Reading Time: 4 minutes

‘Strategy without tactics is the slowest route to victory. Tactics without strategy is the noise before defeat.’

Sun Tzu

While plenty Go-to-Market frameworks have emerged over time, they often fall short of capturing the intricate dynamics of the real-world market. These frameworks are much more complex than it’s needed. I believe reality is too complex so it’s better to simplify it as possible.

That’s why this article aims to distill the essence of crafting an effective GTM strategy for digital products, stripping away unnecessary complexities and focusing on the core elements that drive success.

Ideal Customer Profile (ICP) and to whom should you sell

First of all, a lot of startup gurus talk about the importance of having an Ideal Customer Profile, but not a lot of them talk about an Early Customer Profile [1].

This idea refers to a normal distribution, where only 13.5% of the population are early adopters – people who accept and untested your beta phase product (some of them even enjoy it)!. While creating GTM, you should have clear division between ICP and ECP.

Secondly, it’s important to know that your customer doesn’t always make a decision whether to buy or not of your product [2]. That’s why during the discovery process you should point out who is your persona (ICP) and who is decision-making unit (DMU);

In my opinion, a lot of companies struggle with this and don’t have a division between end-users and decision-makers. Unclear strategy affects execution so when you go on such companies’ website, you don’t know what they sell and for whom.

Racecar Growth Framework

Lenny Rachitsky in his article compared Growth and Go-To-Market to racecar [3]. According to this concept:

1. When you first start off, concentrate on kickstarts and perhaps a few turbo boosts until most of your growth is driven by your growth engine.
2. After your growth engine is operating, you should spend money on lubricants to make it function more smoothly and on the odd turbo boost to accelerate growth.
3. Once you reach a certain size, investigate one or two mid-stage stimulants.
4. As you continue to lubricate your current growth engine(s), experiment with and start a second growth engine before your primary engine asymptotes.
5. To continue growing, add a new business unit, go after new markets (like enterprise), and develop inside current accounts (such raising NRR) if you want to keep expanding.

Go-to-Market Growth Strategies

Luka Ivicevic posted on LinkedIn that “Paid channels is a terrible way to build and scale a business. Great businesses don’t depend on paid channels to acquire customers. Paid channels are great to kick-start growth, and get feedback. Especially if you’re venture-backed. Most non-venture-backed, bootstrapped companies don’t use paid ads because they can’t afford it. Instead, they find creative ways to acquire customers using free channels. This pays off in the long term” [4].

I definitely agree with Luka’s idea to use inbound only as a test and then use creativity and growth hacking in order to scale.

On top of that, famous LinkedIn growth influencer – Maja Voje – posted a post where she clearly described the most common GTM strategies [5].

Maja suggested that you should not consider growth to be “random acts of marketing” but rather movements. Each has unique unit economics, varying sales cycles, and varying degrees of demand generation and capture.

Furthermore, it’s crucial to consistently prioritize strategies that have proven success while simultaneously experimenting with new approaches. I advocate for applying the Pareto Principle, allocating 80% of resources to proven strategies and dedicating 20% to testing innovative concepts. This approach ensures that established strategies remain the foundation while allowing for exploration and adaptation to emerging trends

How is the winner’s approach?

There is no need to reinvent the wheel, so a good strategy is to follow what industry leaders do.

Contemporary trends suggest a divergence in go-to-market (GTM) strategies between B2B and B2C startups. B2B companies increasingly adopt a product-led GTM approach, focusing on showcasing the value proposition of their offerings to businesses. In contrast, B2C startups often rely on viral marketing, Search Engine Marketing , and paid advertising to drive user acquisition. This differentiation is rooted in the distinct nature of business and consumer decision-making processes. When selling to businesses, the emphasis lies on demonstrating the tangible benefits and ROI (return on investment) that the product can deliver. On the other hand, B2C marketing often emphasizes social influence and the creation of a buzz around the product to attract consumers.

Summary

In conclusion, navigating the ever-changing e-commerce landscape requires a strategic approach that balances simplicity with effectiveness.

1. Identify and divide ICP and ECP
2. Identify end-customers and create a decision-making unit
3. Then you can implement the Racecar Growth Framework
4. While scaling, focus only on one strategy that works the most (80/20 rule).

Resources

1. https://www.linkedin.com/posts/majavoje_reaching-pmf-is-nearly-impossible-if-you-activity-7136398644626214912-K9P5?utm_source=share&utm_medium=member_desktop
2. https://www.linkedin.com/posts/majavoje_b2b-hill-im-willing-to-die-on-personas-activity-7138799488550305792-4x1v?utm_source=share&utm_medium=member_desktop
3. https://www.lennysnewsletter.com/p/the-racecar-growth-frameworkexpanded
4. https://www.linkedin.com/posts/luka-ivicevic_paid-channels-is-a-terrible-way-to-build-activity-7137521892755660801-84nr?utm_source=share&utm_medium=member_desktop
5. https://www.linkedin.com/posts/majavoje_too-many-startups-jump-straight-into-tactics-activity-7138074712357662720-OwvU?utm_source=share&utm_medium=member_desktop
6. I used ChatGPT 4 to rewrite my text and improve vocabulary. Prompt: please rewrite text and improve vocab: (text).

Reading Time: 5 minutes

Introduction

Capitalism is a process of industrial mutation that incessantly revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one

Joseph Schumpeter

Some people compare AI Revolution to Mobile Revolution, in this article I’m going to do in-depth analysis and answer the question is it accurate comparison.

Apple introduced the iPhone in June 2007 and Uber was founded in March 2009. 

The lesson from charts about is that technology revolutions take time. Despite the hype for AI right now, we’re still early: while 58% of American adults have heard of ChatGPT, only 18% have used it [2]. On the other hand, technology adoption develops faster than in the past, so in my opinion we’re not able to make any accurate predictions

History’s Technology Revolutions

The invention of the microprocessor by Intel in 1971 marked the start of the “Information Age,” our most recent technological revolution. 

According to Carlota Perez’s book Technology revolutions follow predictable boom-and-bust cycles. An exciting new technology leads to frenzied investment in that technology; frenzied investment leads to the formation of an asset bubble; that bubble eventually bursts, cooling an overheated market. [3]  The fact that Perez wrote book in 2002, just after the dotcom bubble crashed, is what sets it apart. At the time, a lot of individuals predicted the end of the internet era. Perez countered that the dotcom crisis was a so-called “turning point” that would usher in the internet’s Golden Age (what she refers to as “Synergy”) and that the bubble bust was only the middle of an expected cycle. [1].

According to Perez, technology revolutions follow ~50-year cycles. “Turning points”—which often come in the form of a market crash—typically occur about halfway into the cycle. Many crashes bear the name of the revolution’s prevailing technology: canal mania (1790s); railway mania (1840s); the dotcom bubble (late 1990s) [3].

A technology moves into the deployment phase, which is roughly 20 years of continuous development and widespread wealth generation, following its turning point. This is supported by the fact that the internet was widely used in the 2000s and 2010s, thanks to the launch of mobile and cloud computing. When viewed in retrospect, Perez’s approach seems ideal. [1].

The corporations that lead an era can be seen to “shift” from one technological revolution to the next. For example, the biggest American corporations throughout the 1930s and 1940s were oil and car firms, taking the place of steel companies.

According to Rex Woodbury the arrival of AI is near-perfect timing to Perez’s framework. For AI, the “big bang” event—to use Perez’s terminology—was probably the release of ChatGPT last year [1].

The Next Revolution: AI

​Artificial Intelligence emerges as the harbinger of the next revolution in computing. At its core, AI refers to the development of algorithms that enable machines to perform tasks that traditionally required human intelligence. One of the fundamental theories underpinning this revolution is machine learning, a subset of AI where algorithms iteratively learn from data and improve their performance over time. This transformative paradigm shift is exemplified by the advent of deep learning, a sophisticated neural network architecture inspired by the human brain. These neural networks consist of interconnected layers, each mimicking the neurons in our brain, fostering an unprecedented ability for machines to recognize patterns and make informed decisions. For instance, in the realm of natural language processing, models like GPT-3 (Generative Pre-trained Transformer 3) showcase the prowess of deep learning by generating coherent and contextually relevant text based on extensive pre-training on diverse datasets. The fusion of machine learning and deep learning propels us into an era where AI not only augments but potentially surpasses human capabilities, laying the groundwork for a future defined by intelligent automation and data-driven decision-making.

In my opinion, this technology (as it was in every tech revolution), will transform the way how people around the world live. A lot of jobs will be replaced by AI, and Western countries will consider universal basic income for everyone [4]. People will have new psychological problems because work is ​​an inseparable part of our lives, and sometimes even gives meaning to life. Big tech companies would have new problems – for example, Google would have to rethink a way how to construct SEO, because today’s algorithm is not the best in cases where more than 90% of content will be generated by Generative AI [5]. 

Conclusions

Rex Woodbury found that the economist Joseph Schumpeter once wrote: “Capitalism is a process of industrial mutation that incessantly revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one.” In his opinion the same is true for technology, which goes hand-in-hand with capitalism; innovation is capitalism’s spark, and technology its fuel. 

On top of that, in my opinion, AI Revolution isn’t comparable to the Mobile Revolution, because computers were built to act like calculators, while AI is networks act like the human brain. Moreover, nowadays technology adoption is much faster than in the past. A perfect example of this is in fact that ChatGPT had 1M users after 5 days from launch, where the collecting the same about of users took Instagram 10 years ago 2.5 months.

Sources

1. https://www.digitalnative.tech/p/the-mobile-revolution-vs-the-ai-revolution
2. https://www.pewresearch.org/short-reads/2023/08/28/most-americans-havent-used-chatgpt-few-think-it-will-have-a-major-impact-on-their-job/
3. “Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages” by Carlota Perez
4. https://www.theguardian.com/global-development/2023/nov/16/ai-is-coming-for-our-jobs-could-universal-basic-income-be-the-solution
5. https://fortune.com/2023/10/21/how-generative-ai-could-change-google-search-68-billion-seo-industry/
6. I wrote part of one paragraph with ChatGPT “The Next Revolution: AI” with ChatGPT 3.5. Prompt: You are a university student that has to write a blog post about The Next Revolution: AI, please prepare a theory with and example for one paragraph. Use a scientific but bachelor student style while writing.

Reading Time: 2 minutes

“Seamless access to text, voice, and data for LTE phones across the globe”

SpaceX has launched a new website dedicated to promoting its upcoming Starlink service for mobile phones. Their tagline is “Seamless access to text, voice, and data for LTE phones across the globe” [1]. The system will tap the growing Starlink satellite network in Earth’s orbit to beam cellular connectivity to unmodified smartphones. Future Starlink satellites will be outfitted with an “advanced eNodeB modem.” Thanks to this invention, a Starlink satellite will basically become a “cellphone tower in space,” allowing for network integration like a typical roaming partner [2].

According to the new website, SpaceX plans to debut the service that will power text messaging via satellites in 2024, with plans to expand to voice and text support in 2025. Additionally, the service will offer cellular connectivity to IoT devices in 2025. It will work with existing LTE phones without the need for any hardware, firmware changes, or special apps. It promises seamless access to text, voice, and data [3].

Approval from the Federal Communications Commission

However, in order to do that SpaceX must first obtain approval from the Federal Communications Commission before its services will become public. The company has been pleading with the US government to grant their request to utilize the required radio channels as soon as possible.

Partnership with T-Mobile?

On the other hand, it is important to notice that a year ago, SpaceX was originally hoping to launch a service with T-Mobile [4], but the companies have been silent about the deal since its announcement.

SpaceTech is growing

In recent years, satellite connection for smartphones has become more and more popular. In an emergency, iPhone 14 models and above may transmit a limited number of messages and position data via satellite thanks to a function Apple implemented to its phones last year. The first satellite call over 5G was made last month from a smartphone that wasn’t altered, according to AT&T-backed AST SpaceMobile [5].

In my opinion, in 2019 Elon Musk and his SpaceX started a SpaceTech revolution in the private sector and showed companies that they were able to enter this industry. What is more interesting after 4 years he is still leading the innovation in the industry.

1. https://www.starlink.com/
2. https://www.tesmanian.com/blogs/tesmanian-blog/direct-to-cell
3. https://www.pcmag.com/news/spacex-debuts-new-website-for-cellular-starlink-service
4. https://www.pcmag.com/news/t-mobile-to-expand-coverage-with-the-help-of-spacexs-starlink-satellites
5. https://www.theverge.com/2023/10/12/23914081/spacex-starlink-direct-to-cell-satellite-internet-lte-connectivity