• 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.

• 3 Growth Hacking Myths
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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
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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
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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.

• 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

• 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

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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
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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

• Step 1: Create and identify your AHA moment, make your product compelling enough to pass the must-have test. This is a prerequisite for fast and sustainable growth, but in itself it’s not sufficient.
• Step 2: Understand exactly how you’re going to drive growth—what your growth levers are and whether they are the right ones to achieve desired results—before you move into high-tempo testing of growth ideas.
• Great products can still fail without a well-focused effort to vigorously drive growth
• Focus not just on growth but on the right levers of growth at the right time.
• Set a disciplined course for experimentation that focuses on the most important levers
• Speed of testing isn’t the goal; scattershot experimentation will waste time and effort even if testing at high tempo.
• Growth hacking isn’t throwing ideas against the to see what sticks, it’s about applying rapid experimentation to find and then optimise the most promising areas of opportunity.
• Running the experiments that will have the greatest impact on growth in the least amount of time. The more focused efforts are at the start, the more intentional your experiments will be, and the more impact you’ll achieve.
• In addition to the potential for bigger wins, high-impact tests will also produce definitive results faster
• Experiments expected to have a high impact / big effect can be measured more quickly - this enables you to move onto the next. Experiments with a small impact will take a long time to prove themselves - and aren’t worth doing
• Be dramatic - don’t just move a button on a page.
• You can shift toward a higher volume of smaller tests once you have more users
• Step 3: High tempo testing of growth ideas

How to determine your growth strategy?

1) Find the Metrics that Matter

• To understand which metrics matter most for growth - craft your fundamental growth equation.
• A simple formula that represents all of the key factors that combine to drive your growth - your core set of growth levers. This is different for every product or business.

• Many products share common drivers of growth (acquisition, activation, retention) but each product has a more specific combination of factors that are uniquely its own
• Yelp: business reviewed and number of reviewers for each
• Facebook: items being shared by users and time spend looking through new feed
• Determine your essential metrics by identifying the actions that correlate most directly to users experiencing the core value of your product
• Your equation should track each of the steps users must take to reach the aha moment and how often they are taking those steps.
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Uber Example:
• Key value is a completed ride - so key things to track are downloading the app, rides being booked, number of riders who return and rebook, frequency of booking rides (but you could also think about the supply side for uber too)
• A growth equation can be simplistic → but its that reduction in complexity that allows for focus
• Many products have a built in ceiling when it comes to frequency of visit - regular use has a different meaning that is specific to your product
• Facebook aims to be visited frequently
• LinkedIn wants both frequent visits, but also important is people to fill out their profile just once - so it looks like a complete professional network
• Ebay wants numbers of items listed for sale to be high, as that’s what going to drive users

Choosing a North Star

• Hone your growth equation and narrow your focus by choosing a single metric of success that all growth activity is geared toward.
• Called the North Star - or the One Metric That Mattes
• It should be the metric that most closely captures the core value you create for your customers
• Which of the variables in your growth equation best represents the delivery of that must-have experience
• WhatsApp: Messages sent
• AirBnB: Nights booked
• Be extremely clinical and emotionally detached.

A good plan violently executed now is better than a perfect plan tomorrow General George Patton

• The North Star goal brings clarity and focus to data analysis and experimentation

The Data Imperative

• Before determining your growth equation and North Star metric you’ll need customer behaviour, product performance and experiment performance data.
• Jack Dorsey refers to data tracking set up as “instrumentation.”
• You’ll need to collect and unify data from different sources - by the time you’re done it should be possible to track every user from first visit, through all product interactions, how they discover it, how they experience the aha moment and when they stop using it.
• Data can tell 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
• Make sure your data reporting is accessible. It has no value if nobody can read and understand it. Create understandable dashboards to keep your team focused on key metrics, and share findings with the whole company
• Reports should be insightful and actionable. Narrow the reporting down to what really matters.
• Show the time period and the % change (also compare to a goal)
• Use cohorts to find exiting trends. Twitter found that those who visited more than 7 times in a month had super high retention.

• High tempo growth hacking is about learning more by learning faster
• Companies that grow the fastest are the ones that learn the fastest.The more experiments you run, the more you learn. It’s really that simple.
• Most experiments fail to produce the results you’re hoping for - so volume is key.
• Very few tests produce dramatic gains. Finding wins is therefore a numbers game
• Big successes come from compounding a series of small wins over time. Each learning leads to better performance and better ideas to test
• 5% improvement in conversion rate every month nets an 80% improvement in a year when compounded.
• Many of the leading growth teams regularly run 20 to 30 experiments a week.
• To maximise the number of experiments you can run it’s essential to follow a highly disciplined process that allows you to create a pipeline of good ideas and efficiently prioritise them.
• Teams should start slow and build to a faster tempo after the new process is understood

The Growth Hacking Cycle

• Data analysis → insight gathering → idea generation → experiment prioritisation → running the experiments → review results → decide
• Each turn through this cycle should be completed on a consistent interval, preferably in one or two weeks. The cycle is managed by a one-hour weekly growth team meeting to review results and agree on the next week’s set of experiments to implement.
• Before your first cycle hold a team meeting to explain how the process will work. Clarify the role to be played by each team member and how they are expected to work.
• Share the results of initial analysis - present the growth levers - the North Star Metric - the area of focus for the team
• Set a goal for the volume and tempo of experiments to launch each week
• Take the next week to brainstorm and percolate ideas for what experiments to run in the first cycle

Stage 1 - Analyse

• Start by separating regular users from those who have never or barely use the product

• Conduct short surveys and interviews

Stage 2 - Ideate

• The best way to have a good idea is to have lots of ideas. THEN use rigorous prioritisation
• Get everyone to submit as many ideas as possible, self-censorship should be discouraged
• Setup an idea pipeline - templated format
• Name, Description, where, when, why, how, Hypothesis, Metrics to be measured)
• Allow people outside of the team to submit ideas
• Prioritise it with a numerical score (detail below)

Stage 3 - Prioritise

• Allow the individual submitting the idea to score it

Stage 4 - Test

• Add the best to your Kanban board
• Communicate your experiments widely across the company
• Carefully select your ideas - the opportunity cost is every other idea
• If you can - make each test produce statistically significant results
• Use a 99% statistical confidence level - if the results are inconclusive, stick with the control
• Share the results of your experiment in a standard format - save it into a knowledge base
• Create a wins email distribution list - to celebrate wins

The Growth Meeting

• Hold once a week - on Tuesdays
• Focus on the nominated ideas and agree on the plan for experimentation
• Don’t brainstorm ideas in the meeting - do as individuals, or in specific meetings once a month
• Use Monday to check on experiments and to prepare for the meeting
• Review of the activity from the prior week:
• number of experiments successfully launched compared to target
• brief the team with the latest view of the important metrics
• distribute reports about the finished tests
• Sum up the previous week’s activity and results
• Send in advance

• Acquiring customers is important - but if acquiring them costs you more that you stand to make from them you have a problem.
• There’s no formula for the exact amount you should spend on acquisition - but making acquisition as cost effective as possible is always a good idea
• Don’t go hard on acquisition until you’ve got product/market fit
• Phase 1: Language/Market fit and Channel/Market fit

Crafting a Compelling Message (Language/Market fit)

• Language/market fit was coined by James Currier - to refer to how well the language you use to describe and market your product to potential users resonates with them and motivates them to give it a try.
• Think about language across the entire customer journey (emails, notifications, print, online advertisements, messaging used within the product itself)
• Not just the tagline and value proposition - everything is important
• With so little time to impress people, it is imperative that they understand almost immediately how your product can benefit them.
• The language must directly and persuasively connect with a need or desire they have in order to hook them—in eight seconds or less!
• Craft language that concisely communicates your product’s core value—conveying the aha moment—and answers: How is this thing you’re showing me going to improve my life?”
• Apple iPod: 1000 songs in your pocket
• Marketing copy is not an exact science. Running experiments can bring some rigour.
• Optimizely and others can easily swap out copy on the web and and measure the responses - email marketing tools and online advertising platforms allow you to do the same
• You can use different links to signify different bits of copy/marketing and count the clicks as they come in

Start Small

• Small changes in language can have a big impact on customers. So doing many experiments is key
• The book gives two examples of hugely successful changes - I think that both of them completely change the positioning of the products
• ‘Store your photos online’ to ‘share your photos online’
• ‘Find a date’ to ‘help people find a date’
• Languages fit helps hone your product, not just your branding. The two changes above, might require them to change the nature of the product themselves

Channel Fit

• Don’t feel that you have to diversify across channels for marketing and distribution - you can spread resources too thin and fail to optimise the channel that’s likely to be most effective.

Put more wood behind fewer arrows Larry Page

It is very likely that one channel is optimal. Most businesses actually get zero distribution channels to work. Poor distribution—not product—is the number one cause of failure. If you can get even a single distribution channel to work, you have great business. If you try for several but don’t nail one, you’re finished. Peter Theil

Narrowing the Field

• Go for a two phase approach: Discovery and Optimisation.
• Discovery Phase: experiment on a wide range of options
• Channels should be researched thoroughly and prioritised
• Find one or two that have high potential to be the right fit
• Optimisation
• Maximise the cost-effectiveness and reach of your channels

Three Types of Channel

For each of those channels - there’s a number of options to pursue.

Making the first cut

Experimenting To Get Channel/Product Fit

• Rank against the following six factors - give a high, medium, low score.

• You can do a little customer research to understand more about which channels might be a good fit
• Even with an established channel or tactics - new options always emerge. Look for opportunities to experiment. However, because there are so many it’s important to take the data-driven, prioritised, and experimental approach to help wade through that vast sea of options and smartly focus your efforts and resources
• As you grow - you’ll hit natural ceilings in channels and have to add more. Teams should also be shifting focus between activation, acquisition and retention.

Designing Customer Loops

• Growth hacks that involve viral loops (hotmail signature, Dropbox referral storage) aren’t easy to create. You can’t necessarily set and forget a viral loop.
• It’s easier for some products to create a viral loop than others. Money sending apps and messaging apps have strong incentives.
• You need to deliver an aha moment for a viral loop to work. It’s a combination of how good ‘the packing is’ and ‘how good the content is’ - you can trick somebody to click, but they aren’t going to share
• Make the experience of sharing the product as user friendly and delightful as possible
• To be truly viral - the product must have a viral coefficient (or K-Factor) of greater than 1. Each new users who signs up brings in one or more new people to the product.
• This is very rare and only for a limited time usually
• Viral Coefficient K = invites sent by customers x % accepted
• Sean Parker’s way of looking at virality is through payload, conversion rate and frequency
• Virality = Payload x Conversion Rate x Frequency
• Payload is the number of people each user will send to and frequency is the frequency with which people will be exposed.
• The best viral loops - the delivery is a natural result of using the product (e.g sent with Hotmail). Otherwise, using a double-sided incentive is helpful. Be mindful of racheting up the payload - that can annoy users and also lower conversion.
• Consider the potential to tap network effects
• Create an incentive that’s in synergy with your products core value
• Make the invite to share an integrated part of the user’s experience - not an add on
• Make sure the invitees are given a good experience
• Experiment, Experiment, Experiment

• Most apps lose 80% of their users within 3 days
• Improving activation is about increasing the rate at which you get new users to your aha moment.
• Find the impediments to the aha experience, and experiment with hacks for improving activation. Your efforts must be tailored specifically to your product, and your ideas for experimentation should be inspired by analysis of your specific data

Follow the Three Steps:

• Use information from the above to generate and prioritise experiment ideas.
• You can’t know ahead of time which experiments are going to be most effective - stay nimble and data-driven: continuously tailoring experiments according to the discoveries you make and then being ready to quickly adjust and try other approaches if experiments aren’t working as hypothesised

Eradicating Friction

• Friction is any hindrance that prevents someone from accomplishing the action they’re trying to complete
• We often don’t recognise sources of friction in products we’ve been involved in creating.
• In usability testing Designers are often shocked to see how much difficulty people are having
• Friction is everywhere, from checkout forms to forced account creation
• At every hurdle your customer is asking - Is it worth it? … if you haven’t communicate a compelling value proposition, customers will abandon
• Desire - Friction = Conversation Rate
• Early adopters are great as they have a strong desire
• To improve activation you can either increase desire or reduce friction
• Desirability is harder than discovering and eliminating friction.
• Friction is the low-hanging fruit
• Your funnel conversion report is your friction roadmap
• NUX = New User Experience

Optimising the New User Experience

• Rule 1: Treat the NUX as a unique onetime encounter with your product (as a different product)
• Rule 2: The first landing page of the NUX must have the conversion trinity

Things To Try:

• Single Sign On → A key area of experimentation - can reduce friction
• Flip the Funnel → allow visitors to start experiencing the joys of the product before asking them to sign up
• Stripe allows developers to start using it immediately - account details are needed only when you turn on real money payment

• Triggers → any prompt that provokes a response from people (notifications, emails, CTAs)
• Success of Trigger = Motivation to take action x Ease of taking the action
• Behaviour = motivation x ability x trigger
• Don’t try to get people to opt into emails or notifications too soon
• Don’t get in touch with the users unless you are alerting them to an opportunity of clear value to them
• Use holdout groups to assess the effectiveness of experiments

• The purpose of business is to create and keep a customer
• The rate of customer churn - is high in many businesses
• High retention is a key factor in achieving strong profitability
• Acquiring customers costs money, so look after the ones that you have
• Of customers who’ve had Amazon Prime for 3 years - renewal rates are 96%

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
• Better retention will drive better results from viral marketing - the longer they stay, the more likely they’ll talk to others about it

Homing in on best bets fast

• Increasing competition is made cost of acquisition high, its more important than ever to focus retention.
• You need to notice and stop problems that induce churn as early as possible.

What Drives Retention?

• Providing a product that addresses the needs of, or delights of a customer is the best way to drive retention

• Reasons for dropping retention:
• New competitor (or existing competitor with a new feature)
• A promotion at a competitor
• Your not communicating with your customers well (staying top of mind)
• Not taking opportunities to build loyalty and habitual use
• The need is no longer urgent - or is being fulfilled in a way that is more satisfying or convenient
• Look for early signs of erosion in retention. Apply the rapid experimentation to pushing retention higher and higher.

• 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
• Evernote has a smile retention graph - the longer people use Evernote the more likely they are going to continue to use it - usefulness of the product improves over time.
• Capitalising on stored value is a great idea - but you need to keep users engaged over time

Three Phases of Retention

What does good retention look like?

• Depending on frequency of use - they’ll measure retention in different ways. Facebook has a daily view, Apple hardware teams will have a multi-year retention view
• E-Commerce: repurchase rate (number of times customers make a purchase per month). Grocery would be different to non-food.
• Always benchmark against the best in the industry.
• AirBnB can’t expect the same retention figures as Instagram
• Your churn rate is the inverse of your retention rate - Costco has 91% retention and 9% churn

Identify and chart your cohorts

• Once you know how to your retention measure - you’ll need to do a cohort analysis
• By time of acquisition - is common
• By channel - to understand channel quality of channel
• By frequency of use (or basket size) - look for interesting correlations
• Purchased within the first 30 days
• Different programs - Mixpanel, Kissmetrics or Amplitude
• Key Question: are the customers were acquiring today as likely to retain as previous cohorts - you may discover that a particular campaign resulted in an acquisition of users more likely to churn

1. On the left - the number of customers who signed up
2. In the table - the absolute number who are retained each month
3. Notice - number of customers acquired jumps up around June - but retention isn’t as good as previous cohorts
4. Follow up - survey the churned customers to ask why they canceled

Hacking Initial Retetnion

• First - identify drop off points in retention. Second - deploy a survey to help understand.
• Experiment with solutions
• refine the NUX - new user experience - get them to experience the core value of the product as quickly as possible
• use of triggers - notifications, emails to cement usefulness and value of the product in the users mind

Building Habits

• You want them to turn to you not a competitor - to be loyal to you
• The key to habit formation is ongoing rewards - rewards for returning to your product
• The Hook Model - or Engagement Loop
• Trigger → Action → Reward → Investment (repeat)
• Amazon Prime wasn’t really about the fee - it was about getting loyalty
• Map out the engagement loop of your product - set out to measure, monitor and optimise it. Experiment with triggers and rewards.
• Improving the perceived value of rewards leads to greater retention. Experiment with a range of rewards, encourage users to take action to receive them.
• Do a cohort analysis - to see who’s using the product the most - what features their using and which features provide the greatest reward and affect retention the most.

Offer rewards - both tangible and experiential

• Tangible rewards: savings, coupons, vouchers or gifts
• Experience rewards: ‘likes, status, access, VIP’

Longterm Retention:

• Two things to try:
1. optimising the current set of product features, notifications and rewards
2. introducing a steady stream of new features over a long period of time
• Beware of feature bloat, don’t make products overcomplicated (and obscure their real value)
• Get new feature prototypes in the hands of users before you have something polished.

Ongoing Onboarding

• Ongoing Onboarding: Continue to educate your customers about the value they can receive from your product
• Lead them on a continuous journey of discovery. Move users along a learning curve
• Start small simple objectives, and build their mastery.
• Getting users to a place where their getting the most value out of the product is called ramp up
• Introduce new features gradually to users - learn a new feature only after having achieved mastery in the previous one.

Resurrecting Zombie Customers

• Resurrection
• Investigate why they churned (interviews and surveys)
• Emails and advertisements.
• After activity drops to zero - add users to a resurrection flow. Sent emails and ads designed to win them back. Reminding them of the aha moment.
• Experiment with frequency, duration and working of your messaging.

• The ultimate goal of acquiring, activating and retaining customers is to earn revenue.
• Goal: earn more revenue from each customer over time - increase the LTV (lifetime value)
• Retail: purchase more. SAAS: More renewals, and plan upgrades. Adverts: creating more space to sell, or charging a higher price

Map Your Monetisation Funnel

• Map the entire customer journey → highlight all the opportunities, from acquisition to retention. Highlight barriers and friction too.
• This is referred to as the purchase funnel
• Opportunities and pinch points are going to be different for different product types
• Retail: Product page, shopping cart, payment page
• SaaS: feature and pricing pages, add-on and upgrade pages.
• Ads: pages where ads can be shown
• Shard by category

• Customers were more likely to book if they used 3G over WIFi → as it was harder for them to shop elsewhere
• Features of software customers are most inclined to pay for could differ by cohort

Using Data and Algorithms to Customise offerings to customers wants and needs

• Use personalisation to build a stronger relationship with customers
• Personalisation is good for monetisation and retention.
• Customised recommendations while visiting, through emails and mobile push messages
• Base selections on: search history, buying habits and similarities to other customers
• Many recommendations are based on simple math - like the Jaccard Index or Jaccard similarity coefficient (determine how similar two products are to each other)

1. 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

Don’t be intrusive

• Personalisation can backfire if you’re not sensitive about how you’re doing it - it becomes creepy. Test any personalisation on a small segment of customers first

Optimising your pricing

• Book Recommendation: They Myth of Fair Value.
• Charm prices (ending in 99) improve sales by 24%.
• 4 Question Pricing Survey
• At what price does (your product) become too expensive that you’d never consider purchasing it
• At what price does (your product) start to become expensive, but you’d still consider purchasing it
• At what price does (your product) start to become a really good deal?
• At what price does (your product) start to become too cheap that you’d question the quality
• Plotting the results gives you a diamond - test prices in that range

• Don’t set your price in stone.
• Combine pricing research with feature research:
• Create a matrix of features and price points
• Helps you build product/pricing plants that meet needs and expectations of customers
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Cross reference with target personas

• This mapping will give you ideas for experimentation (with pricing plans etc)

Persona A	Persona B
Valued Features:	Valued Features:
Feature 1	Feature 4
Feature 4	Feature 1
Feature 6	Feature 3
	Feature 2
Not valued:	Not valued:
Feature 2	Feature 6
Willing to pay x	Willing to pay x
Cost to acquire y	Cost to acquire y
Lifetime value x	Lifetime value x

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Pricing based on value metrics
• Can you find a way to charge customers more as they get more value from your product?
• Find the value metric - by asking three questions
1. Does the value metric align with where your customer perceives value?
2. Does the metric scale as the customer uses the product more?
3. Is it easy to understand?
• Survey Monkey charge based on the number of answers that the survey produce
• You also need to think about how you present and communicate the prices. Make sure the features of different plans can be easily compared to each others
• Dynamic pricing can backfire if done wrong
• Consider adding a decoy package - to drive customers to higher-priced products
• Less is not always more - experiment first if you’re planning to lower prices.
• Sometimes charging more can drive more sales - if you look like the best in class
• The Penny Gap = The difference between free and one penny can be huge.
• If your model is freemium - activation becomes really important
• Consider advertising, referrals or sponsorships to create revenue
• Learn your psychology:
• Principle of social proof: people are more likely to follow the behaviour of others
• Principle of authority: people are more likely to trust experts
• Principle of liking: we buy more when its recommended by people we like
• Principle of scarcity: we’re more likely to take action if we fear missing out

• Breakout companies sustain success by pushing for more, capitalising on new opportunities and creating a virtuous cycle of growth

Avoiding growth stalls

• Often happen when a company is over-confident OR they lose focus on their core products and services
• Channel volatility can bite - many channels institute regular changes in rules that can impact growth

Set a minimum number of tests a week - velocity of testing is really important

Don’t be afraid to double down - push more and more on successful levers

Mine deeper for data gold - review each major tasks and pathways users take to reach the aha product moment.

Open up the idea process to other teams.

Take moonshots - push past the local maximum