Intelligent A/B testing: boost conversions with Countly and AI
Swiftask leverages Countly analytics data to identify growth opportunities and automate your A/B tests in real time.
Result:
Turn raw data into actionable product decisions and validate your hypotheses faster.
AI Agents
countly
Connector countly · Secure OAuth 2.0
The optimization dilemma with siloed data
Most product teams rely on Countly to track user behavior but struggle to turn these insights into effective A/B tests. The process is slow, manual, and often biased by incomplete human interpretation.
Main negative impacts:
Slow data analysis
Time spent correlating Countly events prevents rapid iteration on key features.
Unvalidated hypotheses
Tests are launched without a solid statistical foundation, leading to inconclusive or risky results.
Lost growth opportunities
Without automation, high-potential user segments remain untapped due to lack of responsiveness.
Swiftask connects AI to your Countly streams to automate segment detection and suggest relevant A/B tests based on real statistical evidence.
BEFORE / AFTER
What changes with Swiftask
Without Swiftask
You manually export Countly reports, analyze conversion drops in Excel, create a test hypothesis, then manually configure each variant without knowing if it is statistically significant.
With Swiftask + Countly
The AI agent continuously analyzes your Countly events. It automatically detects tunnel friction, proposes test variants based on real behavior, and tracks performance in real time.
Launch your A/B tests in 4 simple steps
1
STEP 1 : Integrate your Countly data
Connect your Countly instance to Swiftask. The agent immediately begins ingesting and analyzing your event streams.
2
STEP 2 : Define your optimization goals
Configure the AI agent to focus on specific metrics (activation rate, retention, tunnel conversion).
3
STEP 3 : Variant generation and deployment
The AI generates test configurations and automatically deploys them to your target segments via API.
4
STEP 4 : Analysis and continuous learning
The system evaluates statistical significance and adjusts variants in real time to maximize your results.
Advanced analysis capabilities
The agent analyzes the correlation between user actions in Countly and your test results to isolate winning variables.
- Target connector: The agent performs the right actions in countly based on event context.
- Automated actions: Automatic identification of underperforming segments. Creation of A/B test variants based on behavior. Monitoring of statistical significance. Intelligent alerts on conversion anomalies.
- Native governance: All testing decisions are archived in Swiftask to ensure total transparency on your experiments.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-countly@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 for your products
Faster iteration speed
Reduce the time between data analysis and test launch.
Statistical precision
Eliminate human bias through predictive analysis on your Countly data.
Personalization at scale
Test different experiences for ultra-specific user segments.
Measurable ROI
Every test is directly linked to an improvement in your KPIs.
Test governance
Maintain a full history of all past tests and their impacts.
Analytical data security
Swiftask applies enterprise-grade security standards for your countly automations.
- Stream encryption: Data moving between Countly and Swiftask is encrypted according to industry standards.
- Granular access: You control which data segments are accessible by your AI agents.
- GDPR compliance: Swiftask respects the privacy protocols required to process your analytical data.
- Data integrity: No direct modification of your primary database is performed without your validation.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Impact on your key metrics
| Metric | Before | After |
|---|---|---|
| Test preparation time | Several days | A few minutes |
| Test success rate | Random | Based on predictive data |
| Performance visibility | Manual reports | Real-time dashboard |
| Iteration speed | Low | Continuous |
Take action with countly
Turn raw data into actionable product decisions and validate your hypotheses faster.