Hacking Growth

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. The survey asked the simple question “How would you feel if you could no longer use Dropbox?” Users could respond “Very disappointed,” “Somewhat disappointed,” “Not disappointed,” or “N/A no longer using the product” (I wrote the question this way because I found that asking people if they were satisfied with a product didn’t deliver meaningful insights; disappointment was a much better gauge of product loyalty than satisfaction). Having already run this survey at numerous start-ups, I had found that companies where more than 40 percent of respondents said they would be “very disappointed” if they could no longer use the product had very strong growth potential, where those that fell under that 40 percent threshold tended to face a much harder path in growing the business (due to user apathy).

As Andy Johns, who is a leading authority on growth hacking and worked on the growth team at Facebook, said of the effort, “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.” Johns has called it one of the most significant levers in scaling Facebook to the massive reach it enjoys today.

In truth, most growth is due to an accumulation of small wins. Like compounding interest in a savings account, these gains stack on top of one another to create liftoff. And the best growth teams continue to experiment with improvements even once growth takeoff has been achieved.

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 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. (The exception to this rule being businesses such as social networks, where the core value is the people on the platform.)

The opportunity costs of pushing for growth too soon are twofold. First, you’re spending precious money and time on the wrong efforts (i.e., on promoting a product that no one wants); and second, rather than turning early customers into fans, you’re making them disillusioned, even angry, critics.

A pernicious misconception about growth hacking is that it is primarily about building virality into products. That is indeed one of the key tactics, but like other growth efforts, it must only be deployed after the product has been determined a must-have.

This Must-Have Survey begins with the question: How disappointed would you be if this product no longer existed tomorrow? a)  Very disappointed b)  Somewhat disappointed c)  Not disappointed (it really isn’t that useful) d)  N/A—I no longer use it 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.

If less than 25 percent answer “very disappointed,” it’s likely that either the audience you’ve attracted is the wrong fit for your product, or the product itself needs more substantial development before it’s ready for a growth push. In these cases, a set of additional questions on the Must-Have Survey will help to point you toward your next steps: 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: What is the primary benefit that you have received from [name of product]? Have you recommended [name of product] to anyone? No Yes (Please explain how you described it) What type of person do you think would benefit most from [name of product]? How can we improve [name of product] to better meet your needs? Would it be okay if we followed up by email to request a clarification to one or more of your responses?

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. If you don’t have a large enough base of beta users to get about that number, you should be relying more on customer interviews instead, as having just a handful of survey responses can lead to false signals.

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.

In many cases, improvement comes from what you remove, not what you add on,

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. Additional customer surveying, including interviews and getting out in the marketplace to talk to customers and prospective customers; Efficient experimental testing of product changes and messaging; A deep plunge into analysis of your user data.

These days, the variety of online platforms with which to find the core audience for your product is almost limitless, from the large social networks like Facebook and Instagram, to the Apple and Google app stores, to WordPress and Meetup groups of all shapes and sizes. 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.

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. Nor do you necessarily need to ask an elaborate set of questions. Often just a few basic questions are all you need.

Sometimes what’s holding you back from achieving growth is not a matter of lack of value in the product or service itself, but rather of how you are communicating that value to existing and potential customers.

Once you have discovered a market of avid users and your aha moment—i.e., once product/market fit has been achieved—then you can begin to build systematically on that foundation to create a highpowered, high-tempo growth machine.

Creating an aha moment and driving more people to it is the starting point for hacking growth.

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?

One of Schultz’s favorite quotes when he talks about the growth process is of US World War II commander General George Patton, who said, “A good plan violently executed now is better than a perfect plan tomorrow.”

Even the most sophisticated analysis can really only tell you definitively what users are doing, not why they’re behaving that way.

Learning more by learning faster is also the goal—and the great benefit—of the high-tempo growth hacking process. The 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.

Remember that, generally, big successes in growth hacking come from a series of small wins, compounded over time. Each bit of learning acquired leads to better performance and better ideas to test, which leads to more wins, ultimately turning small improvements into landslide competitive advantages.

“The best way to have a good idea is to have lots of ideas.” This is why unbridled ideation is key to the growth hacking process.

The idea should be submitted in this format:

At GrowthHackers, Sean developed the ICE score system, with ICE standing for Impact, Confidence, and Ease, as a way to organize all the ideas generated in the ideation process of the cycle.

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.

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.

You must craft language that very concisely communicates your product’s core value—conveying the aha moment—and answers the simple question foremost in every consumer’s mind: “How is this thing you’re showing me going to improve my life?”

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.

Retention breaks down into three phases: initial, medium, and long-term.6 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. Think of the initial retention rate as a measure of the immediate stickiness of the product.

There is no fixed definition of the initial retention period; it might be as short as a day for a mobile app, or a week or two for a social network. For a software as a service (SaaS) product, the initial retention period might be more like a month or quarter, whereas for e-commerce companies it is often the first 90 days.7 You should determine this period for your product based on both the data you can get about the standards for products of your type across the sector you’re in and by your own analysis of the behavior of your own customers over time.

The key point is that in crafting your retention metrics, it’s important to benchmark your results against the best information you can get from market research about the typical retention rates for your kind of product or service, and any information you can find about the performance of successful companies you are competing with. These benchmarks are the only way to tell whether what you’re seeing with your customers is typical, better, or worse than expected.

Once you’ve determined the metrics you will use for measuring your retention rate, the next step is to break your retention data down more finely, determining the specific rate for various subgroups of users, through a technique called cohort analysis. This allows you to probe more deeply into your data to make discoveries about why those who are staying are doing so—and why others are not.

Breaking down users by month acquired is only the beginning of cohort analysis, however. You’ll also want to create many other sets of cohorts, such as the specific channel that brought the new customers to your product—for example, by a customer referral program versus a paid ad campaign, and so on. Another distinguishing factor might be the numbers of visits to your website or purchases made. For the video streaming growth team, then, cohorts might include breakdowns by number of shows or series watched in the first month, by subscribers who have watched particular series, or by number of days in a month that someone uses the service.

Recall that the core goal during the medium phase of retention is to solidify users’ commitment to your product by making the use of it habitual for them.

All customers appreciate recognition from companies, whether that recognition is big or small. One great way to show them this recognition is by recognizing some achievement or action or what’s called in marketing circles the behavioral email. One kind is when a customer has passed a milestone,

Teams that want to experiment with personalization can start by doing so with the triggers they’re sending customers. Most email marketing software allows for a variety of personalization options. These can be as simple as inserting the recipients’ names in a message, but can also include delivering different content and offers based on their past behavior.

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.

Too many companies make the mistake of introducing too many new features too rapidly, called feature bloat by product teams. This often results in making products overcomplicated and actually obscuring their core value.

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: by starting with small, simple objectives and then building on your mastery incrementally over time.