How the System Learns Over Time

Stairoids isn’t just a signal aggregator — it’s a self-learning system. Every time you take action, you’re training the platform to get smarter, faster, and more accurate in surfacing the leads and companies that matter most to you.

This article explains how Stairoids learns over time, what inputs make it smarter, and how to use that learning to your advantage.

🧠 What Does "Learning" Mean in Stairoids?

Learning means the system is constantly adjusting its behavior based on:

Who you approve or block
Which contacts you heart ❤️
Which accounts you assign
What patterns you act on (e.g. high IWS + LinkedIn engagement)
Who your team interacts with most
What signals consistently lead to follow-up and pipeline

The more you use Stairoids, the more it aligns with your ICP, buying unit structure, and ideal outreach timing.

🧩 What Inputs Drive the Learning?

Action You Take	How It Trains the System
✅ Approving a company	Teaches what a good-fit account looks like
🚫 Blocking a company	Refines what not to show you in the future
❤️ Hearting a contact	Trains the system on your ideal buyer personas
🧑 Assigning accounts/contacts	Prioritizes similar profiles across the platform
🔍 Using filters	Creates feedback loops around what you want to see
📤 Exporting lists	Signals intent-to-act on specific segments

💡 Every decision becomes a training data point for your personal and team-level logic.

🚀 What the System Learns

Over time, Stairoids learns to:

Recommend more relevant accounts (based on your approvals)
Highlight the right contacts earlier (based on hearts & assignments)
Score companies more precisely (based on signal conversion history)
Suggest tasks that match your working style and timing
Surface patterns that match how you define a qualified lead

👥 Shared Learning Across Your Team

The system doesn’t just learn from you — it learns from your team’s behavior as well.

If your colleagues consistently heart CMOs in SaaS companies, you’ll start seeing similar roles suggested faster — even if you haven’t marked them yet.

This creates team intelligence, where the system improves collectively while still personalizing to individual users.

📈 What You’ll Notice Over Time

As the system learns, you’ll experience:

Less noise in the Unassigned feed
More spot-on Suggested Tasks
Faster identification of buying units
Smarter IWS scoring that reflects real pipeline outcomes
Cleaner filters and fewer irrelevant contacts

✅ Best Practices to Help the System Learn

Action	Why It Matters
Be consistent with approvals	Helps refine your ICP model faster
Use hearts on key personas	Builds a strong buyer profile pattern
Don’t skip blocking	Teaches the system what to suppress
Assign contacts/accounts	Activates full AI scoring and prioritization
Create filters for recurring patterns	Helps the system detect what “good” looks like

🟢 Summary

System Learns From…	So It Can...
Your approvals & blocks	Show you better companies and contacts
Hearts & assignments	Prioritize your best-fit decision-makers
Team behavior	Improve performance across users
Your workflows	Tailor suggestions to how you actually work

The more you interact with Stairoids, the better it fits your strategy — and the less manual work you'll have to do.