More on Marketing

Shruti Mishra
3 years ago
How to get 100k profile visits on Twitter each month without spending a dime
As a marketer, I joined Twitter on August 31, 2022 to use it.
Growth has been volatile, causing up-and-down engagements. 500 followers in 11 days.
I met amazing content creators, marketers, and people.
Those who use Twitter may know that one-liners win the algorithm, especially if they're funny or humorous, but as a marketer I can't risk posting content that my audience won't like.
I researched, learned some strategies, and A/B tested; some worked, some didn't.
In this article, I share what worked for me so you can do the same.
Thanks for reading!
Let's check my Twitter stats.
Tweets: how many tweets I sent in the first 28 days.
A user may be presented with a Tweet in their timeline or in search results.
In-person visits how many times my Twitter profile was viewed in the first 28 days.
Mentions: the number of times a tweet has mentioned my name.
Number of followers: People who were following me
Getting 500 Twitter followers isn't difficult.
Not easy, but doable.
Follow these steps to begin:
Determine your content pillars in step 1.
My formula is Growth = Content + Marketing + Community.
I discuss growth strategies.
My concept for growth is : 1. Content = creating / writing + sharing content in my niche. 2. Marketing = Marketing everything in business + I share my everyday learnings in business, marketing & entrepreneurship. 3. Community = Building community of like minded individuals (Also,I share how to’s) + supporting marketers to build & grow through community building.
Identify content pillars to create content for your audience.
2. Make your profile better
Create a profile picture. Your recognition factor is this.
Professional headshots are worthwhile.
This tool can help you create a free, eye-catching profile pic.
Use a niche-appropriate avatar if you don't want to show your face.
2. Create a bio that converts well mainly because first impressions count.
what you're sharing + why + +social proof what are you making
Be brief and precise. (155 characters)
3. Configure your banner
Banners complement profile pictures.
Use this space to explain what you do and how Twitter followers can benefit.
Canva's Twitter header maker is free.
Birdy can test multiple photo, bio, and banner combinations to optimize your profile.
Versions A and B of your profile should be completed.
Find the version that converts the best.
Use the profile that converts the best.
4. Special handle
If your username/handle is related to your niche, it will help you build authority and presence among your audience. Mine on Twitter is @marketershruti.
5. Participate expertly
Proficiently engage while you'll have no audience at first. Borrow your dream audience for free.
Steps:
Find a creator who has the audience you want.
Activate their post notifications and follow them.
Add a valuable comment first.
6. Create fantastic content
Use:
Medium (Read articles about your topic.)
Podcasts (Listen to experts on your topics)
YouTube (Follow channels in your niche)
Tweet what?
Listicle ( Hacks, Books, Tools, Podcasts)
Lessons (Teach your audience how to do 1 thing)
Inspirational (Inspire people to take action)
Consistent writing?
You MUST plan ahead and schedule your Tweets.
Use a scheduling tool that is effective for you; hypefury is mine.
Lastly, consistency is everything that attracts growth. After optimizing your profile, stay active to gain followers, engagements, and clients.
If you found this helpful, please like and comment below.

Yucel F. Sahan
3 years ago
How I Created the Day's Top Product on Product Hunt
In this article, I'll describe a weekend project I started to make something. It was Product Hunt's #1 of the Day, #2 Weekly, and #4 Monthly product.
How did I make Landing Page Checklist so simple? Building and launching took 3 weeks. I worked 3 hours a day max. Weekends were busy.
It's sort of a long story, so scroll to the bottom of the page to see what tools I utilized to create Landing Page Checklist :x
As a matter of fact, it all started with the startups-investments blog; Startup Bulletin, that I started writing in 2018. No, don’t worry, I won’t be going that far behind. The twitter account where I shared the blog posts of this newsletter was inactive for a looong time. I was holding this Twitter account since 2009, I couldn’t bear to destroy it. At the same time, I was thinking how to evaluate this account.
So I looked for a weekend assignment.
Weekend undertaking: Generate business names
Barash and I established a weekend effort to stay current. Building things helped us learn faster.
Simple. Startup Name Generator The utility generated random startup names. After market research for SEO purposes, we dubbed it Business Name Generator.
Backend developer Barash dislikes frontend work. He told me to write frontend code. Chakra UI and Tailwind CSS were recommended.
It was the first time I have heard about Tailwind CSS.
Before this project, I made mobile-web app designs in Sketch and shared them via Zeplin. I can read HTML-CSS or React code, but not write it. I didn't believe myself but followed Barash's advice.
My home page wasn't responsive when I started. Here it was:)
And then... Product Hunt had something I needed. Me-only! A website builder that gives you clean Tailwind CSS code and pre-made web components (like Elementor). Incredible.
I bought it right away because it was so easy to use. Best part: It's not just index.html. It includes all needed files. Like
postcss.config.js
README.md
package.json
among other things, tailwind.config.js
This is for non-techies.
Tailwind.build; which is Shuffle now, allows you to create and export projects for free (with limited features). You can try it by visiting their website.
After downloading the project, you can edit the text and graphics in Visual Studio (or another text editor). This HTML file can be hosted whenever.
Github is an easy way to host a landing page.
your project via Shuffle for export
your website's content, edit
Create a Gitlab, Github, or Bitbucket account.
to Github, upload your project folder.
Integrate Vercel with your Github account (or another platform below)
Allow them to guide you in steps.
Finally. If you push your code to Github using Github Desktop, you'll do it quickly and easily.
Speaking of; here are some hosting and serverless backend services for web applications and static websites for you host your landing pages for FREE!
I host landingpage.fyi on Vercel but all is fine. You can choose any platform below with peace in mind.
Vercel
Render
Netlify
After connecting your project/repo to Vercel, you don’t have to do anything on Vercel. Vercel updates your live website when you update Github Desktop. Wow!
Tails came out while I was using tailwind.build. Although it's prettier, tailwind.build is more mobile-friendly. I couldn't resist their lovely parts. Tails :)
Tails have several well-designed parts. Some components looked awful on mobile, but this bug helped me understand Tailwind CSS.
Unlike Shuffle, Tails does not include files when you export such as config.js, main.js, README.md. It just gives you the HTML code. Suffle.dev is a bit ahead in this regard and with mobile-friendly blocks if you ask me. Of course, I took advantage of both.
creativebusinessnames.co is inactive, but I'll leave a deployment link :)
Adam Wathan's YouTube videos and Tailwind's official literature helped me, but I couldn't have done it without Tails and Shuffle. These tools helped me make landing pages. I shouldn't have started over.
So began my Tailwind CSS adventure. I didn't build landingpage. I didn't plan it to be this long; sorry.
I learnt a lot while I was playing around with Shuffle and Tails Builders.
Long story short I built landingpage.fyi with the help of these tools;
Learning, building, and distribution
Shuffle (Started with a Shuffle Template)
Tails (Used components from here)
Sketch (to handle icons, logos, and .svg’s)
metatags.io (Auto Generator Meta Tags)
Vercel (Hosting)
Github Desktop (Pushing code to Github -super easy-)
Visual Studio Code (Edit my code)
Mailerlite (Capture Emails)
Jarvis / Conversion.ai (%90 of the text on website written by AI 😇 )
CookieHub (Consent Management)
That's all. A few things:
The Outcome
.fyi Domain: Why?
I'm often asked this.
I don't know, but I wanted to include the landing page term. Popular TLDs are gone. I saw my alternatives. brief and catchy.
CSS Tailwind Resources
I'll share project resources like Tails and Shuffle.
Beginner Tailwind (I lately enrolled in this course but haven’t completed it yet.)
Thanks for reading my blog's first post. Please share if you like it.

Jon Brosio
3 years ago
You can learn more about marketing from these 8 copywriting frameworks than from a college education.
Email, landing pages, and digital content
Today's most significant skill:
Copywriting.
Unfortunately, most people don't know how to write successful copy because they weren't taught in school.
I've been obsessed with copywriting for two years. I've read 15 books, completed 3 courses, and studied internet's best digital entrepreneurs.
Here are 8 copywriting frameworks that educate more than a four-year degree.
1. Feature — Advantage — Benefit (F.A.B)
This is the most basic copywriting foundation. Email marketing, landing page copy, and digital video ads can use it.
F.A.B says:
How it works (feature)
which is helpful (advantage)
What's at stake (benefit)
The Hustle uses this framework on their landing page to convince people to sign up:
2. P. A. S. T. O. R.
This framework is for longer-form copywriting. PASTOR uses stories to engage with prospects. It explains why people should buy this offer.
PASTOR means:
Problem
Amplify
Story
Testimonial
Offer
Response
Dan Koe's landing page is a great example. It shows PASTOR frame-by-frame.
3. Before — After — Bridge
Before-after-bridge is a copywriting framework that draws attention and shows value quickly.
This framework highlights:
where you are
where you want to be
how to get there
Works great for: Email threads/landing pages
Zain Kahn utilizes this framework to write viral threads.
4. Q.U.E.S.T
QUEST is about empathetic writing. You know their issues, obstacles, and headaches. This allows coverups.
QUEST:
Qualifies
Understands
Educates
Stimulates
Transitions
Tom Hirst's landing page uses the QUEST framework.
5. The 4P’s model
The 4P’s approach pushes your prospect to action. It educates and persuades quickly.
4Ps:
The problem the visitor is dealing with
The promise that will help them
The proof the promise works
A push towards action
Mark Manson is a bestselling author, digital creator, and pop-philosopher. He's also a great copywriter, and his membership offer uses the 4P’s framework.
6. Problem — Agitate — Solution (P.A.S)
Up-and-coming marketers should understand problem-agitate-solution copywriting. Once you understand one structure, others are easier. It drives passion and presents a clear solution.
PAS outlines:
The issue the visitor is having
It then intensifies this issue through emotion.
finally offers an answer to that issue (the offer)
The customer's story loops. Nicolas Cole and Dickie Bush use PAS to promote Ship 30 for 30.
7. Star — Story — Solution (S.S.S)
PASTOR + PAS = star-solution-story. Like PAS, it employs stories to persuade.
S.S.S. is effective storytelling:
Star: (Person had a problem)
Story: (until they had a breakthrough)
Solution: (That created a transformation)
Ali Abdaal is a YouTuber with a great S.S.S copy.
8. Attention — Interest — Desire — Action
AIDA is another classic. This copywriting framework is great for fast-paced environments (think all digital content on Linkedin, Twitter, Medium, etc.).
It works with:
Page landings
writing on thread
Email
It's a good structure since it's concise, attention-grabbing, and action-oriented.
Shane Martin, Twitter's creator, uses this approach to create viral content.
TL;DR
8 copywriting frameworks that teach marketing better than a four-year degree
Feature-advantage-benefit
Before-after-bridge
Star-story-solution
P.A.S.T.O.R
Q.U.E.S.T
A.I.D.A
P.A.S
4P’s
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Paul DelSignore
2 years ago
The stunning new free AI image tool is called Leonardo AI.
Leonardo—The New Midjourney?
Users are comparing the new cowboy to Midjourney.
Leonardo.AI creates great photographs and has several unique capabilities I haven't seen in other AI image systems.
Midjourney's quality photographs are evident in the community feed.
Create Pictures Using Models
You can make graphics using platform models when you first enter the app (website):
Luma, Leonardo creative, Deliberate 1.1.
Clicking a model displays its description and samples:
Click Generate With This Model.
Then you can add your prompt, alter models, photos, sizes, and guide scale in a sleek UI.
Changing Pictures
Leonardo's Canvas editor lets you change created images by hovering over them:
The editor opens with masking, erasing, and picture download.
Develop Your Own Models
I've never seen anything like Leonardo's model training feature.
Upload a handful of similar photographs and save them as a model for future images. Share your model with the community.
You can make photos using your own model and a community-shared set of fine-tuned models:
Obtain Leonardo access
Leonardo is currently free.
Visit Leonardo.ai and click "Get Early Access" to receive access.
Add your email to receive a link to join the discord channel. Simply describe yourself and fill out a form to join the discord channel.
Please go to 👑│introductions to make an introduction and ✨│priority-early-access will be unlocked, you must fill out a form and in 24 hours or a little more (due to demand), the invitation will be sent to you by email.
I got access in two hours, so hopefully you can too.
Last Words
I know there are many AI generative platforms, some free and some expensive, but Midjourney produces the most artistically stunning images and art.
Leonardo is the closest I've seen to Midjourney, but Midjourney is still the leader.
It's free now.
Leonardo's fine-tuned model selections, model creation, image manipulation, and output speed and quality make it a great AI image toolbox addition.

mbvissers.eth
3 years ago
Why does every smart contract seem to implement ERC165?
ERC165 (or EIP-165) is a standard utilized by various open-source smart contracts like Open Zeppelin or Aavegotchi.
What's it? You must implement? Why do we need it? I'll describe the standard and answer any queries.
What is ERC165
ERC165 detects and publishes smart contract interfaces. Meaning? It standardizes how interfaces are recognized, how to detect if they implement ERC165, and how a contract publishes the interfaces it implements. How does it work?
Why use ERC165? Sometimes it's useful to know which interfaces a contract implements, and which version.
Identifying interfaces
An interface function's selector. This verifies an ABI function. XORing all function selectors defines an interface in this standard. The following code demonstrates.
// SPDX-License-Identifier: UNLICENCED
pragma solidity >=0.8.0 <0.9.0;
interface Solidity101 {
function hello() external pure;
function world(int) external pure;
}
contract Selector {
function calculateSelector() public pure returns (bytes4) {
Solidity101 i;
return i.hello.selector ^ i.world.selector;
// Returns 0xc6be8b58
}
function getHelloSelector() public pure returns (bytes4) {
Solidity101 i;
return i.hello.selector;
// Returns 0x19ff1d21
}
function getWorldSelector() public pure returns (bytes4) {
Solidity101 i;
return i.world.selector;
// Returns 0xdf419679
}
}This code isn't necessary to understand function selectors and how an interface's selector can be determined from the functions it implements.
Run that sample in Remix to see how interface function modifications affect contract function output.
Contracts publish their implemented interfaces.
We can identify interfaces. Now we must disclose the interfaces we're implementing. First, import IERC165 like so.
pragma solidity ^0.4.20;
interface ERC165 {
/// @notice Query if a contract implements an interface
/// @param interfaceID The interface identifier, as specified in ERC-165
/// @dev Interface identification is specified in ERC-165.
/// @return `true` if the contract implements `interfaceID` and
/// `interfaceID` is not 0xffffffff, `false` otherwise
function supportsInterface(bytes4 interfaceID) external view returns (bool);
}We still need to build this interface in our smart contract. ERC721 from OpenZeppelin is a good example.
// SPDX-License-Identifier: MIT
// OpenZeppelin Contracts (last updated v4.5.0) (token/ERC721/ERC721.sol)
pragma solidity ^0.8.0;
import "./IERC721.sol";
import "./extensions/IERC721Metadata.sol";
import "../../utils/introspection/ERC165.sol";
// ...
contract ERC721 is Context, ERC165, IERC721, IERC721Metadata {
// ...
function supportsInterface(bytes4 interfaceId) public view virtual override(ERC165, IERC165) returns (bool) {
return
interfaceId == type(IERC721).interfaceId ||
interfaceId == type(IERC721Metadata).interfaceId ||
super.supportsInterface(interfaceId);
}
// ...
}I deleted unnecessary code. The smart contract imports ERC165, IERC721 and IERC721Metadata. The is keyword at smart contract declaration implements all three.
Kind (interface).
Note that type(interface).interfaceId returns the same as the interface selector.
We override supportsInterface in the smart contract to return a boolean that checks if interfaceId is the same as one of the implemented contracts.
Super.supportsInterface() calls ERC165 code. Checks if interfaceId is IERC165.
function supportsInterface(bytes4 interfaceId) public view virtual override returns (bool) {
return interfaceId == type(IERC165).interfaceId;
}So, if we run supportsInterface with an interfaceId, our contract function returns true if it's implemented and false otherwise. True for IERC721, IERC721Metadata, andIERC165.
Conclusion
I hope this post has helped you understand and use ERC165 and why it's employed.
Have a great day, thanks for reading!

Sofien Kaabar, CFA
2 years ago
Innovative Trading Methods: The Catapult Indicator
Python Volatility-Based Catapult Indicator
As a catapult, this technical indicator uses three systems: Volatility (the fulcrum), Momentum (the propeller), and a Directional Filter (Acting as the support). The goal is to get a signal that predicts volatility acceleration and direction based on historical patterns. We want to know when the market will move. and where. This indicator outperforms standard indicators.
Knowledge must be accessible to everyone. This is why my new publications Contrarian Trading Strategies in Python and Trend Following Strategies in Python now include free PDF copies of my first three books (Therefore, purchasing one of the new books gets you 4 books in total). GitHub-hosted advanced indications and techniques are in the two new books above.
The Foundation: Volatility
The Catapult predicts significant changes with the 21-period Relative Volatility Index.
The Average True Range, Mean Absolute Deviation, and Standard Deviation all assess volatility. Standard Deviation will construct the Relative Volatility Index.
Standard Deviation is the most basic volatility. It underpins descriptive statistics and technical indicators like Bollinger Bands. Before calculating Standard Deviation, let's define Variance.
Variance is the squared deviations from the mean (a dispersion measure). We take the square deviations to compel the distance from the mean to be non-negative, then we take the square root to make the measure have the same units as the mean, comparing apples to apples (mean to standard deviation standard deviation). Variance formula:
As stated, standard deviation is:
# The function to add a number of columns inside an array
def adder(Data, times):
for i in range(1, times + 1):
new_col = np.zeros((len(Data), 1), dtype = float)
Data = np.append(Data, new_col, axis = 1)
return Data
# The function to delete a number of columns starting from an index
def deleter(Data, index, times):
for i in range(1, times + 1):
Data = np.delete(Data, index, axis = 1)
return Data
# The function to delete a number of rows from the beginning
def jump(Data, jump):
Data = Data[jump:, ]
return Data
# Example of adding 3 empty columns to an array
my_ohlc_array = adder(my_ohlc_array, 3)
# Example of deleting the 2 columns after the column indexed at 3
my_ohlc_array = deleter(my_ohlc_array, 3, 2)
# Example of deleting the first 20 rows
my_ohlc_array = jump(my_ohlc_array, 20)
# Remember, OHLC is an abbreviation of Open, High, Low, and Close and it refers to the standard historical data file
def volatility(Data, lookback, what, where):
for i in range(len(Data)):
try:
Data[i, where] = (Data[i - lookback + 1:i + 1, what].std())
except IndexError:
pass
return Data
The RSI is the most popular momentum indicator, and for good reason—it excels in range markets. Its 0–100 range simplifies interpretation. Fame boosts its potential.
The more traders and portfolio managers look at the RSI, the more people will react to its signals, pushing market prices. Technical Analysis is self-fulfilling, therefore this theory is obvious yet unproven.
RSI is determined simply. Start with one-period pricing discrepancies. We must remove each closing price from the previous one. We then divide the smoothed average of positive differences by the smoothed average of negative differences. The RSI algorithm converts the Relative Strength from the last calculation into a value between 0 and 100.
def ma(Data, lookback, close, where):
Data = adder(Data, 1)
for i in range(len(Data)):
try:
Data[i, where] = (Data[i - lookback + 1:i + 1, close].mean())
except IndexError:
pass
# Cleaning
Data = jump(Data, lookback)
return Data
def ema(Data, alpha, lookback, what, where):
alpha = alpha / (lookback + 1.0)
beta = 1 - alpha
# First value is a simple SMA
Data = ma(Data, lookback, what, where)
# Calculating first EMA
Data[lookback + 1, where] = (Data[lookback + 1, what] * alpha) + (Data[lookback, where] * beta)
# Calculating the rest of EMA
for i in range(lookback + 2, len(Data)):
try:
Data[i, where] = (Data[i, what] * alpha) + (Data[i - 1, where] * beta)
except IndexError:
pass
return Datadef rsi(Data, lookback, close, where, width = 1, genre = 'Smoothed'):
# Adding a few columns
Data = adder(Data, 7)
# Calculating Differences
for i in range(len(Data)):
Data[i, where] = Data[i, close] - Data[i - width, close]
# Calculating the Up and Down absolute values
for i in range(len(Data)):
if Data[i, where] > 0:
Data[i, where + 1] = Data[i, where]
elif Data[i, where] < 0:
Data[i, where + 2] = abs(Data[i, where])
# Calculating the Smoothed Moving Average on Up and Down
absolute values
lookback = (lookback * 2) - 1 # From exponential to smoothed
Data = ema(Data, 2, lookback, where + 1, where + 3)
Data = ema(Data, 2, lookback, where + 2, where + 4)
# Calculating the Relative Strength
Data[:, where + 5] = Data[:, where + 3] / Data[:, where + 4]
# Calculate the Relative Strength Index
Data[:, where + 6] = (100 - (100 / (1 + Data[:, where + 5])))
# Cleaning
Data = deleter(Data, where, 6)
Data = jump(Data, lookback)
return Datadef relative_volatility_index(Data, lookback, close, where):
# Calculating Volatility
Data = volatility(Data, lookback, close, where)
# Calculating the RSI on Volatility
Data = rsi(Data, lookback, where, where + 1)
# Cleaning
Data = deleter(Data, where, 1)
return DataThe Arm Section: Speed
The Catapult predicts momentum direction using the 14-period Relative Strength Index.
As a reminder, the RSI ranges from 0 to 100. Two levels give contrarian signals:
A positive response is anticipated when the market is deemed to have gone too far down at the oversold level 30, which is 30.
When the market is deemed to have gone up too much, at overbought level 70, a bearish reaction is to be expected.
Comparing the RSI to 50 is another intriguing use. RSI above 50 indicates bullish momentum, while below 50 indicates negative momentum.
The direction-finding filter in the frame
The Catapult's directional filter uses the 200-period simple moving average to keep us trending. This keeps us sane and increases our odds.
Moving averages confirm and ride trends. Its simplicity and track record of delivering value to analysis make them the most popular technical indicator. They help us locate support and resistance, stops and targets, and the trend. Its versatility makes them essential trading tools.
This is the plain mean, employed in statistics and everywhere else in life. Simply divide the number of observations by their total values. Mathematically, it's:
We defined the moving average function above. Create the Catapult indication now.
Indicator of the Catapult
The indicator is a healthy mix of the three indicators:
The first trigger will be provided by the 21-period Relative Volatility Index, which indicates that there will now be above average volatility and, as a result, it is possible for a directional shift.
If the reading is above 50, the move is likely bullish, and if it is below 50, the move is likely bearish, according to the 14-period Relative Strength Index, which indicates the likelihood of the direction of the move.
The likelihood of the move's direction will be strengthened by the 200-period simple moving average. When the market is above the 200-period moving average, we can infer that bullish pressure is there and that the upward trend will likely continue. Similar to this, if the market falls below the 200-period moving average, we recognize that there is negative pressure and that the downside is quite likely to continue.
lookback_rvi = 21
lookback_rsi = 14
lookback_ma = 200
my_data = ma(my_data, lookback_ma, 3, 4)
my_data = rsi(my_data, lookback_rsi, 3, 5)
my_data = relative_volatility_index(my_data, lookback_rvi, 3, 6)Two-handled overlay indicator Catapult. The first exhibits blue and green arrows for a buy signal, and the second shows blue and red for a sell signal.
The chart below shows recent EURUSD hourly values.
def signal(Data, rvi_col, signal):
Data = adder(Data, 10)
for i in range(len(Data)):
if Data[i, rvi_col] < 30 and \
Data[i - 1, rvi_col] > 30 and \
Data[i - 2, rvi_col] > 30 and \
Data[i - 3, rvi_col] > 30 and \
Data[i - 4, rvi_col] > 30 and \
Data[i - 5, rvi_col] > 30:
Data[i, signal] = 1
return DataSignals are straightforward. The indicator can be utilized with other methods.
my_data = signal(my_data, 6, 7)Lumiwealth shows how to develop all kinds of algorithms. I recommend their hands-on courses in algorithmic trading, blockchain, and machine learning.
Summary
To conclude, my goal is to contribute to objective technical analysis, which promotes more transparent methods and strategies that must be back-tested before implementation. Technical analysis will lose its reputation as subjective and unscientific.
After you find a trading method or approach, follow these steps:
Put emotions aside and adopt an analytical perspective.
Test it in the past in conditions and simulations taken from real life.
Try improving it and performing a forward test if you notice any possibility.
Transaction charges and any slippage simulation should always be included in your tests.
Risk management and position sizing should always be included in your tests.
After checking the aforementioned, monitor the plan because market dynamics may change and render it unprofitable.
