Stepping into the driver’s seat as a Startup Founder is already a challenging enough job. Why then would you make it harder and blindfold yourself at the same time? But, that’s essentially what you do if you fail to prioritise the collection and analysis of data generated by your users.
Despite what many headlines show, not all startups rocket out of the gate and achieve rapid success in a short few months.
Many have to take a longer, harder road to success. But before they get there, what stops the founder(s) from quitting?
The answer, in my opinion, is data. It continues to surprise me to this day how few startups are focused on collecting and analysing data from the outset. But failure to do so can literally kill your startup.
Beyond a lack of funding or failing to find product market fit, one of the key reasons why startups fail is because the founders quit. In this situation, without any data to analyse or mark your progress against, these founders are at best acting on a hunch or at worse taking a complete gamble on whether or not to throw away months, if not years of work and give up.
That’s why putting in place a system to collect and analyse data is critical in understanding the progress (or lack thereof) you are making with your startup. With this information at hand, you can then make more informed decisions about your company and the steps you wish to take.
Here’s why data has played such an important role in my startups journey.
Data Helps Tell The Real Story
Task Pigeon, a task management application augmented by an on-demand marketplace of freelancers, has been my focus for the past 18 months to 2 years. The most important metric for me, if not all SaaS companies, is seeing sustained and consistent growth in Monthly Recurring Revenue (MRR).
Being completely honest Task Pigeon isn’t where I wanted it to be at this stage of its life (more on that in a minute). But, without data it would be easy to miss the forest for the tree. Despite the lack of growth in MRR in recent months there have been extremely promising signs, many of which are only uncovered through the data we collect.
But first, I want to provide some context to all of this. As I mentioned, the last couple of months have been very promising. In particular, what I have discovered is that Task Pigeon can attract and secure customers from large companies. Much larger than I originally envisaged we would be attracting at this stage of our journey.
While, I haven’t got permission to share their corporate names I can say that one is a $1bn UK listed company looking to on-board 15 users. The other is literally at the cutting edge of transportation and has funding from a famous UK entrepreneur (I’ll let you fill in the gaps).
This has come at an important time for Task Pigeon and reinvigorates my belief in what I am trying to achieve. But this information alone isn’t enough. For startups who stopped at this level, they would be missing out on a wealth of data that can help them make more informed decisions about their business.
What the two examples above demonstrate to me is that we don’t have an issue getting customers to our site and to sign up. While we always want more visitors to our site, we achieve a very healthy conversion rate of 2.74% for the people who do make it there. That gives me confidence that our message and branding resonates with people and when they hit the Task Pigeon home page they see that we can solve a problem for them, and enter their email to sign up.
The strong performance on this front is also reflected in the growth in user numbers we have seen during this period. Last month, the number of new sign ups increased by 50%.
Attracting people is of course only one part of the equation. You want to have engaged users, people who keep coming back to the app time and time again, and who expand their usage. That’s where I turn to data again to understand just how people are using Task Pigeon. There are two key metrics I track in this regard. One, new tasks created, which shows how active people are in creating and assigning new tasks. And two, task views, which helps capture insight into people who may not create tasks themselves, but actively check back as part of their daily workflow.
On this front the numbers are just as encouraging. In June Task Pigeon users created more than 811 new tasks. This is an increase of 31% on the prior only, and over the four month period since we implemented new event tracking results in an average monthly growth rate of 45.4%.
When it comes to viewing tasks, people have been equally engaged. In May 2018 people viewed tasks 2,229 times. In June, this jumped to 3,728, an increase of 67%. Averaged out over the preceding 4 month period this shows a 34.8% growth rate.
What Data & The Story It Creates Then Allows You To Do
Unlike a startup founder who is flying blind, what this data allows me to do, is get a more comprehensive picture of Task Pigeon and where it is today.
This links back to where I mentioned above that I had hoped for Task Pigeon to be further along than it is today. In an ideal world, I would love us to already be at $5k or $10k MRR. While that isn’t the case, the data shows that there are a number of positives to be found and then helps point me in the direction of what areas we need to fix.
Through reviewing the data (and having conversations with users) this largely boils down to two key points in my mind. First of all, at a high level we don’t have an issue getting people to sign up initially, and can even attract some large and established companies at the same time. In fact, one of our recent users is pre-paying for a 3 month license for a large team which is great to see.
Where we need to tighten our game is ensuring that a larger proportion of those who initially sign up find their “wow moment” so they too stick around. If they do, then we can see from the data that teams who use Task Pigeon, keep using it, and even increase their usage of it.
Secondly, once we have these users who are sticking around and who are using the app regularly we need to improve the incentives to upgrade.
The solution to both of these issues is relatively straight-forward and something I am excited about embarking on in the next few months. Firstly, giving the application an updated UI, without losing the core of what works so great for us, will significantly improve the user experience and lift our design to a 9+ out of 10. With this there should be no reason why Task Pigeon doesn’t feel just as modern or as slick as any other application in the market.
With this in place we can then improve our user on-boarding with a clearer message and interface. This once combined with a number of new features our users have been screaming out for (such as recurring tasks) will help lift the number of users who convert to paid.
How To Track This Data & Key Takeaways
Hopefully through sharing my story I have sold you on the value of collecting and analysing data from the earliest inception of your app’s lifecycle. It really does help to provide context around the feedback and support emails you get from your users, and it isn’t difficult to do with programmes like PowerPivot, which makes analysing any data easy. If you would like to learn more about PowerPivot you can read this post here: http://isitvivid.com/burgeoning-analysis-software-has-reached-its-cruising-altitude/.
Not only that, but unlike those founders who grind away and are never really sure how things are going at an individual user level, the use of data and analytics doesn’t lie. It shows you exactly what is taking place in your application, where engagement is, and where it isn’t.
The good news on all of this is that adopting a data and analytics strategy doesn’t have to be a huge time suck for your development team. Numerous tools exist to help make all of this tracking straightforward and easy.
At a high level, at Task Pigeon, I use Google Analytics to track all of the data associated with our website and blog. I then use Woopra as our event tracking tool within the app. The default reports of both are more than sufficient for early stage startups, yet in time also offer the flexibility to be combined with other data sources or insight to really dive into the minute optimisations that can improve a user experience by a percentage point here, and a percentage point there.
For now though, with the data at hand and my goals for Task Pigeon, I am focused on uncovering issues where I can see a 3x, 5x or 10x improvement. Data, and talking with customers allows me to do that and if you don’t already, I recommend you adopt a similar strategy for your startup today.
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