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Building Early Stage Products: Finding your North Star Metric for Success

Evan Leong By on February 19, 2017

People who are spearheading the development of new products will often face the dilemma of creating something perfect, vs making compromises and justifying their decision, and often it’s the latter that takes place. Ultimately it’s those decisions that can make or break a company in it’s early stages, because in theory every startup should succeed given an infinite amount of time, talent, and resources.

The characteristics of someone who is trying to build the perfect product is not what is on the chopping block, but rather the lack of analysis along the way. Building great companies are rarely the result of building the perfect product from the get-go, and more so about the accuracy of the decisions throughout the lifespan of the company. If you can make better decisions throughout your day to day, the better your chances of success. The biggest setbacks I see with many great ideas and founders is letting their aspiration for perfection drive decisions that are not optimized for the current state of their business.

Pick a metric of success and stick with it

How do you gauge the success of your product? Is it monthly active users? Revenue? Every startup will have a different metric of success. Pick one and use it as your north star. Without it, you may fall into feature fatigue, where every new feature idea or customer feedback sounds like the most logical next addition. Often times they are not wrong, and the feature does in fact add value. Where many go astray is not vetting their features against their metric of success, and in turn suffocating their runway at the expense of what on the surface seems to be a step in the right direction.

Let me paint an example:

Suppose your startup is a music streaming app that is competing with Spotify. You are paying your 2 developers $10,000 / month each and have just launched version 1.0 of your awesome new app. You then compare Spotify with your app side by side. Wow, they’re product is so much more mature. We need to implement at least some similar features to keep us in the same playing field. 

You ask your developers how long it might take for them to implement a feature where a user can see lyrics to a song they are listening to. You even find a slicker way to implement the UI than Spotify! Everyone is pumped, and your developers get to work. It takes them 1 month to complete the feature and it looks amazing.

Take a step back for a moment. How are we gauging the success this new feature has on our product? If we are aiming for an increase in Daily Active Users, how can we be sure users looking at lyrics are moving the needle? How can we tell that this feature is directly impacting subscriptions? The truth is we might be able to get close, but not close enough to make a concrete conclusion.

Now imagine our metric for success is our subscription rate, which means every feature that you decide to add needs to pass our north star revenue litmus test in order to get put on to your developers plate. You decide to implement a feature in your app that you anticipate will increase freemium to paid conversions from 2% to 5%. Your developers take 1 month to build this feature.

For simplicity’s sake, let’s say you currently have 20,000 users, and your subscription is $10 / month. At a 2% conversion rate you’re making $4,000 / month, which has now been increased to $10,000 / month! You have effectively increased your annual revenue by $72,000, which gives your runway a lot more breathability to add awesome features down the line. Given the overhead of your developers, your decision allows your startup an additional 3-4 months of developer runway which you can use to build out additions that add value beyond your north star.

The right feature implementation may literally make or break your runway. If we analyzed our decisions too late, our company may have run out of money by the time we decided to implement the right features. This is why it’s crucial to choose your metric of success, and run it against every feature add.

This is obviously a simple example to a highly complex process with many variables at play, but the concept remains the same. Our north star metric could have been purely DAU, in which case we could focus on creating specialized playlists throughout the day to get users back into the app more frequently.  Sometimes the answer is not as clear cut as the example above, but adhering to your north star metric will ensure better decisions for the best outcomes. Identify metrics you care about, and allow your team to hyper focus on features that gratify them.

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