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In Defence of Growth Hacking


How did we get here? CEO Matt Warren recently revealed why he started Veeqo In the first of a series of posts from the people that make sellers lives easier. Now it’s the turn of Marketing Manager Prince Appah, who dispels the myths around ‘Growth Hacks’ and how Veeqo’s Marketing lends a hand from Science.

During my last startup as a founder, my primary obsession was how do i grow the business, one of my favourite blogs for learning about startup growth was Startup Marketing by Sean Ellis – the Godfather of Growth hacking.

Growth hacking has become the cool thing of the day, but there has been confusion about the difference between growth hacking and traditional marketing.

The confusion has risen because of two reasons:

1) A lack of a better term other than Growth hacking

2) The notion that growth hacking is about “hacks”

To address the lack of a better term for Growth hacking, I propose replacing “Growth Hacking” with “Growth Marketing”.

Growth marketing focuses on the process to find facts about the complete funnel to drive growth.

When Sean Ellis used the term Growth Hacking, he was using the term to describe the process of finding growth as opposed to hacking together a list of random tactics in the hope of getting something to work.

As Sean Ellis puts it, startups that pursue growth “have to dig deep creatively, and relentlessly test new ideas”.

The Misguided View of Growth Hacking:

When people search for the term Growth Hacking, they normally see lists and more lists of “hacks” which leads to a situation where people want to simply copy the “hacks” without really understanding the process behind the “hacks”.

Most growth hacking lists fail to expose the steps before the “hacks” and the process behind these successful “hacks”.

What is useful is finding the process behind growth hacking and lists of experiments or “hacks” per customer stage and per vertical (eg distribution, activation, retention experiments) not for you to copy blindly, but to give you an idea of what you might want to do when applying the prior learning to your company.

What most people forget is that behind every successful growth hack there is a process to uncover the hacks.

Josh Elman – VC at Greylock Partners

“Growth Hacking: It’s about figuring our step by step how to get people to use your products.”

Lessons From Science

The goal of scientists is to find facts and understand the natural world.

As Richard Bragg puts it “The important thing in science is not to obtain new facts, but to discover new ways of thinking about them.”

Scientists find facts by following an iterative scientific process which looks like this.

By taking a cue from science, as marketers our goal then is to find facts and understand our product, customers, and how to reach them.

What Fast Growth Companies Do: The Process

Most high growth companies have a growth model which is based loosely on the scientific process and other fields, such as lean.

The process behind growth marketing in most growth companies is an iterative model that falls under these categories:

  • Exploration & Discovery
  • Testing & experimentation
  • Playbooks & Systems

Brian Balfour VP of Growth at Hubspot, puts it: “There is no one right or perfect growth process. The important part is just to have one, stick to it, and improve it over time”.

Growth Marketing at Veeqo

At Veeqo, the marketing team has implemented this growth process based on the scientific model of

  1. Exploration and Discovery
  2. Testing and Experimentation
  3. Playbooks and Systems

Our process is not set in stone, it is constantly evolving but the fundamentals will remain the same.

At this point it is worth pointing out that using this process presents no silver bullets.

There will be many failed experiments along the way to finding facts and understanding our product, our customers and how to reach them, what is important is to stick to it until we find and understand these facts.

Before we start with the Growth Marketing process, we ask ourselves why we are doing this. We then come up with a reason which becomes our goal. The goal is then broken into sub goals per customer stage.

The Veeqo marketing team has a goal which is derived from the wider company goal agreed with the CEO.

To further elaborate, our goal is to grow the number of paying customers by a specific number, this goal is broken down into various subgoals along acquisition, activation and retention.

The Exploration and Discovery Phase:

This phase can be conducted in any number of ways. It can be done via customer interviews, brainstorming sessions, customer observation, researching competitors or industry best practise, reading etc.

For Veeqo’s marketing team this stage normally starts with a brainstorming session, looking at customer data or performing market research.

Once we have completed the exploration and discovery phase we create a backlog of the ideas we have, the ideas go into a sheet that looks like this:

Example of Brainstorm Sheet:

Funnel Stage Acquisition Activation
Name PPC Trial to lead conversion
Ideas Increase paid customers through ppc Block specific features to increase conversion
Steps to complete idea 1. Perform keyword research

2. Select target keywords

3. Calculate target cpc

4. Start Adverts

5. Monitor & optimize adverts

1.Go through customer signup flow

2.Map out baseline features

3.Decide on features to block

4.Block features

Resource Marketing: Jamie Marketing:Jamie

backend developer: Sam

Time frame:

Input & Output time.

2hrs Marketing 1 day

Backend developer 2 weeks

Impact Medium(5) Big(10)
Expected outcome Increase number of paid customers by 3. Increase trial to paid conversion by


Probability it will work High (1) High (1)
Priority Priority 1 Priority 1

Terms used in the table.


Description of idea

Steps to complete an Idea:

List of steps to complete a task or execute on an idea


Which team members will perform a task.


Input time refers to how long to complete a task.

Output time refers to how long before we see results.


Based on how big an impact an experiment will make.

Big assigned value of 10

Medium assigned a value of 5

Small assigned a value of 1

Unknown assigned no value

Expected outcome:

What we expect from a test.


Likelihood an idea will work.

1 assigned to high probability idea.

0.5 assigned to medium probability idea.

0 assigned to low probability idea.


Priority assigned after weighing up Impact, Timeframe, probability and expected outcome.

Testing and Experimentation:

Once we have a number of ideas on how achieve a goal.

We map out the steps needed to complete the idea or task.

After mapping the steps, we prioritize and rank those ideas based on timeframe to complete a task, impact the idea or task will have, the resources needed, expected outcome and probability the idea will work.

As an example we may choose an SEO idea because it has a short input and output time, potentially has a huge impact and a high probability it will work.

The SEO idea is given a priority of say 1.

If an idea has a low impact but has a short input and output time, we may decide to leave the idea.

There is a caveat to this approach in that there are times when we may not know the potential impact of an idea, when we have such situations we implement the idea as quickly as we can to ensure we get some results to inform our decisions going forward.

Once we have ranked ideas and prioritized, the next phase is the experimenting phase.

Experiments per stage appear in an experiments document that looks like this:

Test Name & date Expected Outcome Actual outcome Test variables End date Results Conclusion

Test variables depend on what is been tested, in the experiment below we tested for target cpc and number of paid users.

Our hypothesis was:

Increase traffic to 280 visits per week at target cpc of £1.50.

Expected Outcome:

1 paid customer per week.

280 visits per week at £1.50 cpc.

CPC Visits # Conv CAC £ CPL Lead to paid Paid users Net Value LTV End date Results Conclusion
1.31 276 8 2.90% £45 38% 3 £3,329 £3,600 03/08/2015 Pass Keep Running

Experiment results are analysed daily for new experiments and weekly for ongoing experiments we already have initial data for.

If an experiment does not work, we mark the experiment as failed and write down the reasons why the experiment failed, writing down the reasons why an experiment failed helps us go back to the experiment in the future and change a control element in that experiment for a new experiment to begin.

Playbooks and Systems

When an experiment is successful, the experiment goes into a playbook document. The experiment can then be repeated several times over.

I hope you have found this useful, good luck in your pursuit of finding facts about your product, customers and how to reach them.

I focused on a specific element (acquisition) of growth marketing in this article, feel free to add any other elements within the funnel below.

Make Life Easier. Keep your inventory right and your shipping on time.


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Written by Matt Warren

CEO & Founder at Veeqo
CEO and Founder of Veeqo - the inventory and shipping platform for ecommerce, helping online retailers deliver the experience their customers deserve.

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