In the early stages of your venture, the number one goal is to find a scalable business model before the money runs out. Everything you do for your startup should be focused on getting out of the startup phase by proving our your assumptions. The best way and most efficient way to do this are through analytics.
It's easy to become overwhelmed with data. Cohort analysis, A/B testing and segmentation, are all types of data analysis that can cause you to go crazy. Your job is to be able to go through all the data and pick out the analytics that give you the most insight on what to change in your product. Below, I'll walk through the main steps to maximize the return on your analytics.
1. Identify the key metrics you want to track
The first step in setting up an analytics system for your product is deciding what user action you want to focus on. Bad examples are user sign ups, page views or time spent on a certain screen. A good example would be weekly user retention. You want to pick things that are going to drive your business to make money, and be able to not focus on the other actions your user is taking. Trying to fix every user action is a recipe for disaster, since it prevents you from dialing in on what's most important.
2. Find out whose performing the user action the most
It's essential that you find out who your true customers are as fast as possible. To do this, once you decide on the user action you want figure out which segment of your user group is performing it the most. You may be surprised at the results. Many companies have launched focusing on a wide customer base; only to find out their target market is a small niche.
After you identify the core user of your product, figure out why they are performing the desired action you chose in step one. If your goal is user retention, study why users keep coming back to the product. Knowing this will allow us to be much more specific in your iterations and hone in on the value of your users.
3. Decide on what iteration needs to be made and track the results
Only after we've gone through the first two steps are you ready to iterate your product. Now is the time where the quantitative data we have runs out. At this point, we need to make the qualitative decision of what to build for our core demographic.
Once you make the edit to the product, track the success of it in the market. A/B test the change you've made and see the results. Don't get discouraged if you don't get this right the first time, you need to be prepared to go through some trial and error to get this right. If don't correctly, you've mitigated a ton of risk before you actually make the edit to your product. This way you have a much higher chance of getting a homerun on your next iteration.