[Free Guide] How to craft Growth Ideas the right way
We all have great ideas to grow our side-projects, startups, and companies.
But what happens when you are overwhelmed with your day-to-day tasks?
Your team and you brainstorm hundreds of growth ideas per year (or even worst, per month), though only a few of them end up being well-executed.
And what happens when you finish testing something? Do you keep a track record of your learnings, whether it was a big success or a complete failure?
...
Yep, I got you!
You lack a methodology that you can repeat every time you get involved in a growth project.
It doesn't matter if you're a marketer, product manager, founder, or a growth hacker.
We all have the same goal: Grow more and grow better.
I'll try to outline the process that we follow at FROGED to ideate, plan, execute and document all our growth experiments.
Please note that this guide is for Startups and SaaS. Other kinds of businesses may use it with some tweaks. Let me know on Twitter if you need help with this!
If you find it useful, please post a comment. Any feedback is welcome to make this post even better and provide more value.
TL;DR: You need a process, a framework to scale up your growth. To make it easier for you, we just launched a free template to organize and document all your growth initiatives right within Notion. Check it out here.
If you're still with me, let's go ahead!
The Whole Process
Like all processes, there are a few steps we must follow in a specific order.
Those are:
- Choosing your North Star Metric
- Setting Goals
- Craft the hypothesis
- Prioritize your ideas using the PIE Framework
- Planning your experiments
- Document what you've learned
1.- North Star Metric
North Star Metric is your meta KPI, basically where you want to arrive with all your growth initiatives.
For SaaS/Startups, we usually use MRR (Monthly Recurring Revenue), ARR (Annual Recurring Revenue), or MAU (Monthly Active Users), especially when we are at an early stage.
But that's wrong!
You must find the key metric for YOUR product.
In the case of FROGED, we use "Trial Accounts with >2 users and >10 conversations in week 1."
Choosing what metric you'll be after it's essential.
It entirely depends on business objectives, product/company vision/values, and many more variables. Usually set by the C-Suite/company's founders.
But to make it short:
A North Star Metric should be "non-revenue" and indicate if the company is growing, generally speaking.
You can read more on how to choose your North Star Metric in this article from Amplitude.
2.- Setting your Goals
This is where the process of starting to craft a hypothesis begins.
You can't brainstorm or ideate anything that worth pursuing without goals. And you need data to set goals.
This is the process I follow to set goals:
First, I start from the North Star Metric.
Then I ask myself: What I need to improve to be closer to my North Star?
Be careful with the answer; you don't want to start brainstorming actual actions but define what you need to accomplish (goals) to improve your bottom-line.
You can do this by seeing your current data, visualizing your AARRR funnel, and think about what you can improve to help the company achieve its North Star.
For example:
- Only 1% of your free users upgrade to a paid plan. You may want to improve this, which will directly affect your NSM. <- Revenue
- Or maybe your conversion rate is good, but your traffic is horrible: then you'll need to focus on bringing more traffic to your website. <- Acquisition
Only 10% of your users get activated and use your product, so you'll want to pay attention to this and increase the total number of activated users. <- Activation
It's OK if you end up with 5, 10, or 15 different goals.
I recommend pursuing the goal which is closer to your North Star Metric.
Here's an example of 3 of my goals:
In my case, the goal closer to the North Star Metric is:
Increase Conversion Rate ratio from Free Users to Paid Plans from 3% to 5%
3.- Craft the hypothesis
To craft your hypothesis, you'll want to check both quantitative and qualitative data.
Quantitative data tells you the 'what': our conversion rate is low.
Qualitative data tells you the 'why': our conversion rate is low because of X
At this point, you'll start thinking about potential experiments you can test.
An excellent framework to build a solid hypothesis is:
Because we saw data/feedback,
We expect that change will cause impact.
We'll measure this using metric.
4.- Idea prioritization framework
During my career, I worked with three different prioritization frameworks.
One is the ICE Score framework read more here
The other one is from CXL Institute: PXL Framework read more here
And the one I use for SaaS and Startups, in general, is the PIE Score framework.
It's pretty similar to the ICE score framework, but I find it less subjective and more focused on digital products.
Potential: How much improvement can be made on this page(s)? You should prioritize your worst performers. This should consider your web analytics data, customer data, and expert heuristic analysis of user scenarios.
Importance: How valuable is the traffic to this page(s)? Your most important pages are those with the highest volume and the costliest traffic. You may have identified pages that perform terribly, but they aren't testing priorities if they don't have a significant volume of costly traffic.
Ease: How difficult will it be to implement a test on this page or template? The final consideration is the difficulty of running a test on this page, which includes technical implementation and organizational or political barriers.
5.- Planning experiments
This all depends on your workload, what kind of resources you need, and the ones you have.
It's not the same to use only marketing resources for a given experiment as having to work with design + engineering teams.
You'll want to plan all your testings with time to make sure everything's OK. Don't rush things.
I default for 30 days regarding the duration of tests, but maybe one or two weeks are more than enough for small experiments.
That said, I always try the results to be conclusive (whether it is a success or not)
6.- Document your learnings
The final step is to document everything you learn.
An easy step but usually skipped.
Documenting is tedious but necessary. You'll want to have all those learnings when you need some reference for new tests you want to run in the future.
This is especially true for mid-size and bigger companies where employee rotation is much higher.
Imagine if a new "Head of Growth" joins the company and must learn all by herself... it would be horrible.
Having an internal wiki where you documented all you did in the past will help her know where to focus on what worked and what didn't.
And that's it!
To finish this, I want to share with you that to apply this kind of process, the team at FROGED and I have launched a Growth Hacking Framework for Notion. I hope you find it useful!
Read you in the comments!
