Swiftask connects your Heap data to intelligent AI agents. Stop dealing with raw data and start getting immediate answers about feature adoption and usage.
Result:
Move from raw data to product decisions in seconds, without relying on data teams.
Why feature analysis often gets stuck
Extracting value from Heap requires time and technical expertise. Product managers spend hours setting up reports, while data stays siloed, preventing a real understanding of user behavior.
Main negative impacts:
Swiftask acts as an intelligence layer over your Heap data. Ask your questions in natural language and get precise feature analysis, correlated with user context.
BEFORE / AFTER
What changes with Swiftask
The classic approach with Heap
The PM notices a drop in adoption on a new feature. They must open Heap, filter events, create a funnel, export data to a third-party tool for analysis, and wait for a reply from the data team.
Augmented analysis with Swiftask
The PM asks their Swiftask agent: 'Why did adoption of feature X drop this week?'. The agent analyzes the Heap data, identifies affected segments, and proposes a synthesis of likely causes instantly.
Optimize your Heap features in 4 simple steps
STEP 1 : Connect Heap to Swiftask
Use our secure connector to sync your Heap events with your Swiftask AI agent.
STEP 2 : Define your analysis goals
Configure the KPIs you want to track: adoption rate, feature retention, or specific user journeys.
STEP 3 : Query your data in natural language
Ask your questions directly to the AI agent. It interprets your Heap data to provide contextual reports.
STEP 4 : Execute product decisions
Use the recommendations generated by the AI to prioritize your roadmap and improve user experience.
Analytical power for your products
The AI agent crosses Heap data with your business needs: user segmentation, journey analysis, and performance correlation.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-heap@swiftask.ai ). You keep full visibility on every action and every sent message.
Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.
Strategic advantages of AI analysis
1. Increased product velocity
Reduce analysis time from days to minutes.
2. Democratization of data
Every product team member becomes capable of analyzing their own features.
3. Evidence-based decisions
Eliminate cognitive biases by relying on real behavioral analysis.
4. Focus on retention
Identify exactly which features drive engagement and which ones hinder adoption.
5. Cross-functional alignment
Share clear insights understandable by everyone, from marketing to design.
Security and compliance
Swiftask applies enterprise-grade security standards for your heap automations.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Your analysis performance
| Metric | Before | After |
|---|---|---|
| Time to answer product questions | 2-5 days | Real-time |
| Technical complexity | SQL expert required | Natural language |
| Insight adoption rate | Low (raw data) | High (actionable recommendations) |
Take action with heap
Move from raw data to product decisions in seconds, without relying on data teams.