied a timer class, initializer, and usage guidelines.
Apple Xcode requires a playground to test this code. Xcode will report issues after we paste the code to the playground.
Fixing them is simple. Just change Timer to another class name (Xcode shows errors because it thinks that we access the properties of the class we’ve created rather than the system class Timer; it happens because both classes have the same name Timer). I titled our class Timero and implemented the project. After this quick patch, ChatGPT's code works.
Can ChatGPT produce a complete app?
Since ChatGPT can help us construct app components, we may question if it can write a full app in one go.
Question ChatGPT:
ChatGPT supplied basic code and instructions. It's unclear if ChatGPT purposely limits output or if my prompt wasn't good enough, but the tool cannot produce an entire app from a single prompt.
However, we can contact ChatGPT for thorough Swift app construction instructions.
We can ask ChatGPT for step-by-step instructions now that we know what to do. Request a basic app layout from ChatGPT.
Copying this code to an Xcode project generates a functioning layout.
Takeaways
ChatGPT may provide step-by-step instructions on how to develop an app for a specific system, and individual steps can be utilized as prompts to ChatGPT. ChatGPT cannot generate the source code for the full program in one go.
The output that ChatGPT produces needs to be examined by a human. The majority of the time, you will need to polish or adjust ChatGPT's output, whether you develop a color scheme or a layout for the iOS app.
ChatGPT is unable to produce media material. Although ChatGPT cannot be used to produce images or sounds, it can assist you build prompts for programs like midjourney or Dalle-2 so that they can provide the appropriate images for you.
