3 Growth Hacking Techniques That Work Like Magic

What are the primary methods growth teams deploy when they set up an experiment? Below, I will describe the advantages of minimum viable products (MVPs), A/B testing and multi-armed bandit tests.

In recent articles, I described my definition of growth hacking and the characteristics of brilliant growth hackers. I also supplied you with a list of top-of-the-line growth hacking tools. Today, I want to describe the main methods that growth teams deploy when they set up an experiment.

A minimum viable product (MVP) is a product with just enough features to satisfy early customers, while also providing feedback for future product development. Building an MVP is a great way to test your product in the market. Gathering insights from an MVP is often less expensive than developing a product with more features.

Zappos is proof that “MVPing” works. In 1999, founder Nick Swinmurn started with just an online storefront consisting of pictures of shoes from shoe stores. When a pair was sold, he ran to the shoe store to get the shoes, put them in a box, and shipped them. There was no e-commerce or warehousing at all.

The one-man operation experienced tremendous growth. In 2009, Amazon acquired Zappos for $850 million.

While introducing a new proposition in your organization, you don’t have to perfect it. Just ask your growth team to make an MVP and collect market feedback.

Also known as a “split-run test,” an A/B test is a controlled experiment in which two versions of a single variable are compared by testing a subject’s response to variable A against variable B. This will determine which of the two variables is more effective.

This method is one of the keys to the success story of Netflix. Almost all their decisions are based on data analytics and A/B testing. Through split-run testing, Netflix selects the best artwork for its content, sometimes resulting in 20% to 30% more viewing for that title.

Your growth hackers can do the same. A simple example: through split-runs, they test the effectiveness of your price by showing different rates to different groups of website visitors (segmented in customer type). For each group, a rate is calculated which ensures the highest profit. Each group will now see the price that is calculated for them. Variations in prices based on time of day are also possible.

Multi-armed bandit tests are “smarter,” more complex versions of A/B tests. How does it work? Machine algorithms are used to dynamically allocate traffic to variations of a website that perform well, while assigning less traffic to variants that perform worse.

These tests work faster than A/B tests because they send traffic to “winning” alternatives to a greater extent within a specified period. In this way, less time is wasted on testing a poorly performing option (as happens with A/B tests).

Because of their speed, multi-armed bandit tests are particularly suitable for situations where rapid results are required. Variations on news headlines, for example. Your growth team will possibly deploy this method to test short-time campaigns.

Growth hacking can mean the difference between the businesses that fail, survive or thrive. Through our experienced partners and staff, RevelX combines the wisdom of more than 100 years of growth hacking. If you want to know more about this inspiring subject, don’t hesitate to reach out to me. You are always welcome for a cup of coffee at our office.