AI-Powered Conversion Rate Optimization Consulting
Use AI to analyze user behavior, identify conversion bottlenecks, test improvements, and optimize site performance based on data-driven insights.
Analysis Framework
// Analyze user flow
async function analyzeConversionFlow(events) {
const response = await openai.chat.completions.create({
model: 'gpt-4o-mini',
response_format: { type: 'json_object' },
messages: [{
role: 'user',
content: `Analyze these user events and identify conversion bottlenecks:\n${JSON.stringify(events)}\n\nRespond with: { bottleneck, reason, recommendation }`
}],
});
return JSON.parse(response.choices[0].message.content);
}
A/B Testing Setup
// Track variant performance
async function trackVariant(userId, variant, metric, value) {
await db.insert('ab_tests', {
user_id: userId,
variant,
metric,
value,
timestamp: new Date(),
});
}
// Analyze winner
async function analyzeResults(testId) {
const results = await db.query(`
SELECT variant, COUNT(*) as count, AVG(value) as avg_value
FROM ab_tests
WHERE test_id = $1
GROUP BY variant
`, [testId]);
const statSig = await openai.chat.completions.create({
model: 'gpt-4o',
messages: [{
role: 'user',
content: `Are these results statistically significant?\n${JSON.stringify(results)}`
}],
});
return statSig.choices[0].message.content;
}
Heatmap Analysis
// Combine heatmap + session data
async function analyzeEngagement(sessions) {
const insights = await openai.chat.completions.create({
model: 'gpt-4o-mini',
response_format: { type: 'json_object' },
messages: [{
role: 'user',
content: `User sessions (clicks, scrolls):\n${JSON.stringify(sessions)}\n\nProvide: { friction_points: [], opportunities: [] }`
}],
});
return JSON.parse(insights.choices[0].message.content);
}
Timeline
- Analytics setup + data collection — 2–3 days
- Flow analysis implementation — 2 days
- A/B testing framework — 3–4 days
- Heatmap integration — 2 days
- Ongoing optimization & reporting — 2–3 weeks cycle







