Hacking Growth: How Today's Fastest-Growing Companies Drive Breakout Success

by Sean Ellis

But with their goal to generate more income, increasing daily active use wasn’t the metric they needed to be focusing on.

increase the number of subscribing users, not to make the users they al...

they hired a traditional marketing specialist who crafted a new tagline, “Solving the Photo Mess,” hoping that would ignite growth, but it didn’t do the trick.

right levers of growth at the right time.

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

Doing so will make the difference between strong sustained growth that is of real, revenue-generating value and illusory growth that sputters out.

Especially in the early phase of growth, you must set a highly disciplined course for experimentation that focuses intensely on the most important levers to achieve your goals. Speed of testing alone isn’t the goal; scattershot experimentation is a sure way to waste time and effort, and that’s true even if you’re testing at high tempo.

Of course you can’t know ahead of time whether you’ll achieve that impact, but you should have a strong rationale for why a proposed experiment is the best one to run next.

Let’s say experiment A is testing a small change, such as the color of the sign-up button. As results start coming in, it becomes clear that the increase in the number of new visitors signing up is very small—garnering just 5 percent more sign-ups than the original button color.

This proved that at a small scale, small experiments will not help the growth fast enough

In a case like this what a start-up really ought to do is abandon the experiment quickly and move on to a next, potentially higher-impact, one.

“Seriously. Be dramatic. Don’t just move a button on a page. You may run that experiment, given that you have small traffic sizes, and because of the small lift, you may run that test for months or years. Produce dramatic lifts if you’re a young start-up.”

fundamental growth equation.

Take Uber, whose essential metric for riders is rides completed.

Reducing the complexity of your business operations down to a basic formula is immensely helpful in allowing the growth team to focus on the right signals in this vast sea of data noise.

No matter how much they love the service, no one is going to search and make vacation bookings every day.

A metric that means nothing for one company, in other words, may be another’s core growth lever.

the more potential buyers will experience the aha moment of seeing exactly what they want to bid for;

bellwether

领头羊

yardstick.

veer

hilarity

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.

“If you can’t be extremely clinical and extremely unemotionally detached from the thing that you’re building, you will make these massive mistakes and things won’t grow because you don’t understand what’s happened.”9

it’s equally easy to get lost in the weeds of data analysis and lose the sense of urgency to start experimenting with ways to actually drive growth.

Doing more and more data analysis can be an especially alluring trap; because delving into data is scientific, we can convince ourselves that we’re just being rigorous and don’t want to experiment without sufficient evidence of likely success.

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.

Much as an airplane can’t fly without instruments providing information about altitude, air pressure, and wind speed constantly being monitored, without the right data at your fingertips, your growth team will be flying blind.13

As discussed in Chapter Two, combining all of your data so that you can do detailed tracking of customers throughout the experience funnel is essential to learning how to make your product must-have. If you haven’t pooled all your data at that stage, then it’s imperative to take the time to do it now.

in January of 2009, they took the dramatic step of stopping all growth experiments and spending one full month on just the job of improving their data tracking, collection, and pooling.

they could see what each and every user on the site was doing;

Hahahaha is that good or bad.

meaningful action.

trove

John Egan in a post on his eponymous blog about the 27 key metrics that Pinterest tracks.

collecting insights by interviewing Twitter users came in.

If less than a third of the people you were following were following you back then Twitter seemed more like a news site, of which there were already a plethora of other options. The unique product value of Twitter as a place for people to find out what’s happening in their world became clear to people when they had the one-third to two-thirds ratio.

how odd but ok

By actually picking up the phone and calling these people, the team learned exactly what was going on: when these people had first started using Twitter, they had thought of it as mainly about sending tweets, as a form of broadcasting, especially for promotional purposes.

identifying your growth equation and the key metrics to improve, along with establishing the proper instrumentation, data collection, and reporting that includes customer feedback, to discover and monitor your core growth levers, is an essential and powerful first step for successful growth hacking.

disciplined growth meeting;

outhustle

Learning more by learning faster is also the goal—

The companies that grow the fastest are the ones that learn the fastest.

most experiments fail to produce the results you’re hoping for. Others produce some indication of success but are inconclusive, not producing results significant enough to support making the change tested. Some produce small but not earth-shattering wins. Only very few tests produce dramatic gains.

5 percent increase in retention leads to an increase in profits of between 25 and 95 percent,

highly disciplined process

We advise that teams start slow and build to a faster tempo after the team gets its footing with the new process; trying to launch too many experiments right off the bat can lead to poor test implementation, team confusion, and discouragement as targets are missed.

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.

The product team did a good job of building the app. They set it up with the proper analytics instrumentation to provide the most useful feedback on users’ behavior as they move through the app. They also tested the app with likely users during the development phase, and the feedback indicated that it is well designed. It offers lots of appealing features,

Her first step is to pull staff from the marketing, engineering, product, and data science groups to create a team. Next, the team will need to uncover what the aha moment is for people who are using the app, and what it is about them and their usage that differs from those who don’t.

unbridled

Self-censorship is discouraged, and nothing should be considered too crazy to put out there.