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The Ultimate Guide to Growth Hacking Your Startup

In a startup, the focus is narrow, the commitment of time and resources are limited, and the economies risks are modest. To progress, startups must have growth as a central goal.

Essentially, growth hacking is a framework for start-ups and young organizations to define a sustainable growth strategy. One of the most popular growth hacking examples is Dropbox (a cloud-based storage service). Growth hacking methodology helped Dropbox to discover an efficient way to grow the number of users via a referral program. This referral program offered for active users to invite their friends to the service and in return, the program awarded both users with more storage space.


The approach to growing a customer base that does not rely on traditional marketing plans but rather aims to implement marketing into the product itself, is at the core of the growth hacking concept. Most growth hacking approaches are heavily data-driven, which allows even the smallest companies to experiment with new features, branding, or other marketing tactics.


The nature of growth challenges may vary between start-ups and organizations, strategies, and business contexts. Most entrepreneurial companies start from obscurity and must establish a growth strategy as well as prepare themselves for managing user retention as soon as the first customers show interest.

Growth hacking seems like an effective strategy to achieve fast growth. However, to date, there has been limited focus on growth hacking as a methodology for retaining users and driving sustainable growth.


Growth Hacking Framework


Over time, various frameworks have identified the exponential growth in start-ups. Some stated that managerial roles and functions, must be developed gradually at different growth periods; Greiner describes the growth model as a set of different phases: creativity, direction, delegation, coordination, collaboration, and alliances. All these phases are followed by a different crisis, respectively: Crisis of Leadership, Autonomy, Control, and Bureaucracy.


The extent of growth is dependent on the organization’s ability to adapt and evolve. There are four stages in the lifecycle of an entrepreneurial firm: startup, transition, scaling, and exit. Successful growth relies upon accurate business concept definition at the early stage and ‘laying the foundation for a scalable enterprise during the period of transition is equally critical’.


Another lean startup growth framework was created based on continuous innovation and feedback loop. The lean startup model has three parts: build (turn ideas into products or services), measure (examine how customers respond to the product or services, learn (adapt and/or pivot based on the findings).


Both models position experimentation and testing, at the core of the growth strategy.


Different types of growth.

Entrepreneurial companies strive to grow in terms of the number of users. However, for startups that are usually aiming for acquiring new users, they must determine what type of growth is needed. We’ve identified different types of growth in entrepreneurial firms as follows:

  • Top-line growth (new customers who started to use a product).

  • Activated growth (customers who used a product understood the value that was offered).

  • Retained growth (customers who understood the value of a product and used it more than once).

  • Monetized growth (customers who used a product more than once and paid for it).

At the early stages of growth, the entrepreneurs should focus on retained and monetized growth types out of all growth choices, as these types of growth are the most profitable. Also, if approached properly, all of the growth patterns can be replicated.


The Process of Growth Hacking:


Growth hacking process is a set of four continues steps: (1) data analysis and insight gathering; (2) idea generation; (3) prioritizing experiments; and carrying out the experiments. After all four steps are completed, the results are reviewed and the next steps are decided.

The growth hacking process is designed to reduce the complexity of business operations and to focus on one of the key metrics - growth. Ellis called it ‘the North Star metric’ which can be described as a fundamental growth equation, which includes key elements of driving a company’s progress. The North Star metric equation includes all data that is needed to measure the amount of growth that is generated in a specific period of time.

For example, Uber’s (shared transportation service) North Star metric unit is the rides booked, Airbnb’s (shared accommodation service) - the nights booked, Facebook’s (social media platform) - the daily active users because more users and more bookings lead to a higher growth rate.


According to Ellis, the growth hacking process consists of four steps:

  1. Analyze customer’s behaviors, characteristics and the factors that cause customers to churn.

  2. Ideate, brainstorm and collect various ideas that could be implemented to accelerate growth. The ideas should vary from design ideas to business concepts. Collaboration across different teams is the key tactic to achieve a productive and effective ideation process.

  3. Prioritize the ideas by setting ICE (importance, complexity, ease) score. Each of these measures is rated from 1 to 10. Consequently, a higher number of the overall score indicates a higher priority.

  4. Testing ideas that have the highest ICE score and designing an experiment to produce statistically valid results. "A poor test is a one less opportunity to learn, slowing the team down, and bad data can send the team down a very wrong path."

Once the ideas, data, and learnings that were collected are analyzed, they should be well documented. After the first round of the growth hacking process, the growth team starts returns to the first step and starts generating new ideas based on the learnings. By doing this, a continuous growth hacking loop is created.

The growth hacking process requires entrepreneurs to stay agile as it is hard to predict which experiments will be the most efficient. It is important to be data-driven and continuously modify experiments according to new discoveries as well as try new tactics and strategies.

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