Hacking Growth
The book is a step-by-step plan that guides practitioners from a variety of companies through the process of Growth Hacking
Intro
The book is divided into two parts. The first part, “The Method” provides an overview of the process and how to organize Growth Teams.
The second part, “The Growth Hacking Playbook” offers detailed tactics for implementing the method, including separate chapters on user acquisition, activation, retention, and monetization, as well as how to maintain and accelerate growth once achieved.
Problem formulation
One of the most popular illusions is the “Fallacy of the Field of Dreams” when entrepreneurs believe that creating an outstanding product is enough, and customers will come to it themselves. However, this is far from reality. Many startups face high churn rates. Traditional marketing methods, including print and TV advertising and new online formats, are losing their effectiveness.
69.8 million Internet users in the US (up 34 percent year over year), including nearly two out of three millennials, report using ad blocking software.
At the same time, a significant portion of companies continue to focus on so-called “vanity metrics” that look good on paper but do not reflect real growth in product usage or revenue. For example, the number of visits to a site may impress but does not indicate the quality of user engagement.
The lack of focus on data analysis leads to companies relying on Google Analytics, which cannot effectively integrate various data sources, such as sales and customer service. This limits their ability to make valuable discoveries that could lead to growth.
In most product companies, the task of increasing user activation and retention falls not on marketers but on product and engineering teams that focus on building features that help users fall in love with the product. However, these groups rarely collaborate, creating additional barriers to successful growth.
Growth hacking helps overcome these challenges by combining data, cross-functional teams, and innovative methods to achieve real results in customer acquisition and retention.
What is Growth Hacking
Growth Hacking is a method that can be easily adapted to the specific needs of any team or company, regardless of their size or stage of growth. It allows you to extract specific, relevant insights into user behavior in real time from data. These insights can be used to shape growth strategies.
This approach has become the basis for a methodology aimed at accelerating market growth through high-velocity experimentation. The philosophy is similar to that of Agile or Lean Startup. Both have transformed business models and product development, while Growth Hacking focuses on customer acquisition, retention, and revenue growth.
The most significant successes in this area are achieved through a combination of programming knowledge, data analytics skills, and a strong marketing background. Key elements include creating a cross-functional team that breaks down traditional barriers between marketing and product development and using both qualitative research and quantitative data analysis to deeply understand user behavior and preferences.
Growth hacking is not about throwing ideas against the wall as fast as you can to see what sticks, it’s about applying rapid experimentation to find and then optimize the most promising areas of opportunity.
The key aspect of Growth Hacking is the rapid generation and testing of ideas using rigorous metrics to evaluate results and make further decisions. This method allows companies to grow fast without spending money on outdated and expensive marketing campaigns with questionable business value.
About processes in Growth teams
One of the important rules for starting high-speed experimentation is to understand that the product has reached the Must-Have state. For this, it is useful to conduct a so-called Must-Have Survey. If 40% of users answer that they will be “very disappointed” if the product is not available, we can assume that the product has sufficient must-have status. However, if the product is already far beyond the initial development stage, such a survey is not recommended. Imagine if Facebook publishes a survey tomorrow and asks about disappointment from its absence.
As the product develops, it is important to regularly monitor Retention metrics to notice problems in time and not relax, even if a stable base of loyal users has been achieved.
Analysis of user behavior helps to understand what exactly they do but does not always reveal why they do it. Therefore, for successful growth, it is critical to understand what the main value of the product is, who its target audience is, and why it is irreplaceable for them. You need to communicate with users to study their true needs. To do this, you need to “get out of the building” and find out what customers want from the product.
Even the most sophisticated analysis can really only tell you definitively what users are doing, not why they’re behaving that way.
Growth teams play an important role in experimenting with new features and collecting feedback, whether through prototypes or beta versions. Experiments to validate ideas should be low-cost, in the form of a “Minimum Viable Test” (MVT). This could be a prototype or demo that can be used to see how users react. It is important to record the results of experiments in a report and store them in a knowledge base so that future teams can refer to past experiences.
Effective analysis requires creating what’s often called a data lake or data warehouse, where all customer information is collected to identify distinct user groups and their unique behavior patterns. An example of the importance of good data is the Facebook team’s decision in 2009 to pause all experiments for a month to focus on improving data collection and processing processes, highlighting the key role of accurate data for product growth.
Now a little about prioritization and hypothesis generation. Prioritization of ideas for testing is carried out according to the ICE (Impact, Confidence, Ease) system, where each idea is assessed based on its impact, confidence in success, and ease of implementation. During prioritization, it is also worth paying attention to the impact of the experiment per unit of time. For example, you should not “move buttons”, especially at the initial stages, when traffic is low. Such experiments will require a lot of time for testing and will most likely have little impact. It is better to postpone them to a later stage.
When generating hypotheses, it is worth sticking to a standard form and description, which should contain information about what you want to test, why it should have an impact, and how to measure it.
Based on the results of the tests, if the results are equal, preference should be given to the control option in order to avoid potential risks.
Growth teams should also periodically switch to different stages of the funnel — from user acquisition to activation, and then to retention. Many of the best ideas arise unexpectedly, and their implementation requires flexibility.
About the structure and organization of Growth teams
Effective Growth Teams require a multidisciplinary approach, bringing together specialists from different departments, such as marketing, product, engineering, and analytics. This facilitates collaboration and helps teams share knowledge and better understand each other’s views and challenges. This interaction is especially useful for generating new ideas, where, for example, engineering and marketing can work together to create interesting “hacks” to experiment with.
Growth teams should bring together staff who have a deep understanding of the strategy and business goals, those with the expertise to conduct data analysis, and those with the engineering chops to implement changes in the design, functionality, or marketing of the product and program experiments to test those changes.
Typically, product teams follow a clear roadmap for updates, including feature or onboarding process improvements, but as the company grows and processes become more complex, such teams may work less flexibly.
Creating a separate Growth Team with its leader allows you to focus on specific tasks necessary for growth. This leader, combining the roles of manager, product owner, and analyst, is responsible for choosing priorities and key metrics that the team will strive to improve.
There are two main organizational models for Growth Teams. Within the first, functional structure, teams report to product management and focus on experiments to improve all stages of the growth funnel.
The second model involves the allocation of an independent growth team that reports directly to the VP of Growth or even directly to the CEO. Such independent teams are easier to form in the early stages of the company, while organizational structures are not yet fixed.
It is worth mentioning separately the involvement of external experts. These individuals can help the team think outside the box and offer new perspectives. However, handing over key growth responsibilities to outsiders carries risks—they may not have the authority or motivation to drive long-term, sustainable growth. Growth Teams also need support from senior management to avoid bureaucracy, conflict, and inertia that can slow down growth. External teams will have a hard time getting that support.
Fundamental growth equation
To grow, it’s important to boil down complex business operations to a simple formula that captures the key drivers of growth. This allows growth teams to focus on key signals, separating them from the data deluge.
A key element of the formula is the so-called North Star metric — a metric that most accurately reflects the core value delivered to customers. It helps the team stay on track and not get distracted by irrelevant metrics that may be attractive, but do not contribute to real growth.
Creating visual reports and dashboards that reflect progress on North Stars and key growth levers is important. This makes the data more accessible and visible to everyone in the company, helping to ensure that data-driven thinking becomes part of the culture at all levels of the organization, not just the growth team.
Marketing channels
Successful marketing requires taking into account the specifics of your business model and user behavior, such as types of Google queries, preferred stores, and social networks.
One method of prioritizing channels is to rank them by six factors, assigning each channel a high, medium, or low score, and then calculate the average to prioritize channels for experiments:
- Cost — how much do you expect to spend to run the experiment
- Targeting — how easily can you reach your target audience in the experiment
- Control — can you make changes to the experiment after it runs, or stop and adjust it
- Time to run — how much time and resources will it take your team to run the experiment
- Time to exit — how long will it take to see results from the experiment after it runs
You should also consider the cost of customer acquisition — if it exceeds your potential revenue, that’s a problem. Growth Hacking is about finding the most cost-effective methods of acquiring new customers and optimizing them for sustainable growth.
When changing focus to a new growth driver, it’s important to re-analyze the data to find unique insights for the new goal. Even if you have already found working channels, it is always worth looking for innovative methods for testing.
Aha moment
Aha moment is the moment when users begin to understand the value of the product for themselves. Why they might need it, and what benefit they can get from using it.
98 percent of traffic to websites does not lead to activation, and most mobile apps lose up to 80 percent of their users within three days.
To understand whether a product has “aha” potential, find loyal users by collecting data and feedback, and then understand how these people use the product, and what value it gives them. It can also be very useful to compare data on how users who tried the product and became regular users differ from those who tried it and left.
Analyze each point of the user’s path to reaching the aha moment. Build a funnel report measuring conversions at each stage. Even if you think you already know everything, after this exercise you can find many surprises.
A simple formula worth remembering: DESIRE — FRICTION = CONVERSION RATE
Language
Sometimes achieving growth results requires not a change in the product, but an adjustment in the communication of value to potential and current customers. Even small changes can have a significant impact.
Simply changing the language from “Sign Up for Free Trial” to “See Plans and Pricing” netted 200 percent more sign-ups.
The initial phase of customer growth involves achieving two key fits:
- Language/market fit, where the language used to describe the product resonates with the target audience
- Channel/product fit, where the chosen channels, such as search advertising or content marketing, effectively deliver the product to the right audience. This covers all aspects of communication, from emails and notifications to promotional materials and text on product interfaces.
The key requirement for language is that it answers the customer’s question: “How will this improve my life?” Successful headlines and copy can have a significant impact on reach and perception. Therefore, when testing growth strategies, you should focus on the language and style of communication and then move on to other aspects.
“A good headline can be the difference between 1,000 people and 1,000,000 people reading,”
New User Experience
The basic principles of creating and optimizing the New User Experience (NUX) include an approach in which this stage is perceived as a separate product, requiring a unique design. The first landing page should clearly reflect the relevance of the product to the query, show its value to the user, and contain a clear call to action.
The value of the product should quickly answer the question: “What will I get?”, and the call to action should encourage the user to take the next step. Sometimes it is useful to immediately let the user try the product, before signing up, to reduce friction and get to the “aha” moment faster.
This is your moment. You have more attention than you ever will have again, from that user, to try to teach them what your product is really about. To really help them learn the product in a meaningful way.
However, not all friction is bad — adding “positive friction” (e.g. gradual steps) helps users understand the product better and is achieved through experimentation. Methods based on Mihaly Csikszentmihalyi’s “flow” theory and the principle of gradual involvement are also effective. Such methods are constantly used in the Game industry to gradually introduce the player to the game world and the main mechanics.
The team also tested adding more text around the call to action to encourage sign-ups, inserting a testimonial from a happy Airbnb customer. This additional text actually hurt sign-ups. This is an example of a more subtle type of friction, which isn’t actually experienced as annoying, yet still deters visitors or users from taking the action you want them to. You can really only discover whether this kind of friction exists—and how it is impacting your activation rates—through experimentation.
If you decide to experiment with positive friction, it is useful to use questionnaires and gamification elements. Questionnaires with several questions aimed at the interests and problems of users create a sense of involvement and strengthen the connection with the product. Neil Patel advises limiting the number of questions to five and making them with a choice of up to four answer options, as well as adding visual elements to increase engagement.
Now users were first shown just one screen, which asked them to select five topics that they were interested in. After they made their selections, the app delivered them to a feed made up solely of that type of content, where they could practice pinning and saving items. The change resulted in a 20 percent increase in activation rate, a massive win.
The principles of forming “stored value” are also actively used: the more information users enter into the product, the higher their involvement. Useful techniques include surveys and gamification, for example, welcome questionnaires with short questions about the user’s preferences and goals.
Virality
For most products, getting users to send and accept invites requires significant initial experimentation and ongoing optimization. Successful virality is achieved through a balance between how well the product is “packaged” and its value. Finding words that will grab users’ attention is important, but true value is essential to achieving viral growth.
There are several types of virality: traditional (word of mouth) and instrumental — when the product includes features that help users invite new participants. In this case, the experience of the sharing product itself should be intuitive and enjoyable.
A product is considered truly viral if the virality coefficient (K-factor) is greater than 1, i.e. each new user attracts at least one more. The main factors of virality are payload (the number of invitations sent), the conversion of invitations, and the frequency with which people receive invitations. This formula should be taken into account when creating viral engagement cycles.
The choice of invitation delivery method is important for the formation of a natural flow of new users. The best viral engagement loops are created when invitations are integrated into the product and emerge naturally through use.
Often, you want to motivate users through a two-way reward, where both the sender and the recipient benefit. The reward must be related to the product: the closer the value of the incentive is to the product, the more effective it will be. Effective viral loops motivate users to invite others because it improves their own experience with the product.
A common mistake is not optimizing enough for the invited users. When an invitee accepts an invitation, it is important not to immediately ask them to sign up, but first to show the value of the product so that they understand why they should join.
Gamification
Gamification should be viewed as a toolkit rather than a fixed set of tactics that work for all businesses.
The key aspects of gamification include providing meaningful rewards, creating surprise and enjoyment by changing the way rewards are received and presented, and adding an element of instant gratification. Effective rewards in a gamified environment include status, access, power, and tangible rewards (such as financial incentives or gifts).
Triggers work best when they both motivate the user to take the desired action and make it as easy as possible to do so when the trigger is given. The best approach to using triggers is to provide users with information about an opportunity that is useful to them. Triggers fall into three categories based on the user’s motivation and ability:
- Facilitator — helps highly motivated but low-skilled users take action.
- Signal Trigger — targets highly motivated and low-skilled users, helping them stay on track for repeat actions.
- Spark — motivates high-skill, low-motivation users to take action.
It is also useful to consider Robert Cialdini’s six principles of persuasion:
- Reciprocity — people tend to reciprocate favors, even if the reciprocal action is different from the original.
- Commitment and Consistency — people who have done one action are more likely to take another, regardless of the magnitude.
- Social Proof — people rely on the actions of others when faced with uncertainty.
- Authority — users are more likely to follow the recommendations of authority figures.
- Liking — people are more likely to engage with companies and people they like.
- Scarcity — people are willing to act faster if they fear missing out on future opportunities.
Retention
To effectively retain users, companies need to find the right balance in communication: successful messages and their frequency directly affect the loyalty of the audience. In digital products, retention also increases if users find value in the product that only strengthens over the years — as in the case of Evernote, where the likelihood of users returning increases over time due to “stored value”.
Retention can be divided into three phases.
In the initial phase, the main goal is to help the user quickly understand the main benefit of the product so that he decides to stay.
Creating a deeper level of attachment can be achieved through so-called “continuous learning”. The better users master the product, the higher the likelihood of their return. An approach called “continuous onboarding” can be useful, which guides the user along the learning curve of new functionality. This approach is similar to learning to play a musical instrument or to learn a language — the product always offers something new.
According to data published by mobile intelligence company Quettra, most mobile apps, for example, retain just 10 percent of their audience after one month, while the best mobile apps retain more than 60 percent of their users one month after installation.
An important aspect is the perception of the value of rewards. Interestingly, intangible rewards (such as status or access to exclusive features) are often more effective than financial incentives. In the long term, such rewards can become habitual and valuable to users.
Finally, in the long-term phase, it is necessary to continuously maintain the feeling of value of the product, ensuring its relevance and usefulness to the user. To do this, it is useful to update the perception of the product as something “indispensable”.
A long-term retention strategy also involves a combination of improvements to current features and notifications about regular launches of new functionality. These updates and innovations (especially for SaaS products, video games, and content platforms) create a sense of upcoming improvements in users. However, messages about such innovations need to be balanced so as not to irritate with a long wait.
If a user’s activity gradually fades, they can be re-engaged through a process called “resurrection,” which is typically done through targeted advertising and emails that remind them of products or new features designed to meet their needs. When users stop interacting with the product, they can be added to the “resurrection” flow by sending them a series of messages with offers that are likely to pique their interest.
When analyzing retention rates, it’s worth comparing them to industry averages and competitor data to establish objective benchmarks and develop a retention strategy.
Accurate analysis often requires breaking the audience into cohorts — subgroups that can be analyzed based on different retention metrics. Specialized tools (such as Mixpanel, Kissmetrics, and Amplitude) can help with this process, especially if you don’t have a dedicated data analyst on your team.
Business products, such as software as a service, fare much better, with annual retention rates north of 90 percent, according to a study of private SaaS companies done by Pacific Crest in 2013. A 2013 study concluded that credit card companies in the US see annual churn rates of roughly 20 percent, while European cellphone carriers see churn of anywhere between 20 and 40 percent.
Monetization
To successfully monetize a company, it is important to conduct a deep analysis of the data to identify experiments with the greatest potential.
You need to start by building a customer journey map, which will allow you to see at what stages the client brings in the most revenue and where losses occur. After that, it is important to divide customers into cohorts, focusing on which groups bring in the most revenue. This division can be supplemented with other criteria: location, age, gender, acquisition sources, device type, first visit or purchase, etc. Instead of analyzing retention, at this stage, it is worth looking for correlations with revenue, which will give ideas for new experiments.
In some countries, for example, in the US, subscription models are perceived better than in others. This creates an opportunity to test different monetization models by region. One of the proven ways to increase profits is to offer users additional products or features.
Personalization also works for monetization: recommendations can be built, for example, using the Jaccard coefficient. What the equation says is that the similarity between two items, A and B, is equal to the size of the intersection of A and B divided by the union of A and B. However, excessive personalization can cause discomfort for users.
Another common mistake companies make is setting fixed prices, which can and should be tested like other elements of the business. It is important to conduct such experiments at least once a quarter. Dynamic pricing that takes into account factors such as seasonality, purchase history, and device type can also significantly improve profits.
The comparison pricing effect can be managed by offering intermediate options that lead users to more expensive products. For example, companies sometimes introduce a decoy product with limited functionality and a price slightly lower than the main one, which encourages users to choose more expensive offers. This is because users tend to see a high price as an indicator of quality, especially in areas such as technology and professional services. To maintain the customer experience, users must see the same version of the pricing page on repeat visits.
In some cases, such as digital products, even small payments can scare away users, and therefore offering a free tier can be more profitable. An example is the limitations of the free version: Spotify clearly shows its free users the possibilities of a premium account, pushing them to buy it.
Most freemium product conversion rates, [...] hover around 1 percent.
To increase revenue, companies can experiment with subscriptions for upgrades, virtual goods, and in-game currency. Understanding consumer psychology can also help monetize a product. The core principles discussed earlier, such as reciprocity (the desire to reciprocate a benefit provided), consistency (the tendency to repeat an action), social proof (the influence of others’ opinions), authority, likability, and scarcity, are important tools for increasing sales.
Applying these principles, for example by adding testimonials and logos of famous customers, can increase customers’ desire to make a purchase. The principle of scarcity, which creates a sense of “missed opportunity,” is also effective in pushing for action.
Finally, for growth, it is important to overcome the local maximum effect, when the result of improvements ceases to increase. Switching to a new approach, such as changing the structure of the pricing page, can open the way to higher results.
Continuous Cycle of Growth
Business growth is often achieved through many small successes that accumulate over time. This process can be described as a continuous cycle consisting of four main stages: first, analyzing data and collecting insights, then generating ideas, then prioritizing experiments, and finally executing them. Once the experiments are complete, the cycle returns to the analysis stage, where the results are reviewed and next steps are determined.
One of the key aspects of successful growth is the ability to increase the average revenue per customer. This allows more resources to be directed toward growth, creating a so-called “virtuous cycle” where growth itself contributes to further growth.
All growth hackers must always keep in mind that, as the growth team at Airbnb says, “love creates growth, not the other way around.”
However, companies often face the problem of “feature overload,” where the rush to add many new features results in a product that is inferior in quality. Rather than improving, feature overload can confuse users and distract them from the core value the product offers.
Research shows that having too many features can have a negative impact on long-term customer retention. For example, in a study conducted for the Marketing Science Institute, researchers concluded that companies should focus on creating more, more focused products with a limited set of features, rather than trying to include every possible feature in a single product. In this context, reducing the excess can lead to more successful results than constantly adding new features.
The right approach to growth, then, involves not only innovation and experimentation but also paying close attention to what already exists, so as not to lose the value the product brings to its users.
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