Sean Ellis & Morgan Brown. Hacking Growth. Part 1.

 

Hacking Growth: How Today's Fastest-Growing Companies Drive Breakout Success by Sean Ellis (Author), Morgan Brown (Author) https://tinyurl.com/bddmr9v8

Review

This book is far more professional and methodical than its title suggests - don't judge this book by its cover. It perhaps provides the best explanation of the importance of Acquisition, Activation, and Retention that I've come across. It balances engaging anecdotes with practical advice on how to influence your metrics. It's a comprehensive playbook for establishing and operating a growth team. Its emphasis on the importance of rapid experimentation in product development is spot on. This book is surprisingly practical, insightful, and actionable. It's more than enough to get you started.

Key Takeaways

The 20% that gave me 80% of the value.

• You can unlock rapid growth and get more from your marketing spend if you breakdown the traditional silos of marketing and product and setup teams to focus on acquisition or retention. Dropbox acquired 1/3 customers through offering free storage for referrals.
• A multi-disciplinary with a mandate to find growth potential is powerful. Focus them on continuous testing and tweaking of the product (it’s features, messaging, and its acquisition, retention and activation methods). Give them exec sponsorship and point them at acquisition, activation or retention.
• Test if you have product-market fit before spending big on marketing. To find out ask customers how they would feel if they could no longer use your product… If 40% or more are very disappointed → you might be onto something.
• Tag your product so you can understand what’s happening from the beginning to the end of the funnel. Data tells you what users are doing - not why they are doing it. You’ll need to conduct some user surveys or interviews to work out what’s going on
• The ‘aha moment’ is when users experience the value of a product for the first time.
• Once you’ve identified the conditions that make the AHA moment, turn your attention to getting more customers to experience that moment as fast as possible. Spend about 30% of your time and effort on this.
• Your essential metrics are determined by identifying the actions that correlate most directly to users experiencing the core value of your product
• Create your growth equation - it’s simplicity helps focus. It should include each of the steps users must take to reach the aha moment (and how often they are take them).
• Hone your growth equation and narrow your focus by choosing a single metric of success that all growth activity is geared toward.
• Experiment and test at high tempo. The faster you learn the faster you can grow. Most experiments fail to produce results, so volume is key. Set a weekly heartbeat to encourage experiment velocity, discuss results and what to test next. Think minimum viable test. Scattershot experimentation is a waste of time and effort - instead focus on growth levers. Set a minimum number of tests a week.
• Don’t be afraid to double down - push more and more on successful levers. Push past local maximums by taking moonshots. Expect most of the gains to come from more modest changes.
• The growth hacking cycle: Data analysis → insight gathering → idea generation → experiment prioritisation → running the experiments → review results → decide
• Small changes in language and messaging can have a big impact on acquisition. E.g. ‘Store your photos online’ to ‘share your photos online’. Or ‘Find a date’ to ‘help people find a date’
• Channel Strategy - Research and prioritise your channels. Find one or two that have high potential - optimise them for cost-effectiveness and reach. Consider the needs of your business model and the characteristics of your customers. Fish where they are.
• Rank each channel on cost, targeting, control, input time, output time and scale
• Virality = Payload x Conversion Rate x Frequency
• Create a funnel report - then do qualitative research to understand what’s happening at each stage. “What’s the one thing that nearly stopped you from completing your order?”
• The Compounding Value of Retention: The longer a customer is retained - the more chance to earn revenue from them. Increasing the life time value of a customer enables you to invest more in growth. Enables you to predict revenue better. Enables you to learn more about them, their needs, desires - better personalisation - earn more from them
• Providing a product that addresses the needs of, or delights of a customer is the best way to drive retention. Better retention will drive better results from viral marketing - the longer they stay, the more likely they’ll talk to others about it.
• Success of Trigger = Motivation to take action x Ease of taking the action
• Behaviour = motivation x ability x trigger
• A retention rate that grows over time is a strong signal that the product is successful - Often this is because of stored value - the more you use it, the more the data becomes valuable, the more likely you’ll be able to use it
• The Hook Model: Trigger → Action → Reward → Investment (repeat)
• Ongoing Onboarding: Continuing to educate your customers about the value they can receive from your product. Getting users to a place where they’re getting the most value out of the product is called ramp up.
• Monetisation is about earning more revenue from each customer over time - increasing LTV (lifetime value). Look at revenue by cohort. Find your high profit vs low profit customers. Look at average revenue per users.
• Potential Cohorts
• Group by: age, location, gender, types of item purchased, features used, acquisition source, type of device, type of browser, number of visits, date of first purchase
• Look for patterns in retention rates - correlations will give ideas for experiments.
• Utilise the power of simple recommendations → Jaccard similarity coefficient → The similarity of two items (A and B) is equal to size of the intersection of A and B divided by the union of A and B. The intersection is how many people purchased the products together. The union is how many bought either independently
• Use the 4 question pricing survey to find the optimal price.
• Compare personas: Do they value the same features? have the same willingness to pay? Cost of acquisition? Lifetime Value?
• Charge based on value: find a way to charge customers more if they get more value. Does your value metric align with customer value perception? Scale as the customer uses the product more? Is it easy to understand?

Deep Summary

Introduction to Growth Hacking

• Why Growth Hacking?
• Companies achieve rapid growth despite fierce competition and limited budgets
• Engineers create novel methods for finding, reaching and learning from customers
• Get more from your marketing spend → hone your efforts, target cleverly, grow your user base
• Elements to Growth Hacking
• Create a cross-functional team, break down traditional silos of marketing and product development to combine talents
• Use qualitative research and quantitative data analysis to gain deep insights into user behaviour and preferences
• Rapidly generate and test ideas → use metrics rigorously to evaluate and act on results
• The Growth Team Mandate:
• Find growth potential through a focus on continuous testing and tweaking of the product…it’s features, messaging to users, and the means by which they’re acquired, retained, and generate revenue.
• Search for new opportunities for product development, by assessing customer behavior or feedback, or experimenting with ways to capitalize on new technologies such as machine learning and artificial intelligence
• Get involved in all stages and all levers of growth, from attaining product/market fit to customer/user acquisition, activation, retention, and monetization.

Growth Team - Playing nice with the traditional organisaiton

• Growth teams don’t replace traditional departments, they complement them
• You can setup small teams independently - and for finite projects like a product launch
• Staff from the ground up, or take in team members from different teams - evolve size, sscope and responsiblity over time to meet the needs of the company
• Traditional silos slow down customer acquisition learning: Engineering, Product, Marketing, Sales (agencies conculted too)
• Companies agren’t great at collecting data in an integrated way
• Acting on the wrong data, suface level vanity metrics, dots can’t be connected
• Method for tapping into the opportunities of data - craft more effective growth strategies
• Most companies and teams are too slow to adopt promising platforms - trapped by legacy planning, budgeting and organizational norms.

• 3 Growth Hacking Myths
The silver bullet growth hack
• The success of many companies is attributed to silver bullet ‘eureka’ growth hack ideas
• Small compounding gains is a more apt description of what’s going on
• When success is driven by methodical, rapidfire generation and testing of new ideas for product development and marketing, and the use of data on user behavior to find the winning ideas that drove growth.

UpRoar	Allowed a free version of their game to be embedded in other people’s websites
LogMeIn	Made it clear it was free. Improved download activation (making paid ads profitable)
Hotmail	p.s. Get your free email at hotmail
Paypal	Automatically add a ‘pay with paypal’ button to all your auction listings on eBay
LinkedIn	Quickly invite all your contacts
DropBox	Video to get people excited - built a huge waitlist - helped get investment
DropBox	Amplify word of mouth - offer free storage for referrals (250mb)
Facebook	Translation engine for new languages
Facebook	Sign out page - left on screens in internet cafes
AirBnB	Automatic posted AirBnB listings to Craigslist

• Scrappy AirBnB founders created cereals during the 2008 campaign → ‘Obama O’s and Cap’n Mccains… to generate some cash

The lone growth hacker

• You can’t just hire a single lone ranger growth hacker and expect them to transform your business. It’s a team effort - engineering, data, marketing

It’s about new customer acquisition only

• About customer activation, retention and monetisation
• Companies get this wrong
• $92 spent on traffic acquisition $1 spend on converting them to paying customers
• Resulting in bounces and churn.

How would you feel if you could no longer use x? a surprising way to measure loyalty

• Gauge customer loyalty by asking about disappointment not satisfaction. It’s a better predictor
• “How would you feel if you could no longer use Dropbox?”
• Very disappointed | Somewhat disappointed | Not disappointed | N/A no longer using the product
• If more than 40% are “very disappointed” you’re onto something
• A third of Dropbox’s users came from referrals - to supercharge that they started offering free storage for referrals - grew to 2.8 million invites a month

Part I The Method

2) Building a Growth Team

Include people from different disciplines/departments · Work across the entire funnel · bust silos

• Traditional silos stop you working on the most impactful thing. They rarely talk, share information or collaborate.
• Silos: marketing, product management, engineering, and data science
• Collaboration between deparments is difficult and rare
• Work across the whole funnel - what if the best growth strategy is making the most of the customers you already have

Typical Department Owner	Funnel Stage
Marketing	Acquisition
Product & Eng	Activation
Product & Eng	Retention
Product & Eng	Revenue

Typical Team Roles / Capabilities

Growth Lead	Conducts the team (skills: analysis, product and experimentation) Chooses the teams focus area and objectives Keeps focus - stops them getting derailed Agrees appropriate metrics for experiments
SWE	To make the changes, but tap into their creativity and platfrom knowledge
Product Manager	Idea generation, experimentation: customer surveying + interviewing skills
Marketing Specialist	Content or SEO for example
Data Analyst	Data plumbling: Collect, organise, analyse data to gain insight. Experiment design. Compile experiment results
Designer	UX - user journey sequences. UI - product design

• Start small and expand over time. Seed with some people who know the company.
• You can form and disband with different intiatives
• The team need to understand the big picture (strategy, business goals). They need to be able do analysis. They need to be able to engineer changes to the product or its marketing and run experiments to test efficacy

• The Growth Hacking Loop (circle)
• Goal - find new and amplify existing
• The growth team should meet weekly to discuss the testing activity, review results and agree which hacks to try next. This helps maintain experiment velocity.
• Example: Analysis of customers that are abandoning the product reveals those customers haven’t made use of a particular feature - so the team might experiment with ways to get more people to try out that feature (hoping it will reduce churn)
• Some activities can be done as individuals, others will require the whole team to come together and work on something.
• The team must have clarity on who they report to. Appoint an executive sponsor to give the team authority to cross the bounds of ‘established departmental responsibilities.’ They must also have the backing of all of the key leadership - to push through challenges
• ELSE teams will get bogged down in bureaucracy, turf wars, inefficiency, and inertia
• The Product-Led Model:

• Many companies follow this model, with growth teams typically focusing on different parts of the funnel. This structure might be harder to implement in a more established company
• You’ll likely hit cultural resistance to working this way. Different disciplines and teams have preconceived notions about the ownership of initiatives ‘what they’re supposed to do and how they’re supposed to do it’
• Overcoming this requires cross-team collaboration and trust building
• You need the whole team to be incentivised and rewarded for achieving shared goals that create meaningful results for the company
• Growth projects and resources can interfere with other projects and roadmaps.
• The notion of experimenting so much can be uncomfortable to some. There is however a virtuous growth cycle in the adoption of growth hacking - wins spark enthusiasm.
• Start with one team, working on one part of (acquisition, activation, retention) for one product.

Determining if your product is a must have

• ALL FAST-GROWTH companies share one thing in common, they’ve built products that, in the eyes of their customers, are simply must-have.
• Avoid spending people and resources on driving people towards a product that isn’t loved and understood by your target market.
• This is one of the most common, and deadly, mistakes start-ups make, and it’s also a huge problem that often surfaces when established firms
• A cardinal rules of growth hacking:

You must not move into the high-tempo growth experimentation push until you know your product is must-have, why it’s must-have, and to whom it is a must-have: in other words, what is its core value, to which customers, and why.

• Pressure to start growing is intense, so this can take patience. The belief that growth can be forced becomes increasingly alluring.
• The opportunity costs of pushing for growth too soon:
• Spending time, energy and money on the wrong things (promoting something nobody wants)
• Your early adopters will become critics not fans. Viral mechanics can work against you
• Instead adopt rigorous methods for probing into user behaviour to discover the core value of your product. Often we think we know which bits of our product customers love and we’re wrong
• AirBnB: Love creates growth, not the other way around

The Aha moment:

• Yelp noticed users were taking advantage of a feature buried deep within the site - one that allowed them to rate local businesses.
• Utility of the product really clicks for the users;
• Users really get the core value—what the product is for, why they need it, and what benefit they derive from using it.
• Why that product is a “must-have.”
• The experience turns early adopters into power users and evangelists.

Examples of Aha moments

• For Yelp: the ability to discover promising local restaurants and businesses through trusted community reviews.
• For eBay: finding and winning one-of-a-kind items at auction from people all over the world.
• For Facebook: instantly seeing photos and updates from friends and family and sharing what you were up to
• For Dropbox: easy file sharing and unlimited file storage
• For Uber: “You push a button and a black car comes up. Who’s the baller? It was a baller move to get a black car to arrive in 8 minutes

• Sometimes a product isn’t yet offering a true aha experience and more product development is needed to create it.
• Sometimes the product already has what it needs to give people an aha experience, and the work is in leading them more effectively to it.
• People often have to use a product a certain amount of time before they truly have this experience with it, or perhaps they have to use a certain feature to really get the full-force aha hit.
• For Twitter: users who quickly started following at least 30 other users were much more engaged and likely to continue using the service. Getting a steady stream of news and updates from people they were interested in was the aha moment for people. Following 30 people created a stream of updates that made the service “must-have
• For Slack: once a team had sent 2,000 messages to one another they became far more likely to make Slack a core part of their communication workflow and upgrade to a paid plan
• Identifying an aha moment can sometimes be quite tricky. Don’t assume anemic growth means you don’t have aha magic. Some users might already be wildly enthusiastic about it.
• Seek out truly avid fans by mining user data and feedback, and then to search for any similarities in the ways these people use the product for hints about what value they get from your product that less enthused users perhaps aren’t.
• Discovering the aha moment can be difficult, but determining whether or not your product meets the baseline requirement generally doesn’t require elaborate diagnostics. Use this 2 part assessment

1) The Must-Have Survey

Question	What you Learn
• How disappointed would you be if this product no longer existed tomorrow? ◦ a)  Very disappointed ◦ b)  Somewhat disappointed ◦ c)  Not disappointed (it isn’t useful) ◦ N/A - I no longer use it	The % that respond ‘very disappointed’ changes what you learn. - Above 40%: The product has achieved sufficient must-have status (you should go for growth) • 25-40% Often you just need to tweak the product or the messaging that describes it or how to use it • 25% or less: Often the product needs more substantial development - or you’ve attracted the wrong audience
• What would you likely use as an alternative to [name of product] if it were no longer available? ◦ I probably wouldn’t use an alternative ◦ I would use:	Helps identify your competition, and point to features or aspects of the experience offered that lead those customers to prefer them over others
What is the primary benefit that you have received from [name of product]?	Helps uncover features you might add to deliver this benefit - or different messages to communicate it
• Have you recommended [name of product] to anyone? ◦ No ◦ Yes (Please explain how you described it)	Gauge whether the product has word-of-mouth potential - their language can unearth benefits, features and language that you could use in your promotion
What type of person do you think would benefit most from [name of product]?	Help you find and define your customer niche and targeting
How can we improve [name of product] to better meet your needs?	Identifies glaring issues that are blocking adoption and opportunities for improvement
Would it be okay if we followed up by email to request a clarification to one or more of your responses?

• Survey enough people to get a few hundred responses. If you don’t have enough customers to get to that number - use customer interviews instead.
• You’re better off surveying the users who are using your product - not those that have gone dormant
• Only use this when you’re trying to establish product-market fit - it’s not a good idea to email the users of an established product, as they might think you’re going to discontinue it

2) Measure Retention

• Retention Rate: the number of people who continue to use your product over a given time.
• Usually the % of users who use or pay for your product on a given month
• If your product is really used frequently - weekly retention might be meaningful too
• Daily active users wouldn’t show your early adopters leaving - if you’re also acquiring users at the same rate (but retention rate would highlight that)
• You’re aiming for a high rate (better than your competitors) that’s stable over time
• Teams should constantly be working on retention
• Find benchmarks for business, product or industry - as they can vary widely.
• Most mobile apps retain just 10% per month
• The best mobile apps retain 60% after one month
• Business products have high retention rates of 90% per month
• Fast food have high retention too 50-80%

• If your product hasn’t made the grade - don’t guess what feature might make your product more appealing. Talk to your users instead - understand the true objections and barriers to your products success.
• 3 things you should be doing
• Additional customer surveying, interviews and marketplace visits
• Efficient experimental testing of product changes and messaging
• A deep plunge into analysis of your user data
• Avoid feature creep. Each feature makes your product more cumbersome and confusing to use. Adding more features almost always isn’t the answer

Getting out in the analog world

• Go to your users. Be dispassionate about your product. Feedback is useless if you sell. Take a prototype into the wild to see exactly how prospective users respond to it.
• Etsy focused on the craft community, and what aspects of the selling experience they considered most important, and what kind of aha moment it would require to convince them to shift that experience to Etsy.
• online message boards, seller tools and resources, social hooks
• Etsy spent next to nothing on customer acquisition - 91% organic growth thanks to this approach
• Tinder focused on college fraternities - spent time on campus - went from fraternity to fraternity showing them who’s signed up locally.
• Finding a community to survey
• There could be preexisting community you could tap into
• PayPal noticed its early adopters were ebay sellers when one asked to use the PayPal logo on their auction listing
• Tapping into these targeted platforms can help you find early adopters who are likely to have the problem your product solves and can give feedback into whether what you’ve built for them delivers an aha experience
• Surveys and interviews may seem prohibitively time consuming but clear insights can be gained with quite moderate numbers of survey responses and very few interviews

Twitter team asked users dormant who had subsequently returned…
• (1) Can you tell us why you signed up in the first place?;
• (2) What didn’t work for you? Why’d you bail?;
• (3) What caused you to come back and try it again?
• (4) What worked this time?

Efficient Experimentation

• Low-cost and easy-to-use data analytics and online marketing technology has made it easy to experiment with product and messaging to find the right combination of customer base and feature set you need to pass the ‘must-have threshold’
• Minimum viable test (MVT) → the least costly experiment that can be run to adequately vet an idea. If successful, the team will invest in a more robust follow-on test or more polished implementation of the concept.
• To keep experiment velocity high run a mix: ‘complicated product changes’ and much-easier-to-run tests of messaging and marketing.
• A/B testing a copy change on the sign-up page drove 200% more signups
• Changing “Sign Up for Free Trial” to “See Plans and Pricing”
• Optimizely and Visual Website Optimizer have built tools that make it easier and cheaper than ever for companies to set up experiments on their websites without much help from the engineering team
• Anyone can run a rapid test on headlines, taglines, images, videos, buttons and more
• This frees up engineers to work on the more complicated tests
• CAUTION - often the tools rely on surface level metrics like clicks - not customer lifetime value. You need to track experiment cohorts through to long-term use
• Multivariate testing - not just A/B but different combinations of elements.
• Multi-armed-bandit - helps you find winning results faster

Experiments within the Product

• More complicated tests require significant engineering.
• Building the simplest possible prototype and asking users to test it
• Creating video or demo showing how a new feature would work and seeing how customers respond
• Adjustments historically proven to improve results and enhance the user experience should be prioritised, such as speeding up the response time of a web shopping cart or improving the signup process
• less battle-tested changes like substantial redesigns or feature building should only be done with a strong hypothesis driven by user research and data
• Minimise the risk of the investment of effort with sound reasoning first, mix bigger and riskier initiatives with more sure things

Taking a data dive

• To uncover what makes (or will make) your product a must-have, you need to collect the right data and build the connective tissue between various sources.
• To create a complete picture you need to connect early funnel (email marketing) to end of funnel (point of sale)
• You need a data analyst who can mine those sources of data for patterns and rich insights that can lead to growth ideas to experiment with
• While metrics like page views, visits, and bounce rates are important to collect, they barely begin to tell the whole story about how customers interact with your product.
• These are very surface level metrics that don’t tend to reveal deeper insights into what customers truly value
• You need data on each piece of the customer experience— well beyond just how often they visit your website and how long they stay there—so that it can be analysed at a granular level to identify how people are actually using your product (vs how you plan for them to use it)
• Once proper tracking is in place, multiple sources of user information can be stitched together to give you a detailed and robust picture of user behaviour you can analyse.
• A single location where all customer information is stored and where you can really dive in and uncover distinct grouping of users who may be using the product differently from other groups

What are active users doing?

• Firstly track the key actions of your users or customers through event tracking. Event tracking should allow you to track the complete path of what a customer does
• Look for behaviours that differentiate those customers who find your product must-have—that is, those who use or buy repeatedly—from those who don’t. Look for features that are most used by the most avid users and any other distinctive aspects of their behaviour in interacting with the product.
• Divide customer data up by many different customer attributes:
• location, age, or gender
• job title, industry
• mobile device they use
• As well as by the ways in which they are using your product
• power users or only intermittently use
• examine the choices they are making
• which products, services
• You will discover correlations between those attributes and behaviour and greater levels of purchasing, higher engagement, and longer-term use.
• Netflix found that Kevin Spacey films and political drama series were both hugely popular with their customers. Giving them confidence to green-light the development of House of Cards

Pivoting to the unexpected

• The distinctive behaviours and preferences can be hard to uncover, in part because sometimes they are so unexpected; paradoxically, you often don’t know what you’re looking for until you find it.
• Such unexpected discoveries are the rationale for investing in data collection up front and the rapid and relentless experimenting growth hacking calls for; the more you test, the more data you have to analyse, and the more data you analyse, the more patterns are bound to emerge.
• Instagram was originally a location sharing app called Burbn. The team noticed people were only really taking and sharing photos. So they pivoted. They kept only the photo, comment, and like features and relaunched as Instagram, positioning themselves between Hipstamatic [a popular photo-editing app] and Facebook.
• Pinterest was originally a mobile commerce app Tote - but they pivoted when they noticed people weren’t buying but were instead stockpiling massive collections of things they coveted
• Youtube was a video dating site - they pivoted when people were uploading videos of all different types to share. Why not let users define what YouTube is a all about
• These pivots prove the importance of collecting and analysing both qualitative and quantitative data about customers use of your product, and their thoughts about its strengths and weaknesses before you try to scale

Driving to the AHA

• Once you’ve identified the conditions that make the AHA moment, the growth team should turn its attention to getting more customers to experience that moment as fast as possible
• Facebook: people that added 7 friends within 10 days were most likely to stay active users
• Twitter: getting people to follow 30 users as soon as possible.
• One third of engineering time goes to getting the new user experience down just right

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