Every time I speak with a CEO about the process behind growth hacking, the thing that makes their ears perk up the most is budget validation.

Let's use a practical example of your website's upgrade for a comparison of a traditional method vs a growth hacking approach . 

The traditional way IT'S always BEEN done

In upgrading your website, one common objective may be to enhance the newsletter email collection. Let’s assume the user experience (UX) team or design team have strong objections against pop-ups on your site, so they craft a slide out email collector. The experience is just beautiful: as you approach the end of the page, the email collector jumps out smoothly from the right side of the page. And, since the reader was finished with the article, this isn't seen as intrusive.

In order to achieve this email collector, it would be wireframed, designed, coded, and launched. This traditional process could take a decent chunk of time (weeks, for example), but everyone would say that it was beautiful and a better experience than the previous version.

The way GROWTH HACKING does it

Take this same objective to enhance email collections.Growth hacking derives much of its process from the scientific method, although we accelerate that process a bit.  So we would simply launch a test with the least amount of work possible, as fast as possible, that would prove out the concept - a minimally viable test (MVT). 

The difference between the two approaches is that in the traditional example, without any testing, the design method relies solely on experience and research to guide its actions. Growth hacking appreciates this, but we also know that this is really just an informed guess - a (slightly better) coin toss.

...we'd feed the data back into the design team and decision makers, ensuring safe budget spend... 

So we start with hypotheses and research, but also assume that we don’t know the answers. By assuming that this experiement could be a complete failure or a win, we devalue the extraordinary efforts of the full design and development cycle for a minimally viable test. We ask ourselves, “What is the fastest way to prove out my hypothesis?”

For growth hacking, our slide out email collector wouldn’t be fancy. It wouldn’t have anything that CSS couldn’t do all by itself. Its animation would be done on stock jQuery. But the important thing is that it would launch in one day, in order to be analyzed and tracked vs. the existing email collector. This stands in stark contrast to the weeks or more that the traditional method and design teams would need in order to deliver an elegantly finished project.

Once we validate through data analysis that the MVT we created causes an increase in email collection, we'd feed the data back into the design team and decision makers, ensuring safe budget spend when we cut the entire team loose.

We devalue the extraordinary efforts of the full design and development cycle in favor of a minimally viable test. 

Quick Summary

Traditional teams will spend time and money into an idea that they deem to be the best direction to pursue because either research, experience, or just gut hunches tell them to. These teams will pursue these hunches to launch and, only after the team has spent valuable resources on this experiment and it has run the appropriate course of time, will they then review the data to determine if the test was successful.

Growth hackers simply assume that no one direction is better than the other until they prove it out. We test all of the hypotheses by building them out very rapidly and quickly reporting back the results. Ultimately, you spend less money on mistakes and more time executing winning directions.

Once a design, marketing or advertising team is fed with the knowledge and data surrounding a winning experiment, they can amplify the results by producing even better versions of the test. Which will ultimately lead to better conversions.

For a growth hacker, our measurement is experiment count or throughput - how many experiments did we launch today? This week? This month? We want to launch as many experiments as possible, because the more we launch the more marketing insight we generate, and the more fuel we can pour into the development and design teams so they can create and execute on confirmed winning ideas instead of assumptions.

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