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本帖最后由 大力Summer 于 16-10-2018 11:00 编辑
来自布村的Summer来报到，这是受Cherry，蜻蜓，Anna等等亲爱的们的鼓励来发表的第一篇读书笔记。新鲜出炉。因为这是我第一次把我的笔记拿出来晒，希望大家多多指正。
Hacking Growth这本书是17年出版的，作者在这方面非常有建树与思考深度，总结出来的方法论都是可以马上实践在工作中的。这是一本可以带来，公司架构与产品迭代的思考与实践的书籍。希望感兴趣的朋友可以跟我一起讨论，我对增长非常感兴趣。
About the Author
Sean Ellis is CEO and founder of GrowthHackers.com, the number one online community for GrowthHackers with 1.8 million global users. Sean coined the term "growth hacker" in 2010 and is the producer of the GrowthHackers Conference.
Prior to GrowthHackers, Sean founded and sold customer insights company Qualaroo, growing it to millions of dollars in recurring revenue with customers such as Starbucks, Amazon and Intuit. He has also led growth or marketing for Dropbox, Eventbrite, LogMeIn (IPO), Uproar (IPO) and Lookout.
Summary
The Method
Building Growth Teams
At the core of today’s fastest growing companies is a new business unit called the Growth Team. This cross-functional team is made up of specialists from across the organization that come together to design and test new experiments that can lead to big growth wins.
Managed by the Growth Lead, the team meets weekly and moves quickly through a prioritized queue of ideas that have the potential to improve business results throughout the customer lifecycle; from acquisition and activation, to retention and revenue.
The team is comprised of builders and doers from software development, product management, data analytics, design and marketing to collaborate on innovative and incremental experiments that can move the metrics that matter most to the business.
- The growth lead: choosing the core focus area and objectives.
- Product manager: overseeing how the product and its various features are brought to life; assisting hacking missions of breaking down the silos between departments and identifying good candidates in engineering and marketing to help start the growth team.
"A good product manager is the CEO of the product"
- Software engineers
- Marketing specialists
- Data analysts: understanding how to collect, organize, and then perform sophisticated analysis on customer data to gain insights that lead to ideas for experiments.
- Product designers
Growth hacking process
Analyze -> Ideate -> Prioritize -> Test -> Analyze
Reporting structure
Determining If Your Product Is Must-have
What's the aha moment?
Whether a company has just been founded and is in the start-up phase trying to figure out its place in the market and the true value of its product or service for potential customers, or whether a company is an established market player acting in a highly dynamic and competitive surrounding that is driven by constant innovation and new product releases: there is a constant need to re-evaluate a company’s product-market-fit to ensure ongoing business growth.
Case: Yelp (They found the aha moment for users is about reviewing restaurants.)
The must-have survey:
Question:
How disappointed would you be if this product no longer existed tomorrow?
- Very disappointed
- Somewhat disappointed
- Not disappointed
- N/A - I no longer use it
If 40 percent or more of responses are 'very disappointed' then the product has achieved sufficient must-have status.
If 25-40 percent, then often what's needed are tweaks either to the product ro to the language used to describe the product and how to use it.
If less than 25 percent, it's likely that either the audience you've attracted is the wrong fit or the product needs more substantial development before it's ready for a growth push.
In these cases, more questions:
- What would you likely use as an alternative to [product name] if it were no longer available?
- I probably wouldn't use an alternative
- I would use:
- What is the primary beneft that you have received from [product name]?
- How likely is it that you would recommend [product name] to a friend or a colleague?
- What type of person do you think would benefit most from [product name]?
- How can we improve [product name] to better meet your needs?
Assess the product’s retention rate
Tracking the no. of users who churn (weekly/monthly basis). Shorter time horizon helps deduce how many users are making the use of the product a habit.
Getting to must-have
Three key methods:
- Additional customer surveying, including interviews and getting out in the marketplace to taok to customers and prospective customers;
- Efficient experimental testing of product changes and messaging;
- A deep plunge into analysis of your user data.
Specifically:
- Watch users' actions: actions speak louder than words
- Finding a community to survey: case: PayPal with eBay
- Efficient experimentation: MVT (minimum viable test) - Decisions about what experiments to run must be made rigorously
- A/B testing
- Taking a data dive
- What are active users doing
Identifying Your Growth Levers
Focus on the right levers of growth at the right time. Be rigorously scientific in identifying the kind of growth you need and the levers that will drive it.
Understand which metrics matter most for your product’s growth. Develop your ‘fundamental growth equation’. To find out essential metrics, identify the actions that correlate most directly to users experiencing the core value of your product. E.g. Uber—essential metric, no. of rides completed. So in addition to the no. of new people downloading the app, Uber would want to track in the no. of rides being booked, the no. of riders who return and rebook, and the frequency with which they are booking new rides.
Cases:
- Inman News: (Website traffic * Email conversion rate * Active user rate * Conversion to paid subscriber) + Retained subscribers + Resurrected subscribers = Subscriber revenew growth
- eBay: Number of sellers listing items * Number of listed items * Number of buyers * Number of successful transactions = Gross merchandise volume growth
- Amazon: Vertical expansion * Product inventory per vertical * Traffic per product pace * Conversion to purchase * Average purchase value * Repeat purchase behavior = Revenue growth
Levers:
- Uber: number of drivers & number of riders
- Yelp: numbers of business reviewed and the numbers of reviews for each
- Facebook: amount of users shared by users & the time spent looking through the News Feed & the results in more time spent browsing it
Choose a north star
Before jumping into a high-tempo process, it’s vital for your team to identify and measure a North Star Metric (NSM).
Identify the actions that correlate most directly to users experiencing the core value of your product.
Develop dashboards to report only the most important metrics that map to your growth levers. Present information in a way that is actionable. Use ratios
Do Cohort analysis for deeper insights
Divide your customers or users into distinctive groups by a common trait (days months, area)
Case: Twitter
- Based on monthly retention rate, they found that those who visited at least 7 tiimes in one month were retained in the next month at 90 - 100 percent.
- Then by dividing users into 3 cohorts: core users (at least 7 times one month; 20%); casual users (less often); cold users (never came back after a first visit).
- They they conducted a correlation analysis, looking for similarities of behavior within one group of users that are not found in other groups. -> core users follow more than 30 users -> 30 is the tipping point
- Those who were being followed by just a third of those they followed were the ones who became loyal users. -> then they found the reasons by interviewing users: Twitter seemed like a news site otherwise.
Testing At High Tempo
Learning more by learning faster. More experiments, the more you learn.
Stage 1: analyze
By understanding more about your customers and how they interact with your product, you will begin to identify opportunities for growth experiments.
Start by diving into the initial wave of users you’ve acquired since launching your product. Separate the engaged users from the inactive ones. Sean and Morgan recommend asking three broad questions with additional detailed questions that help you dive deeper for each one.
Questions to guide analysis:
- What are my best customers’ behaviors?
- What features do they use?
- What screens in the app do they visit?
- How often do they open the app?
- What items do they buy?
- What is their average order size?
- What time of day do they shop and on which days?
- What are the characteristics of my best customers?
- What sources were they acquired from? ad, promotions emal or other place?
- What devices do they use?
- What is their demographic background, including age, income, and more?
- Where do they live?
- How close are they to the store or other stores?
- What other apps do they use?
- What events cause users to abandon the product?
- What screens have the highest exit rates?
- Are there bugs that are preventing users from taking a particular action?
- How are the products priced relative to other services?
- What actions don't they take that users who purchase do?
- What is their path through the app, and how much time do they spend in the app before they abandon it?
These questions should be looked at from both a quantitative and qualitative perspective. While an analyst can work on identifying trends in the data, a marketing expert should interview and survey your customers. Getting qualitative feedback will likely expose your own blind spots, inspire new ideas, and help guide research into quantitative user data.
By analyzing the data up front, you’ll go into the ideation step of the process armed with the data to create ideas for experimentation that have clear hypotheses and supporting evidence.
Stage 2: ideate
Ideas are the leading input for growth. If you don’t have ideas going into the process, there’s a lesser chance your team will make an impact on growth because there’s less to test and learn.
Try brainstorming with other people in your company. By gathering members of your team and asking “how do we solve this problem?” or “how do we meet this objective?” you’ll find that unique ways to solve a problem will arise and they will likely be more feasible since multiple stakeholders are involved.
A good idea should explain how it contributes to a current growth objective. For example, if your team is focusing on improving activation of new users, your team should be contributing ideas that are aimed to improve that metric.
Idea template
- Idea name: brief, limit under 50 characters
- Idea description: Lines of an executive summary. Who, what, where, why and how.
- Who is being targeted: all visitors, new users only, returning users or users from a particular traffic source?
- What is going to be created? new marketing copy or a new feature?
- Where will the new copy or feature be implemented: Will it be on the app's home screen or elsewhere?
- When will it appear during the customer's use? On the landing page?
- Why: rational
- How: a recommendation of the type of test to be done? A/B test, or new feature to be built, or a new ad campaign to be launched
- Hypothesis: expected cause and effect
- Metrics to be measured
Stage 3: prioritize (The ICE store)
- Impact: How much of an impact will this idea have if it’s successful?
- “You might think that only ideas that are very high impact are worthy of being submitted, but remember that a team should be selecting a mix of potentially high-impact experiments, which will generally require more work, and some that are easier to implement but also have a good, if not great, chance of producing meaningful results.”
- Confidence: How confident are you that this idea will work?
- “This rating should be based just on conjecture, but on empirical evidence of some kind, whether from data analysis, review of industry benchmarks, published case studies, or knowledge of previous experiments.”
- Ease: How easy is it to implement this idea?
- “The ease score both provides the growth team a reality check about overly ambitious ideas and helps identify some ‘low-hanging-fruit’ tests to run each time through the growth hacking process.”
Each member of the team should use the guide of the ICE score to then nominate a set number of ideas leading into the team’s weekly growth meeting. Here at GrowthHackers, we each nominate two ideas every week.
The ideas nominated that week are then presented by each person in the growth meeting. The team concludes the meeting with which ideas will be moved into the Up Next queue where the chosen ideas are then prepared for testing.
Stage 4: test
In this step of the process, the outputs of the growth meeting are put into motion. To keep organized, the “Up Next queue” represents all tests that need preparation. This is where ideas should be assigned to different members of the team to move forward.
Once the experiments are ready to go, the growth lead will send a notification around the company that they are being launched so that there are no surprises for other teams also working on the product. If roadblocks to launching certain experiments are encountered, the team member in charge must inform the growth lead right away so that other experiments in their Up Next queue can be considered for deployment in their place.
Each test should then be analyzed and measured against its hypothesis. The analyst will need to report whether the idea worked, didn’t work, or was inconclusive. Regardless of the outcome, it’s important for the analyst or growth lead to share a test summary that includes the lessons learned from a qualitative perspective as well as any supporting data.
Back to stage 1: analysis and learning
The results should be written up in a test summary:
- The name & description of the test: variants used and the target customers
- The type of test run: product function, change to marketing copy on a website page or screen in a mobile app, a creative test or a new marketing tactic deployed?
- Features it impacted
- Key metrics
- Test timing, including start and end dates
- The hypothesis of the test and the results, including original ICE score, sample sizes, statistical confidence and statistical power
- Potential confounding issues, such as the time of year the test was run, or if there were other promotions that may have skewed visitor behavior
- The conclusions drawn
All completed tests should be stored in a central knowledge base that everyone on the growth team can access at any time. It’s important to keep a record of these tests so that new employees can get up to speed on what’s been tested to date, and so that anyone on the team can easily search results and consider variations to what’s already been tested. Which takes us full-circle to the ideation step of the process. - Slack, email, google doc?
The growth meeting
The growth meeting is held on Tuesdays. On Monday, the members check in on experiments in progress to identify any that can be concluded and review:
- look at the number of experiments successfully launched and compare it to the velocity goal of the team
- confer with the data analyst to update all of the key metrics the're following so that she can brief the team about them, perhaps distributing reports
- gather the data about any tests that were concluded
- conduct a high-level assessment of the previous week's activity and results, including a summary of findings about both the positive and negative effects on growth discovered from the experiments
- compile this information and include it with the meeting agenda
Meeting consists of:
- 15 minutes: metrics review and update focus area
- Key positive factors
- Key negative factors
- Growth focus area
- 10 minutes: review last week's testing activity
- Tempo: compare number of experiments with the team's tempo goal
- How many tests were not launched in the last week
- 15 minutes: key lessons learned from analyzed experiments
- 15 minutes: select growth tests for current cycle
- 5 minutes: check growth of idea pipeline
The Growth Hacking Playbook
Hacking Acquisition
These are the three most reliable paths companies can take to scale customer acquisition. But doing more than one of them at a time is next to impossible.
The trick is to figure out which kind works best for your own product type:
- Viral – Think of Dropbox. You grow primarily through other people referring you to their friends, family, or colleagues.
- Sticky – Think of Crazy Egg. You create an irresistible experience that keeps people around as long as possible (and thus, paying you more and more).
- Paid – Think of Groupon. You spend $50 to acquire a customer who will eventually be worth $500 to your business.
Prioritizing Distribution Channels
Hacking Activation
Creating a funnel report
Desire - Friction = Conversion rate
The power of positive friction
Once people take an action, no matter how small, as long as the experience wasn't onerous, they are more inclined to take any action in the future.
Optimize the NUX (new user experience)
The art of questionnaire
Users are likely to give feedback in the website.
Common types of notification triggers:
- Account creation
- Purchase messages
- Reactivation campaign
- New feature announcement
- Top user incentives
- Activity or status change
Hacking Retention
Offer rewards both tangible and experimential
- Brand ambassador programs
- Deisgnating members as high-status users -> social recognition
- Cases: Yelp Elite Squad
- Recognition of achievements
- Cases: Medium sends emails to users when an artical they public receives 50 or 100 recommendations
- Customization of the relationship
- Machine learning is a good way.
- Cases: Amazon can extract a customer's information about user's preferences.
Example:
- Referred to book: 'Hooked'
Hacking Monetization
Using data and algorithms to customize offerings to customers' wants and needs:
For instance, the intersection size in the Jaccard index is how many people buy both A and B together, while the union is how many people bought either A and B independently.
Pricing
- At what price point does [your product] become too expensive that you'd never consider purchasing it?
- At what price point does [your product] start to become expensive, but you'd still consider purchasing it?
- At what price point does [your product] start to become a really good deal?
- At what price point does [your product] start to become too cheap that you'd question the quality of it?
Pricing relativity
Users' decisions about the price they would like to pay are affected by the set of options they have to choose from.
Consumer psychology
- The principle of reciprocity: giving before asking for a commitment to purchase
- The principle of commitment and consistency
- The principle of social proof
- The principle of authority
- The principle of liking: People buy more when a product is recommended by people they like.
- The principle of scarcity
A Virtuous Growth Cycle
Never stop!!!
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发表于 16-10-2018 10:51:02
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楼主
发表于 16-10-2018 11:24:46
1
发表于 16-10-2018 11:45:30
我晚上好好拜读啊~
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