To get started with Humanic you will need to Sign up, which is very straightforward. It is free to create an account and use the platform for up to 500 active users forever.
Post Sign up you will see our main screen which has a few personas built for you already. You can access these personas by clicking on the Demo mode button on the top right of the screen.
These are examples of personas that we see very often with PLG Companies. For example:
When you first log in you will see a blank screen below. You can go to the demo mode explained above by clicking on the button on the top right and reviewing the personas that have been built on top of the demo data.
The first thing you need to do is to click on the big blue button on the left nav and start connecting your data.
Data types are divided into two main buckets - Source and Destination.
Source – These are the data repositories that Humanic will pull data from. These are generally well-known systems that are part of the modern data stack. These could also be data warehouses and custom homegrown solutions. If you do not see your source listed as available please send us a note at systems@humanic.so
Destination – These are data repositories that Humanic will push data to. These are generally CRM or Marketing Automation Tools. If you need to connect to a tool that is not listed under Destinations as available please send us a note at systems@humanic.so
For ease of use, the source and destinations are further categorized under the three major sources of data for PLG companies - user activity, payment, and customer demographic.
It might take a few minutes to several hours for the data to sync up. When the data is available there will be a green check box on the category with the name of the source or destination tool that is connected as shown above.
Once your data is connected and synced you can click on the 'Add New Persona' and start creating personas to see how many users exist in each persona segment.
There are many other features like building Churn propensity, Up-sell and Cross-sell models using Machine Learning, Filters and setting up alerts, etc that we will cover in other posts.