Product managers are always looking for ways to do more with less. It’s no surprise that we’ve seen product teams take Internal and start using it in creative and unexpected ways — helping them maximize team resources, examine data for insights and troubleshoot product issues.
Check out these 3 ways PMs are using Internal today:
1 - Maximize team output by freeing up engineering resources
As a product manager, you’re often facing a huge roadmap with a number of projects to get done and a limited amount of engineering resources. With these tight constraints, developing or updating internal tools often falls on the backburner, leaving internal teams in a bind.
Nowadays, we’re seeing product managers take matters into their own hands and use Internal to quickly deliver internal tools, without involving engineering. Given that many product managers are already designing and speccing the internal tools that go along with their product, it’s easy for them to quickly translate those designs into fully functional tools in Internal. This frees up engineering resources to focus on core product and customer-facing features, increasing team throughput with the same amount of engineers.
Product managers also save time when delivering tools through Internal. You don’t need to worry about building in access controls or instituting processes around handling customer data - each tool built in Internal comes with baked-in permission settings. And in the future, if internal tools need to be updated, product managers are no longer bottlenecked by engineering resources.
2 - Combine data from multiple sources to discover product insights
Gathering and synthesizing information is a key part of being a product manager. One clever way product managers are using Internal is to use it to pull in data from all of the different places their company stores it in: databases, CRM, ERP, support ticket systems, etc. Then, they use Internal to build relationships between datasets and start sifting through the data to mine for any insights that could help them.
By doing this, product managers can do things like looking at user behavior as it relates to sales data, support trends, and more. Support data can be a particularly valuable source of insight, as Lizzie Jaeger explains here. Here’s two specific ways we’ve seen product managers combine data:
- Combine user behavior from your MySQL database with support tickets from Zendesk. This could help you understand what user behaviors and user profiles are driving certain support trends. In this instance, we’re looking at all the tickets filed under the “connectivity” category. Because we mapped our user details from MySQL to the requesting user in Zendesk, clicking on a ticket in the table will pull up the user details. This lets us easily examine their connectivity data so we can get a better idea of what may be causing the issue.
- Combine the deals and opportunity data from Salesforce with feature requests tracked in Google Sheets. This could help you understand what features your prospects in a certain industry might be looking for. In this example, we can see the size of a deal (coming from Salesforce) with any feature requests that company may have made. This can help product managers better prioritize their roadmap.
3 - Troubleshoot product issues during development
Over the course of product development, you’ll often need a way to examine the data within your product to ensure that things are working as expected. Rather than grappling with admin interfaces like RailsAdmin or writing SQL queries to look at data, product managers have been hooking up Internal instead.
All you need to do is connect Internal to the data source you’re using during development (like your staging environment). From there Internal will auto-generate resources of all your data that can be viewed as tables or detailed record formats. You can examine your test data to make sure that your product is computing the discount rate properly on a subscription, for example.
Product managers can also use Internal to edit data to simplify testing. For example, you could set an approval status for a user back to “unapproved” so you can test the approval flow multiple times. A dedicated Space can be built out for a data tool easily as well, allowing you to add any custom functionality you may need to work with your particular product’s data.