Five powerful Growth Hacking lessons learned in Silicon Valley

What your business can learn from Silicon Valley’s approach to grow customers

By Nikolas Vogt
Growth Marketing, Google Assistant | Founder, Growth Akademie | Guest speaker, Santa Clara University

Growth Hacking is not just a buzzword in Silicon Valley. It is a core competence that leading tech companies have developed to systematically grow their customer base. I have worked in several global growth roles at Google over the last 7 years. During that time I realized there is a fundamental difference in how successful tech companies in Silicon Valley approach growth challenges compared to the rest of the world. Here are five powerful Growth Hacking lessons that you can learn from Silicon Valley's leading growth experts:

1) Make Growth Hacking part of your culture

Most of Silicon Valley’s marketing and product organizations understand the importance of Growth Hacking or, how they call it, Growth. It  is an essential part of it; basically the DNA of the most successful tech companies. In Europe, most internet companies do not know what Growth Hacking is, nor do many use it. Our recent Growth Akademie research showed that 74% of digital professionals have not heard of the term “Growth Hacking” or have not had experience with it.¹

Many people promote Growth Hacking as a silver bullet or a collection of secret growth hacks or quick fixes. This view is too short-sighted. So what does Growth Hacking actually mean? The most applicable definition is from growth expert Andrew Chen: Growth Hacking is a multi-disciplinary skill set combining elements of marketing, product management, data analytics, and coding to answer the question “How do I get and retain customers?”. It basically enables your product to market itself by optimizing the entire customer lifecycle or by plugging it into big platforms. Additionally, most growth tactics are free or do not require big budgets.²

Here are some examples of typical Growth Hacking approaches:

  • Optimization of customer interactions throughout the funnel, for example, accounting for customer lifetime value and retention. On the contrary, traditional optimization usually focuses on acquisition cost and volume.
  • Alignment of product and marketing channels to create powerful and innovative acquisition and retention opportunities like Growth Loops (see section 4 for more).
  • Product integration into big platforms like Facebook or Youtube that allow your product to grow on the back of these platforms.
  • Constant optimization of the customer experience through experimentation and application of behavioral economics principles.

To uplevel your career with Growth Hacking, join the waitlist for our intensive 6-week online course. Growth leaders from Silicon Valley and the European Tech Scene teach how Google, Project A, EyeEm, ImmoScout24, and other tech giants acquire and retain customers.

2) Always be experimenting

The most successful businesses in Silicon Valley learned that relentless experimentation is key for growth. A fellow Google growth expert summed it up as follows:

"Traffic that does not contribute to experiments is a lost learning opportunity. Always be experimenting."

This illustrates how Growth Hacking is all about learning and how experimentation is intertwined with that. Nevertheless, how do solid growth experiments look like? A crucial part of growth experimentation is data-driven hypotheses. Based on data points you basically think about product or marketing changes that could improve performance. You try to formulate this in a concise statement: “If ___, then ___, because of ___.”. Then 'translate' this change into an adjusted variant of your current experience, for example, different landing pages or app flow variants.³ Finally, you have to 'A/B test' these variants against your control group - usually a holdback or your current experience - by randomly assigning real users to different test arms. The goal is to find significant differences that allow you to reject or confirm a hypothesis.

Hypothesis-based Growth Experiments Process

Hypothesis are at the core of the "Growth Experimentation Process"⁴

This "Growth Experimentation Process" can be learned and common pitfalls avoided if you know about them. Here are two experiment pitfalls you should know about:

  • Hypotheses should be formulated before the test and should be based on data.

    You might ask yourself: “Why do I need experiments if I have data from market research or customer analysis?” It is tempting to misuse these sources for causal implications, and either fish for data points that support what you suspect, or if you cannot find corroborating data simply modify your suspicion. Be more systematic about it and build a foundation in the form of a hypothesis before looking for evidence. That being said, these sources are crucial for experimentation, but more so for generating speculations than drawing causal conclusions. Another good idea is to use them for pre-validation of your hypotheses which will increase your success rate tremendously.
  • Do not change many variables at once.

    Probably, the most common pitfall during Growth Hacking experiments is changing too many variables at once. Ideally you alter only one variable per test, for example only pricing, and keep everything else the same. This way the disparity in performance can be explained by different prices. If you change, for example, the value proposition and price at the same time you most likely have a problem of determining what caused the performance change. Testing too many variants in one experiment needs more traffic and usually also more time to get significant results. To avoid both issues most companies with less traffic apply phased testing plans that systematically test and optimize one variable after the other.

Experiments and data analytics are also a key module taught at the Growth Akademie. Join the waitlist and discover how well-known growth experts implement experimentation in their Growth Hacking processes.

3) Build Behavioral Economics capabilities

Another nascent trend in Silicon Valley is the infusion of Behavioral Economics insights into Growth to create products that are valuable to customers and their needs. This seems like a logical extension once you learn how Growth Hacking is rooted in experimentation and data analytics. Made popular by influential researchers like Nobel Prize winner Daniel Kahneman⁵ or Wall Street Journal columnist Dan Ariely, Behavioral Economics is at the intersection of psychology and economics. Compared to standard economics, this school of thought explains how choices like buying decisions are actually made without assuming that people are rational.⁶

Insights from Behavioral Science allow you to improve the user experience and tackle Growth Hacking challenges from a completely different angle. This is especially useful for creative parts of Growth like hypothesis generation or landing page optimization. Taking into account powerful concepts such as “Social Proof”⁷ or the “Endowment Progress Effect”⁸ have accelerated the growth of numerous tech companies while providing additional value to their customers.

One good example of “Social Proof” as a growth tactic is LinkedIn’s user experience: Their sign-up page for new users features pictures of people similar to them and allows them to “find your colleague”. Seeing that other like-minded professionals have already joined helps new customers decide whether to join or not because people are heavily influenced by their peers. The skills section of their profile page is a feature built on the premise of a user’s social proof. It leverages the idea that your credibility as an expert is enhanced through endorsements by your peers.

LinkedIn also utilizes the “Endowment Progress” to motivate individuals to complete their LinkedIn profile. Users are more likely to follow through the closer they are to a goal or the closer they perceive it. So showing them their progress increases profile completion versus just reminding them.

Navigating these Behavioral Economics nuances requires a specific skill set that involves not only subject matter expertise but also strong ethical judgment. To amplify business growth in the long run, Behavioral Economics has to be considered in a systematic and ethical way. Consequently, startups and innovative established players have started to form specialized Behavioral Economics teams or they tap into expert services like Behavioral Consultancies such as BEWorks co-founded by Dan Ariely.

The Growth Akademie features industry experts from the fields of Psychology and Behavioral Economics and will give a solid understanding how leading tech companies apply Psychology and Behavioral Economics.

4) Think Growth Loops not dead ends

Tech businesses in Silicon Valley learned that thinking big goes hand in hand with an aggressive target setting. Product and marketing teams have to drastically rethink their approaches to growth in order to achieve these targets. That is why growth experts started to engineer predictable growth models based on growth loops rather than traditional linear activities that evaporate shortly after implementation.⁹ Let’s look closer to why Growth Loops are such an essential part of Growth Hacking:

  • Growth Loops are usually baked into a product and designed to leverage product interactions of new customers to generate even more new customers (see Acquisition Loop example: Instagram’s new user sign-up aims at inviting your friends to join as well).
  • Additionally, Growth Loops for existing customers add notification triggers to useful and repetitive product interactions. They ultimately help to keep your product top of mind by bringing back customers and reinforcing the value of the product (see Retention Loop example: Hubspot sends notifications via Chrome extension once status of contacted prospect changes). Such Growth Loop approaches generate robust and predictable compound effects that apply to all new users.
Growth Loops vs. Linear Channels⁹

Most European tech companies have not tapped into such innovative approaches and tend to focus on linear upper funnel activities. Contrary to Growth Loops, Linear Channels can be defined as activities that imply a ‘dead end’ without a multiplying the loop effect (for example, display ads usually bring only a single visit per click and do not generate additional visits).⁸ This isn’t necessarily wrong since you need strong linear channels to feed and kickstart your loops. But focussing most of your efforts on Linear Channels rather than thinking about implementing Growth Loops leaves a huge growth potential untapped.

Join the Growth Akademie waitlist if you want to become an expert in Growth Modeling and Growth Loops. The industry’s leading growth experts show you how they do it in companies like Google, Project A, EyeEm, ImmoScout24, and other tech giants.

5) Speed over perfection

It struck me how quickly Silicon Valley businesses ship their products. Several times, I have personally witnessed that things have been launched although they were not 100% there. At first, this seems counterintuitive and it confused a European like me who culturally seems to care a bit more about quality and excellence. It makes more sense once you have learned about the three dominant characteristics of most technology and internet products:

  • One big advantage of technology products is that you can easily collect real customer data, which allows you to rapidly optimize the product experience and even product-market-fit right after launch. This also means you cannot optimize your product if you have not shipped it yet. You can do crazy market research and refine all product details as much as you want prior to a launch, but nothing beats real market response in form of customer data.¹⁰
  • Compared to traditional products, digital products usually have inherent network effects, i.e. the individual value of a product increases the more customers are using it. One example could be payment solutions or digital wallets because you need to send your money to others. Once these network effects kick in, they exponentially attract customers and therefore often create monopoly-like situations, which also means high barriers to entry once a player reaches a greater size. This does not mean you cannot enter this market anymore, but you should focus on a slightly different segment than the dominant player. For example, Snapchat successfully focussed on self-destroying messages and stories compared to Facebook’s feed and status updates combined with regular messages.¹¹
Growth Hacking as a systematic solution for the distribution problem¹²

  • This gives you an idea why the best products do not inexorably win in today’s competitive tech world. This does not mean Silicon Valley's leaders neglect technical solutions or product design. Quite the contrary; solving real customer problems and a great product design turned into standard requirements whereas the real differentiator for success lies more in clever distribution and marketing. To quote Peter Thiel, co-founder of PayPal and early Facebook investor: “Superior sales and distribution by itself can create a monopoly, even with no product differentiation. The converse is not true. No matter how strong your product; even if it easily fits into already established habits and anybody who tries it immediately likes it, you must still support it with a strong distribution plan.”¹²

You might wonder how to solve this distribution challenge in a systematic way. The answer is Growth Hacking. And if you want to learn it, sign-up for the Growth Akademie. We teach the growth frameworks of leading experts and provide step-by-step guidance on how to amplify the growth of your product and business model.

  1. Growth Akademie, Digital Industry Survey, 2019, N=200
  2. Andrew Chen, 2013, https://andrewchen.co/how-to-be-a-growth-hacker-an-airbnbcraigslist-case-study
  3. Shana Rusonis for Optimizely, 2015, https://blog.optimizely.com/2015/01/29/why-an-experiment-without-a-hypothesis-is-dead-on-arrival
  4. Margaret Rouse for TechTarget, 2017, https://whatis.techtarget.com/definition/hypothesis
  5. Julia Kagan for Investopedia, 2018, https://www.investopedia.com/terms/d/daniel-kahneman.asp
  6. Dan Ariely, 2010, https://danariely.com/2010/07/10/three-questions-on-behavioral-economics
  7. Aileen Lee for TechCrunch, 2011, https://techcrunch.com/2011/11/27/social-proof-why-people-like-to-follow-the-crowd
  8. Joseph C. Nunes and Xavier Dreze, 2006, "The Endowed Progress Effect: How Artificial Advancement Increases Effort"
  9. Brian Balfour, 2019, https://brianbalfour.com/essays/how-to-launch-a-product-or-feature-to-maximize-growth
  10. Kathy Chin Leong for Fast Company, 2013, https://www.fastcompany.com/3021956/googles-nine-principles-of-innovation
  11. Tejvan Pettinger for Economics Help, 2013, https://www.economicshelp.org/blog/glossary/network-effects/
  12. Peter Thiel, 2014, "Zero to One: Notes on Startups, or How to Build the Future"