After spending time in the trenches with many startups, I have been lucky to see why many growth marketing engines do not work properly. I say I’m lucky because the problems I’ve seen have taught me a tremendous amount about what makes a well-oiled, polished growth marketing engine fire on all cylinders. My experience with postmates taught me more through mistakes than triumphs, and I learned how to properly scale a growth engine as we march toward an exit.
A common thread of failure connects most startups trying their hand at growth marketing. Some common mistakes include performance metrics that are not measured correctly, product and growth teams working in silos, low test speed, and lack of consideration of the entire marketing funnel.
This is not to say that there are not unique issues with each startup. I’m just saying that there are few who are ubiquitous.
Low test speed
The day is far in the future where you can turn a switch to paid acquisition, life cycle, social media and content, and get it all running automatically. Until that day comes, the need to continue the test is paramount.
It’s simple: test more, and the results will turn into something sooner. Although the concept is simple, you need a proper test framework – one that defines the number and type of weekly tests that are being implemented. A sample weekly test schedule can look like this:
- Paid acquisition: Two creative concepts x three copy iterations = six creative assets.
- Life cycle: Two copy variations x five emails = 10 email variants.
Create a test frame, and most importantly, stick to it. The results follow.
Rely on incorrect measurements
When measuring the success of a campaign, whether it is on social media for paid acquisition or with a lifecycle retention series, it is crucial to have the correct metrics before taking action – this is the foundation of any growth marketing stack.
But what if your performance metrics are inaccurate? And if they are, why? I have listed the three main reasons for not having correct metrics below:
- Attribution source.
- Attribution loss.