This month marks my one year at Oberlo / Shopify. It is also one year since transitioning from doing more growth hacking in my previous company where I was co-founder to joining Oberlo as a growth engineer. The discipline of growth has a negative reputation sometimes, mostly because "growth" to many people is very mysterious, and their only exposure to growth may be through growth hacks that are shared in articles (such as Dropbox's famous referral program), only to fully replicate their tactics and see terrible results. I speak from experience!
This is a term that has probably been too overused but it generally refers to unconventional and creative tactics used by resource-starved startups to achieve outstanding business growth. While this term is relatively new, the principles behind are certainly not. At the time where I started my first company, this term did not exist yet. Being a small and resourceless company, we experimented with different guerrilla marketing techniques which have the same basic principles as growth hacking.
One thing about growth hacking I've learned is that each successful growth hack is unique to the originating business. As a young entrepreneur and technical co-founder, I've certainly attempted Dropbox's referral program to really disappointing results. The mechanics and techniques of a growth hack may be simple to reverse engineer and duplicate, but it will with high probability fail because the environment in which the growth hack succeeded is different from your own business - customer profile, market culture, industry and execution.
The Best Growth Hacks Come From Within
The most successful growth hacks are always those born from within the business, with large doses of creativity as a result of being starved for resources. Growth hacks are mostly written from the perspective of SAAS business but that need not not always be the case. We were a physical goods brand, and one of our more successful growth hacks came from joining a design exhibition where we were trying to enter a new geographical market.
We only had a small booth to showcase and sell our products, but the problem was that the real value of our solution came from our vast catalogue of designs and the ability to customize our products to what you want. This was not possible in such a small booth. To allow people to really experience the true value of our products, we created a copy of our online shop and modified it to be suitable for a physical retail experience. A visitor to our booth would be able to interact physically with our products, and place a customized order via our modified online shop. They could even pay by cash!
Hacking a copy of our online shop for the physical retail experience was required only a fraction of the time it took to build our actual online shop. It was a scrappy solution, did not have proper code tests and in fact even a little buggy in certain edge cases. It was a huge success business wise as it enabled us to let our audience experience our value on the spot. Had they just left with a name card or a flyer, they would have forgotten about us when they reached home. The scrappy retail version of our online shop also opened our eyes to more opportunities of experimenting our online experience in physical retail spaces. Not too bad for something put together in a week.
Growth engineering is growth hacking grown up. Another way of looking at growth hacking is the intersection of software engineering and marketing. In a startup environment, growth hacking is more throwing different things at the wall and seeing what sticks. Often it is due to either the startup not having a proper data infrastructure setup yet or simply it still being at an early stage and not having enough data. Hence in growth engineering, there is a third pillar - data. One large aspect of growth engineering is collecting and looking at data to identify areas and trends where can be acted upon to bring the most business value.
Growth engineering unlike growth hacking is a very methodical and scientific process which as a software developer is something I find really comforting. At the very core of growth engineering is experimentation. You analyze your data to identify certain patterns and trends. You see a co-relation that 60% of your new newsletter subscribers purchase on the same day. From here, you form a hypothesis. Encouraging new visitors to subscribe to your newsletter would result in a higher conversion rate of new visitors to customers. An experiment is then crafted around this hypothesis. Perhaps if the newsletter signup form was more obvious, above-the-fold or immediately visible on the landing page, it will increase conversion rate. Usually the experiment takes place in the form of an A/B test to see how your hypothesis performs against your control, the original version.
Of course, not all experiments will succeed but each experiment gives you more learnings about your business and brings you one step closer. Each successful experiment will help improve a business lever, most of the time by a little bit, but over time will work like compound interest in growing your business.
Do You Need a Growth Hacker or Engineer?
Growth works like a magnifier and when used right is a very powerful tool in your business arsenal. However, as a magnifier, the base being magnified is very important. 10 to the power of 2 is 100, but 1000 to the power of 2 is 1,000,000. As an early stage startup, it is usually best to first focus on the product. A piece of crap magnified is an even bigger piece of crap. When you have product-market fit and have users that absolutely love your product, growth hacks can help to connect more of these users to your product.
Doing growth properly usually requires large enough datasets for more accurate analyses. As such, startups should not dabble too early on into or rely too much on growth hacking and especially growth engineering. Without large enough volumes of users, A/B tests would also take a far longer time before the results are statistically significant. At the same time, you don't want to cut short the experiment time and make assumptions based on inaccurate experiment results. However even if product-market fit has not been found yet, it is never too early to start collecting data. The earlier data is collected, the more is available later on to analyze and make meaningful assumptions.
Want to Chat Growth?
What about you? How do you apply growth in your company? Are you a growth hacker or growth engineer? Feel free to reach out to me if you would like to talk more about growth.
I first wrote and posted this article on HackerNoon. You can read the original article or check out others that I've written there.