Hey everyone! 👋 I've been using PingIntelligence for API security monitoring for about six months now, and while the alerts are super valuable, I found the native reporting a bit... limited for our marketing and sales team's needs. They really wanted a clearer view of threat patterns and how they might correlate with campaign spikes.
So this weekend, I finally built a custom dashboard pulling those alerts into our main analytics stack! I used a combination of Ping's SIEM integration and some API calls to pipe the data into a Looker Studio dashboard. Now we have a live view that shows:
* **Top targeted endpoints** – helps us see if a specific API tied to a recent content campaign is getting hit.
* **Geographic threat sources** layered over our lead gen maps.
* **Alert volume trends** alongside our website traffic from Google Analytics.
The biggest win was setting up a Slack alert that pings the CRM team if a high-severity threat originates from a region where we just launched a big email nurture stream. It's not a direct cause-and-effect thing, but the context is incredibly useful for cross-team visibility.
Has anyone else tried building custom visualizations for Ping data? I'm curious if you connected it to other tools in your stack (like a CRM for account-based security insights) and if you ran into any data formatting hurdles. I had to do some gymnastics with timestamps!
Cheers
Keep it simple.
That's really clever, tying the threat data back to marketing campaigns. I'd never thought about the correlation between attack patterns and new email launches.
How did you handle the API calls for the real-time data? Was there any delay getting it into Looker Studio? I'm trying to do something similar for our helpdesk alerts.
Nice! For the real-time piece, I used Ping's API with a lightweight Python service as a middle layer - it batches and transforms the data before sending it to Looker Studio's API. There's about a 2-3 minute lag, mostly from the batching, but for our use case that's fine.
One thing I'd check: make sure your API client handles throttling gracefully. I got rate-limited at first because of alert spikes. Adding a simple exponential backoff made it way more stable.
For your helpdesk alerts, are you pulling from a REST API or a streaming source? The approach changes a bit.
Clean code is not an option, it's a sanity measure.
That Slack alert to the CRM team is a smart move. Too often security data stays siloed.
How are you handling the cost tracking for this? Those API calls and data pipeline aren't free. I've had to justify similar setups by showing the business risk reduction, not just the tech cost.
Also, make sure you've got a clause in your Ping contract covering data extraction for custom reporting. Some vendors get tricky about that.