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A beginner's guide to growth hacking by Mind Map: A beginner's guide to growth
hacking
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A beginner's guide to growth hacking

What is it?

It describes tactics and processes to help you increase your numbers.

The phrase "growth hacker" was coined by Sean Ellis in 2010. "A growth hacker is a person whose true north is growth"

clever, original, or inventive

will use software, databases, API’s, and related tools to grow a startup

must understand technology very deeply to be successful

is on the lookout for system weaknesses which will allow growth

growth should be on the mind of every person working in the company that wants to grow

The process

You can't growth hack a product that people don’t love.

Product-market fit

If at least 40% of your existing users wouldn’t be “very disappointed” if your product disappeared then you don't have enough product-market fit. This basically means that your product doesn’t solve enough of a pain. It isn’t adequately loved by the users, and the team needs to focus on product more than growth.

The experiment

Define actionable goals

Implement analytics to track your goal

Leverage your existing strengths

Execute the experiment, Write down your hypotheses before you execute an experiment, Do not be naive about the resources needed to run the experiment, Do not get discouraged by the initial results, Learn from success and failure

Optimise the experiment

Repeat

The funnel

Get visitors, The 3 P's of getting visitors, Pull them in, Push them in, Product

Activate members

Retain users, 1. Identify trial users most likely to buy, 2. More rapidly onboard new users, 3. Identify and engage users at risk

The tools

Key Performance Indicator (KPI)

eg. how many new subscriptions you sell per day, how many people cancelled their subscription per day

have a quick way of seeing it, share it within the c ompany

Viral coefficient (K)

how many people are brought to your product because of the existing users

Cohorts

Is a portion of your users based on when they signed up.

Segments

Like cohorts, but instead of segmenting the users based on their signup date, you base the group on other segmenting factors.

Multi-variate testing (A/B testing)

Is multi-armed bandit testing is the best kind of A/B test? Bandit testing is a continuous form of A/B testing that always send people towardthe best performing options. In essence, the experiment never ends.

Customer acquisition cost (CAC)

It’s important that you know the CAC for each channel because it can very greatly. Also, once you know the CAC per channel then you know how much you can spend on that channel, or if you should spend anything on that channel.

Lifetime value of a customer (LTV)

Segments come in handy when calculating LTV because you might discover that certain segments of your users have a much higher LTV than other users. This will also affect the CAC that you are willing to pay for those specific segments.

General Analytics

eg. Google Analytics

Event / People based analytics

Can provide answers to: - Do people who use feature X have a higher LTV? - Do users in segment Y have higher engagement with feature Z? - And almost anything else you can dream of.

eg. KISSmetrics, Mixpanel

Niche analytics

eg. for mobile apps

Custom analytics

Based on the book "The Definitive Guide to Growh Hacking" by Neil Patel & Bronson Taylor