📰 The Solo Founder Newsletter #104

Casper Marketing: 14 Proven Growth Strategies You Need to Steal Below are 14 strategies Casper used to grow their company. Not all of them will be relevant to you. That’s a given. So, to save time, I’ve added a table of contents so you can jump to the strategies that interest you most.

Reinvent The Buying Experience

Create an Unbeatable Guarantee

Answer Your Target Market’s Questions (ToFu)

Create a Go-To Comparison Resource (MoFu)

Showcase All Reviews in One Place (BoFu)

Build White-Hat Education Links with “The CSD Method”

Publish Original Research (and Become a Go-To Authority in Your Marketplace)

Use “The Best-of Backlink Builder” (with a Twist)

Translate Your Ads to Capture New Markets

Try This Little-Known Trick to Monopolize Your Search Ads

Combine Advertising and Remarketing to Get More Leads for Your Online Store

Use This 3-Step Cart Abandonment Process to Recover Lost Sales

Turn Customers into Salespeople with This Replicable Referral Engine

Get Better Customer Reviews with This Simple, Yet Powerful Copy Hack

Ready? Let’s dive in.

Some people think having 1,000, 5,000, 10,000, or even 50,000 subscribers on Telegram is the same as having that many followers on other social networks. They’re wrong.

Here’s why:

Telegram is a messenger, not a social network: People don’t subscribe to hundreds of channels like they follow accounts on social networks. A typical user follows only a few channels.

Quality over quantity: The number of subscribers doesn’t matter as much as their engagement. Even 1,000 engaged subscribers can be profitable.

Channel theme matters: Whether your channel is about entertainment, education, or something niche, the topic plays a huge role in attracting and keeping subscribers.

If I see a lot of subscribers in a Telegram channel, it's a sign that I should check the channel. In 70% of cases, it's a channel with bots.

First Telegram channel I created my first Telegram channel in June 2022. Within a few months, with just over 1,000 subscribers, I started earning money and selling ads because advertisers began reaching out to me.

This channel is in a pretty narrow niche: a Telegram channel for beginner data analysts. In my posts, I share useful content that helps subscribers learn for free, practice skills, find internships and jobs worldwide, and much more.

Monetization Now, the channel has over 15,000 subscribers, and last month I earned about $3,000 from this channel alone.

To monetize this channel, I use sponsored ads. Each ad now costs $250, and I post about 10-12 ads per month, gradually increasing the price. Most of my clients are repeat customers who advertise regularly.

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ChatGPT Content is Mirage Content 2.0

In 2016, I wrote an article called Mirage Content, it argued that most of the long form content produced by marketing departments looked, on the surface, like it was well-written, but if you actually read the details it was just high-level fluff. Specifically, when you do a Google search on a topic, many of the articles on the first page have interesting titles, but when you click into them, they all just regurgitate versions of the same few talking points.

I argued in that piece that this problem stemmed from two flaws in the content production process:

Most companies would hire freelance writers to write on a subject they had no expertise in. That writer would “research” the topic by Googling it and reading the top 10 results and then rehashing what those articles already said. We coined this The Google Research Paper approach, as it mimics a high school student producing a research paper where you can clearly tell the person doesn’t have expertise on the topic they’re writing about.

The second flaw was that most articles weren’t specific enough. They would cover broad concepts, which forces them to cover them at a high level. They never got deep enough into the details that people actually care about. This specificity problem is also a function of the writer not having expertise on the topic they were writing about. Now if we think about what AI does, it basically mimics the flawed approach outlined above. AI is trained from a large portion of the web, books, and articles written on a topic, so when you ask it about anything, it simply rehashes what’s been written on a topic (in grammatically pristine English, to be fair).

But what is the “correct” answer? How does AI decide what to say? What does it say on topics where there is no right answer? Does it ever take a strong stance on a topic?

The answer is that AI writers are biased towards saying the most average thing because that’s how they’re built. They’re programmed to produce a response that is as similar to the information they were trained on. All AI-writing tools know is what they’ve been trained on, which is by definition, things that people have already said. They are literally programmed to find the most likely word that goes after the word it just wrote, over and over again.

This is why AI content feels so much like what I defined as Mirage Content 7 years ago: when you first read it, it sounds really articulate and well-written, but when you stop to really dissect the arguments, you realize it’s just stating the same generic arguments in different ways.

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The most terrifying 10 minutes of 2023 One lazy Saturday afternoon in February, I heard a knock on my door. Standing on my porch was a mid-fifties guy in jeans and a windbreaker. I opened the door, still in my pajamas.

“Are you the TinyPilot guy?” he asked me.

“Uh oh,” I thought. Did a disgruntled customer find my house?

“Yes…” I said cautiously.

“I’m the handyman at the office. A sprinkler burst, and we can’t get into your suite. Can you come down?”

That didn’t sound good.

During my five-minute drive to the office, I wondered if this was the end of my business. We kept all of our inventory in TinyPilot’s office. Would circuit boards work after being drenched? Probably not.

TinyPilot had insurance, but I chose coverage a year before when we carried half as much inventory. And even if insurance paid out, TinyPilot would be dead in the water for months until we could restart our whole manufacturing pipeline.

I arrived at the building and walked up to TinyPilot’s office on the second floor, the carpet squishing damply with every step I took.

When I reached my floor, I was relieved to see that the sprinkler had actually burst in the shared conference room, not TinyPilot’s suite. I unlocked our office and found everything was bone dry. The water hadn’t even trickled under our door.

My relief was short-lived, as the landlord told me he might have to kick us out for “weeks to months” to repair the wall we shared with the conference room.

A sprinkler burst in the office adjacent to TinyPilot’s, destroying everything inside.

Normally, being forced to move my entire office on a few days’ notice would be disruptive, but it was especially disruptive this week. I was about to take a two-week trip to Europe, my longest travel since starting TinyPilot.

If the team had to move while I was away, no one would be able to set up the computers or printers — the office IT guy was me. And if the team couldn’t print shipping labels, they couldn’t fulfill orders.

Long story short, we ended up not having to move, but the experience made me never want to be in that situation again. I was risking so much by centralizing TinyPilot’s operations in a single, small office.