17 posts tagged with "growth"

Infuse the IOZ personal growth loops with a triangle of faith.

Architects model the world in system thinking to optimize everything. As an engineer and businessman, I am continually working on the orchestration of work and life and maintain a high personal growth rate. Lessons learned are generalized to the BOZ growth loops.

BOZ is the acronym for a big loop that engages three small loops:

• Build and Sell Loop. Build products and sell them. Solve problems and get paid.
• Outlook and Invest Loop. Be radically curious to seek truth from facts. And optimize the web of customers, channels, people, tech, and capital.
• Zen MSEP Loop. Being present and do everything with mindfulness. Fuel the mind and body by moving, sleeping, eating, and playing well with people.

Two sources of distress​

Stress is a good thing for people while the distress is not.

1. Stagnation: You are stuck in one step of the loops.
2. Frictions: Too many frictions prevent small wins.

Product Market Fit​

Product market fit refers to whether your product is good enough; if it is, you can start investing more in paid customer acquisition channels. User retention may be the best measure, after all, actions speak louder than words.

What you need to clarify is: "Is the product effective? Is word-of-mouth and retention growing on its own?" Usually, the answer is no. So make sure you try enough times—focus on the solution rather than the problem or the mission. The solution is the reason people use your product.

Product Channel Fit​

Do you have repeatable and scalable channels? The two most common repeatable and scalable methods for consumers are Search Engine Optimization (SEO) and referrals.

• Search Engine Optimization (SEO): Generate unique user-generated content
  • SEO takes time to set up; you won't see benefits right away. It's more like "If this company wants to grow in 5 years, SEO must be done well." Therefore, you shouldn't spend 100% of your time on it. More like 10% of your time setting up the basics ("Set it and forget it").
• Referrals: Provide an incentive mechanism that encourages people to invite their friends for rewards
  • Referrals can start working from day one.

Important Metrics​

In the early stages, the quality of data is more important than quantity (e.g., retention rate). A 50% or 10% long-term retention rate is more important than user growth rate. In some cases, Daily Active Users (DAU) are important. The metric is not "Can this acquire users?" but rather "Can this retain users or convert them to paying customers?" Many companies over-focus on monthly growth rather than whether the product has genuinely improved. At the beginning, data is scarce, and you might convince yourself that it is effective. But if retention is low, growth won't be sustainable.

Control Analysis​

Segment users into control groups so you can analyze how user behavior changes over time and with product changes. You can determine if there is natural churn and whether your changes have unlocked new behaviors.

Lifetime Value (LTV) / Customer Acquisition Cost (CAC) Payback Period​

Using just a few months of data to calculate LTV for future predictions is not very instructive. What people want to know is, "How will this product grow over time?" So you should focus on what it will look like as it scales.

Payback Period (PBP) can sometimes be better than LTV/CAC. It means if I spend $1, how long until I can recoup not just revenue but also profit. The importance of the payback period is that unless you have a quick return on investment, it's hard to build rapid growth on paid channels.

What you really need to ask yourself is, "Can I reinvest this money into more growth?" If it takes one or two years to get that money back, then you need to rely on another source of funding to support your growth.

Why Should We Avoid Spending on Customer Acquisition Initially?​

If possible, try to avoid spending on customer acquisition at the beginning. Companies with a long-term mindset and large companies do not spend money to buy customers. Avoiding it will force you to find ways for viral growth. Unless you can prove that spending $1 can yield$5, and you don't have a high churn rate, then you can consider using paid acquisition.

Simply looking at the current trend of MAU cannot predict its future trajectory. For example, in the Growth Accounting Framework — during a certain period, some people start using your product (user acquisition), some leave your product (churn), and some leave and then return (reactivation), resulting in a net MAU value. As time goes on, user acquisition and reactivation become increasingly difficult; the more users there are, the higher the churn rate. The overall MAU curve tends to flatten or decline.

So what are the indicators that can predict future MAU? Andrew believes there are two:

1. Positive feedback from user acquisition
2. Positive feedback from retention and reactivation

Positive Feedback from User Acquisition​

UGC + SEO Positive Feedback​

Representative Companies: Yelp, Houzz, Wikipedia

1. New users see good content
2. Some new users join in to create new content
3. Google indexes this unique new content
4. Users search for more content

Paid Marketing Positive Feedback​

Representative Companies: Blue Apron, Casper, Uber

1. New users click on ads
2. Some new users try the product
3. Some become paying users
4. More budget is allocated for advertising

Viral Marketing Positive Feedback​

Representative Companies: Dropbox, LinkedIn, Instagram

1. New users register
2. New users invite/share content with friends
3. Some friends click on the link
4. Friends respond to the invitation/shared content

The conversion rates and numbers of these four steps can be calculated. For example, 30% of new users may import contacts and send invitation links to 10 people, of which 40% actually send the link, and 50% of those who receive the link will register. Thus, the growth factor is 0.6, meaning that from 1,000 registrations, there will be 600+ new registrations; over time, this could reach 2,500.

How to improve? Break down the steps and tackle them one by one.

Positive Feedback from Retention and Reactivation​

Social Positive Feedback​

Representative Companies: Instagram, LinkedIn, Gmail

1. Users create content
2. Content is seen by other users
3. Content receives social feedback
4. Notifications are sent to the content creator

Personalized Content Positive Feedback​

Representative Companies: Zillow, Credit Karma, Netflix

1. Users subscribe or add
2. New content appears
3. Users are notified or receive a push feed
4. Users see and like the content

Non-Scalable Channels​

PR, promotions, holiday features, conferences, content marketing, partnerships, and app store feature updates. These are all drivers that can attract people into these positive feedback loops, but they are not the positive feedback itself. These drivers are either difficult to attribute or hard to sustain over time.

Only Live "Day 1" = Without Growth, There is Death​

The office building where Amazon CEO Jeff Bezos works is called "Day 1." Over the years, no matter which other building he moves to, he always brings this same name with him. Therefore, he has a lot of authority on this term.

Someone might ask, what is "Day 2"? Day 2 is stagnation, followed by irrelevance, then suffocating, painful decline, and finally, death.

This is why Bezos believes that every day should be Day 1; without growth, there is death. So how do we prevent "Day 2"? There are four foundations.

A True Obsession with Customers​

There are countless business strategies, but why focus on "obsession with customers"? The benefits are numerous, with the biggest being: Customers are always dissatisfied, even when they say they are satisfied. Customers often don’t know what they truly want: they actually want something better. If you want to serve customers well, you must create products and services in their name. For example, the Prime service was not something customers asked Amazon for, but the results proved it was indeed what they wanted.

Maintaining "Day 1" requires patience; you need a lot of experimentation and to accept failure. Planting seeds and growing saplings takes time, but once you see what makes users happy, double down on it.

Resisting Proxies​

As companies grow larger, we often tend to rely on proxies or intermediaries. This form of dependency can take many shapes and is very much "Day 2." Here are two examples:

1. Relying on processes as proxies for results. Good processes serve you, allowing you to better serve customers. You must never serve the process. Why? When you serve the process, you only focus on doing the process correctly, regardless of the outcome. When failures occur, only inexperienced leaders say, "We followed the process," while seasoned leaders say, "We found an opportunity to improve the process." Constantly ask yourself, does the process own us, or do we own the process?

2. Relying on market research and customer surveys as proxies for customers. When you invent and design products, relying on research can be dangerous; "satisfaction increased from 47% to 55%" is a vague statement that can be misleading.

   1. Good investors and designers deeply understand customers; they invest significant energy in developing intuition and study numerous fascinating anecdotes rather than average data from surveys. They exist to design.
   2. Bezos does not oppose public testing and surveys; they help you identify blind spots, but as a provider of products and services, you must prioritize your vision and unique value over customer feedback. Exceptional customer experiences begin with intuition, curiosity, playfulness, courage, and taste—qualities that user surveys cannot provide.

Embracing External Trends​

The trends of the world favor those who align with them and doom those who resist. These trends are not hard to identify, but strangely, large companies often struggle to embrace them. One such trend today is machine learning and artificial intelligence.

Over the past few decades, many tasks could be solved with precise rules and algorithms; next, with machine learning, we can tackle tasks that cannot be described by exact rules.

Much of what happens in machine learning occurs at the foundational level, out of sight, but you can at least call them very simply via APIs.

Fast Decision-Making​

"Day 2" companies make high-quality decisions, but their decision-making speed is very slow. To maintain the energy and vitality of "Day 1," you must make "high-quality and high-speed" decisions. This is important not only because "speed" matters in the business world but also because having an atmosphere of "fast decision-making" is more enjoyable.

How can you achieve fast decision-making? Bezos does not have a complete answer, but here are some thoughts:

1. Decisions are inherently unequal; never treat them all the same. Reversible decisions should use lightweight decision-making processes.

2. Most decisions can be made when you have 70% of the information. Waiting until you have 90% may be too late. Also, in either case, you must quickly identify and address bad decisions. When you are highly responsive, making mistakes is cheap, while being slow is costly.

3. Use a management style of "==I disagree, but I commit to executing well==." This saves a lot of time spent on disputes.

   1. When no one knows the outcome, ask, "I know we have a disagreement, but are you willing to take a gamble with me? I disagree, but I commit to executing well?" The answer you get is likely to be, "Sure."
   2. The party that disagrees does not commit out of indifference but from a genuine and sincere disagreement, allowing the other party to reconsider your "disagreement" while still acting quickly due to your commitment.

4. Identify misalignments early and escalate them immediately. Sometimes, goals between teams conflict, and disputes at the same level cannot be resolved, wasting a lot of time and energy. In such cases, escalating will make decision-making faster and easier.

Every aspiring entrepreneur knows that creating something no one wants is a fatal trap. This is why we must conduct the right data analysis. The book "Lean Analytics" provides entrepreneurs with some good metrics for evaluating success.

Moving in the Right Direction, Then Data-Driven​

Data is vital for business. Entrepreneurs need to use data to persuade others. Sometimes, entrepreneurs tend to overestimate their success, but data does not lie. It can help founders stay grounded. However, personal judgment on which data to pursue is also important. Entrepreneurs should not simply become slaves to the numbers.

What Are Good Metrics?​

To collect data, you need to find metrics that can provide meaningful information. Good metrics have three characteristics:

• Comparable: A good metric can be compared across different time periods and consumer groups.
• Understandable: Good metrics are simple and easy to comprehend.
• Ratios: Metrics are often ratios because they are effective and comparable.

The Five Stages Startups Will Experience​

• Empathy Stage: Identify people's needs and define your niche market.
• Stickiness Stage: Discover how to meet those needs with products that keep users coming back.
• Growth Stage: Add features that attract users.
• Revenue Stage: The business starts generating income.
• Scaling Stage: Expand or penetrate new markets.

Focus on One Metric​

To achieve success, founders must focus on the most critical metric. Knowing what the most important metric is can prevent you from getting lost in the world of data.

What Are the Best Metrics?​

There is never a one-size-fits-all best metric. The best metrics vary across different industries. For e-commerce companies, the most important metric is revenue per customer. But for media websites, the most important metric is click-through rate.

Every aspiring entrepreneur should always be aware of the deadly pitfall of building something that nobody wants. That is why the right kind of analytics becomes so necessary. The book Lean Analytics introduces good metrics for start-up founders to navigate through the unknown and assess their success.

Data-driven in the right direction​

Data is vital to business. Entrepreneurs need data to convince others that their ideas will work. Sometimes, entrepreneurs tend to overestimate their success but data will not lie. Data helps founders to stay grounded in reality. However, personal judgement of what data to pursue is also important. Don’t be just a slave to numbers.

What are good metrics?​

In order to stay data-informed, you need to find some metrics which can provide meaningful data. Good metrics have three characteristics:

• Comparable: a good metric can be compared to different time periods, groups of consumers and so on
• Understandable: a good metric is simple and easy to comprehend
• Ratios: ratios are effective and comparable

Five distinct stages by the Lean Analytics framework​

The Lean Analytics framework suggests a start-up will go through five stages:

• Empathy — identify a need that people have / identity your niche market
• Stickiness — figure out how to satisfy the need with a product
• Virality — add features that attracts people
• Revenue — the business starts to grow and generate revenue
• Scale — expand or break into new markets

Focus on one metric​

To achieve success, founders must focus on one metric that’s most critical. Knowing what is the most important metric prevents you from getting lost in the data world.

What’s the best metric?​

There is no best metric in general. In different industries, the best metric differs. For E-commerce companies, the most important metric is revenue per customer. However, for media sites, the best metric is the click-through rates.

When you know where to go, it is often too late; if you always stick to the original path, you will miss the road to the future.

Charles Handy illustrates this with the analogy of "David's Bar": on the way to "David's Bar," you should turn right up the hill when you are half a mile away. However, by the time he realized he was going the wrong way, he had already arrived at "David's Bar."

Growth curves are typically S-shaped, which we refer to as the S curve. To keep the growth rate consistently high, you must invest time and resources to develop a second S curve while there is still time.

Intel's CPUs, Netflix's video streaming, Nintendo's games, and Microsoft's cloud services are all excellent examples of businesses driven by this second curve.

How can you discover and seize the second curve? You need to input more information, discern good from bad, and identify opportunities. Then, once the opportunity arises, having a strong team to tackle the hard work is essential to determine whether you have truly found the second curve.

The reasons that made you successful in the past may not lead to future success; growth always has its limits. The second curve theory helps us reflect on why and how to embrace change for a better life.

Facebook's VP of Growth, Alex Schultz, once discussed with Mark Zuckerberg why they succeeded. The answer isn't that they are exceptionally smart or experienced, but rather that they work incredibly hard and execute effectively. Compared to execution, growth is optional. Everyone understands the reasoning; the difference lies in whether people can execute quickly.

Execution is challenging, and there are ten reasons why growth execution fails.

1. Not starting with retention. Growth without retention is like a ring of fire in a wheat field; it will eventually burn out. Without retention, there is no Product-Market Fit (PMF). A sign of achieving PMF is that the retention curve in cohort analysis flattens out.

2. Believing the product is everything. Based on this misconception, people tend to mistakenly focus on "doing more" with the product rather than "doing better" with the existing product. Growth is a process of "doing better." Builders love to create new things, but as a leader, you need to ensure they are at least partially accountable for the results.

3. Looking for a silver bullet. Great products are polished through time and effort spent on details, not conjured up like magic. Good ideas are a byproduct of having many ideas; you can't control the outcome of finding good ideas, but you can create a process that allows more good ideas to emerge.

4. Lack of focus. It's about cutting down one at a time, not chopping at everything in sight. How do you break through the threshold effect here? Remember two points: 1) Most companies' primary scale comes from a single channel, and 2) There are only a few methods to scale; choose one.

5. Insufficient data and analysis. The challenge here is that it's hard to quantify the output of data analysis, so you must firmly believe that this is very valuable, as it enables you to make the right choices.

6. Not enough experimentation, far from it. HubSpot ran thousands of experiments in just six months.

7. Not asking why. When an experiment ends poorly, they just move on to the next one without asking why.

8. Not doubling down on successes. If you find a channel that works exceptionally well and hasn't been fully utilized, continue to invest in it. Zynga discovered that a virtual gift in one game was highly profitable and that viral marketing worked exceptionally well, so they immediately added this feature to all their games.

9. Insufficient resource allocation. Growth requires dedicated teams to focus on it.

10. Unable to embrace change. A company's growth typically goes through three stages: Traction, Transition, Growth. The reasons for success in one stage won't necessarily help you succeed in the next stage.

Question: For Hubspot's freemium and fully automated (touchless) software business, how can one achieve the highest growth in the least amount of time while being VC-backed?

Solution: The Four Fits Model identifies four interrelated elements that drive company growth: product, market, channel, and model. The author believes these four factors are interconnected and must align with each other.

PMF: Product-Market Fit. There are two types of companies in the world: tailwinds companies and headwinds companies, with the distinction being PMF. Achieving PMF means your product has a group of users who repeatedly engage over time, generating enough profit to support continued growth; it means your product has sticky users, resulting in a retention curve that may decline over time but ultimately levels off.

PCF: Product-Channel Fit. The attributes of the product itself determine the best channels for promotion. Simple, universal products correspond to inexpensive, mass-market channels, while complex, niche products correspond to specialized channels.

CMF: Customer Acquisition and Business Model Fit. On the ARPU ↔ CAC spectrum, high ARPU corresponds to high CVC; low ARPU corresponds to low CVC. The concern is that if ARPU is set too high, low CAC users cannot afford it, and if ARPU is set too low, there won't be enough revenue to sustain high CAC.

MMF: Business Model and Market Fit. Our goal is ARPU × total consumers in the market × the proportion of consumers you can capture >= $100 million. If this equation does not hold true, you need to adjust your business model to increase your pricing or target a broader user base.

When using this growth model, there are several key points to consider:

1. The premise is a target VC-backed $100 million business.
2. If you want to change one element, you must adjust others accordingly.
3. The elements themselves are constantly evolving.
4. It is best not to change too many elements at once; if you are unfamiliar with the related fields, you may struggle to manage the changes.