It’s a term that we’re all too familiar with as marketers.
As one of the industry’s most overused buzzwords today, growth hacking was once an exciting term that talked about the intersection between marketing, data analysis, engineering, and design. A “growth hacker”, therefore, was someone who could build a strategy that leverages all four of those things to drive growth for a business.
Today, that’s no longer the case in many marketing circles.
Instead, “growth hacking” has come to be ridiculed as a catch-all term for hacky, unscalable, one-off wins.
That’s not what Ladder is all about. We use data-driven experiments and scalable processes that demonstrate how to meet a company’s goals over time.
In this post, I will address the misconceptions around growth hacking and explain why Ladder’s processes are different.
What Is Growth Hacking?
Some define growth hacking as “black hat” methods that help you cheat the system for faster results. Others define it as easy-to-do “hacks” that can instantly solve a business problem.
In reality, growth hacking is a term meant to signify experimentation in order to target specific parts of the funnel with a mix of marketing, creative, and technology in order to drive scalable growth.
The Growth Marketing Funnel
One-off successes are not real “growth hacks”–instead, they’re throwaway tactics built around a marketing strategy (or lack thereof) that doesn’t actually scale. You’ll get that giant spike of growth immediately from something like a successful Product Hunt launch, but that traffic and lead gen will eventually slow down.
The real growth hacking comes when you take your Product Hunt success and combine it with clever email tactics, on-site A/B testing for Product Hunt traffic to optimize conversion, and build lookalike audiences and retargeting audiences based on that traffic.
That’s what growth hacking should be all about: fewer one-off tactics and more concentrated growth strategy.
Unfortunately, growth hacking has become the type of industry buzzword whose definition is no longer what you might find on Wikipedia or in blogs written by true growth hackers. It’s instead started to signify those one-off successes I mentioned above.
Growth hacking now survives on one-off success case studies, like cases from Airbnb or Dropbox, but these case studies ignore the real strategy and the real data insights behind their success and the how these companies doubled down on that success with full-funnel strategy.
That’s precisely why we began distancing ourselves from the term. We wanted current and potential clients to understand that data, experimentation, and strategy are the cornerstones of everything we do.
Why We Don’t Do It
We love stories of winning tactics, but a focus on tactics instead of strategy and scalability leads many marketers to think that they can do these one-off hacks and build a billion-dollar business.
At Ladder, we don’t like to think that way. We’ll take the exciting and hacky tactics and execute them when they fit into a full growth strategy for any given month, sure. But those tactics will always align around a unifying goal for that month. Every tactic we pick, from the most basic to the hackiest, will focus on driving ROI for that goal.
What We Actually Do
At Ladder, our growth process, which has helped us grow both high-potential startups and well-established enterprises, is similar in many ways to the more traditional definition of growth hacking:
“Growth hacking is a process of rapid experimentation across marketing channels and product development to identify the most efficient ways to grow a business.”
But instead, we think of this as “scientific marketing” — a process by which we apply the scientific method to grow a business.
Here’s how that looks:
- Step 1: First, collect data and information through observation – what does Analytics say? What are your website visitors saying? What can you find using 3rd party audit tools?
- Step 2: Create tentative descriptions of what is being observed – what story is the data showing? How does it apply to your growth bottom line?
- Step 3: Form hypotheses that predict different outcomes based on these observations – if you were to pull “Lever A” (e.g. CTA button copy), what do you expect to be the result?
- Step 4: Design and run an experiment to test your hypotheses – what tools can you use to execute the experiment? Are you testing the right variables? Will your test have an actual measurable impact?
- Step 5: Analyze the data, drawing conclusions and insights from the results – what did pulling “Lever A” actually do? In the above case, did it drive more clicks on the CTA button?
- Step 6: Rinse and repeat – successful test? Double down on those learnings. Failed test? Great! You should know exactly what to test next.
This process, alongside our technology-driven tactic recommendations, enables us to persistently test and scale growth tactics that increase ROI across every channel.