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published 28 Apr 2015 4 minutes 49 seconds to read

How to use metrics to optimise your product development

You can only manage what you can measure. You’ve probably heard this old saying before, and it is widely applicable when it comes to product management.

How to Web MVP Academy

About the author
Irina Scarlat is passionate about communication, startups, and technology, and does the marketing magic for How to Web and TechHub Bucharest. Entrepreneur at heart, she is also the cofounder of Akcees, organization that fuels the entrepreneurial spark of young people, and, before joining forces with the How to Web power team, she had her own communication agency offering specialised services for startups and tech events (Prove PR). In her spare time she loves riding horses, reading good books and spending valuable time with people that matter.

You need to choose the right metrics to look at and have a good understanding of them in order to optimise every single stage of your product development process. So you’ve got an early stage tech startup, you’ve built a minimum viable product (MVP) and you’re committed to turn it into a full-blown product, scale and go big. You’ve probably already started collecting lots of qualitative and quantitative data, but the real question here is what do you actually do with it and how can you leverage it to guide your product development and optimise your processes. So where do you start?

Define your conversion funnel

The first thing to do, before actually choosing the metrics to look at, is to carefully define your conversion funnel - that is the stages your users pass through, from the first interaction they have with your product to the moment when they actually make the purchase and become your customers. The difficult part here is that there is no generally applicable model of conversion funnel and you have to understand your users’ journey to define the funnel that’s adequate for you.

Choose your metrics

Once you’ve got your conversion funnel straight, you should proceed to choosing the right metrics to analyse. Closely monitoring these metrics will help you optimise your product development process based on the information provided by data. If you’re an early stage tech startup looking to make documented decisions, here are a couple of indicators you should take a look at:

  • Monthly Active Users (MAU): number of users that are actively using your product over a period of one month (you can also take a look at DAU – daily active users, WAU – weekly active users, or YAU – yearly active users);
  • Churn rate: the percentage of customers that you lose over a specified period of time;
  • Retention rate: this is the opposite of churn, reflecting the number of users that you keep over a specified period of time;
  • Average lifetime of a customer: the average period of time that a customer keeps using your product / being active in your application;
  • Net promoter score (NPS): indicator that measures customer satisfaction and the likelihood that your users will recommend your product to others;
  • Virality factor: number of free users that starts using your product for one paid user. A virality factor higher than one will show exponential growth and will help you get the graphs investors want to see;
  • Customer acquisition cost (CAC): how much does it cost to bring on board one more user;
  • Average Revenue per User (ARPU): how much revenue every user brings you.

Bear in mind that besides all these metrics, there are several other industry-specific indicators that you should consider in order to understand where you’re standing right now and how can you constantly improve your product and user experience.

Understand the data

Remember: Measuring the right indicators is not enough! You should have an in-depth understanding of their actual meaning and you should constantly test and analyse the results for being able to optimise your processes. You can do so by using:

  • Landing pages: standalone pages that you design for a specific purpose (in this case for testing and validating your assumptions) with the main goal of generating leads that you’ll further push through your conversion funnel
  • Cohort analysis: analysing the user behavior of different cohorts (clusters of users computed on a daily, weekly, or monthly basis, generally situated in the upper part of your funnel - the ones that have just had your first interaction with your product)
  • A/B Testing: comparing two different versions of the same feature in order to understand which one performs better for your target market

Test, test, test and constantly analyse the results to get an in-depth understanding of how you can better solve the problems of your users!

What tools to use?

There are several tools you can use to help you out along this process, starting from the very basic Microsoft Excel, that you are already familiar with, and going up to several automated ones such as Google Analytics, MixPanel, KissMetrics or LaunchRock, to name just a few. The tools you use for analytics are your personal choice, and their complexity has to evolve as your understanding of the product grows.

It’s not easy to choose the right product metrics and get a complete understanding of them, but it’s definitely worth investing the time and effort needed to make it happen. Once you do this right, you’ll be able to optimise your product development process and take the right decisions at the right time.

Bogdan Ripa, ex-Master Product Owner at Adobe Romania, now looking for cofounders to start a new entrepreneurial journey, has extensively discussed these aspects with the MVP Academy Class of 2015. is closely following the evolution of the teams that are part of the second batch of the pre-accelerator programme and will get back to you soon with more valuable insights from the workshops in the program.

This article is brought to you in cooperation with HowToWeb. is a mediapartner


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