Hacking Growth

What was the secret? I worked with the engineers to utilize technology for what was, to them, an unconventional purpose: to craft novel methods for finding, reaching, and learning from customers in order to hone our targeting, grow our customer base, and get more value from our marketing dollars.

I decided that we should try to get feedback from people who had signed up but had then abandoned the service. We had collected their email addresses as part of the sign-up process, and we sent out an email asking them why they weren’t using LogMeIn.

Once again, the solution had been found in just weeks, using a recipe that included healthy doses of out-of-the-box thinking, cross-company collaboration and problem solving, real-time market testing and experimentation (conducted at little or no cost), and a commitment to being nimble and responsive in acting on the results.

The result was the emergence of a rigorous approach to fueling rapid market growth through high-speed, cross-functional experimentation, for which I soon coined the term growth hacking.

first step was to get Houston’s buy-in to conduct a simple survey of the current users to calculate what I called (and what you’ll read about in more detail later in the book) the product’s must-have score.

Then came the second step in the growth process: a dive into Dropbox’s user data. One discovery this yielded was that a full third of Dropbox users came from referrals of current users of the product.

Using PayPal’s program as a template, our small team quickly crafted a referral program that offered users an extra 250 megabytes of space in exchange for referring a new friend to the service, who would also get 250 megabytes added to their own account.

The plan was working, no doubt about it, but we didn’t stop there; determined to make the most of the opportunity, our team worked furiously for weeks to optimize every element of the program, from the messaging, to the specifics of the offer, to the email invites, to the user experience and interface elements. Implementing a method I call high-tempo testing, we began evaluating the efficacy of our experiments almost in real time.

“Growth was not about hiring 10 people per country and putting them in the 20 most important countries and expecting it to grow. Growth was about engineer[ing] systems of scale and enabling our users to grow the product for us.”

Using some sophisticated programming, and lots of experimentation to get it right, the team figured out a seamless way to cross-publish Airbnb listings on Craigslist, free of cost, so that whenever someone searched the popular classifieds site for a vacation rental, listings for properties on Airbnb popped up.

By rapidly testing promising ideas and evaluating them according to objective metrics, growth hacking facilitates much quicker discovery of which ideas are valuable and which should be dismissed.

In reality, their success was driven by the methodical, rapid-fire 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.

Growth hacking adopted the continuous cycle of improvement and the rapid iterative approach of both methods and applied them to customer and revenue growth. In the process, the growth hacking method broke down the traditional walls between marketing and engineering in order to discover novel methods of marketing that are built into the product itself, and can only be tapped with more technical know-how.

And while the details of how it is implemented vary somewhat from company to company, the core elements of the method are:

There is no question that stalled growth is one of the most pernicious and pressing problems for today’s businesses, and that’s not just true for start-ups, but for just about any business, large or small, in just about any industry you can think of.

But growth hacking isn’t just about how to get new customers. It’s about how to engage, activate, and win them over so they keep coming back for more. It’s about how to adapt nimbly to their ever-changing needs and desires and turn them not only into a growing source of revenue, but also passionate ambassadors and an engine of word-of-mouth growth for your brand or product.

At LinkedIn, for example, the growth team has evolved from an initial 15-person unit to comprise 120-plus members, broken down into five units dedicated to: network growth; SEO/SEM operations; onboarding; international growth; and engagement and resurrection of users.

MINING DATA GOLD Indeed, yet another way growth hacking gives companies a vital competitive edge is by helping them make good use of the mountains of customer data

Growth hacking cultivates the maximization of big data through collaboration and information sharing.

First, the process is not, as it’s been misunderstood by some, about discovering one “silver bullet” solution.

But while finding such big breakthrough ideas—like Dropbox’s referral program—is absolutely a goal of the process, in truth, most growth is due to an accumulation of small wins.

Second, many companies believe they can simply hire a single Lone Ranger to be the growth hacker, who will swoop in with a bag of magic tricks to bring growth to their business.

growth hacking is a team effort, that the greatest successes come from combining programming know-how with expertise in data analytics and strong marketing experience, and very few individuals are proficient in all of these skills.

One final misconception must be addressed. Growth hacking is often characterized as being specifically about bringing in new users or customers. But in fact, growth teams are, and should be, tasked with much broader responsibilities. They should also work on customer activation, meaning making those customers more active users and buyers, and figuring out how to turn them into evangelists.

Customer disengagement and flight, known as bounces for website visitors, and churn for paying customers, are two of the biggest problems for start-ups

Then there is the misconception that growth hacking is all about marketing. As we mentioned earlier, growth teams should also be involved in new product development, to analyze whether or not a product is optimized for its intended market—whether it’s offering what we call a must-have experience, and whether it has figured out how to deliver that experience to the right customers, what is often referred to as achieving product/market fit.

In short, growth teams should be involved in all stages and all levers of growth, from attaining product/market fit to customer/user acquisition, activation, retention, and monetization.

Growth hacking is a new fundamental business methodology that all companies, and every founder, every corporate team leader, and every department head and CEO who wishes to meet high expectations, produce meaningful results, and achieve their business goals with limited investment and maximum return on their marketing dollars must adopt.

One of the cardinal rules of growth hacking is that 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.

But the hard truth is that no amount of marketing and advertising—no matter how clever—can make people love a substandard product. If you haven’t created and identified core value before you make your growth push, you’ll either end up with illusory growth at best or market rejection at worst.

The opportunity costs of pushing for growth too soon are twofold.

as the growth team at Airbnb says, “love creates growth, not the other way around.” And for there to be love, there needs to be that aha moment.

Identifying what a product’s aha moment is can sometimes be quite tricky. It’s entirely possible to launch a product and conclude, because you’re experiencing anemic growth, that the product simply doesn’t have any aha magic

So a vital step in determining whether your product has the aha potential is to 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.

THE MUST-HAVE SURVEY The first step is a simple survey Sean designed, one that he has found again and again throughout his career

Interpreting the results is simple enough; if 40 percent or more of responses are “very disappointed,” then the product has achieved sufficient must-have status, which means the green light to move full speed ahead gunning for growth.

In these cases, a set of additional questions on the Must-Have Survey will help to point you toward your next steps:

The question about alternative products can help identify your chief competition for customers, and often point to features or aspects of the experience those products are offering that lead those customers to prefer them over others.

From the responses to the question about whether users have recommended the product, teams can gauge whether the product has word-of-mouth marketing potential, and if so, what you can do to make the most of it.

You’re looking to get at least a few hundred responses to the first question to be a reliable guide for this kind of survey.

Somewhat ironically, it’s best if you target the survey at active users rather than those who have gone dormant.

One caveat: the Must-Have Survey isn’t recommended much beyond the stage of determining whether you’ve achieved core product value.

once you have moved past this early diagnostic stage, your surveying and testing of the quality of the customer experience can and should become progressively more refined

MEASURING RETENTION The second measure to use in assessing whether or not you’ve achieved must-have status is your product’s retention rate, which is simply the number of people who continue to use your product over a given time.

The retention rate is simply calculated as the percentage of users who continue to use or pay for your product, generally tracked month to month.

If you’ve determined the product hasn’t made the grade, the first thing to do is to stop yourself from doing something that feels all too natural: guessing at what the elusive feature might be that may make your product more appealing to your customers.

So it’s vital to take an analytical approach to finding out why that aha moment hasn’t been achieved—and how to achieve it—rather than relying on conjecture. For this there are three key methods, all of which should be employed in concert.

The best practice is to take the product, or a prototype, out into “the wild” so that you can actually see exactly how prospective users respond to it.

Etsy “did something that works and is often overlooked. We got off the Internet.”17 By sending a team of people out to attend craft fairs all around the country and meet with prospective sellers to bring onto the site

Etsy’s community forums not only acted as a place for sellers to get tips on how to improve sales, they acted as recruiting boards for new sellers and as hubs of discourse around the feminist crafting movement.

Guided by this early adopter feedback, the team spent their time building tools and resources to make sellers successful, such as the aforementioned forums, the Seller Handbook blog, and developing tools and partnerships to help sellers with customer communication, order management, and more.

Whitney Wolfe, an earlier team member, did the legwork to actually go out and visit college campuses, making presentations to sororities, getting members onboard, and getting instant, face-to-face feedback about the app from real live users.

Conducting surveys and interviews may seem prohibitively time consuming but, in fact, crystal clear insights can often be gained with quite moderate numbers of survey responses and very few interviews.

Twitter team asked users who had gone dormant and subsequently returned:

Decisions about what experiments to run must be made rigorously, and most growth teams have adopted the practice of a minimum viable test (MVT), the least costly experiment that can be run to adequately vet an idea.

One particularly powerful and typically inexpensive method is A/B testing,

simply changing the language from “Sign Up for Free Trial” to “See Plans and Pricing” netted 200 percent more sign-ups.

Remember that a core tenet of growth hacking is experimentation all through the customer experience funnel: not just customer awareness and acquisition but also activation, retention, revenue, and referral.

EXPERIMENTS WITHIN THE PRODUCT The more complicated tests that require significant engineering time are usually those that are changes to the products themselves.

you need to collect the right data for your business, and build the connective tissue between various sources, such as your email marketing database and your point of sale system, so you can create a complete data picture. Then 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.

But 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. That’s because these are very surface level metrics

It’s essential that your team have data on each piece of the customer experience—well

What this means is that the marketers, data scientists, and engineers must work together to add the proper tracking to websites, mobile apps, point of sale systems, email marketing, and customer databases.

WHAT ARE ACTIVE USERS DOING? The first step in collecting the data to then pan for nuggets of insight is to track the key actions of your users or customers. This is done through the process of event tracking.

The key mission at this stage is to look for the behaviors that differentiate those customers who find your product must-have—that is, those who use or buy repeatedly—from those who don’t. Specifically, analysts should be looking for features that are most used by the most avid users and any other distinctive aspects of their behavior in interacting with the product.

All of these pivots speak to the importance of collecting and analyzing both qualitative and quantitative data about customers’ use of your product and their thoughts about its strengths and weaknesses before investing extensive time and resources in pushing for growth.

DRIVING TO THE AHA Remember that all of this experimentation and analysis should be focused on discovering the aha moment you are offering, or can offer, customers. Once the conditions that create that magical experience have been identified, the growth team should turn its attention to getting more customers to experience that moment as fast as possible.

Companies deploy many additional tactics to drive users to the aha, such as product tours, email communication, special offers, and more,

and the conversion rate to the paid version was an extraordinary 12.4 percent, far above most freemium product conversion rates, which hover around 1 percent.

But they made one fatal mistake: they failed to focus on finding a way to leverage the enthusiasm of their early adopters in order to drive much faster growth.

The Everpix tragedy demonstrates the importance of focusing not just on growth but on the right levers of growth at the right time.

what the Everpix founders needed to do was shift attention from making the product pleasing to making it more profitable—i.e., channel their considerable design and engineering talent toward the mission of turning more customers into paying ones.

HACKING YOUR GROWTH STRATEGY Creating an aha moment and driving more people to it is the starting point for hacking growth. The next step is to determine your growth strategy. You have to 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.

In the early phase of growth, you want to craft a strategy for running the experiments that will have the greatest impact on growth in the least amount of time.

Running lots and lots of tests of small changes, like button colors, isn’t the way to start practicing the growth hacking process. Instead, small teams must focus on those tests that promise to have the highest potential for impact first.

THE METRICS THAT MATTER The first step in determining your growth strategy and figuring out where to focus is to understand which metrics matter most for your product’s growth. The best way to do this is to craft what Johns dubbed a company’s fundamental growth equation. This is a simple formula that represents all of the key factors that will combine to drive your growth;

While all products will share common drivers of growth, such as new user acquisition, higher activation, and better retention, each product or business has a more specific combination of factors that are uniquely its own.

it’s of greater importance to identify the specific metrics unique to the product or business you are attempting to grow.

The way to determine your essential metrics is to identify the actions that correlate most directly to users experiencing the core value of your product,

You want to track, at a minimum, the metrics for each of the steps users must take to reach the aha moment and how often they are taking those steps.

Josh Elman explains that if you’re a travel service, like Airbnb, for example, then daily active users—though it may look good on paper—is nonsensical as a metric for you. Why?

CHOOSING A NORTH STAR To hone your growth equation and narrow your focus, it’s best to choose one, key metric of ultimate success that all growth activity is geared toward.

The North Star should be the metric that most accurately captures the core value you create for your customers. To determine what that is you must ask yourself: Which of the variables in your growth equation best represents the delivery of that must-have experience you identified for your product?

When you’re gunning for growth, it’s easy to find yourself in the moors, working madly on improving a metric that ultimately doesn’t matter. Picking the right North Star helps to reorient growth efforts to more optimal solutions, because it helps illuminate when the focus of your experiments isn’t producing the results you need.

To clarify how dedication to improving a North Star metric helps make difficult decisions about how to spend time and resources, let’s look at how the Airbnb founders decided to conduct an experiment they thought might generate more nights booked—their North Star.

THE DATA IMPERATIVE In order to determine your growth equation and establish your North Star metric, of course the prerequisite is the ability to both gather data on customer behavior and measure product performance and the results of experiments.

without the right data at your fingertips, your growth team will be flying blind.

Again, this often involves more than what the standard, off-the-shelf data apps like Google Analytics allow you to do. While those tools serve their purpose, when you’re starting to make your aggressive growth push, it’s important to be able to track every user from first visit all the way through all of that person’s interactions with the product, from how they discover it, to experiencing the aha moment, to when they stop using it.

The best growth teams take the time to get their data collection and analysis right.

In fact, marketing specialist Rob Sobers has outlined a simple method using off-the shelf tools that creates a data tracking system that (at time of writing) costs just $9 a month.

DESIGN ACCESSIBLE REPORTING One last point on data: the critical importance of reporting the results of your data discovery (and then from the experiments you’ll be running) in the most simple and accessible way possible.

To get a good sense of how valuable accessible reports can be, take a look at how complex the spreadsheets that growth teams typically create to track the metrics that matter can get. The figure below was shared by Dan Wolchonok,

There exist numerous tools to create sharp data visualizations, from simple tools designed for small start-ups such as Geckoboard and Klipfolio, to enterprise solutions such as Tableau and Qlik Sense and dozens more.

After narrowing the reporting to what really matters, the next step is to present information in a way that is actionable. For one, metrics should be presented as ratios rather than static numbers.

Elman made an initial discovery by doing what’s called cohort analysis, which is dividing your customers or users into distinctive groups by a common trait.

loves to point out that a 5 percent improvement in conversion rate every month nets an 80 percent improvement in a year due to the compounding nature of wins. If you were generating visitors through search ads, that increase in conversions would cut your costs of advertising per customer just about in half.

THE GROWTH HACKING PROCESS

The growth hacking process is designed to help discover the most cost-effective ways to acquire new customers—and then optimize those efforts to drive growth.

Once you’ve put together your growth team, determined your key growth levers, and done sufficient testing to establish that your product is a must-have, you’re ready to start hacking the first stage of the growth funnel: acquiring customers.

The first phase of work in scaling up your acquisition of customers should be devoted to achieving two additional types of fit: language/market fit, which is how well the way you describe the benefits of your product resonates with your target audience, and channel/product fit, which describes how effective the marketing channels are that you’ve selected to reach your intended audience with your product, such as paid search advertising or viral, or content, marketing.

First we’ll look at how to hone your marketing language to best communicate what is not just valuable, but special, about what you have to offer. Then we’ll talk about how to identify a core channel or two to focus on, and ways to leverage that channel for optimal growth. Next we’ll explore how to come up with clever hacks for acquiring customers through viral mechanisms, like referral programs, built into the product itself.

CRAFTING A COMPELLING MESSAGE The term language/market fit was coined by James Currier (who we met in the introduction) 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.

Research has shown that the average attention span (the amount of time we focus on a new piece of information online) of humans is now eight seconds, which is down from twelve seconds in 2000, and confers on us the dubious distinction of having an attention span shorter than that of goldfish.

This means that the language you use must directly and persuasively connect with a need or desire they have in order to hook them—in eight seconds or less!—into

Another reason the up-tempo growth hacking process is so perfectly suited to this challenge is the fact that language is a breeze to run A/B tests on. Website copy can be swapped out and tested relatively easily with tools like Optimizely and Visual Website Optimizer,

They pick two promising headlines for the same story and give each its own Bitly URL.

Given that, according to Eli Pariser, the site’s founder, “a good headline can be the difference between 1,000 people and 1,000,000 people reading,” this extra work is well worth it.

One is to adopt the language that your customers are using to describe your product and its benefits in social media posts and in online reviews. Another is to draw on comments from the customer surveys you hopefully conducted when determining if your product is a must-have.

Marketers commonly make the mistake of believing that diversifying efforts across a wide variety of channels is best for growth. As a result, they spread resources too thin and don’t focus enough on optimizing one or a couple of the channels likely to be most effective.

At the same time, too many companies get caught in the trap of following the herd, using the same channels as everyone else, such as Google paid ads or Facebook advertising, and not experimenting with options that might be more effective for their specific product, and less expensive.

NARROWING THE FIELD There are two phases in which to home in on your best channels: discovery and optimization. In the discovery phase, the growth team should experiment with a range of options,

method for doing that in just a moment. Once you have found those one or two with the right fit, you can move to the second phase, optimization, in which you should be working to maximize both the cost-effectiveness and the reach of your channels as you keep scaling up.

To get started, you’ve first got to get a fix on all of the channels that might make sense for you to consider.

THE THREE CATEGORIES OF CHANNELS

THE LEADING TYPES OF CONTENT MARKETING

created this handy chart of types of user behavior that you can use as a guide in making these decisions.

created a simple scheme for ranking channels according to a set of six factors:

PRIORITIZING DISTRIBUTION CHANNELS

The team decides to also do some additional market research, running some feedback surveys on the company’s main website and on the app, and also interviewing some existing customers.

The team comes up with the following hacks to consider:

Let’s say the scores come out as follows:

if your product isn’t delivering value, if it doesn’t deliver the aha moment—then no viral loop strategy is going to help you.

For one thing, it’s important to distinguish between the different types of virality, one being the traditional word-of-mouth variety and the other being a feature built into a product that provides a mechanism for users to hook in more users, which is often referred to as instrumented virality.

As you begin considering what sort of viral loop to experiment with, you’ve got to make a couple of key decisions.

Here are a number of best practices for experimenting with creating loops that will help you avoid such pitfalls.

Improving activation is at its core about increasing the rate at which you get new users to your aha moment.

There is no one formula 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.

In this chapter, we will first introduce the three essential steps every growth team must take in order to identify the highest-impact activation experiments to run.

MAPPING THE ROUTE TO THE AHA MOMENT The first step in hacking activation is to identify each point in your customers’ journey toward the aha moment.

The next thing the team needs to do is list all of the steps that new users must take in order to have this experience: they need to download the app; find items they want; add them to their carts; create an account by adding in their name, credit card, and delivery information; then make the purchase itself.

But in growth hacking, it’s crucial that you never assume why users are behaving as they are; rather, you’ve always got to study hard data about their behavior and then query them on the basis of observations you’ve made in order to focus your experimentation efforts most efficiently on changes that will have the greatest potential impact.

the next step toward homing in on stumbling blocks for customers and figuring out what’s causing them to flee is to calculate the conversion rates for each of the steps on the way to the aha moment, or, in other words, the percentage of all visitors who are taking each of those steps along the path to success.

CREATING A FUNNEL REPORT OF CONVERSIONS AND DROP-OFFS One of the best ways to measure conversion rates is through a funnel report,

For another company—let’s say Uber—the funnel report might display the rate at which people are downloading the app, then the opening of the app, then the number who proceed to create a new account, the rate at which people book a ride, and the rate at which they rate their driver, and so on.

The point is that whatever your product is, you should be tracking all essential steps of the customer journey to that moment of activation.

Once this data is available, you will look for differences between active customers, those who activated but then went cold, and those who never activated, or have “bounced.”

The data analyst on the growth team will create a funnel report that calculates the rates for downloading and opening the app, the rates at which people are searching for items to buy, the rate at which people are adding items to the shopping cart, and, finally, creating an account and purchasing.

Armed with this data it is clear that one major stumbling block is the checkout experience. So the team will want to consider experiments with making it easier to check out, perhaps by trying a new payment form design that’s easier or quicker to complete.

So they’ve got lots of options to choose from. But before they start experimenting, there is one more step in data discovery. They must “get out into the wild” and conduct some surveys and interviews to probe into the reasons for the user behavior the data has revealed.

To get the most useful responses, while at the same time assuring a survey is not a turn-off to customers, it should be very brief, and should be delivered to users under two main conditions: (1) when their activity indicates confusion, such as lingering on one page for too long, or leaving the screen or page on the app or site; or (2) right after they’ve gone ahead and taken the step that many others aren’t taking, such as creating an account or making a purchase.

stopped them from moving forward, with questions such as:

“What’s the one thing that nearly stopped you from completing your order?” We’ve found this “one thing” question elicits a high number of responses, and ones that are very eye-opening.

Once the grocery team has done all this, they now have both the data and the color commentary from customers they need to evaluate a first set of ideas for experiments.

They began by segmenting their users into buckets of people with similar attributes, starting with the general set of common differences, including the different traffic sources they were coming from, such as Google and Facebook.

One discovery they made was that users who signed up using their work email address as opposed to their personal email account had a higher activation rate.

ERADICATING FRICTION In user experience design, friction is the term used to refer to any annoying hindrances that prevent someone from accomplishing the action they’re trying to complete,

OPTIMIZING THE NEW USER EXPERIENCE The first rule of designing and optimizing your NUX is to treat it as a unique, onetime encounter with your product;

The second rule is that the first landing page of the NUX must accomplish three fundamental things: communicate relevance, show the value of the product, and provide a clear call to action.

SINGLE SIGN-ON

THE ART OF THE QUESTIONNAIRE Neil Patel, a leading expert in growth hacking, has highlighted the effectiveness of asking users a set of questions as you greet them.

When Patel tested similar questionnaires with Hello Bar, which he owns, he was able to increase the number of leads generated by 281 percent.

A key caution here is that you also don’t want to ask too many questions. Patel recommends no more than five, and making them multiple-choice rather than open-ended, with no more than four possible answers each.

GAMIFICATION PROS AND CONS Gamification is, in essence, offering rewards, such as perks and benefits not available to all people, to customers for taking certain actions.

Nir Eyal, the author of Hooked: How to Build Habit-Forming Products,

THE COMPOUNDING VALUE OF RETENTION It should go without saying that the longer you retain customers, the more opportunity you have to earn more revenue from them,

Yet another benefit of higher retention is that it allows you to see stronger results from both word of mouth and your viral marketing efforts, because the longer users stay with your product, the more opportunities they’ll have to talk about it and even to show it to friends and others.

THE THREE PHASES OF RETENTION

The initial retention period is the critical time during which a new user either becomes convinced to keep using or buying a product or service, or goes dormant after one or a few visits.

For example, Pinterest might determine from analysis of user data that if a new user doesn’t return to the site at least three times within the first two weeks after signing up, they are highly likely to abandon use.

Once new users have crossed the threshold of initial retention, they move into the medium retention phase, a period when the interest in a product’s novelty often fades.

Then, we’ll move on to the tactics for long-term retention. This is the phase in which growth teams can help to assure that a product keeps offering customers more value.

For e-commerce, the basic metric of retention is the repurchase rate of customers, which might, for example, be the number of times customers make a purchase per month.

HACKING INITIAL RETENTION Once you’ve analyzed the cohort data to identify drop-off points in initial retention, and deployed surveys to probe into the causes of the defections, you can begin to experiment with solutions.

The key to habit formation is convincing customers of the ongoing rewards they will receive from returning to your product or service.

There are social rewards, such as Facebook’s “Like” feature, which has been a strong driver in making the posting of photos and comments habitual.

The Yelp Elite Squad program has been one of the most successful at using this approach to increase retention.

2. RECOGNITION OF ACHIEVEMENTS All customers appreciate recognition from companies, whether that recognition is big or small.

Optimizely, has shared how the company improved a number of metrics, including activation and retention, by delivering a personalized home page experience to their most important audiences. The company went from having one home page to more than 26 variations based on key accounts, time of day visiting the site, business vertical, and more.

The results of the program have been extraordinary, driving the growth of users who return to the site each month (monthly active users, or MAUs)

Communicating to customers that some new features or product offerings are just around the corner, and telling them how they’ll benefit, can be a powerful inducement for them to stick with you.

So another important element of long-term retention is figuring out how to move your users along a learning curve. This developmental process—called ongoing onboarding—is similar to how you would learn any subject, such as an instrument or language or technical skill:

RESURRECTING “ZOMBIE” CUSTOMERS Winning back users who’ve abandoned a product is called resurrection in growth circles.

The first thing to do, of course, is investigate why people disappear in the first place. Getting to the bottom of this can be done quite simply by interviewing people who canceled or no longer use your product about why they left. For example, when Evernote was struggling with their retention, their growth team found that one of the big reasons people stopped using the service was that when they purchased a new computer or phone, they didn’t immediately install the app again on their new device.

Most of the work of resurrecting past known customers is done through emails and advertisements. When teams notice that a customer’s purchasing or a user’s activity has dropped to zero, after some designated time—which the team should experiment to determine—these people should be added to a resurrection flow, which means that they should be sent a series of email communications or targeted ads designed to win them back, often by reminding them of the aha moment, or core value that once drew them to the product.

Attempts to resurrect such “cold” customers may seem low priority. There’s no question that if your retention is suffering, your first area of focus should be on early retention of new users.

So in this chapter, we’ll focus specifically on this mission of earning more money from the base of customers you have.

If you’re a software as a service (SaaS) company, it is achieved by getting more subscribers to renew their subscriptions, and to do so for more years, as well as by persuading more of them to upgrade to higher-fee levels of service (or in the special case of freemium services, by getting more users to upgrade to paid plans).

MAP YOUR MONETIZATION FUNNEL As with all growth hacking efforts, the first step is to perform data analysis that will help you home in on the highest-potential experiments. When it comes to monetization, analysis starts by returning to the basic mapping of the entire customer journey, which, recall from Chapter Six the team should create when it first starts the growth hacking process.

The next step after doing this basic mapping is to analyze where in the customer journey the company is making the most money, and where there seem to be pinch points, meaning steps where potential earnings are lost, which vary by model. By identifying high-value pages and features within a product, website, or app, growth teams can experiment with ways to generate even more revenue from them, while identifying those pinch points with poor conversion rates and high friction will generate ideas for patching up revenue leaks.

For SaaS businesses, the pages displaying the options for plans and their prices are often underoptimized, hurting rates of purchase.

For a SaaS company the analysis might show a pinch point in the step from free trial sign-up to paid subscription.

HOW MUCH ARE YOU MAKING FROM COHORTS? In analyzing your customer data to assess opportunities you also want to divide customers into a number of cohorts, as you did for hacking retention.

For an e-commerce company, you can break customers into groups according to how much they spend per year (or month, or week, depending on your model) on purchases.

But again, instead of looking for patterns in retention rates, at this stage you want to look for correlations to revenue being made from each of these groups, which will provide ideas for experiments.