The above SlideShare is based on a talk we’ve given to a number of incubators and startups. Metrics can be totally overwhelming for startup teams, so we wanted to share some of our learnings from working with thousands of startups over the years.
Why should I care about the metrics I track?
If you want to build a data driven culture, it’s something that you have to cultivate from the start.
We really can’t emphasise this enough.
At GoSquared we’ve had the good fortune to understand how companies of all sizes use data.
In larger companies, one of the most frustrating situations we often see is when data scientists and analysts put forward data-driven proposals and get overruled by someone higher up the food chain with a gut-based decision. There’s even an industry term – “HIPPO” (Highest Paid Person’s Opinion) for the boss that will chose to ignore the data and instead trust their instinct.
“HIPPO”: Highest Paid Person’s Opinion
This is a common industry problem and it can take a considerable effort to change the mindset of employees to be more data-reliant. If you want a business that makes decisions based on data, you have to cultivate this from the very beginning – that’s why we really emphasise this early on with startups.
Different types of metrics for startups
For some, just knowing if a metric is going up or down is good enough. But this can lead to a lot of confusion, misunderstanding, and ultimately cause decisions to be made off the wrong data. When we talk to our customers, we talk about the other metrics they use to run their business – not just the ones they want to track online.
Often a large proportion of the team don’t have a clear understanding of how important KPIs are calculated. If you don’t know how they’re calculated or what a metric actually means, it can be difficult to determine whether this a leading or lagging metric. For example, should the team view a specific metric on a larger timeframe? Should they be discounting the result of an A/B experiment because there simply isn’t sufficient volume of data to prove it?
Once you have a solid conceptual understanding of how each metric is calculated and what it actually means, then you can start to make better decisions more confidently and iterate quicker.
Importance of frameworks
While we only mention a few analytics frameworks in our SlideShare, there are dozens more out there. The framework that works for you will depend on the type of business you run and the stage you’re at. Choosing a good framework is important, because it can provide a guide for the metrics you want to track and help you focus on fewer but better metrics.
A five-person startup will struggle to focus simultaneously on content marketing, paid acquisition, onboarding conversion, user retention, and new feature releases. It’s just too much. The end result is usually a subpar outcome of all of the above.
By following a framework, startups can focus on one or two areas of the business at a time, optimising until there are diminishing returns and then moving onto the next weakest performing area of the business.
While frameworks help focus efforts, startup teams can still be easily distracted, feeling the pressure to improve all of their metrics at once. For example, it’s often very tempting to start paid acquisition because you see your competitors doing the same. This can be a costly mistake if churn is high, as you’re effectively pouring money into a leaky bucket. Startups that have discipline and focus are the ones we see growing the fastest.
We’ve defined our own framework – the ABCD framework – to help guide our own decision making.
It’s easy to wax lyrical about the benefits of being data driven.
We’ve seen many startups make the same mistakes, because too often early implementation advice isn’t shared. Simple things like defining an agreed naming convention for events upfront can save hours of confusion and miscalculations further down the line.
Many of the lessons in this SlideShare are personal ones that we have learned along the way. We’re sharing them because if you can skip these mistakes then you’re going to be in a much better position from the start.
Getting analytics right in a startup is hard. The product could be changing weekly. Your target customer might be different next month. Your pricing will likely change two weeks from now.
Just because a metric is hard to measure doesn’t mean it should be ignored – quite the opposite. Startups need to know what’s working and what isn’t, and with these guiding principles we hope you can iterate faster, build a better product, and find your inner metrics zen.
Feel free to ping us a message anytime on Chat – we’ll be more than happy to help out!