It’s been 7 years since the term ‘Growth Hacking’ was coined and until today, there is a lot of confusion about what it actually means. One of the problems I see is the enormous amount of misleading information you find when researching the concept online.

Content like the below for example has nothing to do with Growth Hacking. However, since it’s a trending term and perfectly suited for click bait headlines, marketers have been using it aggressively to drive traffic to their articles.

WHAT IS GROWTH HACKING?

There are probably hundreds of definitions available online. My 3 favourite ones are:

MAIN TAKEAWAYS:

WHAT IS THIS ARTICLE ABOUT?

At my company Growth Hacking Asia, our goal is to equip as many startups in South East Asia as possible with the mindset, strategies and tools necessary to develop predictable, repeatable and scalable growth processes for their ventures.

So far, we have trained and worked with 4,000+ early stage entrepreneurs across 7 South East Asian countries and observed 2 common problems:

WHICH IS WHY THIS ARTICLE IS BROKEN DOWN INTO:

GETTING STARTED

So where to start? Easy, with data! Without data, you are unable to make decisions so it is absolutely crucial to get your tracking setup right before even thinking about growth.

THERE ARE 2 BASIC THINGS YOU HAVE TO TRACK:

1. HOW TO SET UP GOALS AND FUNNELS IN GOOGLE ANALYTICS

It’s crucial for you to understand where along the conversion path your users drop off. If you haven’t set up your conversion funnels yet, it’s time to do it right now.

I’ll focus on Google Analytics here since it’s the tool most early stage startups use.

GOAL TRACKING SETUP

Goal Types:

a. URL Destination Goals

URL destination goals keep track of specific URLs. Each time someone loads that specific page, they trigger the goal. This Goal Type is ideal for thank you pages, confirmation pages, etc.

For example, each time a customer completes a purchase and lands on the ‘thank you’page, it counts a s goal completion or 1 successful conversion.

Goal URL: This is the URL that will trigger a goal. Don’t enter in the full URL, use only what comes after the domain part. So if the full URL is http://growthhackingasia.com/contact, you only need to enter /contact.

Match Types:

Funnel:

Setting up your conversion funnel is a must if you want users to follow a certain conversion flow and learn at what stage along the path you’re currently losing them.

You’re limited to 10 steps in your funnel. So if you need more, split it between two different goals.

Example of an ecommerce conversion funnel setup:

b. Visit Duration Goal

URL destination goals keep track of specific URLs. Each time someone loads that specific page, they trigger the goal. This Goal Type is ideal for thank you pages, confirmation pages, etc.

For example, each time a customer completes a purchase and lands on the ‘thank you’page, it counts a s goal completion or 1 successful conversion.

Duration: In the below case, Google Analytics will count each website visitor that spends more than 1.5 minutes on the site as a goal completion.

c. Pages/Screens Per Session Goal

Pages/screens per session goals track the number of pages each user visits before they leave. In order to trigger this goal, visitors must view more than the specified number of pages in a single session.

Pages/Screens Per Session: In the below case, Google Analytics will count each website visitor that browses through 3+ pages during their session.

d. Event Goals

Event goals are less straight forward to set up but can provide you with highly valuable insights. Any element that your visitors interact with can be tracked as an event, for example:

Event Category: This is the name assigned to the group of similar events you want to track. For example, YouTube Video, PDF, etc.

Event Action: This is the name assigned to the type of event you want to track for a particular page element. For example, click, download, play.

Event Label: This is the name assigned to the page element, whose users’ interaction you want to track. Your event label can be a title of a video, title tag of a web page, name of the downloadable file, etc.

Event Value: This is the numerical value assigned to the event you want to track. For example, it can be the length of the video played, download time,etc.

In the below example, we’re tracking how often our Growth Hacking 101 guide has been downloaded.

For Google Analytics to be able to measure an event, you always need to tie it to a website element. You can do this by using what we call an ‘event handler’, the most common one being onClick (meaning an event occurs when a visitor clicks on an item on the webpage).

<button onClick=“ga(‘send’, ‘event’, ‘guides’, ‘Download’, ‘Growth Hacking 101’, 10;”>Download Our Growth Hacking 101 Guide</button>

Example:

There’s a lot more to event tracking but I don’t want to go into too much detail here as this is meant to be an introductory article. If you want to learn more about how to set up advanced event tracking for your site, check out this awesome guide >>

Where to find my goals and funnels once I set them up?

1. HOW TO SET UP GOALS AND FUNNELS IN GOOGLE ANALYTICS

The first part of this article focused on setting up tracking for CRO (Conversion Rate Optimisation) purposes. Goal is to track the actions visitors take from the moment they land on your site to the moment they convert. Based on the insights extracted from your conversion data, you’ll then be able to run A/B tests and increase the overall conversion rate from visitor to customer.

However, we’ll also have to make sure to measure the effectiveness of our acquisition channels and tactics to optimise our CPA. This is where UTM Tags come into the picture.

http://growthhackingasia.com/&utm_medium=email&utm_source=Newsletter&utm_campaign=July+Newsletter&utm_content=logo+link

The part starting after ‘&’ is the UTM code and it tracks multiple variables, including traffic source, medium, campaign and content.

Please note that adding the UTM code doesn’t impact the actual page. In the above example, the website http://growthhackingasia.com would load as always but thanks to the UTM code we added, we’ll know exactly which campaign or user acquisition experiment the visitor came from.

Once you have created a UTM code, you can track it in Google Analytics by going to Acquisition -> Campaigns -> All Campaigns.

How to create UTM codes?

There are multiple ways to create UTM codes, my preferred one is using this spreadsheet:

Rather than having everyone in your company create and document their UTM tags in separate sheets, it makes sense for just one person to ‘own’ this document and set the rules to make sure the data collected is complete and naming of the parameters is consistent.

To learn more about how and when to use UTM Parameters, check out this article >>

What’s Next?

Once you have completed your tracking setup and collected some acquisition and user behaviour data (e.g. where in the conversion funnel are users currently dropping off the most), it’s time to focus on experimentation to optimise each stage of the customer journey.

OKR Framework – Set Goals

Based on your data, you’ll be able to identify areas for improvement. Choose the most urgent one first (based on how much it can potentially improve your One Metric That Matters.

The framework we use for goal setting is the so called OKR framework. It sets ONE goal, which is then broken down into a few different measurable results, within a certain time period. Here’s the basic layout:

The best part about the OKR framework is that it keeps you focused on what you should be working on. These OKRs are designed for each division (e.g. content team, product team, etc), as well as individuals within each division.

Here’s a great example of how Swipely applied the OKR framework to their startup >>

Once you’ve created your OKRs, it’s time to get started with the fun part — experimentation 🙂

Make sure to watch this video with Brian Balfour: How to Design & Track Viral Growth Experiments. Until today, it’s one of my favourite videos on Growth Hacking!

The Experimentation Process

Once you know your OKRs, it’s time to become active and run experiments to hit your key results. Below you can see the process you need to apply.

a. Brainstorm

During the first phase, you need to compile a list of all the ideas you and your team have to achieve the key results.

All ideas need to be documented in a backlog. Here’s a Google Spreadsheet template for your Backlog Document (make sure to copy it before you start to edit).

b. Prioritize

Your backlog can easily have 80–100 ideas so the question is — what to start with?

Once you gave each factor a score between 1 and 10, the average of these three scores is the ICE-score. Check which idea scored the highest and get started with it.

Each experiment you kick off from here needs to be added to your Pipeline Document, a list of past, present and future tests, actual results and resource estimations.

You can find a template for the Pipeline Document here >>

c.  Test

Before you can dive headfirst into testing, you need to create a structured Experiment Doc (you can find the template here >>).

After you are done with your experiment you’ll need to come back to this Experiment Doc and add the results as well as the learnings you gained.

d. Implement

This should be pretty straight forward. Go ahead and run the experiment.

e. Analyze

Once you have gathered enough data (i.e. your results are statistically significant), you can move into the analysis phase and make decisions.

f. Systemize

If your experiment was successful (i.e. close enough to the expected results), you have 2 options: Productizing or Creating a Playbook.

Productizing means that the experiment will be directly embedded into the product (e.g. improvements in the onboarding flow).

If you can’t do that, build it into playbooks. A playbook is a set of instructions for repeatable growth tactics (e.g. product distribution best practices).

Example: Hello Bar

FOUNDATIONS

To identify which metric to improve and how to potentially improve it, the Hello Bar team collected both quantitative and qualitative data.

FOUNDATION 1: Analyse the conversion funnel for drop offs

Metric to Focus on: Installation Rate

Potential OKRs (these are not included in the original case study but could look like this):

Objective: Increase the installation rate

Timeframe: 60 days

FOUNDATION 2: Gather Qualitative Data To Understand Why The Installation Rate Is Low

Quantitative data showed the team that there was a problem with the installation process of the tool. Keep in mind that quantitative data can only tell you that there is a problem, it can’t tell you why.

This is why the Hello Bar team started quantitative data collection to better understand WHY their visitors were dropping off.

“Why didn’t you install Hello Bar?”

“What would have made it easier to install Hello Bar?”

The most relevant insight was that more than 40% of survey participants said they wanted to install Hello Bar through a WordPress Plugin. A second finding was that potential users seemed to look for the option to email instructions to their developer.

These and any additional insights gathered from surveys allowed the team to populate their backlog with experiment ideas.

EXPERIMENTATION PROCESS

STEP 1: Brainstorming

STEP 2: Prioritization

Based on the ICE scores of the ideas, we see that Experiment #1 (‘Add multiple installation options’) has the highest score and is therefore the first test to run.

STEP 3: Testing & Implementing

Below is the Experiment Doc breaking down how to test whether the Control Variant (= existing installation options) or Variant B (= multiple installation options) generates a higher installation rate.

STEP 4: Analysis

Data showed a 40.15% increase in the installation rate.

To make sure that the results were statistically significant, they needed to run the numbers through isvalid.org. It showed 100% significance, meaning it was time to move on to the next step – Systemisation.

STEP 5: Systemisation

Hello Bar replaced the old installation screen with the new variation that generated a higher installation rate during the A/B Test.

I hope that after reading this article, you’re able to better understand the term Growth Hacking and the underlying experimentation process. In the coming weeks, I’ll share more actionable content about strategies, tactics, best practices and tools to grow your company. Stay tuned and happy growth hacking 🙂