Geoffrey Hinton, one of the pioneers of AI, believes AI could surpass human intelligence in 5 to 20 years. That's a pretty short time frame, and what happens after that is unpredictable. Some experts think AI will follow human-set goals. Others worry AI might develop its own, and we won't be able to control it. The fact that AI can instantly share knowledge across copies gives it a huge advantage over humans, making it a superior form of intelligence.

AI Needs a Containment Plan

One of the big worries is that AI could displace jobs—especially intellectual ones. Driving, journalism, and mid-level office jobs are all at risk. But some jobs, like plumbing, might be safe for a while because they require physical manipulation, which AI still struggles with.

Jobs Under Threat

The wealth created by AI will likely go to the rich, widening the gap between the wealthy and the poor. This could lead to more social instability and even political shifts, like the rise of right-wing populism. Universal Basic Income (UBI) could help by providing a safety net, but it doesn't solve the deeper issue of people losing the sense of self-respect they get from work.

Rich vs. Poor

There's also the military angle. AI-controlled autonomous weapons could make decisions without human intervention, and that's a separate but equally terrifying risk. Governments aren't doing much to regulate AI in military applications. The competition between countries like China, Russia, and the West is only speeding up AI development, making safety an afterthought.

AI in military

Almost everybody I know who's an expert on AI believes they will exceed human intelligence; it's just a que﻿stion of when. And at that point, it's really difficult to control them.

Geoffrey Hinton, the Nobel Prize winning former Vice President of Google and sometimes referred to as the 'Godfather of AI' speaks to BBC about AI.

The Nobel Prize winning ‘Godfather of AI’ speaks to Newsnight about the potential for AI “exceeding human intelligence” and it “trying to take over.”

Geoffrey Hinton, former Vice President of Google and sometimes referred to as the ‘Godfather of AI’, has recently won the 2024 Nobel Physics Prize. He resigned from Google in 2023, and has warned about the dangers of machines that could outsmart humans.

In May 2024, Faisal Islam spoke to the professor for Newsnight.

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‘Godfather of AI’ on AI “exceeding human intelligence” and it “trying to take over”

<ul><li class="ql-align-justify">Founders often receive bad advice on scaling companies, particularly to adopt "manager mode" over "founder mode."</li><li class="ql-align-justify">"Manager mode" advocates delegating responsibilities, but for founders, this can be harmful to the company.</li><li class="ql-align-justify">Founders struggle with advice that assumes they must run companies as professional managers.</li><li class="ql-align-justify">Business schools teach "manager mode," missing the nuances of how founders should lead.</li></ul>

Manager Mode

<ul><li class="ql-align-justify">Founders face unique pressures and challenges that professional managers don’t understand.</li><li class="ql-align-justify">"Founder mode" could help companies scale without losing their original vision and dynamism.</li><li class="ql-align-justify">Steve Jobs ran an annual retreat for 100 key people, not based on hierarchy, but importance.</li><li class="ql-align-justify">Founders engaging in "skip-level" meetings might be more effective than traditional management structures.</li><li class="ql-align-justify">Many founders experience disastrous results when following advice to delegate and remove themselves from details.</li></ul>

Founder Mode

VCs who haven’t been founders themselves don’t know how founders should run companies.

Founders should trust their instincts, avoid conventional "manager mode," and engage deeply to scale their companies effectively.

TAKEAWAY

Paul Graham explores "founder mode" vs. "manager mode" in running companies, inspired by Brian Chesky's insights about scaling Airbnb successfully.

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Personalized welcome emails serve as a key strategy for SaaS companies to engage new users and uncover the deeper motivations behind their choices. In your welcome email, by asking, "What's happening in your world that brought you here?" you can initiate a valuable conversation, gaining insights into the functional, emotional, and social jobs your product is hired to do (<a href="https://justinjackson.ca/what-is-jobs-to-be-done/">JTBD</a>). This approach not only enriches customer understanding but also guides more effective marketing and product development strategies, ensuring your offerings resonate more closely with user needs.

Harness Personalized Emails for Deeper Insights

You can't get this information from 'last click attribution' tracking. Inviting users to share their story transforms a digital interaction into a meaningful connection, providing your business with actionable insights and a competitive edge.

Empower Connections Through Genuine Inquiry

A simple welcome email can uncover valuable insights about your customers.

When we understand the underlying "jobs" customers are trying to accomplish, we can develop marketing strategies that speak to those needs.

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Send your users this welcome email

Incentive programs like referrals, free trials, and coupons may seem appealing, but they often attract users with lower lifetime value (LTV), poor conversion rates, and less engagement. These "incentivized users" typically contribute less to the business compared to organically acquired users, highlighting the need for a strategic approach to user acquisition.

The Hidden Costs of Incentive-Based Growth

A common misconception in growth marketing is that more users always equal better outcomes. However, attracting users through incentives can lead to negative selection—where the additional users are less qualified and more discount-oriented, ultimately diluting the quality of the user base and impacting the long-term health of the product.

Quality vs. Quantity in User Growth

While referral programs can boost user numbers, they often attract users looking for quick gains rather than long-term engagement. This leads to lower engagement rates and higher instances of fraud, challenging the initial financial models that justified these programs and underscoring the importance of targeting the right kind of user growth.

Referral Programs: A Double-Edged Sword

Incentive programs can prematurely "pull forward" users who might have discovered the product organically, incurring unnecessary costs. This phenomenon highlights the delicate balance between incentivizing new users and allowing organic growth through word-of-mouth, which often brings in higher-intent users at no additional cost.

The Cannibalization Effect of Incentives

Uber's extensive experience with referral programs reveals a nuanced picture: while driver-side referrals attracted motivated users, rider-side referrals often brought in discount-seekers, leading to a misallocation of millions in marketing spend. This underscores the importance of understanding the different impacts of referral incentives on various segments of your user base.

Lessons from Uber's Referral Experiences

Great article that provides a critical perspective on the effectiveness of referral programs, free trials, coupons, and gamification in attracting quality users.

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Product & Design

Why the worst users come from referral programs, free trials, coupons, and gamification

On November 17th, Sam Altman, CEO of OpenAI (creator of ChatGPT and world's hottest AI company), was fired by the board without any explanation to stakeholders, leading to significant drama.Numerous conspiracies and speculations emerged. After cycling through three CEOs in under a week, the company reverted to its original CEO, and the initial board stepped down.

What happened?

<ul><li>AI is old stuff, having been studied at universities by researchers since the 1950s.</li><li>In the last 10 years, big tech companies have realized AI's power and started working on it for their own benefits.</li><li>These companies, including Google, Amazon, Meta, and Microsoft, quickly adopted new strategies to transfer talent from universities, paying lucrative salaries, and also acquiring AI research companies.</li></ul>

Let's zoom out

<ul><li>OpenAI was founded in 2015 as a non-profit research organization aimed at developing AGI for the benefit of humanity, in response to the rise of AI developments by those companies. This is why Elon Musk joined and donated $10M.</li><li>AGI means AI reaching and overtaking human capabilities in every area of life, capable of improving itself autonomously and recursively. In the extreme (hyperintelligence), it's a God. It can know and do everything.</li><li>OpenAI aimed to mitigate these existential risks facing humanity: AI safety and ethics must be secured, and all discoveries should follow open standards!</li></ul>

Artificial General Intelligence (AGI)

Co-founder Ilya Sutskever, a successful scientist, has groundbreaking papers published as a researcher. He's well aware of the threats of the coming AI wave and wants to ensure every improvement is safe and useful for humanity.Ilya's vision was that creating AGI is possible by scaling the tech stack (with more data and larger infrastructure), but this requires a substantial amount of money for hardware and to attract talent.Consequently, securing investment became a necessity.

OpenAI Co-Founders — Ilya Sutskever 

This was where non-profit to for-profit transformation happened (2019) and Sam Altman joins as CEO. They altered the corporate structure.Although they shifted towards a Silicon Valley startup model, they still maintained their strict rules to prevent possible misleading and drift from the initial objectives. Measures were implemented to avert investor involvement in management and to limit investor profits. Additionally, founders were not allowed to hold any equity in the company.Sam Altman is an expert in Silicon Valley startup culture, which emphasizes moving fast and growing infinitely.

OpenAI Co-Founders — Sam Altman

Co-founder Greg Brockman, sharing an entrepreneurial mindset and background with Sam Altman, is also a hustler. That's the reason for their deep mutual solidarity.Sam Altman secured significant funding from Microsoft, but his entrepreneurial approach began to pose risks and inconsistencies with OpenAI's foundational principles.On November 17th 2023, the board fired Sam for straying from their main altruistic mission. Greg immediately resigned in support of him. This was followed by the resignation of three senior employees.

OpenAI Co-Founders — Greg Brockman

OpenAI was successful to bring skilled people into the company by emphasizing altruistic reasons — working for the benefit of humanity. Employees care about humankind but also their state of mind. They became distraught after the chaos began, as they never received any explanation about what was happening, leading to significant anger and a feeling of being left in the dark.The other thing they care is their pockets. Their financial expectations were slipping into dangerous territory. Nobody wanted to see the company's skyrocketing valuation take a downturn due to a fiasco.

OpenAI Employees

Simultaneously, Satya Nadella (CEO of Microsoft), offered a guaranteed position to all OpenAI staff at Microsoft. It was a reasonable move because Microsoft put billions in OpenAI and didn't want to lose it all of a sudden.Over 700 out of 770 employees signed a letter that threatens to quit unless Sam Altman was reinstated.Without employees there is no company. This made the board reverse their decision and despairingly call Sam Altman back to his position.This is the end of drama.

OpenAI Employees (cont'd)

Do you recall the part where I mentioned key people implementing safety measures to protect their lofty goals by isolating the company from external influences like superpower investors, various political situations, and even the founders themselves?

The Big Dilemma

Everyone has a plan 'till they get punched in the face.

When AI governance is concerned, self-regulation does not work!

Moral of the Story

⚠️

OpenAI has faced similar challenges in the past. In early 2018, a disagreement between Sam Altman and Elon Musk led to Musk completely withdrawing his support and exiting the company.Furthermore, a dispute over the commercialization of GPT-3 prompted the departure of senior scientist Dario Amodei, who took along a significant portion of the team to found Anthropic, now a major competitor to OpenAI.

Bonus-1: Not the First Time

Companies like Meta are open-sourcing (rather than commercialize) their AI models, claiming to democratize AI. However, they never share the data used to train these models. This attitude creates a significant barrier for other researchers who wish to analyze, understand and, shepherd these AI models.

Bonus-2: Democratize(!?) AI

AI safety does not only mean as extreme as preventing existential risks or national security threats. When you think of AI safety, remember that it also relates to avoiding discrimination and bias in any form. Ethics and misinformation are critical components that require proactive management to mitigate AI's potential adverse effects on society.

Bonus-3: AI Ethics

I dropped out of my PhD study while working on my thesis in AI. Those were the days AI was not a buzzword and my SVM models were outperforming NN models. I quit to start my own business, immersing myself in both academic and startup cultures. Wearing both hats in the past has been invaluable. From this perspective, I believe AI needs to be managed with great caution. Because it's a huge challenge (in fact impossible) to predict the complete outcomes of an autonomous and self-improving technology.

My two cents

AI community is broadly divided into two ideological camps:<ol><li>Techno-optimists: Most entrepreneurs & business people support unbounded development of AI. They have a commercial vision. Move fast, get more money in, quickly build and release products for public use.</li><li>Existential-risk Advocates: Most scientists & researchers support AI containment. AI safety is the utmost priority for them. Move cautiously, make sure it's completely tested against potential risks and do not release products until they're resistant to misuse and misbehave.</li></ol>We'll see who prevail and what the consequences will be. Soon<warningtag>.</warningtag>

Who will prevail?

You're familiar with ChatGPT, but how well do you know the company behind it? Let’s dive in OpenAI’s latest implosion and explain it from a broad perspective, examining AI's past, its future, and the challenges along the way.

You know ChatGPT, but how much do you know about the company that made it? Journalist Karen Hao joins us to talk OpenAI’s latest implosion.

Subscribe to Big Think on YouTube ► https://www.youtube.com/channel/UCvQECJukTDE2i6aCoMnS-Vg?sub_confirmation=1

Journalist Karen Hao joins Big Think’s Editor-in-Chief, Robert Chapman-Smith, to discuss the recent events at OpenAI, including the ousting and reinstatement of CEO Sam Altman, as well as the ideological clashes regarding the development and release of powerful AI models like ChatGPT.

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Background Context on OpenAI:
The inside story of Microsoft's partnership with OpenAI, Charles Duhigg for The New Yorker ► https://www.newyorker.com/magazine/2023/12/11/the-inside-story-of-microsofts-partnership-with-openai
Inside OpenAI’s chaos, Karen Hao and Charlie Warzel for The Atlantic  ►  https://www.theatlantic.com/technology/archive/2023/11/sam-altman-open-ai-chatgpt-chaos/676050/
OpenAI profile, Ross Andersen for The Atlantic ► https://www.theatlantic.com/magazine/archive/2023/09/sam-altman-openai-chatgpt-gpt-4/674764/
OpenAI profile, Karen Hao for MIT Technology Review  ►  https://www.technologyreview.com/2020/02/17/844721/ai-openai-moonshot-elon-musk-sam-altman-greg-brockman-messy-secretive-reality/

Background Context on how AI works:
How Large Language Models Work, Andrej Karpathy  ► https://www.youtube.com/watch?v=zjkBMFhNj_g
What is ChatGPT Doing and Why Does It Work?, Stephen Wolfram  ► https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work/
Are Conscious Machines Possible?, Michael Wooldridge for Big Think  ► https://www.youtube.com/watch?v=uf6zZfLat-8
There is no AI, Jaron Lanier  ► https://www.newyorker.com/science/annals-of-artificial-intelligence/there-is-no-ai

Background Context on accelerating AI:
Why AI will save the world, Marc Andreessen ► https://a16z.com/ai-will-save-the-world/
My Techno-Optimism, Vitalik Buterin  ► https://vitalik.eth.limo/general/2023/11/27/techno_optimism.html
Are AI Risks Overhyped?, Andrew Ng  ► https://www.deeplearning.ai/the-batch/issue-220/
To fear AI is to fear Newton and Einstein, Rohit Krishnan for Freethink  ► https://www.freethink.com/robots-ai/dreams-of-utopia

Background Context on AI risk:
AI risk does not equal AGI risk, Gary Marcus  ► https://garymarcus.substack.com/p/ai-risk-agi-risk
AI pioneer calls to stop AI before it's too late, Stuart Russell for Freethink  ► https://www.youtube.com/watch?v=EOyljx7Pi7A
Why the Godfather of AI fears what he's built, Joshua Rothman, forThe New Yorker  ► https://www.newyorker.com/magazine/2023/11/20/geoffrey-hinton-profile-ai
On the dangers of Stochastic Parrots: Can Language Models Be Too Big?, Emily Bender, Timnit Gebru, et al  ► https://youtu.be/N5c2X8vhfBE?si=xS3B5NCk5np-ghDD

Books on AI:
AI 2024: Ten Visions for Our Future, Kai-Fu Lee  ► https://a.co/d/61BHsfW
The Worlds I See, Dr. Fei-Fei Li  ► https://www.momentoflift.com/the-worlds-i-see
The Coming Wave, Mustafa Suleyman  ► https://bigthink.com/the-future/technology-unintended-consequences-containment/
Weapons of Math Destruction, Cathy O’Neil ► https://www.penguinrandomhouse.com/books/241363/weapons-of-math-destruction-by-cathy-oneil/

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About Karen Hao:
Karen Hao is an award-winning journalist covering artificial intelligence, currently contributing to The Atlantic. Previously, she was a foreign correspondent at The Wall Street Journal focused on AI, China tech & society, and a senior editor at MIT Technology Review, where she wrote about the latest AI research & its social impacts. She was also a fellow with the Harvard Technology and Public Purpose program, the MIT Knight Science Journalism program, and the Pulitzer Center’s AI Accountability network.

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The chaos inside OpenAI – Sam Altman, Elon Musk, and existential risk explained | Karen Hao

Simon Sinek is one of the most followed people on the planet when it comes to leadership.Prepare to be inspired as Eric Partaker presents his curation in his newsletter, unveiling Sinek's transformative insights for aspiring leaders worldwide.

14 of the Wisest Things Ever Said About Leadership 

People don’t buy what you do; they buy why you do it.

A boss has the title. A leader has the people.

When people are financially invested, they want a return. When people are emotionally invested, they want to contribute.

You don’t hire for skills; you hire for attitude. You can always teach skills.

You can easily judge the character of a man by how he treats those who can do nothing for him.

Bad leaders care about who’s right. Good leaders care about what’s right.

We achieve more when we chase the dream instead of the competition.

Leadership is not about being in charge. Leadership is about looking after those in our charge.

Stars want to see themselves rise to the top. Leaders want to see those around them rise to the top.

Customers will never love a company until the employees love it first.

Leadership is not a license to do less; it is a responsibility to do more.

It is not the genius at the top giving directions that makes people great. It is great people that make the person at the top look like a genius.

Stress and anxiety at work have less to do with the work we do and more to do with weak management and leadership.

Be the leader you wish you had.

14 of the wisest things ever said by Simon Sinek:

 1. “People don’t buy what you do; they buy why you do it.”
    
 2. “A boss has the title. A leader has the… | 347 comments on LinkedIn

14 of the wisest things ever said by Simon Sinek

Content Curation is the process of gathering, organizing, and presenting information relevant to a particular topic or area of interest. This involves sifting through vast amounts of content on the web and presenting the best, most relevant content in a structured manner.

Content Curation

Content Curator, is the one manages the process of finding, grouping, organizing, or sharing the best and most relevant content on a specific topic.She identifies key themes, latest trends, and the most insightful resources, and then presents these in an easily digestible format for her audience.The goal of a curator is not to generate new content (although Deepstash allows to create from scratch as I'm doing right now), but to extract the best content available from various sources. She adds value by saving her audience or herself time and effort in finding and understanding the information.

The Curator

Based on my experience, I've observed two types of curators, each differentiated by their motivations, goals, and the unique expectations they have from the medium where they share their curated content.

Two Types of Curators

Authority-driven Curators: These curators are primarily motivated by extrinsic factors such as gaining authority, growing a community, and increasing their number of followers or likes. Their goal is to appear authoritative, which in turn attracts more followers or prospects. They curate and share content that will boost their numbers and enhance their perceived authority.

Two Types of Curators (#1)

Intrinsic Curators: These curators are driven by intrinsic motivation. They curate content because it is useful to them personally. In the era of information overload, their goal is to learn deeply about useful resources, digest them to uncover valuable insights, and organize them in a way that makes it easy to find important information when needed.A secondary effect of their curation is that when they share their collections, they can also help others. This type of curator is more focused on the value and utility of the information rather than the potential for gaining followers or likes.

Two Types of Curators (#2)

From the product perspective, I pondered on some key features that a curator-focused platform should possess for optimal growth.But first, I'd like to introduce the terms "closed" and "open" platforms. Then we can delve into what do curators expect from a product.

What Do Curators Want From the Product They Want to Use?

In a "closed platform" the connection of the content creator with the audience is controlled by the platform itself. For example on YouTube, there's no way to migrate your subscribers to another video sharing site. It doesn't matter how many subscribers you have, most viewers primarily see recommended videos, an aspect you have limited control over.In an "open platform" content creator has a direct connection with the audience. You can take your email list, RSS feed, and customer list anywhere you move. Substack (email), WordPress (RSS), Patreon (membership) are good examples.

Closed vs. Open Platforms

Authority-driven Curators prefer open platforms because they allow for a more direct and controlled communication with their audience. They are also in search of tools that can amplify their perceived authority and facilitate the growth of their audience.

What Authority-driven Curators Want?

<ol><li>Tools for driving engagement and increasing followers or likes: This includes highlighting features like social sharing buttons, comment or reaction systems, and analytics to understand their audience behavior and preferences.</li><li>Possibility for direct communication and branding: Authority-driven curators would appreciate customization options to reflect their authoritative persona, and direct message or email features to manage communication with followers.</li><li>Openness and portability: They require the ability to transfer their followers list and data when switching platforms.</li></ol>

Crucial Product Features for Authority-driven Curators

Intrinsic Curators are seeking more flexible platforms which allow them to organize their content in the best way possible to express their unique insights and where gaining popularity is less central. Integrations that brings ease of use is one of the most critical features they're looking for.

What Intrinsic Curators Want?

<ol><li>Features aiding content organization and discovery: This would consist of categorization, tagging and search functions, saving for later, and suggestions based on interests or activity.</li><li>Flexibility: As intrinsic curators focus less on followers and more on the value of the content, they'd prefer platforms that allow them to manage their curated content without interference or limitation.</li><li>Interoperability: This curators would value the ability to easily exchange and synchronize their content between different products or platforms so they can manage and share their content wherever they prefer.</li></ol>

Crucial Product Features for Intrinsic Curators

While answering Deepstash's customer survey today, I found myself deep in thought about the topics if I would be building a curator-led product. :)

Curator-Led Product

In simple terms, APIs serve as a bridge that connects different software applications. Via the bridge, connected software can seamlessly integrate to send data back and forth.

What Is an Application Programming Interface (API)?

API-based SaaS is a cloud-based software application that allows users to access its features, data, and functions via an API instead of a user interface.

What Is API-Based SaaS?

<ul><li>API-based SaaS improves the user experience by making it easier for users to import and export data and customize their workflow by integrating specific apps.</li><li>It simplifies development: Instead of building features from scratch, developers can simply integrate your software with other apps that already have the desired features.</li></ul>

Benefits

<ul><li>Increases accessibility: Users can access API-based SaaS software via an internet-connected web browser or mobile app.</li><li>It is flexible and scalable: Allows you to quickly and easily update the software to improve its performance in the background without disrupting user activities or existing integrations.</li></ul>

Benefits (cont.)

<ul><li>While APIs may be familiar to developers, they may not be intuitive or user-friendly for all users. Some users may prefer a graphical user interface (GUI) or find APIs difficult to use without additional training or support.</li><li>It can introduce security risks if not properly secured.</li></ul>

Challenges

If you're an aspiring SaaS founder, you may consider to build an API-based SaaS business.

Are you an aspiring SaaS founder? If so, you may be overwhelmed with your options, including API-based SaaS. In this guide, we'll help you make sense of

API-Based SaaS: Definition, Benefits & Challenges - Baremetrics

Any potential lender or investor will want to see a reliable revenue projection to gauge how likely you are to pay their money back (ideally at a large multiple).

SaaS Revenue Forecasting

To build a good forecast, you first need to define where the company is going and how you plan to get there. Forecasting helps you and the rest of the team constantly answer the question: is what we're doing taking us where we want to go?

The Why?

Before implementing automated tools, it's generally helpful to begin revenue forecasting with a simple, accurate spreadsheet model. Just <a href="https://docs.google.com/spreadsheets/d/1nj0LtyG6Q9HhXk-iaj9-3taT9gwWpF8XnxYahpn--to/edit">make a copy of this template</a> and follow along.

Building a Revenue Forecast in Google Sheets

The most straightforward forecasting tools rely on the recent past to predict the future. The "straight-line" method uses historical revenue and growth trends to map high-level revenue expectations. Start with your last six months of data and map out the next six months based on your current trajectory. For example, if you had $50k in monthly recurring revenue six months ago and today you have $60k, a straight-line forecast would show that in 6 months, you'll hit $70k in MRR.

Basic Forecasting Options

<ol><li>Your funnel model</li><li>From funnel to "new customer"</li><li>Revenue forecasting models</li><li>Converting customers to MRR</li></ol>

Creating a Revenue Model

Start by mapping out your marketing funnel data and customer signup information. Understanding each funnel step and conversion rate helps you see the complete process behind your revenue generation.

1. Your funnel model

After mapping out your historical funnel data, analyze the formulas and how your conversion factors have moved over the past few months. Then, make your best guess what ratios are reasonable going forward.

2. From funnel to "new customer"

Get the number of new customers your marketing funnel will generate each month. Revenue from these customers flows into your new MRR, where we’ll pick up the second part of your revenue forecast.Aside from attracting new customers, there are a few significant factors impacting MRR:<ul><li>Expansion and contraction (subscription upgrades or downgrades)</li><li>Churn and reactivation: Customers canceling subscriptions or reactivating a previously canceled subscription.</li></ul>

3. Revenue forecasting models

We’ve effectively established the total number of customers we expect each month from the marketing funnel to our expectations for expansion, churn, and contraction. Using these figures and the average revenue per customer (ARPC) for each category, we can make a solid prognosis for MRR.

4. Converting customers to MRR

Once you’ve established your revenue forecasting formulas and the data relationships necessary to build your forecast, it’s simply a matter of refreshing the data and assumptions each month. You’ll be able to copy your traffic and conversions data directly from your marketing funnel software. Then input your revenue and churn information. If your assumptions were way off, go ahead and reassess for the next forecast.

Maintaining Your Revenue Forecast

Revenue forecasting is essential, especially for SaaS businesses. Don’t wait until you’ve got an entire finance team ready or investors to satisfy to implement the most advanced cloud forecasting solutions. Getting started with a Google Sheets tool is massively better than not forecasting at all.

The Bottom Line

Many founders treat revenue forecasting as a luxury, until suddenly, revenue forecasting becomes a necessity. This guide to SaaS revenue forecasting will walk you through building a revenue forecast.

Many companies stick with pretty basic financial systems when first getting off the ground.  Once there's revenue coming in, the founder and their How to build a SaaS revenue forecast using google sheets, and why you might benefit from using an automated software solution like Flightpath by Baremetrics.

A Founder’s Guide to SaaS Revenue Forecasting

Whether you created your SaaS product to help solve a problem you had or because you wanted some extra income, the truth is that your SaaS business is a valuable asset.Whether you’re an early-stage founder or you’ve built up an established B2B SaaS business, it's crucial to understand how valuations work and how you can prepare for an exit when the time is right for you.

It’s a Valuable Asset

There are three ways to look at SaaS valuations:<ol><li>Seller discretionary earnings (SDE)</li><li>Earnings before interest, taxes, depreciation, and amortization (EBITDA)</li><li>Monthly recurring revenue (MRR)</li></ol>No matter which formula you use, they boil down to how much money your SaaS business generates and set that number against a multiple that reflects the quality of your business.For SDE and EBITDA, you would set annual profit against an annual multiple; typically, this multiple ranges from 2-10X.MRR is set against a monthly multiple that usually ranges from 25X to 100X.

Valuing SaaS Companies Based on SDE, EBITDA, and MRR

SDE reflects how much money your business makes after all expenses are paid and any salaries are added back into the business. The figure is one way to indicate a business’s earning potential and is often confused with EBITDA. Businesses valued with SDE tend to earn less than $2 million in annual recurring revenue (ARR) and tend to be run by solopreneurs. Year-on-year revenue growth is usually less than 50%.

SDE for Businesses Valued at Less Than $5 Million

Businesses that make over $5 million in ARR will likely use EBITDA, as the business will have a high growth velocity and a more fleshed-out infrastructure. The owners tend to be thought leaders in their industry and operations are developed with department heads and teams working under them. There are usually more stakeholders than the owner. EBITDA takes many factors into consideration, which is why this metric is more suitable for mature and complex businesses.

EBITDA for Businesses Valued Above $5 Million

MRR is a popular way to value SaaS businesses because it’s a key indicator of revenue growth.Investors prefer looking at MRR rather than ARR because annual recurring revenue doesn’t provide proof of churn.Big SaaS brands generating high MRR can raise a lot of money during seed funding rounds, despite not generating profit. For less mature brands that haven’t built up a name, people prefer monthly plans; with a recognizable brand, they can charge a discounted annual plan.A newer startup could be valued using MRR if it’s experiencing rapid growth and ARR is more than $2 million.

MRR for Fast-Growing SaaS Companies

No matter which valuation formula is used, investors look for proof of these three characteristics in a business: <ol><li>Transferability </li><li>Sustainability </li><li>Scalability </li> </ol>

The Three Key Elements of Attractive Assets

Investors look for businesses that can be easily transferred. To prepare your business for a sale, focus on making the transition as seamless as possible. Payment processing can cause huge headaches for buyers if the account can’t be transferred. Payment processing aside, you’ll need to document your business operations as much as possible to make your business plug and play. Creating well-documented code that can be understood by another developer ensures continuity if the new owner wants to develop the product or fix any issues. Standard operating procedures (SOPs) help buyers to learn how to run the business as you did; SOPs are great for training new staff or to refer back to during the transitional period when the business changes hands. While buyers are doing their due diligence, they’ll need to see clean financials. This will include tax returns from the past three years, a balance sheet, income statements, and cash flow.

1. Transferability

Scaling your revenue (MRR) is great, but it needs to be done efficiently.A business with high MRR won’t be worth as much if the churn rate is through the roof and your retention rate is poor. Buyers pay attention to your LTV, churn rate, and conversion rate optimization.Investors will also look at how efficient your operations are at acquiring new leads. Organic lead generation is highly attractive because there are no expenses involved; if you have other customer acquisition channels (CACs), the conversion rates will indicate whether these marketing channels are worth maintaining.

2. Sustainability

The most exciting prospect of SaaS businesses is their room for growth.Buyers will be looking at how scalable your business is based on a number of factors, such as the LTV/CAC ratio.A low LTV/CAC ratio may indicate that more capital is needed than expected to scale a business; on the other hand, a high ratio could mean your growth is slower than your competitors because you aren’t spending enough on marketing.

3. Scalability

If you're thinking an exit strategy from your SaaS startup, you have to be prepared for it.

Whether you created your SaaS product to help solve a problem you had or because you wanted some extra income, the truth is that your SaaS business is a Here is an article on what investors look for in SaaS businesses and the factors that affect multiple sales.

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