Marketing Insights
Analytics and insights from patient conversations, including satisfaction metrics, topic trends, medication discussions, and engagement patterns.
Dashboard overview
Get a comprehensive summary of key metrics across all patient interactions.
/marketing-insights/overviewStart date (YYYY-MM-DD).
End date (YYYY-MM-DD).
curl "https://api.isomera.ai/v1/marketing-insights/overview?start_date=2024-12-01&end_date=2024-12-18" \
-H "Authorization: Bearer sk_live_..."{
"total_calls": 1250,
"total_patients": 890,
"avg_satisfaction": 4.2,
"avg_call_duration": 245,
"calls_by_outcome": {
"coverage_confirmed": 650,
"pa_required": 320,
"callback_requested": 180,
"adverse_event": 45,
"other": 55
},
"calls_by_topic": {
"benefits_verification": 890,
"pa_requirements": 420,
"copay_assistance": 210,
"adverse_event": 45
},
"top_medications": [
{"name": "Keytruda", "count": 180, "jcode": "J9271"},
{"name": "Opdivo", "count": 145, "jcode": "J9299"},
{"name": "Humira", "count": 120, "jcode": "J0135"}
],
"period": {
"start": "2024-12-01",
"end": "2024-12-18"
}
}Call volume trends
Get call volume data over time, segmented by call type and outcome.
/marketing-insights/call-volumeStart date (YYYY-MM-DD).
End date (YYYY-MM-DD).
Time granularity.
Default: day
curl "https://api.isomera.ai/v1/marketing-insights/call-volume?granularity=day" \
-H "Authorization: Bearer sk_live_..."{
"data": [
{
"date": "2024-12-16",
"total": 45,
"patient_calls": 38,
"insurance_calls": 7,
"completed": 42,
"failed": 3
},
{
"date": "2024-12-17",
"total": 52,
"patient_calls": 44,
"insurance_calls": 8,
"completed": 50,
"failed": 2
}
],
"granularity": "day"
}Satisfaction analysis
Analyze patient satisfaction scores and trends.
/marketing-insights/satisfactionStart date (YYYY-MM-DD).
End date (YYYY-MM-DD).
curl https://api.isomera.ai/v1/marketing-insights/satisfaction \
-H "Authorization: Bearer sk_live_..."{
"overall_average": 4.2,
"distribution": {
"1": 12,
"2": 28,
"3": 95,
"4": 420,
"5": 695
},
"trend": [
{"date": "2024-12-16", "avg": 4.1},
{"date": "2024-12-17", "avg": 4.3},
{"date": "2024-12-18", "avg": 4.2}
],
"by_outcome": {
"coverage_confirmed": 4.5,
"pa_required": 3.8,
"callback_requested": 3.5,
"adverse_event": 3.2
}
}Medication insights
Analytics on medications discussed in patient conversations, including J-code mappings.
/marketing-insights/medicationsStart date (YYYY-MM-DD).
End date (YYYY-MM-DD).
Number of medications to return.
Default: 20
curl https://api.isomera.ai/v1/marketing-insights/medications \
-H "Authorization: Bearer sk_live_..."{
"medications": [
{
"name": "Keytruda",
"jcode": "J9271",
"mention_count": 180,
"unique_patients": 165,
"common_topics": ["pa_requirements", "cost_sharing"],
"avg_satisfaction": 4.1,
"pa_required_rate": 0.92
},
{
"name": "Opdivo",
"jcode": "J9299",
"mention_count": 145,
"unique_patients": 132,
"common_topics": ["pa_requirements", "step_therapy"],
"avg_satisfaction": 4.0,
"pa_required_rate": 0.88
}
],
"total_unique_medications": 45
}Adverse events summary
Overview of adverse events reported through patient conversations.
/marketing-insights/adverse-eventsStart date (YYYY-MM-DD).
End date (YYYY-MM-DD).
curl https://api.isomera.ai/v1/marketing-insights/adverse-events \
-H "Authorization: Bearer sk_live_..."{
"total_events": 45,
"by_severity": {
"mild": 22,
"moderate": 15,
"severe": 6,
"life-threatening": 2
},
"by_medication": [
{"medication": "Keytruda", "count": 12},
{"medication": "Opdivo", "count": 8}
],
"common_symptoms": [
{"symptom": "fatigue", "count": 18},
{"symptom": "nausea", "count": 15},
{"symptom": "rash", "count": 12}
],
"requires_immediate_action": 8,
"pending_review": 12
}Topic analysis
Breakdown of topics discussed in patient conversations.
/marketing-insights/topicscurl https://api.isomera.ai/v1/marketing-insights/topics \
-H "Authorization: Bearer sk_live_..."{
"topics": [
{
"topic": "benefits_verification",
"count": 890,
"percentage": 71.2,
"avg_satisfaction": 4.3
},
{
"topic": "pa_requirements",
"count": 420,
"percentage": 33.6,
"avg_satisfaction": 3.9
},
{
"topic": "copay_assistance",
"count": 210,
"percentage": 16.8,
"avg_satisfaction": 4.1
},
{
"topic": "adverse_event",
"count": 45,
"percentage": 3.6,
"avg_satisfaction": 3.2
}
]
}Topics are automatically detected during conversations using keyword analysis and AI classification. Multiple topics can be associated with a single call.
Payer breakdown
Analytics segmented by insurance payer.
/marketing-insights/payerscurl https://api.isomera.ai/v1/marketing-insights/payers \
-H "Authorization: Bearer sk_live_..."{
"payers": [
{
"payer_id": "aetna",
"payer_name": "Aetna",
"call_count": 320,
"patient_count": 285,
"avg_satisfaction": 4.2,
"pa_required_rate": 0.85,
"top_medications": ["Keytruda", "Humira", "Opdivo"]
},
{
"payer_id": "cigna",
"payer_name": "Cigna",
"call_count": 280,
"patient_count": 245,
"avg_satisfaction": 4.0,
"pa_required_rate": 0.78,
"top_medications": ["Opdivo", "Keytruda", "Enbrel"]
}
]
}Data export
Export insights data in CSV or JSON format for further analysis.
/marketing-insights/exportExport format.
Default: json
Type of data to export.
Start date (YYYY-MM-DD).
End date (YYYY-MM-DD).
curl "https://api.isomera.ai/v1/marketing-insights/export?format=csv&data_type=calls" \
-H "Authorization: Bearer sk_live_..." \
-o export.csv