Hacking Growth: How Today’s Fastest-Growing Companies Drive Breakout Success

Quick Orientation

Hacking Growth: How Today’s Fastest-Growing Companies Drive Breakout Success by Sean Ellis and Morgan Brown presents a systematic methodology for achieving rapid and sustainable business growth. The book argues that traditional marketing approaches are often insufficient in today’s fast-paced digital landscape. Instead, it advocates for a data-driven, cross-functional, and experimentation-focused approach pioneered by some of the most successful tech companies.

The authors provide a detailed playbook that breaks down the growth process into key stages: acquisition, activation, retention, and monetization. By applying a scientific method of continuous analysis, idea generation, prioritization, and testing across these stages, companies can discover and optimize the most effective strategies for driving breakout success. This summary promises to cover every core idea, example, and actionable step presented in the book, ensuring readers gain a complete understanding of the growth hacking methodology.

INTRODUCTION

The Introduction sets the stage by highlighting the limitations of traditional marketing and introducing the concept of growth hacking through early success stories.

The Problem with Traditional Marketing

Traditional marketing methods like print ads, television commercials, and even early online banner ads are becoming less effective and more expensive. The internet audience is plateauing in developed markets, ad-blocking software is prevalent, and streaming services reduce exposure to traditional commercials. Studies show no correlation between marketing investment and growth rates for software companies, and CEOs often question marketing’s business credibility.

• High Costs: Traditional advertising is increasingly expensive as competition for attention rises.
• Declining Effectiveness: Consumers are tuning out ads through various technologies and habits.
• Unmeasurable Results: It’s often difficult to tie traditional marketing spend directly to business growth.
• Slowing Internet Audience: The pool of new internet users in major markets is growing slowly, increasing competition for existing users.

The Emergence of Growth Hacking

Growth hacking emerged from Silicon Valley startups that needed to grow rapidly with limited budgets against established competitors. These companies integrated technical know-how with marketing goals to build growth into the product itself. Early examples demonstrated the power of novel, low-cost approaches using technology.

• Uproar: Created an embeddable single-player game widget offered to other websites, paying affiliates per new player acquired, achieving explosive growth against larger competitors.
• LogMeIn: Used email surveys to learn why free users weren’t converting to paid, discovered a trust issue (users didn’t believe it was truly free), and optimized landing page copy and design, leading to a 700% increase in profitable search ad scaling.
• Hotmail: Added “P.S.: Get Your Free Email at Hotmail” tagline to every email sent, creating a viral loop.
• PayPal: Created AutoLink tool that automatically added PayPal logo and sign-up link to eBay auction listings, igniting viral growth on the platform.
• LinkedIn: Enabled easy uploading and inviting of email contacts, kicking network effects growth into high gear.
• Airbnb: Reversed engineered Craigslist to cross-publish listings, driving massive traffic and bookings for free before being blocked.

What is Growth Hacking?

Growth hacking is a rigorous approach to fueling rapid market growth through high-speed, cross-functional experimentation. It relies on harnessing software development to build marketing into products and using data to find, reach, and learn from customers.

• Core Elements: Cross-functional teams, qualitative research and quantitative data analysis, rapid idea generation and testing, rigorous metrics.
• Origin: Developed by startups facing fierce competition and limited budgets, often by engineers applying agile and Lean Startup principles to customer growth.
• Versatility: Applicable to product innovation, continuous product improvement, and growing existing customer bases in businesses of all sizes and industries.

Who Can Become a Growth Hacker?

Anyone involved in building, growing, or improving a product or business can adopt growth hacking principles. It’s not limited to marketers or entrepreneurs.

• Roles: Product developers, engineers, designers, salespeople, managers can all contribute.
• Company Size: Effective in both large established companies and small startups.
• Scope: Can be implemented company-wide or for a single campaign or project.

Why Growth Hacking Now?

Several factors make growth hacking essential for businesses today.

• Surviving Disruption: Companies must be agile and innovative to avoid being overtaken by faster-moving competitors, often leveraging technology.
• The Need for Speed: The business landscape changes rapidly; growth hacking’s high-tempo experimentation allows companies to adapt quickly.
• Mining Data Gold: Growth hacking provides a method for extracting actionable insights from the vast amounts of available customer data.
• Rising Costs of Traditional Marketing: It offers a more cost-effective way to grow compared to increasingly expensive and less effective traditional methods.
• Getting the Jump on New Technology: It fosters cross-functional collaboration needed to adopt and leverage new platforms quickly.

Myth Busting

Several misconceptions about growth hacking need clarification.

• Myth 1: Silver Bullet: Growth comes from a series of small, compounding wins, not just one brilliant hack.
• Myth 2: Lone Ranger: Growth hacking is a team effort combining diverse expertise, not the work of a single individual.
• Myth 3: Breaking Rules: While some famous hacks involved workarounds, most successful growth relies on aboveboard strategies and building value.
• Myth 4: Only About Acquisition: Growth teams focus on the entire customer funnel: acquisition, activation, retention, and monetization.
• Myth 5: Only About Marketing: Growth teams are involved in product development, strategy, and leveraging data across the business.

Growth hacking is a fundamental business methodology for achieving meaningful results with limited investment and maximum return on marketing dollars. The book is organized into two parts: Part I explains the method, and Part II provides a playbook of specific hacks.

PART I : THE METHOD

CHAPTER ONE: BUILDING GROWTH TEAMS

Chapter One delves into the structure and composition of effective growth teams, emphasizing the necessity of breaking down traditional departmental silos for optimal collaboration and performance.

The Problem of Silos

Traditional business structures often organize teams into isolated departments like marketing, product, engineering, and data science. This siloing impedes effective collaboration, slows innovation, and makes it difficult to develop customer-centric products and strategies because departments lack shared information and priorities.

• Impeded Innovation: Lack of cross-departmental communication slows down the process of updating existing products and creating new ones.
• Customer Focus Issues: Engineers and product designers may lack direct insight into customer needs and desires.
• Inefficient Processes: Product development and marketing efforts are often sequential and disconnected, creating delays.
• Misaligned Priorities: Departments may focus on their own goals rather than a unified business objective like growth.

The BitTorrent Example

The BitTorrent mobile team’s success illustrates the power of cross-functional collaboration. Initially organized in traditional silos, their mobile app adoption was sluggish. A product marketing manager (PMM) started collaborating with the product team, using customer feedback to identify growth opportunities not just in acquisition but throughout the funnel (activation and monetization).

• Survey Insights: A PMM’s survey revealed users didn’t know about the paid version, leading to a simple button change that increased revenue by 92%.
• “Love Hack”: Analyzing user data showed negative reviews impacted downloads. Encouraging reviews after the first torrent download led to a 900% increase in positive reviews and a boost in installs.
• Engineered Solutions: Engineers used user feedback (battery drain) to build a popular “battery saver” feature for the paid version, significantly increasing revenue.
• Cultural Shift: The success of the mobile team’s data-driven, collaborative approach inspired other teams and led to increased investment in data science and a more open company culture.

The Necessity of Cross-Functional Teams

Growth hacking requires bringing together individuals with diverse expertise to work collaboratively towards a shared growth goal. This breaks down silos, facilitates information sharing, and sparks innovative solutions.

• Diverse Skills: Teams need people with expertise in data analysis, engineering, product management, and marketing.
• Shared Goal: All team members are aligned around driving growth metrics.
• Faster Execution: Collaboration accelerates the process of generating, testing, and implementing growth ideas.

The “Who”: Roles on a Growth Team

An effective growth team comprises members with specific skills, though roles may be combined in smaller teams.

• The Growth Lead: Acts as a manager, product owner, and scientist, setting the focus area, tempo, and goals for the team, monitoring progress, and running meetings. Requires fluency in data analysis, product management, and experimentation design.
• Product Manager: Oversees product development and features, contributing customer insights and product expertise to the team.
• Software Engineers: Write code for product changes and experiments, bringing technical creativity and understanding of new technologies to ideation.
• Marketing Specialists: Provide expertise in various marketing channels (content, SEO, email, etc.) and help design and implement promotional experiments.
• Data Analysts: Collect, organize, and analyze data, design rigorous experiments, compile results, and provide insights into user behavior and test outcomes.
• Product Designers: Develop user interfaces and experiences, offer insights into user psychology, and create necessary design elements for experiments.

The “Size and Scope” of Growth Teams

Growth teams can vary greatly in size and focus depending on the company’s needs and stage of growth.

• Size: Can range from a few individuals to over a hundred members.
• Scope: Can be broad (growing all areas) or specific (optimizing a single feature or channel).
• Structure: Can be permanent or temporary, dedicated units or composed of existing staff.
• Evolution: Teams often change in size, scope, and responsibilities over time.

The “How”: The Growth Hacking Process Cycle

The growth hacking process is a continuous loop of four key steps managed by regular team meetings.

• Analyze: Data analysis and insight gathering to understand user behavior and identify opportunities.
• Ideate: Generating a large volume of ideas for potential growth experiments.
• Prioritize: Evaluating and ranking ideas to determine which to test.
• Test: Running experiments and collecting results.
• Cycle: The process circles back to analysis to review results and plan next steps.

The Growth Meeting

Regular, focused meetings are crucial for managing the growth hacking cycle, reviewing progress, prioritizing experiments, and maintaining tempo.

• Frequency: Typically held once a week.
• Purpose: Review results, discuss ideas, prioritize experiments, assign ownership.
• Collaboration: Facilitates the amplification of expertise through discussion and debate.

Executive Sponsorship Required

Strong support from high-level executives is critical for growth teams to succeed, granting them the authority to cross departmental boundaries and prioritize growth initiatives.

• Authority: Executives ensure growth teams can prioritize their work and access necessary resources.
• Commitment: Leadership must prioritize growth throughout the company.
• Alignment: Executives help align the entire company around growth goals.

The Reporting Structures for Teams

Growth teams typically report either functionally (to a product management executive) or as a stand-alone unit (to a VP of Growth who reports to senior leadership).

• Product-Led Model: Teams report to a product manager responsible for a specific product or set of products. Easier to implement in established firms.
• Independent-Led Model: Stand-alone teams with authority across products, reporting to a dedicated VP of Growth. Easier to establish early in a company’s development.

Melding Minds and Dismissing Lore

Establishing growth teams can face resistance due to ingrained organizational cultures, conflicting priorities, and different professional perspectives. Overcoming this requires data-driven decision-making and demonstrating success.

• Cultural Friction: Traditional silos and norms create resistance to cross-functional collaboration.
• Conflicting Priorities: Growth experiments may compete with established project roadmaps.
• Diverse Perspectives: Different professional backgrounds can lead to disagreements on what is important.
• Data-Driven Decisions: Using data to evaluate ideas and results helps overcome subjective biases and build consensus.
• Demonstrating Success: Early wins build enthusiasm and break down resistance.

Teams Evolve

Growth teams are not static; they evolve in size, composition, and focus as the company grows and its needs change.

• Scaling: Teams grow from a few members to multiple dedicated units focusing on specific areas (acquisition, retention, international growth, etc.).
• Adapting Focus: Team mandates shift as the company’s priorities change.
• Adding Specialists: External experts or temporary members can be brought in for specific initiatives.
• Avoiding Stalls: Continuous evolution helps prevent complacency and maintain focus on growth.

A Growth Hack to Start Growth Hacking

Implementing growth hacking doesn’t have to happen company-wide all at once. Starting small with a focused team on a specific problem can build momentum and prove the methodology’s value.

• Start Small: Begin with a small team focused on a narrow area (a single product, feature, channel, or metric).
• Get Buy-In: Secure support from peers and supervisors to navigate inevitable stumbles.
• Focus on Must-Have: Ensure the product has core value before aggressively pushing for growth.

The chapter concludes by emphasizing the critical prerequisite for growth: ensuring your product is a “must-have.” The next chapter will detail how to determine if your product has achieved product/market fit.

CHAPTER TWO: DETERMINING IF YOUR PRODUCT IS MUST-HAVE

Chapter Two stresses that a product must be truly loved by its users before aggressive growth efforts can be successful. It introduces methods for determining if a product has achieved “must-have” status and understanding its core value to its target market.

The Baseline Requirement for Growth

Rapid and sustainable growth is only possible if a product is “must-have” in the eyes of a large group of people. Launching products without this core value, or failing to identify it, leads to wasted resources and market rejection.

• Must-Have Status: A product that users feel they cannot live without.
• Wasted Resources: Promoting a product that isn’t loved is inefficient and costly.
• Market Rejection: Products lacking core value will fail to achieve sustainable adoption.
• Negative Word of Mouth: Disappointed early users can quickly spread negative feedback.

The Flameout of BranchOut

The story of BranchOut, a Facebook professional networking app, serves as a cautionary tale about pushing for viral growth without delivering a compelling product experience. Despite rapid user acquisition through clever hacks, users quickly abandoned the app because it lacked value.

• Aggressive Growth Hack: Used a workaround to bypass Facebook’s invite limit, leading to millions of new users quickly.
• Lack of Product Value: Users found little utility in the app once they joined.
• Rapid Churn: The surge of new users was followed by an equally rapid decline.
• Wasted Investment: Despite significant funding, the company ultimately failed due to poor retention.

What’s the Aha Moment?

The “aha moment” is when a user truly understands and experiences the core value of a product. This experience is what converts early adopters into power users and evangelists. Identifying this moment is crucial for successful growth.

• Core Value: The fundamental benefit a user derives from the product.
• User Understanding: The moment the product’s utility clicks for the user.
• Conversion: The experience transforms casual users into loyal ones.
• Examples: Yelp (finding local businesses through reviews), eBay (finding unique items at auction), Facebook (connecting with friends and family), Dropbox (easy file sharing).

Identifying the Aha Moment

Sometimes the aha moment is obvious, but often it requires investigation to discover. It might be tied to a specific feature, usage pattern, or target audience. Growth teams must use data and user feedback to pinpoint this moment.

• Usage Patterns: Analyzing how active users interact with the product can reveal the actions associated with the aha moment (e.g., following 30 people on Twitter).
• Tipping Point: Identifying the specific usage threshold after which users are significantly more likely to be retained (e.g., 50 survey responses for Qualaroo, 2,000 messages for Slack).
• Unexpected Discoveries: The most valuable insights may come from observing user behavior that differs from initial assumptions.

The Two-Part Must-Have Assessment

A simple, two-part assessment helps determine if a product has achieved sufficient must-have status.

• Part 1: The Must-Have Survey: A survey asking users how disappointed they would be if the product no longer existed.
• Threshold: More than 40% of respondents answering “Very disappointed” indicates strong growth potential.
• Diagnostic Questions: Additional questions probe reasons for disappointment or satisfaction, alternative products used, primary benefits, and suggestions for improvement.
• Target Audience: Surveys should be targeted at active users to gather meaningful insights.
• Part 2: Measuring Retention: Analyzing the rate at which users continue to use the product over time.
• Stable Rate: A consistent retention rate indicates a core group of users who see the product as worthy of continuous use.
• Benchmarking: Comparing your retention rate to industry standards and competitors helps assess performance.
• Frequent Tracking: Monitoring churn and retention rates regularly provides early warning signs of problems.

Getting to Must-Have

If a product doesn’t meet the must-have threshold, the focus must be on understanding why and improving the product or targeting before pushing for growth. Relying on conjecture is dangerous; instead, use analytical methods.

• Avoid Guessing: Don’t rely on internal assumptions about what will improve the product.
• Talk to Users: Conduct interviews and surveys to understand the true objections and barriers to success.
• Observe Behavior: Watch how prospective users interact with the product in real-world settings.
• Minimize Feature Creep: Adding too many features without a clear understanding of value can make products cumbersome.
• Focus on Core Value: Improvements should aim to deliver the identified aha moment more effectively.

Getting Out and About in the Analog World

Conducting customer interviews and observing users interact with the product in person provides invaluable qualitative data that complements quantitative analysis.

• Customer Interviews: Talk to users to understand their needs, desires, and how they perceive the product’s value. Be dispassionate and listen actively.
• “In the Wild” Testing: Observe users interacting with the product or prototypes in realistic settings to identify usability issues and unexpected behaviors.
• Etsy Example: Meeting crafters at fairs helped Etsy understand the importance of community and influencer networks, guiding their growth strategy away from traditional advertising.
• Tinder Example: Focusing on college fraternities and sororities with in-person visits helped identify a tightly networked initial market and understand user motivations.

Finding a Community to Survey

Identifying and engaging with existing communities where your target audience is already active provides a concentrated pool for gathering insights and finding early adopters.

• Online Platforms: Leverage social networks, app stores, forums, and groups where your potential users gather.
• PayPal on eBay: Observed eBay sellers using PayPal and interviewed them to understand their needs, leading to the creation of the AutoLink tool.

Efficient Experimentation

Testing changes to the product and messaging is crucial for achieving must-have status. Experiments should be designed for speed and rigor.

• Minimum Viable Test (MVT): Run the least costly experiment that can adequately vet an idea before investing heavily.
• Mix of Tests: Run a combination of complicated product changes and easier messaging/marketing tests to maintain tempo.

Experimenting to Get Language/Market Fit

Optimizing the language used to describe and market the product is essential. A/B testing is a powerful and often inexpensive method for this.

• A/B Testing: Compare two versions of messaging to see which resonates better with the target audience.
• Iterate Quickly: Use tools that allow for rapid sequential testing of different copy and design elements.
• Learn from Results: Even small changes can have significant impacts on sign-ups and conversions.

Experiments Within the Product

More complex experiments involve making changes to the product itself. These require more engineering time and should be based on strong hypotheses derived from user research and data.

• Prototype Testing: Test changes or new features with a small group of users before wide release.
• Data-Driven Hypotheses: Base costly product changes on insights from data analysis and user feedback.
• Balancing Risk: Mix bigger, riskier initiatives with more certain incremental improvements.

Taking a Data Dive

Analyzing customer data is fundamental to understanding user behavior and uncovering insights that lead to growth ideas. Go beyond basic metrics to get a detailed picture.

• Unified Data Store: Collect and combine data from all customer interaction points (website, app, sales, customer service, etc.).
• Event Tracking: Identify and track key user actions within the product or service.
• Identify Behavioral Patterns: Look for differences in behavior between active and inactive users.
• Cohort Analysis: Segment users based on shared characteristics or behaviors to find correlations with engagement and purchasing.

What Are Active Users Doing?

Focus on identifying the specific actions and features used by your most avid users to understand what drives their engagement.

• Correlations: Look for links between user attributes, behaviors, and higher engagement or purchasing.
• Netflix Example: Analyzing viewing habits revealed the popularity of Kevin Spacey and political dramas, influencing the decision to produce House of Cards.
• RJMetrics Example: Identified that editing charts correlated with conversion to paid customers, leading them to emphasize this action in new user orientation.

Pivoting to the Unexpected

Deep data analysis can reveal surprising insights that lead to fundamental product pivots. Successful companies often iterate significantly based on observed user behavior.

• Instagram (from Burbn): Analysis showed users were only using the photo-sharing feature, leading to a pivot and the creation of Instagram.
• Pinterest (from Tote): Observed users stockpiling items on the app, leading to a pivot to a discovery and sharing site focused on visual collections.
• Groupon (from The Point): Noticed success in campaigns offering group buying power, leading to the pivot to daily deals.
• YouTube (from video dating): Realized users were uploading videos of all types, leading to a pivot to a general video-sharing platform.
• Invalidating Lore: Data-driven analysis can challenge ingrained assumptions about products and markets.
• HubSpot Example: Data showed paid training increased retention, leading to a policy change that defied industry norms but fueled growth.

Driving to the Aha

Once the aha moment and the conditions that create it are identified, growth efforts should focus on getting more users to experience that moment as quickly and effectively as possible.

• Facebook: Identified that users who added at least seven friends in ten days were more likely to stay active, leading to NUX optimizations focused on finding friends.
• Twitter: Identified that following around 30 people led to higher retention, leading to NUX changes emphasizing suggestions of accounts to follow.
• Qualaroo: Identified that receiving at least 50 survey responses led to higher conversion, leading to efforts to help trial users reach this threshold.
• Prioritize NUX: Many companies dedicate significant resources to optimizing the new user experience to drive users to the aha moment.

Achieving product/market fit is the essential foundation for successful growth hacking. The methods outlined in this chapter provide the framework for determining if your product is a must-have and understanding what truly drives value for your users.

CHAPTER THREE: IDENTIFYING YOUR GROWTH LEVERS

Chapter Three focuses on crafting a strategic approach to growth by identifying the key factors and metrics that drive your business forward. It emphasizes the importance of focus and rigorous prioritization before launching into high-tempo testing.

The Importance of Focused Growth

Having a must-have product isn’t enough; companies need a well-designed and executed strategy for driving growth. This involves understanding your specific growth levers and focusing efforts on the most impactful ones.

• Beyond Must-Have: A great product still requires a strategy to reach and engage a large audience.
• Ineffective Spending: Without focus, companies risk wasting resources on acquisition efforts that don’t lead to sustainable growth (e.g., Everpix).
• Intentional Experimentation: Growth hacking is about applying rapid testing to the most promising areas, not random experimentation.
• High Impact First: Especially for smaller teams, prioritize experiments with the greatest potential for impact to produce definitive results faster.

Hacking Your Growth Strategy

Defining your growth strategy involves understanding what drives growth for your specific product or business and identifying the metrics that matter most.

• Fundamental Growth Equation: A simple formula representing the key factors that combine to drive your growth (your core growth levers). This equation is unique to each product or business.
• Examples: Inman News (Website Traffic × Email Conversion Rate × Active User Rate × Conversion to Paid Subscriber + Retained Subscribers + Resurrected Subscribers = Subscriber Revenue Growth), eBay (Number of Sellers Listing Items × Number of Listed Items × Number of Buyers × Number of Successful Transactions = Gross Merchandise Volume Growth).
• Beyond Vanity Metrics: Focus on metrics that directly correlate to users experiencing the core value of your product, not just surface-level numbers like page views.

The Metrics That Matter

Identify the specific actions users take that indicate they are experiencing the core value of your product and build your metrics around these actions.

• Core Value Metrics: Track actions that lead users to the aha moment and how often they take those steps.
• Uber Example: Essential metrics for riders include rides completed, return booking rate, and booking frequency.
• Yelp Example: Core factors are the numbers of businesses reviewed and the number of reviews per business.
• LinkedIn Example: Total sign-ups was a crucial metric because the value was tied to the number of profiles, not just active users.
• Context is Key: A metric that is important for one business may be meaningless for another (e.g., Daily Active Users for Facebook vs. Airbnb).

Choosing a North Star

Select one key metric of ultimate success that all growth activity is geared toward. This “North Star” metric acts as a guiding light to keep the team focused.

• Guiding Light: The metric helps the team stay focused on the ultimate goal of creating value for customers.
• Represents Core Value: The North Star should accurately capture the delivery of the must-have experience.
• Examples: eBay (Gross Merchandise Volume – GMV), WhatsApp (Number of Messages Sent), Airbnb (Nights Booked).

Setting New Sights

The North Star metric may evolve as the company grows and its priorities shift. Larger companies may have multiple teams with their own North Stars aligned with the overall company goal.

• Evolution: The key metric can change over time (e.g., Facebook shifting from monthly to daily active users).
• Multiple Teams: Different growth teams within a large company may focus on specific North Stars (e.g., LinkedIn’s teams for different growth areas).

Illuminating the Best Bets

Dedication to improving the North Star metric helps teams make difficult decisions about which experiments to prioritize, avoiding investing time and resources in initiatives that won’t significantly impact the ultimate goal.

• Avoiding the Moors: The North Star prevents teams from getting lost in irrelevant metrics or vanity metrics.
• Data Over Emotion: The metric provides an objective basis for evaluating ideas and abandoning unsuccessful experiments.
• Airbnb Example: Focusing on “Nights Booked” led to the discovery that photo quality was a critical lever, despite initial assumptions focusing on driving traffic.

The Data Imperative

Having the ability to gather and analyze customer data is a fundamental prerequisite for identifying growth levers and measuring experiment results. This “instrumentation” is essential for making informed decisions.

• Instrumentation: Setting up data tracking to measure product performance and user behavior.
• Unified Data Store (Revisited): Combining data from multiple sources provides a complete picture of the customer journey.
• Facebook Example: The growth team stopped all experiments for a month to improve data tracking, leading to a much richer understanding of user behavior and new experiment ideas.
• Accessibility: Data should be collected and analyzed in a way that is accessible and understandable to the entire growth team.

It’s Not All About the Numbers

While quantitative data is crucial, qualitative data from user surveys and interviews is equally important for understanding the why behind user behavior and uncovering hidden insights.

• Understanding Motivations: Data tells you what users are doing, but qualitative feedback explains why.
• Identifying Roadblocks: Surveys and interviews can uncover issues or desires that data alone cannot reveal.
• Complementary Data: Qualitative insights should be used to inform and interpret quantitative analysis.

Design Accessible Reporting

Presenting data and experiment results in a clear, simple, and accessible way (often through dashboards) is essential for keeping the team focused and encouraging data-driven behavior throughout the company.

• Dashboards: Visual representations of key metrics that make trends and progress immediately clear.
• Focus and Clarity: Dashboards help teams prioritize and avoid getting overwhelmed by data.
• Company-Wide Sharing: Making results visible encourages participation and data-driven decision-making across the organization.
• Actionable Insights: Reports should highlight trends and implications for future experiments.
• Metrics as Ratios: Present metrics in a way that allows for comparison over time (e.g., per day, per week).

Putting It All Together

The Twitter example demonstrates how identifying growth levers, conducting in-depth data analysis (including cohort and correlation analysis), and supplementing it with qualitative user feedback can lead to the discovery of critical insights that fuel growth.

• Cohort Analysis: Segmenting users to identify patterns in behavior and retention.
• Correlation Analysis: Looking for links between specific behaviors and outcomes (e.g., number of people followed on Twitter and retention).
• Qualitative Confirmation: Using interviews to understand the reasons behind observed correlations and validate hypotheses.
• Twitter’s Aha Moment: Discovering that following around 30 people and a specific follower ratio correlated with long-term engagement.
• Iterative Discovery: The process of analysis and feedback led to a deeper understanding of what made Twitter “sticky.”

Identifying your growth equation, selecting a North Star metric, and establishing robust data collection and analysis are foundational steps for successful growth hacking. This strategic focus prepares the team for high-tempo experimentation, the subject of the next chapter.

CHAPTER FOUR: TESTING AT HIGH TEMPO

Chapter Four introduces the core engine of growth hacking: high-tempo experimentation. It explains why speed is crucial, how to manage the experimentation cycle, and provides practical guidance for generating, prioritizing, and running experiments effectively.

Why Tempo Matters

The fastest-growing companies are the ones that learn the fastest. Running a high volume of experiments, even if many fail, leads to more learning, which in turn fuels more wins and compounding growth over time.

• Learning Rate: The more experiments you run, the more insights you gain about what works and what doesn’t.
• Finding Wins: Finding successful experiments is a numbers game; a higher volume increases the chances of discovering breakthroughs.
• Compounding Gains: Small wins, when layered on top of each other, lead to significant cumulative growth.
• Speed Advantage: Rapid experimentation allows companies to adapt to market changes and outlearn competitors.
• Small Gains, Big Impact: Even small improvements in conversion or retention rates can lead to substantial increases in revenue due to compounding effects.

Tempo Picks Up Over Time

The volume of experiments a team can run increases as they gain experience and the company grows. A disciplined process is essential for maintaining a high tempo without sacrificing quality.

• Start Slow: Begin with a manageable number of experiments per week to build competence and avoid errors.
• Build Velocity: Gradually increase the number of experiments as the team becomes more proficient.
• Disciplined Process: A structured approach to idea generation, prioritization, and execution is needed to manage high volume.
• Avoiding Sloppiness: Poorly designed or implemented tests can lead to invalid results and wasted effort.

The Growth Hacking Cycle (Revisited)

The four-part continuous cycle (Analyze, Ideate, Prioritize, Test) provides the framework for high-tempo experimentation. Each cycle is managed by a regular growth meeting.

• Analyze: Review data and insights from previous experiments and ongoing monitoring.
• Ideate: Generate new ideas based on analysis and brainstorming.
• Prioritize: Evaluate and select ideas for testing based on a scoring system.
• Test: Launch and run the selected experiments.
• Continuous Loop: The cycle repeats, feeding new learning back into the process.

Preparing for Liftoff

Before starting the regular cycle, hold an initial team meeting to establish roles, clarify the process, review initial data, define the North Star and focus area, and set a tempo goal.

• Initial Meeting: Explain the process, assign roles, and set expectations.
• Review Initial Data: Discuss preliminary analysis and insights.
• Define Focus: Clarify the key growth levers and metrics the team will target.
• Set Tempo Goal: Agree on a realistic number of experiments to launch per week.

STAGE 1: ANALYZE (Cycle Begins)

At the start of each cycle, the team focuses on analyzing data and gathering insights to inform idea generation.

• Data Dive: Work with the data analyst to explore user behavior, identify patterns, and uncover potential growth opportunities.
• Guiding Questions: Formulate specific questions about user behavior and characteristics to direct the analysis.
• User Research: Conduct surveys and interviews to understand the why behind the data.
• Synthesize Findings: Summarize key observations and insights to share with the team.

STAGE 2: IDEATE

Generate a large volume of ideas for potential growth experiments. Encourage creativity and discourage self-censorship at this stage.

• Pipeline: Maintain a system (spreadsheet, software) to collect and manage ideas.
• Templated Format: Standardize idea submissions with a clear description, hypothesis, and metrics to be measured.
• Cross-Company Contribution: Encourage ideas from individuals across different departments and even outside the company.
• Focus on Specifics: Ideas should articulate the exact change, rationale, and measurement method.
• Quantity Matters: Generate many ideas to increase the chance of finding valuable ones.

STAGE 3: PRIORITIZE

Evaluate and rank the generated ideas using a scoring system to determine which to test next. This process brings structure and objectivity to decision-making.

• Scoring System: Use a framework like ICE (Impact, Confidence, Ease) to rate each idea.
• Impact: Potential degree of improvement on the target metric.
• Confidence: Belief that the idea will achieve the expected impact, based on evidence.
• Ease: Time and resources required to implement the experiment.
• Aggregate Score: Calculate an average score for each idea to rank them.
• Relative Prioritization: Score and rank ideas based on the current area of focus.
• Mix of Tests: Select a combination of potentially high-impact, complex tests and easier “low-hanging-fruit” experiments.
• Review and Nominate: Team members review the idea pipeline and nominate promising candidates for discussion in the growth meeting.

STAGE 4: TEST

Launch and run the selected experiments. This stage requires strong cross-functional collaboration to prepare and deploy the tests.

• Up Next Queue: Move selected experiments to a dedicated list for the current testing cycle.
• Assign Owners: Designate a team member responsible for managing each experiment.
• Cross-Functional Collaboration: Work with necessary individuals from other departments to implement the test.
• Notifications: Inform others in the company about experiments being launched to avoid conflicts or confusion.
• Roadblocks: Address delays or issues promptly and adjust the testing schedule as needed.

Testing Rules of the Road

Follow guidelines to ensure experiments produce statistically valid results and avoid misleading conclusions.

• Statistically Valid Results: Design tests rigorously to minimize the risk of false positives or negatives.
• 99 Percent Confidence Level: Aim for a higher confidence level (99%) to increase the reliability of winning test results.
• Control Always Wins: If results are inconclusive, stick with the original version; the new variant may be a long-term loser.

BACK TO STAGE 1: ANALYSIS AND LEARNING

Once experiments are concluded, analyze the results and document the key lessons learned to inform future idea generation and prioritization.

• Analyze Results: Evaluate the performance of experiments based on the predefined metrics.
• Test Summary: Document the details of each test, including the hypothesis, metrics, results, and conclusions.
• Knowledge Base: Store all test summaries in an easily searchable database for future reference.
• Share Learning: Communicate key findings (wins, losses, inconclusive results) with the entire growth team and potentially other departments.

THE GROWTH MEETING

The weekly growth meeting is the central mechanism for managing the high-tempo experimentation cycle. A structured agenda ensures efficiency and focus.

• Regular Cadence: Hold the meeting consistently (e.g., every Tuesday).
• Preparation: Growth lead reviews prior week’s activity, updates metrics, gathers test results, and prepares the agenda.
• Agenda:
  • Metrics Review and Update Focus Area: Discuss overall growth metrics and confirm or change the team’s focus area.
  • Review Last Week’s Testing Activity: Assess the tempo of experiments launched and discuss any delays.
  • Key Lessons Learned from Analyzed Experiments: Review test results, discuss implications, and codify conclusions.
  • Select Growth Tests for Current Cycle: Discuss nominated ideas and collectively decide which experiments to launch in the coming week, assigning owners.
  • Check Growth of Idea Pipeline: Review the number of ideas in the pipeline and encourage continued ideation.

GROWTH WITHIN WEEKS

The high-tempo growth hacking process can produce significant improvements and learning within a short timeframe, often just a couple of weeks.

• Rapid Results: Simple experiments can yield conclusive results quickly, leading to immediate improvements.
• Iterative Learning: Even failed experiments provide valuable insights that inform subsequent tests.
• Compounding Wins: A series of rapid experiments can lead to a significant cumulative impact on growth.

The high-tempo experimentation process, managed through the structured growth hacking cycle and weekly meetings, is the engine that drives rapid learning and compounding growth. Part Two of the book will explore specific tactics and hacks for each stage of the customer funnel.

PART II : THE GROWTH HACKING PLAYBOOK

CHAPTER FIVE: HACKING ACQUISITION

Chapter Five focuses on the crucial task of gaining new customers, emphasizing cost-effectiveness and strategic channel selection. It introduces methods for crafting compelling messages, identifying optimal distribution channels, and leveraging viral mechanisms.

The Challenge of Costly Acquisition

Acquiring new customers is essential, but it’s increasingly expensive. Companies must find cost-effective ways to attract users, especially when facing limited budgets or fierce competition. High acquisition costs coupled with poor retention can lead to financial ruin.

• Rising Costs: Online advertising expenses are increasing as competition for attention grows.
• Sustainability: The expense of acquiring a customer must be lower than the revenue they generate over time (LTV).
• Cautionary Tale (Fab): Spent excessively on customer acquisition, leading to unsustainable costs and failure.
• Strategic Spending: Sometimes high upfront spending is necessary (e.g., “winner take all” markets), but requires a plan to recoup costs.
• Cost-Effectiveness: Always strive to acquire customers as efficiently as possible.

Hacking Your Acquisition Strategy

Acquisition efforts should focus on achieving language/market fit and channel/product fit before a full-scale push. The growth hacking process helps discover the most effective and cost-efficient methods.

• Language/Market Fit: Ensuring the way you describe your product resonates with your target audience.
• Channel/Product Fit: Identifying the most effective marketing channels for reaching your intended audience.
• Data-Driven Approach: Use analysis and experimentation to find the best fits.

Crafting a Compelling Message

Language/market fit is crucial for capturing attention quickly in today’s crowded landscape. Crafting concise and persuasive messaging that communicates core value is key.

• Attention Spans: Messages must grab attention and convey value rapidly (within seconds).
• Core Value Communication: Clearly articulate the product’s main benefit or “aha moment.”
• User-Centric Language: Focus on how the product improves the customer’s life.
• Steve Jobs Example (iPod): Reframed portable music players with “1,000 Songs in Your Pocket,” highlighting core value.
• Experimentation: Use A/B testing to iterate and optimize messaging across various platforms (website, email, ads).
• Sources for Language: Draw inspiration from customer feedback, reviews, social media, and support interactions.
• Upworthy Example: Used a rigorous testing process for headlines to maximize virality, demonstrating that creativity can be hacked.

Start Small (with Language)

Often, small changes in language can have significant impacts on acquisition. Experimenting with these minor tweaks is a cost-effective way to start optimizing.

• Tickle Example: Changing website copy from “store your photos online” to “share your photos online” dramatically increased user acquisition.
• Dating App Example: Changing the tagline from “Find a Date” to “Help People Find a Date” ignited viral growth by repositioning the app socially.

Language Fit Helps Hone Your Product, Not Just Your Branding

Experimenting with language can not only improve marketing copy but also reveal insights that lead to changes in branding and even the product itself.

• Product Influence: Language that resonates with customers can highlight aspects of the product that should be emphasized or improved.
• Procter & Gamble (Febreze): Market research on user behavior revealed that focusing on scent and using it as part of a cleaning routine was a more effective positioning than highlighting odor elimination.
• Nasty Gal: Learning the language their target customers used influenced the brand’s identity and messaging.

Finding Channel Fit is Not Like Portfolio Management

Diversifying acquisition efforts across many channels is often less effective than focusing intensely on optimizing one or two key channels that are the best fit for your business.

• Focus is Key: Concentrating resources on a few high-potential channels yields better results than spreading efforts thinly.
• “More Wood Behind Fewer Arrows”: Prioritize channels that are most likely to work for your specific product.
• Distribution is Crucial: Getting even a single distribution channel to work effectively can lead to significant business success.

Narrowing the Field

Identify potential channels and filter them down based on your business model, target audience behavior, and experimentation.

• Categorize Channels: Group channels into viral/word-of-mouth, organic, and paid.
• Business Model Alignment: Identify channels that align with your business type (e.g., sales team and trade shows for B2B).
• User Behavior: Consider where your target audience spends time online and how they search for solutions.
• Prioritize for Experimentation: Select a few promising channels for initial testing.

Experimenting to Get Channel/Product Fit

Use a prioritization method to evaluate potential channels based on factors like cost, targeting, control, input time, output time, and scale. This helps select the most promising channels for experimentation.

• Prioritization Factors: Evaluate channels based on specific criteria relevant to your business and resources.
• Scoring System: Assign scores to each factor for potential channels to create a ranking (e.g., using a numerical scale).
• Collaborative Selection: Discuss and collectively decide which channels to prioritize for testing.
• Iterate on Channels: Continuously experiment with new channels and optimize existing ones as your business grows and market conditions change.

Optimizing Your Experiments

Once channels are identified, focus on optimizing specific tactics within those channels through rapid experimentation.

• Drill Down: Once a channel shows promise, invest in optimizing various aspects of your approach within that channel.
• Facebook Ad Example: If Facebook ads are effective, experiment with different targeting, messaging, and creative elements.
• Organic Channel Optimization: If email marketing or website promotion works, test different subject lines, calls to action, and placements.

Keep Trying New Things

Even when established channels are working, continuously explore and experiment with new channels and tactics to stay ahead and avoid growth stalls.

• Evolving Landscape: New online platforms and marketing tactics emerge constantly.
• First User Advantage: Being an early adopter on a promising new platform can provide a significant growth edge.
• Channel Saturation: Existing channels may reach a point where they yield diminishing returns.
• Layer on Additional Channels: Introduce new channels as needed to sustain growth.
• Organic Channels are Crucial: Don’t overlook or deprioritize organic methods, which can be powerful long-term drivers.

Designing Customer Loops (Viral Growth)

Viral loops are mechanisms built into a product that encourage users to bring in new users. While powerful, they are not “set it and forget it” solutions and require continuous optimization.

• Viral Loops: Mechanisms (like referral programs) that leverage existing users to acquire new ones.
• Instrumented Virality: Features explicitly designed to facilitate sharing and referrals.
• Beyond “Set It and Forget It”: Effective viral loops require significant effort to create and optimize.
• Must-Have Prerequisite: Viral growth is only sustainable if the underlying product delivers core value.

Understanding Viral Dynamics

Sean Parker’s formula (Virality = Payload × Conversion Rate × Frequency) provides a simple way to think about the factors that drive viral growth. Focus on optimizing these variables.

• Payload: The number of people each user is likely to invite at once.
• Conversion Rate: The percentage of invited people who accept the invitation.
• Frequency: How often users are exposed to the opportunity to invite others.
• Optimize Variables: Experiment with different approaches to increase payload, conversion, and frequency.
• Avoiding Dark Patterns: Don’t use manipulative tactics that annoy users, which can harm long-term growth.

Best Practices for Designing Viral Loops

Several strategies can increase the effectiveness of viral loops while providing a good user experience.

• Tap Network Effects: Design loops where users are incentivized to invite others because it improves their own product experience (e.g., social networks, marketplaces).
• Synergistic Incentives: Offer rewards that are relevant to the core value of your product (e.g., free storage for Dropbox, discounts for a grocery app).
• Integrated Prompts: Make the invitation to share a seamless part of the user experience, not an afterthought on a rarely visited page.
• Good Invitee Experience: Ensure that the experience for people who receive an invitation is positive and encourages them to join.
• Continuous Experimentation: Viral loops require ongoing testing and optimization to maximize their effectiveness.

Acquisition is the first step in the growth funnel, and hacking it involves strategically selecting channels, crafting compelling messages, and leveraging viral mechanisms through rapid experimentation. The next chapter will focus on turning these new customers into active users.

CHAPTER SIX: HACKING ACTIVATION

Chapter Six focuses on turning newly acquired customers into active, engaged users. It outlines a systematic process for identifying and overcoming barriers to activation and introduces effective tactics for guiding users to the “aha moment” and building habit-forming products.

The Activation Challenge

A significant number of potential customers acquired never become active users. Improving activation rates is crucial for maximizing the return on acquisition efforts and building a sustainable user base.

• High Drop-Off: A large percentage of website traffic and app downloads do not lead to active use.
• Return on Investment: Low activation rates mean wasted money spent on acquiring inactive users.
• Must-Have Connection: Activation is fundamentally about getting new users to experience the product’s core value or “aha moment.”

Mapping the Route to the Aha Moment

The first step in hacking activation is to clearly define the steps users must take to reach the “aha moment.” This journey will be unique to each product.

• Identify Steps: List all the necessary actions a user must complete to experience the product’s core value.
• Grocery App Example: Steps include downloading the app, finding items, adding to cart, creating an account, purchasing, and receiving the order.
• Potential Barriers: Each step represents a point where users might lose interest or encounter difficulties.

Creating a Funnel Report of Conversions and Drop-Offs

A funnel report visualizes the conversion rates at each step of the customer journey to the “aha moment,” highlighting where users are dropping off. This data provides a roadmap for identifying problematic areas.

• Visualize the Journey: Display the percentage of users who move from one step to the next.
• Identify Sticking Points: Pinpoint the steps with the lowest conversion rates.
• Segment by Channel: Analyze conversion rates for users acquired through different channels to identify variations.
• Compare User Groups: Look for differences in behavior between active users, inactive users, and those who never activated.
• Tools: Use analytics platforms (Kissmetrics, Mixpanel, etc.) or data analysis to create and track funnel reports.
• Grocery App Insight: Data might reveal high drop-off rates at the checkout stage or low search volume among new users.

User Surveys and Interviews (Revisited for Activation)

Qualitative feedback from users is essential for understanding why users are dropping off at specific points in the activation funnel. Supplement quantitative data with direct user input.

• Probe for Causes: Use surveys and interviews to ask users about the difficulties they encountered or the reasons they stopped using the product.
• Targeted Surveys: Deploy surveys to users at specific points in the journey, especially where drop-off rates are high.
• Qualaroo Example: Surveying users revealed that receiving at least 50 survey responses was the key to activation, leading to experiments focused on helping users reach this threshold.
• Survey Dos and Don’ts: Keep surveys brief, ask relevant questions based on observed behavior, and consider open-ended questions to uncover unexpected insights.
• Ask Users Who Activated: Gather feedback from users who successfully navigated a difficult step to understand what helped them overcome the challenge.

Be Persistent and You’ll Get the Payoff

Improving activation is an iterative process that requires continuous experimentation and learning. Unexpected discoveries are common, and persistence is key even when initial experiments fail.

• HubSpot Sidekick Example: The team ran many experiments to improve activation, failing initially, but eventually discovered that a simple message after installation was a crucial trigger.
• Unexpected Discoveries: The most effective solutions may not be the ones initially hypothesized.
• Stay Nimble: Continuously adjust your approach based on experiment results.

Eradicating Friction

Friction refers to any hindrance that prevents a user from completing an action. Eliminating sources of friction in the user experience, especially in the new user experience (NUX), is crucial for improving activation.

• Hindrances: Obstacles that make it difficult or annoying for users to progress.
• “Is It Worth It?”: Friction can cause users to abandon the product if the perceived value isn’t high enough.
• Desire – Friction = Conversion Rate: A simple formula illustrating the impact of friction on conversion.
• Lower-Hanging Fruit: Eliminating friction is often easier than increasing user desire.
• Identify Friction Points: Use the funnel report and user feedback to locate where users are struggling.

Optimizing the New User Experience

The NUX is the critical first impression and should be designed to quickly engage users and guide them to the “aha moment.” Treat the NUX as a separate product requiring dedicated optimization.

• Treat NUX as a Product: Craft a dedicated and enticing experience for new users.
• Conversion Trinity: Ensure the NUX landing page communicates relevance, shows value, and provides a clear call to action.
• Language and Aesthetics: Experiment with messaging, design, and visuals to optimize engagement.
• Simplifying vs. Adding: Test stripping out unnecessary elements or adding helpful information.

Key Tactics for Reducing Friction in NUX

Several effective tactics can significantly reduce friction in the new user experience.

• Single Sign-On: Allow users to sign up using existing accounts (Facebook, Google, etc.) to simplify the process.
• Hello Bar Example: Allowing users to create their bar before signing up increased activation.
• Stripe Example: Allowing users to grab code and start using it before providing account details reduces upfront commitment friction.
• Warby Parker Example: The home-try-on program lets users experience the product before committing to a purchase.
• Testing is Crucial: What works for one product may not work for another, so always test these tactics.

Optimizing is a Push and Pull with Friction

While reducing friction is key, sometimes adding a small amount of “positive friction” can guide users and increase engagement.

• Positive Friction: Manageable steps that help users understand the product and progress towards the aha moment.
• Airbnb Example: Experimented with different frequencies and designs of sign-up prompts to increase sign-ups without negatively impacting bookings.
• Subtle Friction: Friction isn’t always obvious annoyance; it can also be elements that distract or deter users.

The Power of Positive Friction

Positive friction, often used in gamification and onboarding, can increase user commitment and guide them through the initial product experience by providing rewards and a sense of accomplishment.

• Commitment and Consistency: Getting users to take small actions upfront increases their likelihood of taking subsequent actions.
• Psychological Rewards: Provide a sense of satisfaction and accomplishment for completing tasks.
• Flow: Design the NUX to be engaging and appropriately challenging to get users into a state of “flow.”
• Stored Value: The more information or effort users invest in the product, the more committed they become.
• Facebook Profile Example: Filling out a profile creates commitment and provides psychological rewards.

Crafting a Learn Flow

For complex products, a dedicated “learn flow” within the NUX educates users about the product’s value and how to use it, taking advantage of their initial high attention levels.

• Purposeful Education: Guide users through key features and benefits.
• Twitter Example: The learn flow guided users to follow accounts and build their feed to experience the core value.
• Pinterest Example: Experimented with personalizing the learn flow by asking users about their interests to deliver relevant content immediately.

Additional Tactics for Positive Friction

Questionnaires and gamification can be effective ways to personalize the NUX, increase commitment, and guide users.

• Questionnaires: Ask users about their needs or interests to personalize their experience and create a sense of commitment.
• Gamification: Offer rewards and a sense of accomplishment for completing tasks or milestones in the NUX.
• Meaningful Rewards: Rewards should be relevant to the product’s value and genuinely appealing to users.
• Adobe LevelUp: Used gamification to make Photoshop tutorials engaging and increase trial-to-purchase conversion.
• Caution with Gamification: Ensure rewards are valuable and the approach doesn’t feel manipulative.

Ins and Outs of Triggers

Triggers (emails, push notifications, in-app prompts) can be powerful for re-engaging users, but they must be used judiciously to avoid annoying customers.

• Prompting Action: Triggers alert users to opportunities or encourage them to return.
• Motivation and Ability: The effectiveness of a trigger depends on the user’s motivation and ability to take action (Fogg Behavior Model).
• Avoid Annoyance: Excessive or irrelevant triggers can lead users to disable notifications or uninstall the app.
• Trigger Best Practice: Alert users to opportunities of clear value to them.
• Experimentation is Key: Test different types, frequencies, and messaging of triggers.
• Holdout Groups: Use control groups to measure the true impact of triggers.
• Types of Triggers: Experiment with triggers for account completion, purchases, reactivation, new features, and user activity.
• Cialdini’s Principles (Revisited): Leverage psychological principles (Reciprocity, Commitment, Social Proof, Authority, Liking, Scarcity) to craft effective triggers.
• Internal Triggers: The most powerful triggers are the subconscious ones that lead to habitual product use.

Activating customers is a critical step in the growth funnel, requiring a deep understanding of user behavior, mapping the journey to the “aha moment,” and using experimentation to remove friction and guide users effectively. The next chapter will explore how to keep these active users engaged over the long term.

CHAPTER SEVEN: HACKING RETENTION

Chapter Seven focuses on the essential task of keeping customers engaged and coming back to the product over time. It highlights the significant impact of retention on profitability and introduces strategies for analyzing churn, building habits, and delivering ongoing value.

The Profitability of Retention

High customer retention rates are crucial for achieving strong profitability. Acquiring new customers is expensive, so retaining existing ones significantly increases lifetime value and reduces the cost of growth.

• Increased Profits: Even small increases in retention rates lead to disproportionately higher profits.
• Reduced Acquisition Costs: Retaining customers means less money spent on acquiring new ones.
• Compounding Revenue: Loyal customers generate more revenue over time through repeat purchases or subscriptions.
• Amazon Prime Example: Demonstrates how a successful retention program can drive significant revenue and profit.
• Investment Fuel: Reliable earnings from retained customers allow for investment in further growth and innovation.
• Enhanced Viral Growth: Loyal customers are more likely to spread positive word of mouth and participate in viral programs.

Homing In on Best Bets Fast

Growth hacking allows teams to quickly identify problems with retention and experiment with solutions before significant numbers of users churn. Prioritizing experiments that address early signs of defection is crucial.

• Early Warning Signs: Monitor data for signs of user disengagement or churn.
• Prioritize Retention Experiments: Focus on hacks aimed at keeping users engaged, especially in the early stages.
• Rapid Iteration: Quickly test different ideas (notifications, promotions, features) to see what effectively re-engages users.

What Drives Retention?

Retention fundamentally depends on providing a high-quality, must-have product that continually meets user needs or delights them. A stable retention curve indicates that a core group of users is consistently finding value.

• Product Value: The core offering must provide ongoing utility or satisfaction.
• Stable Retention Curve: Indicates that a product has achieved a baseline level of stickiness.
• Erosion Factors: Competition, outdated product features, poor communication, or changing user needs can lead to declining retention.
• Beyond Stability: Strive to increase retention over time by continuously improving the product and user experience.
• Evernote Smile Graph: Illustrates how a product’s value can increase with continued use (stored value), leading to higher retention over time.

The Three Phases of Retention

Retention can be broken down into three distinct phases, each requiring different strategies and tactics.

• Initial Retention: The critical period where new users decide whether to stick with the product after their first or few visits. Focus is on solidifying the “aha moment” and encouraging early repeat use.
• Medium Retention: The period where the goal is to make product use a habit. Focus is on creating engaging loops and providing ongoing rewards.
• Long-Term Retention: The phase where the focus is on keeping engaged users happy over the long haul by optimizing existing features and introducing new value.

What Does Good Retention Look Like?

Defining “good” retention depends on the nature of the product or service and the typical frequency of use in that industry. Benchmark your retention rate against comparable products and companies.

• Product-Specific Metrics: Retention is measured differently depending on how often users are expected to return (daily for social media, less often for travel booking, etc.).
• Repurchase Rate: A key metric for e-commerce, measuring how often customers make repeat purchases within a given timeframe.
• Churn Rate: The inverse of retention rate, measuring the percentage of customers lost over a period.
• Benchmarking: Compare your retention and churn rates to industry standards to assess performance.

Identify and Chart Your Cohorts

Cohort analysis is essential for understanding retention patterns and identifying opportunities. Segment users into groups based on shared characteristics or behaviors to uncover why some users are retained better than others.

• Cohort Definition: Group users based on common traits (e.g., acquisition date, channel, features used).
• Overall Health: Tracking cohorts acquired at different times reveals the overall trend in customer base health.
• Problematic Trends: Identify cohorts with unusually high churn rates.
• Video Streaming Example: Analyzing cohorts acquired during specific campaigns revealed that some groups were churning quickly, prompting investigation into the reasons (e.g., content selection).
• Retention Curves: Visualize cohort data to easily identify patterns and compare the retention performance of different groups.
• Drill Down: Investigate cohorts with high churn to understand the specific factors contributing to their departure.
• Sophisticated Tools: Use advanced analytics platforms for detailed cohort analysis.

Hacking Initial Retention

Improving initial retention involves tactics similar to those used for activation, focusing on reinforcing the “aha moment,” streamlining the NUX, and using triggers to encourage early repeat use.

• Reinforce Aha Moment: Ensure new users fully experience the product’s core value quickly.
• Optimize NUX (Again): Continuously refine the initial user experience based on data and feedback.
• Strategic Triggers: Use timely and relevant notifications to encourage early repeat visits and engagement.

Building Habits

The core goal of medium-term retention is to make product use a habit. This is achieved by creating engaging loops where external triggers lead to actions that provide valuable rewards, eventually becoming internal triggers.

• Habit Formation: Integrating product use into a user’s regular routine.
• Engagement Loops (Hook Model): A process where a trigger prompts an action that provides a reward, leading the user back to the product.
• External Triggers: Initial prompts (notifications, emails) that initiate the loop.
• Rewards: The benefits users receive from using the product.
• Internal Triggers: Subconscious cues that lead to habitual use (e.g., having breakfast and checking Snapchat).
• Optimize the Loop: Continuously measure and refine the trigger, action, and reward components of the engagement loop.
• Amazon Prime Example: The program creates a strong habit by providing frequent and compelling rewards (free shipping, instant gratification) that reinforce the subscription value.
• Perceived Value: Increasing the perceived value of the rewards drives greater habit formation and retention.
• Reward Variation: Experiment with different types and frequencies of rewards.

Offer Rewards Both Tangible and Experiential

Effective rewards go beyond just monetary savings. Social and experiential rewards can be powerful motivators for building loyalty and habit formation.

• Tangible Rewards: Discounts, coupons, cash vouchers, physical gifts.
• Experiential Rewards: Enjoyable experiences provided by the product or service.
• Social Rewards: Recognition, status, belonging, community.
• Yelp Elite Squad: Combines social recognition with perks to incentivize writing reviews and build loyalty.
• Brand Ambassador Programs: Formal programs that leverage status and perks to incentivize advocacy and retention.
• Blending Rewards: Experiment with combinations of tangible and non-tangible rewards.

Additional Strategies for Habit Formation

Recognizing user achievements and customizing the relationship based on user data can further strengthen habit formation and retention.

• Recognition of Achievements: Acknowledge user milestones or actions within the product or through notifications.
• Behavioral Emails: Send emails triggered by specific user actions (e.g., completing a task, reaching a milestone).
• Social Recognition: Highlight user achievements to others (e.g., endorsements on LinkedIn, likes on Facebook).
• Customization of the Relationship: Personalize user experiences, communications, and recommendations based on data.
• Mass Personalization: Use data and technology to tailor experiences for large numbers of individual customers.
• WalmartLabs Example: Shifted from a one-to-many marketing mindset to delivering customized one-to-one experiences.
• Personalization Technology: Use tools and algorithms to deliver relevant content and offers.
• Machine Learning: Leverage algorithms to continuously optimize personalization based on user responses (e.g., Pinterest Copytune).

More Value Coming Soon

Communicating about upcoming features or product enhancements can create anticipation and incentivize users to remain subscribed or engaged while awaiting new value.

• Anticipation: Build excitement for future value.
• Retention Hook: Provides a reason for users to stick around.
• SaaS and Content Providers: Particularly effective for products with regular updates or new content releases (Salesforce, Netflix, HBO).
• HBO Rome Example: Announcing an expensive new show significantly reduced customer churn while subscribers waited for its release.
• Timing is Key: Experiment with when and how to announce upcoming value to avoid disappointing users.

Long-Term Retention

Sustaining retention over the long term requires a balance of optimizing existing features and introducing new value through continuous product improvement.

• Optimize Existing Features: Continuously refine the performance and user experience of existing features.
• Introduce New Features: Steadily add new items or features to keep the product fresh and valuable.
• Avoid Feature Bloat: Don’t overwhelm users with too many features that complicate the product.
• Road Test New Features: Experiment with prototypes or beta versions with small user groups before wide release.
• Growth Team Collaboration: Growth teams can identify new feature ideas and optimization opportunities based on data and user feedback.
• Ongoing Onboarding (Ramp Up): Continuously educate users about existing and new features in a progressive manner, building on their mastery over time.
• Google Analytics Example: Uses progressive notifications to guide users deeper into the product’s capabilities.
• Experiment with Messaging: Test different approaches for communicating about new features and their value.

Resurrecting “Zombie” Customers

Growth hacking can be used to re-engage users who have become inactive. The first step is to understand why they left and then design targeted campaigns to win them back.

• Understand Churn Causes: Interview or survey inactive users to learn the reasons for their departure.
• Address Controllable Factors: Focus on reasons for churn that the company can actually influence or fix.
• Resurrection Flow: Send targeted email or advertising campaigns to inactive users.
• Remind of Aha Moment: Reiterate the core value of the product.
• Incentivize Return: Offer special promotions or highlight new features.
• Inman Example: Targeted emails to inactive readers increased return visits by highlighting important news.
• Avoid Overdoing It: Don’t send excessive or pleading messages that further alienate users.
• Lower Cost Acquisition: Re-engaging past users is often cheaper than acquiring new ones.

Retention is a continuous effort that builds on successful acquisition and activation. By focusing on understanding user behavior, building habits, and delivering ongoing value, growth teams can significantly increase customer lifetime value and drive long-term business success. The final chapter will focus on monetizing the retained customer base.

CHAPTER EIGHT: HACKING MONETIZATION

Chapter Eight focuses on maximizing revenue from the customer base. It outlines how to map the monetization funnel, analyze revenue data by cohorts, and experiment with pricing, product offerings, and psychological triggers to increase customer lifetime value.

The Goal: Increase Lifetime Value (LTV)

The ultimate goal of acquiring, activating, and retaining customers is to generate revenue. Growth hacking efforts should aim to increase the amount of revenue earned from each customer over their entire relationship with the company.

• Maximize Earnings: Focus on strategies to get more revenue from existing customers.
• LTV: The total revenue a customer is expected to generate over their lifetime.
• Monetization Levers: Different tactics apply depending on the business model (retail, SaaS, advertising).
• Growth Team Focus: Monetization is a key area where growth teams can have a significant impact, often overlooked.

Map Your Monetization Funnel

Identify all opportunities for earning revenue throughout the customer journey and pinpoint any junctures where potential earnings are being lost (pinch points).

• Revenue Opportunities: Highlight all points where a customer can make a purchase, upgrade, or view an ad.
• Pinch Points: Identify steps with high drop-off rates that prevent users from generating revenue (e.g., abandoned shopping carts, low free-to-paid conversion).
• Business Model Specifics: Monetization funnels and pinch points vary by business type (retail purchase funnel, SaaS upgrade path, ad engagement points).
• Common Pinch Points: E-commerce checkout process, SaaS pricing pages, intrusive or ineffective ads.
• Detailed Analysis: Go beyond common pinch points to identify specific weak spots unique to your product.
• Metrics: Track conversion rates at each step of the monetization funnel.

How Much Are You Making from Cohorts?

Analyze revenue data by cohorts to understand which groups of customers are most valuable and identify opportunities to increase earnings from others.

• Revenue-Based Cohorts: Segment customers based on how much revenue they generate (e.g., high-profit vs. low-profit, different subscription tiers).
• Segment by Characteristics: Break down customers into groups by location, demographics, acquisition channel, features used, etc., and look for correlations to revenue.
• HotelTonight Example: Discovered that customers connecting via cellular data booked at twice the rate of those on Wi-Fi, leading to targeted advertising.
• E-commerce Cohorts: Analyze revenue by number of purchases, average order size, item types, purchase frequency, and purchase timing.
• SaaS Cohorts: Investigate revenue by business type, size, industry, and feature usage.
• International Monetization: Analyze revenue by country to identify differences in payment preferences and norms.
• SurveyMonkey Example: Identified that educational and nonprofit users were less likely to purchase premium plans, leading to discounted offers.

Learning Who Your Customers Are

Identify distinct groupings of customers who share similar characteristics and needs. Creating customer personas can help in generating ideas for satisfying their specific wants and increasing revenue.

• Customer Segmentation: Group customers based on shared traits and behaviors.
• Personas: Create fictional representations of typical customers within each segment.
• Targeted Strategies: Design experiments and offerings tailored to the specific needs and desires of each customer segment.

Ask Customers What Benefits They Want

Directly solicit feedback from customers about desired product improvements, new features, or offerings. This helps ensure that efforts to increase revenue are focused on providing value that customers are willing to pay for.

• Identify Desired Benefits: Ask customers what they would like to see improved or added to the product.
• Prioritize Based on Feedback: Use survey responses to determine which potential offerings are most valuable to different customer segments.
• BitTorrent Example: Surveying users about desired features led to the development of high-revenue-generating features like battery saver and auto-shutdown.
• Beyond Open-Ended: Consider providing a list of potential benefits for users to rank.

Using Data and Algorithms to Customize Offerings to Customers’ Wants and Needs

Personalization, particularly customized recommendations based on data and algorithms, is a powerful monetization tactic. Tailoring offerings to individual customer preferences can increase purchase volume and revenue.

• Personalized Recommendations: Use data to suggest products, content, or features that individual customers are likely to be interested in.
• Amazon Recommendation Engine: A prime example of using algorithms to personalize the shopping experience and increase purchases.
• Data and Algorithms: Recommendations can be based on past behavior, similar users, and various algorithms (e.g., Jaccard index for product similarity).
• Enhance Recommendations: Use data to identify products that are often purchased together.

Don’t Be Intrusive (with Personalization)

While personalization is effective, it must be done sensitively to avoid making customers feel uncomfortable or surveyed. Poorly executed personalization can backfire and hurt revenue.

• Avoid Creepiness: Be mindful of how much data you use and how you present personalized offerings.
• Target Example: Inadvertently outing a teenage pregnancy through targeted coupons led to negative backlash.
• Missed Mark: Recommending irrelevant products or content can alienate customers.
• Experiment with Delivery: Test different ways of presenting personalized offers (emails, in-app prompts, on-site).

Optimizing Your Pricing

Setting the right prices is crucial for maximizing revenue. Growth teams can assist by conducting research and experiments to find the optimal pricing range and model.

• Pricing Challenge: Balance pricing too low (leaving money on the table) and pricing too high (losing customers).
• Research and Surveys: Use customer feedback to identify perceived value and willingness to pay.
• Price Intelligently Survey: Ask specific questions to determine price points that are too expensive, too cheap, expensive but still considered, and a good deal.
• Experimentation: Continuously test different pricing points and models.
• Qualaroo Example: Experiments showed that raising prices increased revenue and attracted a new market of larger companies.
• Charm Prices: Experiment with using prices ending in 9 or 99 to influence perception and increase sales volume.
• Pricing Relativity: The perception of price is influenced by other options presented (e.g., decoy packages).
• Decoy Package Example (The Economist, SmartShoot): Offering a slightly less attractive option at a similar price can drive customers to the higher-priced item.
• Value Metrics: Base pricing on metrics that align with where customers perceive value and scale with product usage (e.g., contacts for HubSpot, responses for SurveyMonkey).

Less Is Not Always More (with Pricing)

Sometimes, lowering prices can actually hurt sales or fail to provide the desired boost in demand. Experimentation is crucial to determine the actual impact of price changes.

• Price Sensitivity: Customers may be less price sensitive than initially assumed.
• Signal of Quality: For some products, a higher price can signal higher quality.
• Qualaroo Example (Raising Prices): Increased revenue by demonstrating the product’s value at a higher price point.
• Test Discounts: Experiment with different discount levels to find the optimal balance between conversion lift and revenue capture.
• Inman Example (Discount Test): Found that a smaller discount had a similar conversion impact to a larger one, increasing captured revenue.

Proceed with Caution (with Pricing Changes)

Changes to pricing can be sensitive for customers. Experiments should be implemented carefully to maintain a consistent user experience and avoid negative reactions.

• Consistency: Ensure customers see the same pricing variant throughout their experience.
• Coordination: Coordinate pricing tests with sales and finance teams, especially in companies with sales-based models.
• Stakeholder Awareness: Ensure all relevant teams are informed about pricing experiments and their impact.

The Penny Gap

The “penny gap” refers to the psychological barrier between a product being free and costing even a small amount. For some digital products, offering a free version with monetization through ads or add-ons may be more lucrative than charging an upfront fee.

• Free vs. Paid: The transition from free to even a small price can cause significant friction.
• Cost of Acquisition: Sometimes acquiring a paying customer is more expensive than giving the product away for free and monetizing elsewhere.
• 7 Minute Workout App Example: Offering the app for free with in-app purchases dramatically increased downloads and overall revenue.
• Mobile App Norm: Free apps with in-app monetization are dominant in many categories (e.g., mobile games).

Monetizing Freemium Products

If your product is freemium, optimize strategies for converting free users to paid, often through add-ons, upgrades, virtual goods, or alternative monetization models.

• Encourage Upgrades: Design the free experience to highlight premium features and provide clear calls to action for upgrading.
• Spotify Example: Displays premium features within the free app to entice upgrades.
• Add-ons and Upgrades: Offer additional features or higher service tiers for a price.
• Virtual Goods/Currency: Introduce in-game or in-app currency for purchasing items or accelerating progress (e.g., Candy Crush, Pokémon Go, Coffee Meets Bagel).
• Monetization Mix: Combine different strategies (advertising, referrals, sponsorships, data monetization).

Bone Up on Consumer Psychology

Understanding the psychological principles that influence purchasing decisions can provide valuable inspiration for monetization experiments.

• Behavioral Economics: Learn from research on how consumers make choices.
• Cialdini’s Principles (Revisited): Apply principles like Reciprocity, Commitment, Social Proof, Authority, Liking, and Scarcity to design monetization hacks.
• Reciprocity: Give value first (samples, free content, freemium model) to increase the likelihood of a purchase later.
• Commitment and Consistency: Get small commitments upfront (adding to wish list, starting a trial) to increase the likelihood of a larger purchase.
• Social Proof: Showcase testimonials, customer numbers, or popular items to validate purchase decisions (e.g., daFlores, ModCloth).
• Authority: Feature experts or influential people to increase trust and encourage purchases (e.g., Kaya Skin Clinic, celebrity endorsements).
• Liking: Leverage personal connections or appealing visuals to increase purchases (e.g., Airbnb referral photo, popular models on e-commerce sites).
• Scarcity: Create a sense of urgency by highlighting limited availability or time-sensitive offers (e.g., Booking.com, Amazon inventory).

Hacking monetization is a continuous process of mapping revenue opportunities, analyzing data to understand customer value, experimenting with pricing and offerings, and leveraging psychological principles to increase customer lifetime value. The final chapter will discuss how to maintain this virtuous cycle of growth and avoid stalls.

CHAPTER NINE: A VIRTUOUS GROWTH CYCLE

Chapter Nine brings together all the elements of growth hacking, emphasizing the need for continuous effort across all stages of the funnel to create a self-reinforcing cycle of growth and avoid the dangers of stagnation.

Sustaining Breakout Success

Truly successful companies don’t rest on their laurels. They leverage their initial success to fuel further growth, capitalizing on new opportunities and creating a virtuous cycle.

• Continuous Push: Sustained success requires ongoing experimentation and innovation.
• Leverage Success: Use current growth to invest in future opportunities.
• Virtuous Cycle: Growth in one area (e.g., users) fuels growth in others (e.g., revenue), which in turn supports further investment.
• Facebook Example: Unrelenting growth has funded massive innovation and expansion into new areas like virtual reality.

Avoiding Growth Stalls

Growth stalls are periods of dramatic slowdown that can be devastating for companies, often sneaking up even after periods of strong growth. Complacency and failure to adapt are major causes.

• Unforeseen Slowdowns: Stalls can happen unexpectedly to companies of all sizes.
• Causes: Failure to monitor customer satisfaction, overlooking competitive threats, lack of aggressive innovation, losing focus on core products, or talent drain.
• Data Blindness: Ignoring or misinterpreting early warning signs in customer data.
• Overconfidence: Becoming complacent after achieving a strong market position.
• Incrementalism: Focusing only on small improvements rather than pursuing new opportunities.
• Distraction: Losing focus on core products due to pursuing shiny new initiatives.
• Channel Volatility: Overreliance on single marketing channels that can change rules or lose effectiveness (e.g., Facebook News Feed changes, Google algorithm updates).
• Market Disruptions: While some disruptions are unavoidable, growth hacking helps companies be more agile and responsive.

Swimming with Sharks (Maintaining Tempo)

Growth teams must maintain a high tempo of experimentation to stay ahead and avoid becoming stagnant. Complacency or distractions can quickly lead to stalled growth.

• Constant Innovation: Teams must continuously analyze, ideate, prioritize, and test.
• Avoiding Stagnation: Competing priorities and corporate inertia can derail even high-performing teams.
• GrowthHackers.com Example: Experienced a growth stall when experimentation tempo dropped, and recovered rapidly by recommitting to high-tempo testing.
• Prioritize Growth: Dedicate time and resources to growth initiatives above other tasks.
• Regular Review: Continuously monitor growth metrics and assess whether the team is maintaining a healthy tempo.

Don’t Underestimate the Power of Doubling Down

Teams can leave significant growth potential on the table by not fully optimizing channels and tactics that have already proven successful. Doubling down on wins amplifies their impact.

• Maximize Successes: Invest in getting the most out of effective growth levers.
• “Battleship” Strategy: Once a “hit” is found, intensely focus on that area to extract maximum value.
• GrowthHackers.com Email Newsletter: Repeatedly experimented with optimizing sign-up forms and messaging to significantly increase subscriber numbers from a successful initial channel.
• Compounding Effect: Doubling down on wins creates a powerful ripple effect on overall growth.

Mining Deeper for Data Gold

Teams may incorrectly assume they’ve exhausted the potential of their data. Investing in more comprehensive data collection and analysis capabilities can uncover new insights and ideas.

• Data Gaps: Identify areas where data is missing or not granular enough.
• Ramp Up Analytics: Invest in tools and expertise to improve data tracking, collection, and analysis.
• Facebook Example (2009): Stopped experiments to improve analytics, leading to a rich new source of growth ideas.
• Refined Analysis: Go beyond basic metrics to analyze specific user actions and behaviors.
• Data Skills: Ensure the team has the necessary data analysis expertise.

Dive into New Channels

When existing channels are plateauing or becoming less effective, experimenting with new channels is crucial for reaching new audiences and mitigating the risk of channel volatility.

• Reach New Audiences: Explore channels where your target customers are present but you haven’t yet engaged them.
• Mitigate Risk: Reduce overreliance on single channels that are subject to external changes.
• Complement Existing Channels: Introduce new organic or paid channels to supplement existing efforts.
• Organic Channel Investment: Don’t neglect organic channels (SEO, content marketing, social media), which can be powerful long-term drivers.

Open Up the Ideation Process

Bringing in fresh perspectives from outside the growth team can generate a wealth of creative new ideas when the team is struggling for inspiration.

• Cross-Departmental Collaboration: Invite participation from individuals in other teams and departments.
• External Advisors: Seek ideas from trusted advisors, investors, or industry experts.
• Customer Feedback (Again): Continuously solicit ideas and suggestions directly from customers.
• Science Incubator Example: Sharing winning experiments across portfolio companies spurred new ideas.

Taking Moonshots

Regularly experimenting with significant redesigns, new features, or bold strategic shifts (“moonshots”) is essential for breaking out of incremental thinking and unlocking entirely new growth opportunities.

• Break the Mold: Challenge existing successful approaches to find even better ones.
• Push Past Local Maximums: Avoid getting stuck in optimizing only small changes; experiment with fundamental overhauls.
• Balance Incremental and Bold: Schedule a mix of small optimizations and larger, higher-risk experiments.
• Pinterest Copytune Example: A massive leap in optimization through machine learning.
• Uber Flat-Fee Test: A bold experiment with a fundamental aspect of the service model.
• Continuous Innovation: Bold experimenting is a key defense against growth stalls caused by competitive innovation.

Growth hacking is a dynamic philosophy that requires continuous effort and adaptation. By maintaining a high tempo of experimentation across all growth levers, leveraging successes, mining data deeply, exploring new channels, opening up ideation, and taking bold moonshots, companies can create a powerful, virtuous cycle of growth that positions them for long-term success.

Big-Picture Wrap-Up

Hacking Growth provides a comprehensive framework for building and scaling businesses in the digital age. It argues that sustainable growth is achieved not through luck or massive marketing budgets alone, but through a rigorous, data-driven, and experimentation-focused methodology. By breaking down silos, forming cross-functional teams, and continuously optimizing the customer journey from acquisition to monetization, companies can unlock significant growth potential.

The core lesson is that growth is a continuous process of learning and adaptation. Teams must remain vigilant, analyzing data to understand user behavior, generating and prioritizing ideas based on insights, and rapidly testing solutions. Success comes from accumulating small wins and strategically doubling down on what works, while also being willing to take bold steps and explore new opportunities.

• Core Lesson: Growth is a continuous, data-driven process of high-tempo experimentation across the entire customer funnel.
• Team Structure: Cross-functional teams are essential for breaking down silos and fostering collaboration.
• Must-Have First: Ensure your product delivers core value before aggressively pursuing growth.
• Identify Levers: Define your specific growth equation and North Star metric to focus efforts.
• Optimize Acquisition: Find cost-effective channels and craft compelling messages.
• Drive Activation: Guide users to the “aha moment” by reducing friction and creating engaging experiences.
• Fuel Retention: Build habits and deliver ongoing value to keep customers engaged long-term.
• Maximize Monetization: Optimize pricing, offerings, and triggers to increase revenue per customer.
• Stay Vigilant: Continuously monitor metrics, explore new opportunities, and avoid complacency to prevent growth stalls.