Once you get into product development, heaps of data wait to be collected and analyzed for your benefit. As you move through the product development process, both the pre-launch and post-launch stages have data to be mined and analyzed closely for better-informed decisions.
To successfully employ product development innovations you need to take the gathered data and use it as user-centric compasses that lead to greater user satisfaction and business growth.
Definition of Product Development Analytics
Product development analysis refers to gathering and analyzing quantitative data with set tools that track how users interact with a product or service.
Using product development analysis has multiple benefits for your business. It helps you understand your users and optimize the user experience (UX). By getting into the intricacies of the current state of your UX, you also know which hurdles the user comes across, and which features they find lacking. Then, you can start plotting for improvements such as merchandising features.
Here is the type of data you gather with product development analysis:
- The most often accessed features of a product,
- The average time users spend making a particular action
- A map of each user’s journey through the product
4 different product management analyses to collect data and act on it
Now, let’s see how you can effectively collect data for product management analysis.
More specifically, let’s see 4 useful and different methods for that.
#1 Dividing Users Into Different Behavioral Groups
To get a good glimpse at your target base, divide it into groups based on behavioral characteristics. The results you get can help set a foundation for great product experiences and useful marketing ideas.
There are many ways to do this, but we recommend the following:
- Segment users with a product development analytics tool – Find a tool that has a lot of pre-set filters (and ones you can add yourself!), so you can divide users by demographics, user attributes, in-app behavior, and NPS (Net Promoter Score).
- Hire a proven product development consultancy – A consultancy that has lots of experience with businesses such as yours can provide invaluable feedback. They stretch their creativity and use their full potential to introduce new ideas.
- Combining the previous two methods – Self-explanatory. Why not use the best of both worlds?
Segmenting users by behavior can also help product managers repeat successful patterns for their best users.
#2 Conduct Cohort Analysis to Understand the Logic Behind Users’ Behavior
Cohort analysis, as opposed to customer behavioral segmentation, allows you to observe a consumer group over time who share certain traits. A product manager can then see how certain product updates affect particular product management analytics metrics.
For instance, you may wish to determine how changes to the onboarding process influence the number of users who completed it.
As another option, you can use cohort analysis to determine which user groups churn the most and go further into the causes of drop-off.
#3 Perform Funnel Analysis to Discover Conversion and Drop-Off Spots
The next thing you should do is perform a funnel analysis. Especially if you noticed a significant signal in your users’ journeys. For instance, if you just had a month with a high churn rate, you should find out in which segment of the user’s journey the drop-off happens.
Funnel analysis improves your user’s journey to events like:
- Initial conversion
And now we’ll move to the fourth and final analysis method you should use and combine with the previous three ones.
Perform Retention Analysis and Find Out How and Why Users Churn
As soon as you spot a potential problematic metric in your retention, you should do a retention analysis.
Such an analysis tells you which parts of the user’s journey are susceptible to churn, how users act, and if there was a bug or some other kind of lag pushed the user to quit.
Retention analysis is a method that lets you know:
- Most valuable users
- Methods for improving customer lifetime value and product retention
- User segments susceptible to churning
- Problematic points in the user journey
How to Act on Data Collected with Product Development Analytics
Performing product analysis keeps the product connected to the user. Getting out of touch with the user and ignoring their needs is a one-way ticket to stagnation and failure.
So once you collect data, you should act on it. Here’s how.
Position Upgrades as Increased Value
Upgrades ARE increased value, but you also need to remind your users of this fact. That way, you’re letting them know that they will get even better results than before when using the product.
Do this right, and you’ll drive upsells in a way that pushes both your company and user forward.
Sometimes you don’t even need an upgrade. You may just need to remind your users that there’s an underutilized feature they already have at their disposal but fail to use it.
Direct New Feature Launch Communication to Particular Segments
Don’t go overboard when launching a new feature. There may be no need to target all your users when introducing a new feature, but rather just a part of your user base.
To know which segment of your user base to target, analyze the data you collected in your product development analysis journey. That way, you’ll understand who will and won’t benefit from the new feature. Ask yourself if this will help your users in their workplace or everyday life. Or is this an upgrade they’ll see as a new challenge to overcome just to get the same result as before?
Use the data you have and construct your feature announcements to effectively target segments of your user base. You can adapt your message to highlight certain advantages the feature offers to each user segment by using the analysis data. That will ultimately enhance the adoption rate of your recently introduced feature.
Make the most of your data to understand the marketplace and the users. Experiment, try different data extraction methods, get to know your target base, and polish your product to perfection.