/api/journey_markovPOST https://api.Fluxrails.app/api/v1/ai/journey_markov
X-Customer-Api-Id: <uuid>
X-Secret: <secret>
Content-Type: application/json
// Request Body Schema
{
"absorb_on": "string", // Label for the success absorbing state (e.g. "Conversion")
"sessions": [ // Array of session objects
{
"session_id": "string", // Optional, for debugging/tracing
"steps": ["string", …], // Ordered list of unique step labels
"converted": 0|1 // 1 = session succeeded; 0 = session ends in "EXIT"
}
]
}
// Example Request
{
"absorb_on": "Conversion",
"sessions": [
{ "session_id": "S-001", "steps": ["Landing","Search","PDP","Cart"], "converted": 1 },
{ "session_id": "S-002", "steps": ["Landing","Search"], "converted": 0 },
{ "session_id": "S-003", "steps": ["Landing","Promo","PDP"], "converted": 1 },
{ "session_id": "S-004", "steps": ["Landing"], "converted": 0 },
{ "session_id": "S-005", "steps": ["Landing","Search","PDP"], "converted": 0 }
// … include all your sessions …
]
}
// Example Response
{
"transitions": [
{ "from_step": "Cart", "to_step": "Conversion", "probability": 1.0 },
{ "from_step": "Landing", "to_step": "Promo", "probability": 0.24 },
{ "from_step": "Landing", "to_step": "Search", "probability": 0.65 },
{ "from_step": "PDP", "to_step": "Cart", "probability": 0.5652 },
{ "from_step": "PDP", "to_step": "Conversion", "probability": 0.2899 },
{ "from_step": "Promo", "to_step": "PDP", "probability": 0.5833 },
{ "from_step": "Search", "to_step": "PDP", "probability": 0.8462 }
],
"drop_off_probs": {
"Landing": 0.11,
"Search": 0.1538,
"Promo": 0.4167,
"PDP": 0.1449,
"Cart": 0.0,
"Conversion": 1.0
},
"interpretation": "Highest drop-off is after **Promo** (41.7%). Next steps: optimise promo-to-PDP flow and monitor average journey depth (2.97 steps)."
}
• Converts raw click-stream sessions into a Markov-chain funnel. • Returns per-step transition probabilities and drop-off rates. • Auto-appends absorbing states for success ("Conversion") and failure ("EXIT"). • Provides a natural-language summary of top bottlenecks and average path length.
• Identify which funnel steps leak the most traffic and prioritise UX fixes. • Estimate probability of reaching critical stages (e.g. PDP → Cart). • Benchmark different variants (by device, region, campaign) with one API call. • Track improvements by comparing transition/dropp-off deltas over time.
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