Kaltura Analytics Reports API¶

Pull analytics data out of Kaltura — content performance, viewer engagement, event attendance, and operational metrics. Multiple report surfaces exist (API v3 report service, Reports Microservice, live reports, stream health beacons) and this guide unifies them into a single reference.

Base URL: https://www.kaltura.com/api_v3 (report, liveReports, stats, beacon services)
Auth: KS passed as ks parameter in POST form data
Format: Form-encoded POST, format=1 for JSON responses

Services covered:

Service	Actions	Description
`report`	7 actions	Historical analytics — tables, totals, graphs, CSV export
Reports Microservice	2 endpoints	Async report generation for C&C, registration, enrichment
`liveReports`	`getEvents`	Real-time live stream analytics
`stats`	`collect`	Server-side statistics collection
`beacon`	`list`	Stream health diagnostics and encoder data

1. When to Use¶

Executive dashboards surfacing content performance, viewer engagement, and platform usage at a glance
Content strategists measuring play counts, watch-through rates, and drop-off points to optimize video libraries
Event organizers tracking attendance, session participation, and engagement scores for virtual events
Compliance and billing teams generating usage reports for license audits, SLA verification, or chargeback models
BI and data engineering teams exporting analytics data into external warehouses or visualization tools

2. Prerequisites¶

KS type: ADMIN KS (type=2) with the ANALYTICS_BASE permission (role permission ID 1085)
Plugins: No additional plugins required for the report service; Reports Microservice requires Bearer token auth
Session guide: Generate a KS using session.start or appToken.startSession (see Session Guide)

3. Authentication¶

All report service calls use the standard API v3 pattern with a KS. Reports Microservice calls use Bearer token auth.

# Set up environment
export KALTURA_SERVICE_URL="https://www.kaltura.com/api_v3"
export KALTURA_REPORTS_URL="https://reports.nvp1.ovp.kaltura.com"
export KALTURA_KS="your_kaltura_session"
export KALTURA_PARTNER_ID="your_partner_id"

Generate an ADMIN KS (type=2) via session.start (see Session Guide) or appToken.startSession (see AppTokens Guide).

Analytics access requires the ANALYTICS_BASE permission (ID 1085) on the KS role. See section 14 for the full permissions table.

4. Report Response Format¶

All report service responses use pipe-delimited strings (parsed by splitting on | for columns and ; for rows).

4.1 Table Response¶

report.getTable returns:

Field	Format	Description
`header`	Pipe-delimited	Column names: `"object_id\\|entry_name\\|count_plays\\|sum_time_viewed"`
`data`	Semicolon-separated rows, pipe-delimited columns	`"1_abc123\\|My Video\\|150\\|3600;1_def456\\|Other Video\\|75\\|1800"`
`totalCount`	Integer	Total rows available (for pagination)

Example response:

{
  "header": "object_id|entry_name|count_plays|sum_time_viewed",
  "data": "1_abc123|My Video|150|3600;1_def456|Other Video|75|1800",
  "totalCount": 2,
  "objectType": "KalturaReportTable"
}

4.2 Totals Response¶

report.getTotal returns the same format as a table but with a single row (no semicolon separators).

4.3 Graphs Response¶

report.getGraphs returns an array of KalturaReportGraph objects:

[
  {
    "id": "count_plays",
    "data": "2025-06-01|45;2025-06-02|62;2025-06-03|38",
    "objectType": "KalturaReportGraph"
  },
  {
    "id": "sum_time_viewed",
    "data": "2025-06-01|1200;2025-06-02|1850;2025-06-03|980",
    "objectType": "KalturaReportGraph"
  }
]

Each graph has an id (metric name) and data (semicolon-separated label|value pairs).

4.4 Parsing Pattern¶

To parse pipe-delimited report data into structured rows:

# Parse header into column names
IFS='|' read -ra COLUMNS <<< "$HEADER"

# Parse each row
IFS=';' read -ra ROWS <<< "$DATA"
for ROW in "${ROWS[@]}"; do
  IFS='|' read -ra FIELDS <<< "$ROW"
  echo "Entry: ${FIELDS[0]}, Plays: ${FIELDS[2]}"
done

5. report.getTable¶

Retrieves tabular analytics data with dimensions and metrics. Supports pagination.

curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[timeZoneOffset]=-240" \
  -d "reportInputFilter[interval]=days" \
  -d "order=-count_plays" \
  -d "pager[pageSize]=25" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|" \
  -d "responseOptions[skipEmptyDates]=false"

Required parameters:

Parameter	Description
`reportType`	KalturaReportType integer ID (see section 12)
`reportInputFilter[objectType]`	Always `KalturaEndUserReportInputFilter`
`reportInputFilter[fromDate]`	Start date as Unix timestamp in seconds
`reportInputFilter[toDate]`	End date as Unix timestamp in seconds

Optional parameters:

Parameter	Default	Description
`reportInputFilter[timeZoneOffset]`	0	Timezone offset in minutes
`reportInputFilter[interval]`	`days`	Granularity: `days`, `months`, `hours`, `tenSeconds`, `years`
`order`	varies	Sort field with direction prefix: `-count_plays`, `+date_id`
`pager[pageSize]`	25	Results per page (max 500)
`pager[pageIndex]`	1	Page number (1-based)
`responseOptions[delimiter]`	`,`	Field delimiter (use `\|` for consistency)
`responseOptions[skipEmptyDates]`	false	Omit dates with zero values

5.1 Filtering by Entry¶

curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[entryIdIn]=$ENTRY_ID" \
  -d "pager[pageSize]=25" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

5.2 Filtering by Category¶

curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[categoriesIdsIn]=$CATEGORY_ID" \
  -d "pager[pageSize]=25" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

Multiple values within a filter are pipe-separated (e.g., entryIdIn=1_abc123|1_def456).

5.3 Filtering by Virtual Event¶

curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[virtualEventIdIn]=$VIRTUAL_EVENT_ID" \
  -d "pager[pageSize]=25" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

6. report.getTotal¶

Retrieves aggregate totals for a report type as a single row.

Parameters

Parameter	Type	Required	Description
`reportType`	int	Yes	KalturaReportType integer ID (see section 12)
`reportInputFilter[objectType]`	string	Yes	Always `KalturaEndUserReportInputFilter`
`reportInputFilter[fromDate]`	int	Yes	Start date as Unix timestamp in seconds
`reportInputFilter[toDate]`	int	Yes	End date as Unix timestamp in seconds
`reportInputFilter[timeZoneOffset]`	int	No	Timezone offset in minutes. Default: `0`
`reportInputFilter[entryIdIn]`	string	No	Filter by entry IDs (pipe-separated)
`reportInputFilter[virtualEventIdIn]`	string	No	Scope to virtual event(s)
`responseOptions[objectType]`	string	No	`KalturaReportResponseOptions`
`responseOptions[delimiter]`	string	No	Field delimiter. Default: `,` (use `\\|` for consistency)

curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTotal" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

Response:

{
  "header": "count_plays|unique_known_users|sum_time_viewed|avg_time_viewed",
  "data": "1250|340|45600|36.5",
  "objectType": "KalturaReportTotal"
}

7. report.getGraphs¶

Retrieves time-series data for charting. Returns an array of KalturaReportGraph objects, one per metric.

Parameters

Parameter	Type	Required	Description
`reportType`	int	Yes	KalturaReportType integer ID (see section 12)
`reportInputFilter[objectType]`	string	Yes	Always `KalturaEndUserReportInputFilter`
`reportInputFilter[fromDate]`	int	Yes	Start date as Unix timestamp in seconds
`reportInputFilter[toDate]`	int	Yes	End date as Unix timestamp in seconds
`reportInputFilter[timeZoneOffset]`	int	No	Timezone offset in minutes. Default: `0`
`reportInputFilter[interval]`	string	No	Granularity: `days`, `months`, `hours`, `tenSeconds`, `years`. Default: `days`
`reportInputFilter[entryIdIn]`	string	No	Filter by entry IDs (pipe-separated)
`reportInputFilter[virtualEventIdIn]`	string	No	Scope to virtual event(s)
`responseOptions[objectType]`	string	No	`KalturaReportResponseOptions`
`responseOptions[delimiter]`	string	No	Field delimiter. Default: `,` (use `\\|` for consistency)

curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getGraphs" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[interval]=days" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

Use interval=hours for intraday granularity, interval=months for long-term trends, and interval=tenSeconds for live/realtime views.

8. Multi-Request Batching¶

A single analytics dashboard view typically combines getTotal + getGraphs + getTable in one HTTP call via KalturaMultiRequest. This reduces round trips from 3 to 1.

curl -X POST "$KALTURA_SERVICE_URL/service/multirequest" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "1:service=report" \
  -d "1:action=getTotal" \
  -d "1:reportType=38" \
  -d "1:reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "1:reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "1:reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "1:responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "1:responseOptions[delimiter]=|" \
  -d "2:service=report" \
  -d "2:action=getGraphs" \
  -d "2:reportType=38" \
  -d "2:reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "2:reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "2:reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "2:reportInputFilter[interval]=days" \
  -d "2:responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "2:responseOptions[delimiter]=|" \
  -d "3:service=report" \
  -d "3:action=getTable" \
  -d "3:reportType=38" \
  -d "3:reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "3:reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "3:reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "3:order=-count_plays" \
  -d "3:pager[pageSize]=25" \
  -d "3:pager[pageIndex]=1" \
  -d "3:responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "3:responseOptions[delimiter]=|"

Response is a JSON array with 3 elements: [KalturaReportTotal, [KalturaReportGraph, ...], KalturaReportTable].

9. CSV Exports¶

9.1 report.getUrlForReportAsCsv¶

Generates a downloadable CSV export URL. The URL is valid for a limited time.

Parameters

Parameter	Type	Required	Description
`reportTitle`	string	Yes	Title included in the CSV header
`reportText`	string	Yes	Description text included in the CSV header
`headers`	string	Yes	Comma-separated column headers for the CSV
`reportType`	int	Yes	KalturaReportType integer ID (see section 12)
`reportInputFilter[objectType]`	string	Yes	Always `KalturaEndUserReportInputFilter`
`reportInputFilter[fromDate]`	int	Yes	Start date as Unix timestamp in seconds
`reportInputFilter[toDate]`	int	Yes	End date as Unix timestamp in seconds
`responseOptions[objectType]`	string	No	`KalturaReportResponseOptions`
`responseOptions[delimiter]`	string	No	Field delimiter. Default: `,` (use `\\|` for consistency)

CSV_URL=$(curl -s -X POST "$KALTURA_SERVICE_URL/service/report/action/getUrlForReportAsCsv" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportTitle=Content+Performance" \
  -d "reportText=Generated+report" \
  -d "headers=Entry+ID,Entry+Name,Plays,Minutes+Viewed" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|" | tr -d '"')

# Download the CSV
curl -o report.csv "$CSV_URL"

9.2 report.getCsvFromStringParams¶

For specialized reports (IDs 4021, 6000-6002, 3006-3008) that use semicolon-delimited parameters instead of the standard filter object.

Parameters

Parameter	Type	Required	Description
`id`	int	Yes	Report ID: `4021` (User Reactions), `6000` (KME Room Data), `6001` (Attendee Data), `6002` (Breakout Sessions), `3006` (Added to Calendar), `3007` (Session Viewership), `3008` (Attachment Clicked)
`params`	string	Yes	Semicolon-delimited key=value pairs (format varies by report ID, see examples below)
`excludedFields`	string	No	Comma-separated column names to exclude from output

User Reactions Report (ID 4021)¶

Per-user engagement data for virtual events. Requires virtualeventid:<EVENT_ID> KS privilege.

curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getCsvFromStringParams" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "id=4021" \
  -d "params=from_date=$FROM;to_date=$TO;entry_ids=$ENTRY_ID;virtualeventid=$EVENT_ID"

Columns returned: email, combined_live_engaged_users_play_time_ratio, download_attachment, add_to_calendar, raise_hand, mic_on, cam_on, clap_clicked_count, heart_clicked_count, think_clicked_count, wow_clicked_count, smile_clicked_count, total_reactions_activity, answered_polls, messages_sent_group, qna_threads

KME Room Data (ID 6000), Attendee Data (ID 6001), Breakout Sessions (ID 6002)¶

# Room data
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getCsvFromStringParams" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "id=6000" \
  -d "params=from_date=$FROM;to_date=$TO"

# Attendee data (id=6001), Breakout sessions (id=6002) — same pattern

Use the excludedFields parameter to optionally exclude columns and reduce payload size.

Enriched Reports (IDs 3006, 3007, 3008)¶

Reports enriched with user metadata (first name, last name, company):

ID	Name	Key Columns
3006	Added to Calendar	`entry_id`, `user_id`, `email`, `count_add_to_calendar_clicked`, `first_name`, `last_name`, `company`
3007	Session Viewership	`user_id`, `email`, `entry_id`, `entry_name`, `media_type`, `view_time`, `play`, `first_name`, `last_name`, `company`
3008	Attachment Clicked	`user_id`, `email`, `entry_id`, `attachment_id`, `attachment_title`, `download_attachment_clicked`, `first_name`, `last_name`, `company`

curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getCsvFromStringParams" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "id=3007" \
  -d "params=from_date_id=$FROM_DATE;to_date_id=$TO_DATE;timezone_offset=-240"

Parameters are semicolon-delimited: from_date_id, to_date_id, timezone_offset.

10. Reports Microservice¶

A separate async service for generating CSV reports that require cross-service data aggregation (registration data, C&C engagement, enriched analytics).

Base URL: https://reports.{region}.ovp.kaltura.com (e.g., reports.nvp1.ovp.kaltura.com for US production)
Auth: Authorization: Bearer <KS>

10.1 Two-Step Generate/Serve Pattern¶

# Step 1: Generate — returns a sessionId
SESSION_ID=$(curl -s -X POST "$KALTURA_REPORTS_URL/api/v1/report/generate" \
  -H "Authorization: Bearer $KALTURA_KS" \
  -H "Content-Type: application/json" \
  -d '{
    "reportName": "registration",
    "reportParameters": {"appGuid": "'$APP_GUID'"}
  }' | jq -r '.sessionId')

echo "Session: $SESSION_ID"

# Step 2: Poll until ready
while true; do
  STATUS=$(curl -s -X POST "$KALTURA_REPORTS_URL/api/v1/report/serve" \
    -H "Authorization: Bearer $KALTURA_KS" \
    -H "Content-Type: application/json" \
    -d '{"sessionId": "'$SESSION_ID'", "statusOnly": true}' \
    | jq -r '.status')
  echo "Status: $STATUS"
  [ "$STATUS" = "completed" ] && break
  sleep 2
done

# Step 3: Download CSV
curl -s -X POST "$KALTURA_REPORTS_URL/api/v1/report/serve" \
  -H "Authorization: Bearer $KALTURA_KS" \
  -H "Content-Type: application/json" \
  -d '{"sessionId": "'$SESSION_ID'"}' > report.csv

10.2 Report Types¶

Report Name	Key Parameters	Description
`registration`	`appGuid`	Registration data for an event
`attachment`	`entries_ids`, `virtual_event_ids`, `from_date_id`, `to_date_id`	Attachment download activity
`reportsEnrichment`	`taskType`, `params.from_date`, `params.to_date`	Enriched analytics data

10.3 Chat & Collaboration (C&C) Reports¶

C&C reports require virtualeventid:<virtualEventId> in the KS privilege string.

Report Name	Description
`pollsActivity`	Poll participation data per question
`chatUserActivity`	Per-user chat engagement metrics
`moderatorTranscripts`	Moderator-visible chat transcripts
`chatModeration`	Moderation actions log
`groupChatTranscripts`	Group chat transcripts
`privateTranscripts`	Private chat transcripts

# Generate a C&C report
SESSION_ID=$(curl -s -X POST "$KALTURA_REPORTS_URL/api/v1/report/generate" \
  -H "Authorization: Bearer $KALTURA_KS" \
  -H "Content-Type: application/json" \
  -d '{
    "reportName": "pollsActivity",
    "reportParameters": {
      "entries_ids": ["'$ENTRY_ID'"],
      "virtual_event_ids": ["'$EVENT_ID'"],
      "from_date_id": "2025-09-15",
      "to_date_id": "2025-09-16"
    }
  }' | jq -r '.sessionId')

Date format for C&C reports: ISO 8601 with zero-padded days (e.g., 2025-09-15).

11. Live Analytics¶

Real-time analytics for active live streams.

11.1 liveReports.getEvents¶

Parameters

Parameter	Type	Required	Description
`reportType`	string	Yes	Report type string. Use `ENTRY_TIME_LINE` for per-entry live viewer timeline
`filter[objectType]`	string	Yes	Always `KalturaLiveReportInputFilter`
`filter[entryIds]`	string	Yes	Live entry ID(s) to monitor
`filter[fromTime]`	int	Yes	Start of time window as Unix timestamp in seconds
`filter[toTime]`	int	Yes	End of time window as Unix timestamp in seconds
`filter[live]`	int	No	Set to `1` to include only live (not DVR) viewers

# Calculate time window: now - 110s to now - 20s (90-second window)
FROM_UNIX=$(($(date +%s) - 110))
TO_UNIX=$(($(date +%s) - 20))

curl -X POST "$KALTURA_SERVICE_URL/service/liveReports/action/getEvents" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=ENTRY_TIME_LINE" \
  -d "filter[objectType]=KalturaLiveReportInputFilter" \
  -d "filter[entryIds]=$ENTRY_ID" \
  -d "filter[fromTime]=$FROM_UNIX" \
  -d "filter[toTime]=$TO_UNIX" \
  -d "filter[live]=1"

The 20-second offset accounts for data propagation delay. Use the 90-second window for reliable real-time viewer counts.

11.2 Stream Health via beacon.list¶

Parameters

Parameter	Type	Required	Description
`filter[objectType]`	string	Yes	Always `KalturaBeaconFilter`
`filter[eventTypeIn]`	string	Yes	Beacon types (comma-separated). Health: `0_healthData,1_healthData`. Diagnostics: `0_staticData,0_dynamicData,1_staticData,1_dynamicData`
`filter[indexTypeEqual]`	string	Yes	`log` for health alerts (time-series), `state` for diagnostics (latest snapshot)
`filter[relatedObjectTypeIn]`	string	Yes	Object type. Use `4` for entry-level beacons
`filter[objectIdIn]`	string	Yes	Entry ID(s) to monitor
`filter[orderBy]`	string	No	Sort order. Use `-updatedAt` for most recent first

Health Beacons (Alerts)¶

curl -X POST "$KALTURA_SERVICE_URL/service/beacon/action/list" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "filter[objectType]=KalturaBeaconFilter" \
  -d "filter[eventTypeIn]=0_healthData,1_healthData" \
  -d "filter[indexTypeEqual]=log" \
  -d "filter[relatedObjectTypeIn]=4" \
  -d "filter[objectIdIn]=$ENTRY_ID" \
  -d "filter[orderBy]=-updatedAt"

Diagnostics Beacons (Encoder Data)¶

curl -X POST "$KALTURA_SERVICE_URL/service/beacon/action/list" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "filter[objectType]=KalturaBeaconFilter" \
  -d "filter[eventTypeIn]=0_staticData,0_dynamicData,1_staticData,1_dynamicData" \
  -d "filter[indexTypeEqual]=state" \
  -d "filter[relatedObjectTypeIn]=4" \
  -d "filter[objectIdIn]=$ENTRY_ID"

Beacon event type prefixes: 0_ = primary stream, 1_ = backup/secondary stream.

Stream health severity levels:

Level	Name	Description
0	Debug	Verbose diagnostic data
1	Info	Normal operational events
2	Warning	Potential issues requiring attention
3	Error	Stream quality degradation
4	Critical	Stream failure or severe degradation

11.3 Recommended Polling Intervals¶

Data Type	Interval	Endpoint
Stream status	5 seconds	`entryServerNode.list`
Stream health alerts	10 seconds	`beacon.list` (log index)
Stream diagnostics	30 seconds	`beacon.list` (state index)
Live viewer analytics	30 seconds	`liveReports.getEvents`

11.4 Realtime Report Types¶

Use these report types with report.getTable / report.getGraphs for live dashboard panels:

ID	Name	Description
`10005`	USERS_OVERVIEW_REALTIME	Current concurrent viewers and engagement
`10006`	QOS_OVERVIEW_REALTIME	Quality of Experience: buffer rate, bitrate, error rate
`10001`	MAP_OVERLAY_COUNTRY_REALTIME	Live geographic distribution by country
`10002`	MAP_OVERLAY_REGION_REALTIME	Live geographic distribution by region
`10003`	MAP_OVERLAY_CITY_REALTIME	Live geographic distribution by city
`10004`	PLATFORMS_REALTIME	Live device breakdown
`10008`	ENTRY_LEVEL_USERS_DISCOVERY_REALTIME	Per-entry live viewer counts
`10011`	PLAYBACK_TYPE_REALTIME	Live vs DVR vs VOD breakdown
`10007`	DISCOVERY_REALTIME	Real-time content discovery metrics

12. Report Types Reference¶

The reportType parameter uses integer IDs (KalturaReportType enum). Pass the numeric ID in your API call (e.g., reportType=38).

12.1 VOD / Historical Reports¶

ID	Name	Description
`1`	TOP_CONTENT	Top videos by plays
`2`	CONTENT_DROPOFF	Impressions-to-play and quartile drop-off analysis
`6`	TOP_SYNDICATION	Syndication domains and referrers
`13`	USER_TOP_CONTENT	Per-user engagement tables
`21`	PLATFORMS	Device overview
`22`	OPERATING_SYSTEM	Top operating systems
`23`	BROWSERS	Top browsers
`30`	MAP_OVERLAY_CITY	Geographic distribution by city
`32`	OPERATING_SYSTEM_FAMILIES	OS family breakdown
`33`	BROWSERS_FAMILIES	Browser family breakdown
`34`	USER_ENGAGEMENT_TIMELINE	Per-user engagement highlights and heatmaps
`35`	UNIQUE_USERS_PLAY	Unique viewer counts
`36`	MAP_OVERLAY_COUNTRY	Geographic distribution by country
`37`	MAP_OVERLAY_REGION	Geographic distribution by region
`38`	TOP_CONTENT_CREATOR	Top content by creator, category top content
`39`	TOP_CONTENT_CONTRIBUTORS	Top content contributors
`41`	TOP_SOURCES	Upload sources
`45`	PLAYER_RELATED_INTERACTIONS	Content interactions (shares, downloads)
`46`	PLAYBACK_RATE	Playback speed statistics
`52`	CATEGORY_HIGHLIGHTS	Category summary metrics
`60`	SELF_SERVE_USAGE	Self-serve usage overview
`201`	PARTNER_USAGE	Partner usage and bandwidth

12.2 Webcast / Events Platform Reports¶

ID	Name	Description
`40001`	HIGHLIGHTS_WEBCAST	Webcast highlights summary
`40004`	MAP_OVERLAY_COUNTRY_WEBCAST	Geographic distribution for webcasts
`40007`	PLATFORMS_WEBCAST	Devices for webcasts
`40008`	TOP_DOMAINS_WEBCAST	Domains for webcasts
`40009`	TOP_USERS_WEBCAST	Top webcast viewers
`40011`	ENGAGMENT_TIMELINE_WEBCAST	Webcast engagement timeline
`60001`	EP_WEBCAST_HIGHLIGHTS	Events Platform webcast highlights
`60010`	EP_WEBCAST_LIVE_USER_ENGAGEMENT	Combined VOD + live engagement

Virtual event report IDs:

Report ID	Description
3006	Add to Calendar (calendar engagement)
3009	Session Attendance (per-session attendee tracking)
3010	Certificate of Completion (attendance-based certificates)

12.3 Multi-Account Variants¶

Every VOD report has a multi-account counterpart with IDs in the 20000 range (e.g., 20001 = multi-account Content Dropoff, 20005 = multi-account Platforms, 20011 = multi-account Unique Users Play). Parent accounts use these variants to aggregate analytics across child accounts.

For detailed multi-account analytics workflows (cross-account aggregation, per-account drill-down, session.impersonate, full report type enumeration), see the Multi-Account Management Guide.

13. Filter Fields Reference¶

The KalturaEndUserReportInputFilter supports these filter fields. Multiple values within a filter are pipe-separated.

Filter	Type	Description
`fromDate`	int	Start date as Unix timestamp (seconds)
`toDate`	int	End date as Unix timestamp (seconds)
`timeZoneOffset`	int	Timezone offset in minutes
`interval`	enum	`days`, `months`, `hours`, `tenSeconds` (live), `years`
`entryIdIn`	string	Filter by entry IDs (pipe-separated)
`categoriesIdsIn`	string	Filter by category IDs (pipe-separated)
`mediaTypeIn`	string	Filter by media types (pipe-separated)
`countryIn`	string	Filter by country codes (pipe-separated)
`regionIn`	string	Geographic region drill-down
`citiesIn`	string	Geographic city drill-down
`playbackTypeIn`	string	`live`, `dvr`, `vod`
`deviceIn`	string	Filter by device types
`browserFamilyIn`	string	Filter by browser family
`operatingSystemFamilyIn`	string	Filter by OS family
`ownerIdsIn`	string	Filter by content creator IDs
`userIds`	string	Filter by viewer user IDs
`domainIn`	string	Filter by syndication domains
`canonicalUrlIn`	string	Filter by canonical URLs
`virtualEventIdIn`	string	Scope to virtual event(s)
`searchInTags`	string	Filter by entry tags
`searchInAdminTags`	string	Filter by admin tags
`playbackContextIdsIn`	string	Filter by category context

14. Error Handling & Permissions¶

14.1 Analytics Permissions¶

Permission	ID	Description
`ANALYTICS_BASE`	1085	Gate for all analytics views
`FEATURE_NEW_ANALYTICS_TAB`	1125	New analytics dashboard
`FEATURE_LIVE_ANALYTICS_DASHBOARD`	1128	Live analytics dashboard access
`FEATURE_MULTI_ACCOUNT_ANALYTICS`	1130	Multi-account (cross-account) analytics
`FEATURE_LIVE_STREAM`	1104	Required alongside ANALYTICS_BASE for live
`FEATURE_END_USER_REPORTS`	1096	End-user level reporting

14.2 Common Errors¶

Error Code	Cause	Resolution
`INVALID_KS`	Expired or malformed session	Generate a new KS
`SERVICE_FORBIDDEN`	KS role lacks `ANALYTICS_BASE`	Assign analytics permissions to the role
`REPORT_NOT_FOUND`	Invalid `reportType` value	Use a valid integer ID from section 12
`INVALID_PARAMS`	Missing required filter fields	Include `fromDate` and `toDate` at minimum

14.3 Reports Microservice Errors¶

The Reports Microservice returns HTTP status codes. A report/serve call with statusOnly: true returns {"status": "pending"}, {"status": "in_progress"}, or {"status": "completed"}. If generation fails, the status response includes an error message.

15. Common Integration Patterns¶

15.1 Event ROI Dashboard¶

After a virtual conference, pull aggregate attendance, per-session breakdown, and engagement trends in a single multi-request call, then export per-attendee data for BI tools.

# Set date range for the event
FROM_TIMESTAMP=$(date -d "2025-06-01" +%s 2>/dev/null || date -j -f "%Y-%m-%d" "2025-06-01" +%s)
TO_TIMESTAMP=$(date -d "2025-06-03" +%s 2>/dev/null || date -j -f "%Y-%m-%d" "2025-06-03" +%s)

# Step 1: Multi-request for dashboard data (totals + graphs + table)
curl -X POST "$KALTURA_SERVICE_URL/service/multirequest" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "1:service=report" \
  -d "1:action=getTotal" \
  -d "1:reportType=38" \
  -d "1:reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "1:reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "1:reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "1:reportInputFilter[virtualEventIdIn]=$VIRTUAL_EVENT_ID" \
  -d "1:responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "1:responseOptions[delimiter]=|" \
  -d "2:service=report" \
  -d "2:action=getGraphs" \
  -d "2:reportType=38" \
  -d "2:reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "2:reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "2:reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "2:reportInputFilter[virtualEventIdIn]=$VIRTUAL_EVENT_ID" \
  -d "2:reportInputFilter[interval]=days" \
  -d "2:responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "2:responseOptions[delimiter]=|" \
  -d "3:service=report" \
  -d "3:action=getTable" \
  -d "3:reportType=38" \
  -d "3:reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "3:reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "3:reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "3:reportInputFilter[virtualEventIdIn]=$VIRTUAL_EVENT_ID" \
  -d "3:order=-count_plays" \
  -d "3:pager[pageSize]=25" \
  -d "3:pager[pageIndex]=1" \
  -d "3:responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "3:responseOptions[delimiter]=|"

# Step 2: Per-attendee engagement (User Reactions Report)
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getCsvFromStringParams" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "id=4021" \
  -d "params=from_date=$FROM_TIMESTAMP;to_date=$TO_TIMESTAMP;virtualeventid=$VIRTUAL_EVENT_ID"

# Step 3: Export full dataset for BI tools
CSV_URL=$(curl -s -X POST "$KALTURA_SERVICE_URL/service/report/action/getUrlForReportAsCsv" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportTitle=Event+ROI" \
  -d "reportText=Conference+Performance" \
  -d "headers=Entry,Name,Plays,Minutes" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[virtualEventIdIn]=$VIRTUAL_EVENT_ID" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|" | tr -d '"')
curl -o event_roi.csv "$CSV_URL"

15.2 Content Performance Optimization¶

Identify top-performing content and drop-off points to improve engagement.

# Top content by plays
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "order=-count_plays" \
  -d "pager[pageSize]=50" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

# Drop-off analysis — shows impression-to-play and quartile play-through rates
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=2" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[entryIdIn]=$ENTRY_ID" \
  -d "pager[pageSize]=25" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

# Per-user engagement heatmap (4-tier: not viewed / once / twice / 3+ times)
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=34" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[entryIdIn]=$ENTRY_ID" \
  -d "pager[pageSize]=25" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

15.3 Live Stream Operations Dashboard¶

During a live event, poll multiple endpoints at recommended intervals to monitor stream health, viewer counts, and quality metrics.

# Stream health alerts — poll every 10 seconds
curl -X POST "$KALTURA_SERVICE_URL/service/beacon/action/list" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "filter[objectType]=KalturaBeaconFilter" \
  -d "filter[eventTypeIn]=0_healthData,1_healthData" \
  -d "filter[indexTypeEqual]=log" \
  -d "filter[relatedObjectTypeIn]=4" \
  -d "filter[objectIdIn]=$ENTRY_ID" \
  -d "filter[orderBy]=-updatedAt"

# Live viewer count — poll every 30 seconds
FROM_UNIX=$(($(date +%s) - 110))
TO_UNIX=$(($(date +%s) - 20))
curl -X POST "$KALTURA_SERVICE_URL/service/liveReports/action/getEvents" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=ENTRY_TIME_LINE" \
  -d "filter[objectType]=KalturaLiveReportInputFilter" \
  -d "filter[entryIds]=$ENTRY_ID" \
  -d "filter[fromTime]=$FROM_UNIX" \
  -d "filter[toTime]=$TO_UNIX" \
  -d "filter[live]=1"

# Quality of Experience — concurrent with viewer poll
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=10006" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_UNIX" \
  -d "reportInputFilter[toDate]=$TO_UNIX" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

If health beacon severity >= 3 (error/critical), alert the production team for backup stream activation.

15.4 Compliance Training Verification¶

Pull per-user engagement and completion data to generate audit-ready compliance records.

# Per-user engagement by category (training library)
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=13" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[categoriesIdsIn]=$TRAINING_CATEGORY_ID" \
  -d "reportInputFilter[userIds]=$USER_ID" \
  -d "pager[pageSize]=100" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

# Verify completion via drop-off report (confirm 100% quartile)
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=2" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[entryIdIn]=$ENTRY_ID" \
  -d "pager[pageSize]=25" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

# Enriched report with employee name, email, company
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getCsvFromStringParams" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "id=3007" \
  -d "params=from_date_id=$FROM_DATE;to_date_id=$TO_DATE;timezone_offset=-240"

15.5 Per-User Event Engagement Report¶

Pull granular per-attendee engagement data for follow-up campaigns.

# Step 1: User Reactions Report (per-user polls, reactions, Q&A)
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getCsvFromStringParams" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "id=4021" \
  -d "params=from_date=$FROM;to_date=$TO;entry_ids=$ENTRY_ID;virtualeventid=$EVENT_ID"

# Step 2: C&C reports via Reports Microservice
SESSION_ID=$(curl -s -X POST "$KALTURA_REPORTS_URL/api/v1/report/generate" \
  -H "Authorization: Bearer $KALTURA_KS" \
  -H "Content-Type: application/json" \
  -d '{
    "reportName": "pollsActivity",
    "reportParameters": {
      "entries_ids": ["'$ENTRY_ID'"],
      "virtual_event_ids": ["'$EVENT_ID'"],
      "from_date_id": "'$FROM_DATE'",
      "to_date_id": "'$TO_DATE'"
    }
  }' | jq -r '.sessionId')

# Poll and download
while true; do
  STATUS=$(curl -s -X POST "$KALTURA_REPORTS_URL/api/v1/report/serve" \
    -H "Authorization: Bearer $KALTURA_KS" \
    -H "Content-Type: application/json" \
    -d '{"sessionId": "'$SESSION_ID'", "statusOnly": true}' | jq -r '.status')
  [ "$STATUS" = "completed" ] && break
  sleep 2
done
curl -s -X POST "$KALTURA_REPORTS_URL/api/v1/report/serve" \
  -H "Authorization: Bearer $KALTURA_KS" \
  -H "Content-Type: application/json" \
  -d '{"sessionId": "'$SESSION_ID'"}' > polls_report.csv

# Step 3: Enriched session viewership with user metadata
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getCsvFromStringParams" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "id=3007" \
  -d "params=from_date_id=$FROM_DATE;to_date_id=$TO_DATE;timezone_offset=-240"

15.6 Multi-Account Analytics¶

Parent accounts use multi-account report variants to aggregate analytics across child accounts.

# Per-account usage
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=60" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "pager[pageSize]=100" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

# Bandwidth and storage totals
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTotal" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=201" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

15.7 BI Pipeline / Data Warehouse Integration¶

Pull analytics data on a schedule, transform pipe-delimited responses, and load into a data warehouse.

# Pull multiple report types with rolling date window
YESTERDAY=$(($(date +%s) - 86400))
TODAY=$(date +%s)

# Engagement data
curl -s -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$YESTERDAY" \
  -d "reportInputFilter[toDate]=$TODAY" \
  -d "pager[pageSize]=500" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

# Geographic data
curl -s -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=36" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$YESTERDAY" \
  -d "reportInputFilter[toDate]=$TODAY" \
  -d "pager[pageSize]=500" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

# Bulk CSV export for warehouse ingestion
CSV_URL=$(curl -s -X POST "$KALTURA_SERVICE_URL/service/report/action/getUrlForReportAsCsv" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportTitle=Daily+ETL" \
  -d "reportText=Automated+export" \
  -d "headers=Entry,Name,Plays,Minutes,Unique+Viewers" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$YESTERDAY" \
  -d "reportInputFilter[toDate]=$TODAY" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|" | tr -d '"')
curl -o daily_export.csv "$CSV_URL"

15.8 Geographic Analytics¶

Drill down from country to region to city for geographic distribution analysis.

# Country level
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=36" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "pager[pageSize]=50" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

# Drill down to region within a country
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=37" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[countryIn]=US" \
  -d "pager[pageSize]=50" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

15.9 Device and Technology Analytics¶

Analyze viewer device, browser, and OS distributions.

# Device overview
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=21" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "pager[pageSize]=25" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

# Top browsers
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=33" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "pager[pageSize]=25" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

15.10 Accessibility Coverage Reporting¶

Universities and government agencies subject to WCAG 2.1 AA requirements need to audit their entire video library for caption coverage, prioritize uncaptioned content by viewership, and auto-queue captioning jobs. This workflow combines eSearch for discovery, captionAsset.list for per-entry detail, report-based prioritization, and REACH task submission.

# Step 1: Find entries that already have captions using eSearch
#   captionAssetItems with an exists condition returns only entries with at least one caption track
curl -X POST "$KALTURA_SERVICE_URL/service/elasticsearch_esearch/action/searchEntry" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "searchParams[objectType]=KalturaESearchEntryParams" \
  -d "searchParams[searchOperator][objectType]=KalturaESearchEntryOperator" \
  -d "searchParams[searchOperator][operator]=1" \
  -d "searchParams[searchOperator][searchItems][0][objectType]=KalturaESearchCaptionItem" \
  -d "searchParams[searchOperator][searchItems][0][fieldName]=content" \
  -d "searchParams[searchOperator][searchItems][0][itemType]=3" \
  -d "pager[pageSize]=500" \
  -d "pager[pageIndex]=1"

# Step 2: List caption languages for a specific entry
curl -X POST "$KALTURA_SERVICE_URL/service/caption_captionAsset/action/list" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "filter[objectType]=KalturaAssetFilter" \
  -d "filter[entryIdEqual]=$ENTRY_ID"

# Step 3: Rank uncaptioned content by play count for prioritization
#   Use topContentCreator (reportType=38) filtered to the list of uncaptioned entry IDs
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[entryIdIn]=$UNCAPTIONED_ENTRY_IDS" \
  -d "order=-count_plays" \
  -d "pager[pageSize]=100" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

After ranking, submit the highest-traffic entries to REACH for automatic captioning (see REACH Guide section on entryVendorTask.add). Track caption completion through webhooks on ENTRY_VENDOR_TASK_STATUS_CHANGED events (see Webhooks Guide), then re-run the eSearch query to update the coverage dashboard.

See also: eSearch Guide for advanced search operators, Captions & Transcripts Guide for caption management.

15.11 Lecture Capture & LMS Analytics¶

Universities track per-student engagement to identify struggling students before they fall behind. This workflow pulls individual student viewing data scoped to a course category, analyzes drop-off patterns for specific lectures, and exports enriched reports with student name and email for LMS gradebook sync.

# Step 1: Per-student engagement for a course category
#   userTopContent (reportType=13) filtered by course category and specific students
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=13" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[categoriesIdsIn]=$COURSE_CATEGORY_ID" \
  -d "reportInputFilter[userIds]=$STUDENT_USER_IDS" \
  -d "order=-sum_time_viewed" \
  -d "pager[pageSize]=200" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

# Step 2: Drop-off analysis for a specific lecture
#   contentDropoff (reportType=2) shows impression-to-play ratio and quartile play-through
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=2" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[entryIdIn]=$LECTURE_ENTRY_ID" \
  -d "pager[pageSize]=25" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

# Step 3: Enriched per-student report with name, email, company for LMS export
#   Report ID 3007 returns CSV with user metadata joined to engagement data
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getCsvFromStringParams" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "id=3007" \
  -d "params=from_date_id=$FROM_DATE;to_date_id=$TO_DATE;cat_ids=$COURSE_CATEGORY_ID;timezone_offset=-240"

Students with low quartile completion on key lectures are candidates for early intervention. Parse the count_plays_25 through count_plays_100 columns from the drop-off report to identify where students disengage.

See also: Player Embed Guide for embedded player analytics events, Categories & Access Control Guide for course category setup.

15.12 Investor Relations Webcast Analytics¶

Public companies hosting earnings webcasts need segment-level engagement heatmaps for the IR team, geographic distribution for SEC Regulation FD compliance documentation, per-user engagement for investor follow-up, and bulk CSV exports for the board package.

# Step 1: Segment-level engagement heatmap
#   userEngagementTimeline (reportType=34) returns time-based engagement data
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=34" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[entryIdIn]=$WEBCAST_ENTRY_ID" \
  -d "pager[pageSize]=100" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

# Step 2: Geographic distribution for Regulation FD compliance
#   mapOverlayCountry (reportType=36) provides country-level viewer breakdown
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=36" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[entryIdIn]=$WEBCAST_ENTRY_ID" \
  -d "pager[pageSize]=50" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

# Step 3: Per-user engagement for investor follow-up
#   Report ID 4021 (User Reactions Report) provides per-attendee interaction data
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getCsvFromStringParams" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "id=4021" \
  -d "params=from_date=$FROM_TIMESTAMP;to_date=$TO_TIMESTAMP;entry_ids=$WEBCAST_ENTRY_ID"

# Step 4: Bulk CSV export for the board package
CSV_URL=$(curl -s -X POST "$KALTURA_SERVICE_URL/service/report/action/getUrlForReportAsCsv" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportTitle=Earnings+Webcast+Analytics" \
  -d "reportText=Q2+2025+Earnings+Call" \
  -d "headers=Entry,Name,Plays,Minutes,Unique+Viewers,Avg+Completion" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$FROM_TIMESTAMP" \
  -d "reportInputFilter[toDate]=$TO_TIMESTAMP" \
  -d "reportInputFilter[entryIdIn]=$WEBCAST_ENTRY_ID" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|" | tr -d '"')
curl -o earnings_webcast_report.csv "$CSV_URL"

The geographic report demonstrates that the webcast was accessible globally, which supports Regulation FD fair-disclosure documentation. The segment heatmap reveals which portions of the earnings call drew peak engagement (e.g., Q&A segment vs. prepared remarks).

See also: Events Platform Guide for webcast setup, User Profile Guide for attendee registration data.

15.13 Thumbnail A/B Testing¶

Content teams optimize click-through rates by testing different thumbnail images. This workflow creates thumbnail variants from video frames, rotates the active thumbnail between test periods, and uses drop-off analytics to measure the impression-to-play conversion rate for each variant.

# Step 1: Create a thumbnail variant from a specific video frame
#   addFromEntry captures a frame at the specified offset (in seconds)
curl -X POST "$KALTURA_SERVICE_URL/service/thumbAsset/action/addFromEntry" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "entryId=$ENTRY_ID" \
  -d "thumbAsset[objectType]=KalturaThumbAsset" \
  -d "thumbAsset[tags]=ab_test_variant_b" \
  -d "thumbOffset=45"

# Step 2: Switch the active thumbnail to the new variant
#   setAsDefault makes this thumbnail the one shown in listings and embed previews
curl -X POST "$KALTURA_SERVICE_URL/service/thumbAsset/action/setAsDefault" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "thumbAssetId=$THUMB_ASSET_ID"

# Step 3: Compare impression-to-play ratio across date ranges
#   contentDropoff (reportType=2) includes count_loads (impressions) and count_plays
#   Run this for each variant's date range and compare the plays/impressions ratio
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=2" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$VARIANT_B_START" \
  -d "reportInputFilter[toDate]=$VARIANT_B_END" \
  -d "reportInputFilter[entryIdIn]=$ENTRY_ID" \
  -d "pager[pageSize]=25" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

Run the same reportType=2 query with Variant A's date range, then compare the count_plays / count_loads ratio. A higher ratio indicates the thumbnail is more effective at converting impressions to plays. For statistically significant results, run each variant for at least 7 days with comparable traffic.

See also: Upload & Delivery Guide for thumbnail management.

15.14 Webhook-Triggered Automated Reporting¶

Automate weekly analytics reports, real-time engagement alerts, and compliance report generation by combining webhooks with the report service. Webhooks fire on content events, trigger report generation, and route results through the messaging system.

# Step 1: Create an HTTP webhook template that fires on entry status changes
#   This webhook can trigger a report-generation endpoint when content goes live
curl -X POST "$KALTURA_SERVICE_URL/service/eventNotificationTemplate/action/add" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "eventNotificationTemplate[objectType]=KalturaHttpNotificationTemplate" \
  -d "eventNotificationTemplate[name]=Analytics+Report+Trigger" \
  -d "eventNotificationTemplate[description]=Triggers+report+generation+on+entry+changes" \
  -d "eventNotificationTemplate[type]=httpNotification.Http" \
  -d "eventNotificationTemplate[eventType]=3" \
  -d "eventNotificationTemplate[eventObjectType]=1" \
  -d "eventNotificationTemplate[url]=$REPORT_WEBHOOK_ENDPOINT" \
  -d "eventNotificationTemplate[method]=2" \
  -d "eventNotificationTemplate[contentType][objectType]=KalturaHttpNotificationObjectData"

# Step 2: Verify the webhook template is registered
curl -X POST "$KALTURA_SERVICE_URL/service/eventNotificationTemplate/action/list" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "filter[objectType]=KalturaEventNotificationTemplateFilter" \
  -d "filter[typeEqual]=httpNotification.Http" \
  -d "pager[pageSize]=25" \
  -d "pager[pageIndex]=1"

# Step 3: Scheduled CSV export (run weekly via cron or webhook timer)
#   Generate a full weekly report and download the CSV
CSV_URL=$(curl -s -X POST "$KALTURA_SERVICE_URL/service/report/action/getUrlForReportAsCsv" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportTitle=Weekly+Content+Report" \
  -d "reportText=Automated+weekly+analytics" \
  -d "headers=Entry,Name,Plays,Minutes,Unique+Viewers" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$WEEK_START" \
  -d "reportInputFilter[toDate]=$WEEK_END" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|" | tr -d '"')
curl -o weekly_report.csv "$CSV_URL"

For real-time alerting: when the webhook endpoint receives an event, call report.getTable with reportType=35 (uniqueUsersPlay) to check concurrent viewer count. If the count drops below a threshold, send an alert via the Messaging service (see Messaging Guide). For enriched compliance reports, use report.getCsvFromStringParams with IDs 3006-3008 to include user metadata.

See also: Webhooks Guide for event notification template configuration, Messaging Guide for alert delivery.

15.15 Cross-Guide Workflow: Full Event Lifecycle¶

This master workflow demonstrates how the Analytics Reports, Events Collection, and Gamification guides work together with other guides to orchestrate a complete virtual event from planning through post-event follow-up.

Pre-Event Setup¶

Create the virtual event with sessions, rooms, and schedule Events Platform
Configure gamification rules for the event — point values for watching, polling, Q&A, and networking Gamification
Set up analytics dashboards by creating report filters scoped to the event's virtualEventId [Analytics Reports]
Register attendees and assign them to user groups for segmented reporting User Profile
Send invitations with personalized join links via the messaging system Messaging
Configure webhooks to fire on session start/end for automated metric collection Webhooks

During the Event¶

Player fires playback events automatically — play, pause, seek, quartile milestones, buffer events — all collected by the analytics pipeline with zero application code Events Collection
Custom portal events are reported via analytics.trackEvent — page views, CTA clicks, resource downloads, booth visits Events Collection
Gamification rules engine scores in real-time — each playback and custom event feeds the scoring engine, updating leaderboards and triggering badge awards Gamification
Production monitors stream health via beacon.list for encoder data and liveReports.getEvents for concurrent viewer counts [Analytics Reports]
Flash challenges are launched via scheduledGameObject — time-limited bonus point opportunities that drive engagement spikes Gamification
Real-time leaderboard displays on the event portal, pulling from the gamification leaderboard API Gamification

# During-event: Monitor live stream health (poll every 10 seconds)
curl -X POST "$KALTURA_SERVICE_URL/service/beacon/action/list" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "filter[objectType]=KalturaBeaconFilter" \
  -d "filter[eventTypeIn]=0_healthData,1_healthData" \
  -d "filter[indexTypeEqual]=log" \
  -d "filter[relatedObjectTypeIn]=4" \
  -d "filter[objectIdIn]=$LIVE_ENTRY_ID" \
  -d "filter[orderBy]=-updatedAt"

# During-event: Get concurrent viewer count (poll every 30 seconds)
FROM_UNIX=$(($(date +%s) - 110))
TO_UNIX=$(($(date +%s) - 20))
curl -X POST "$KALTURA_SERVICE_URL/service/liveReports/action/getEvents" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=ENTRY_TIME_LINE" \
  -d "filter[objectType]=KalturaLiveReportInputFilter" \
  -d "filter[entryIds]=$LIVE_ENTRY_ID" \
  -d "filter[fromTime]=$FROM_UNIX" \
  -d "filter[toTime]=$TO_UNIX" \
  -d "filter[live]=1"

Post-Event Follow-Up¶

Generate lead scoring report from the gamification engine — classify attendees as Hot/Warm/Cold based on total engagement score Gamification
Pull per-user engagement via report ID 4021 (User Reactions Report) with per-attendee poll answers, reactions, and Q&A participation [Analytics Reports]
Generate C&C reports via the Reports Microservice for polls activity, registration data, and session attendance [Analytics Reports]
Export badge and certificate reports listing which attendees earned which awards Gamification
Bulk CSV export via report.getUrlForReportAsCsv for import into BI tools and CRM [Analytics Reports]
Send follow-up emails segmented by engagement tier — personalized content recommendations for high-engagement attendees, re-engagement prompts for low-engagement Messaging
On-demand replay continues feeding both analytics and gamification — viewers who watch the replay earn points and their engagement data flows into the same reporting pipeline Events Collection, Gamification

# Post-event: Per-attendee engagement report
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getCsvFromStringParams" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "id=4021" \
  -d "params=from_date=$EVENT_START;to_date=$EVENT_END;virtualeventid=$VIRTUAL_EVENT_ID"

15.16 Cross-Guide Workflow: Analytics-Driven Content Automation Pipeline¶

This pipeline automates the full content lifecycle from upload through performance monitoring, using webhooks to chain together processing, enrichment, and analytics-driven optimization.

Upload content via chunked upload or addFromUrl Upload & Delivery
Webhook fires on ENTRY_READY when transcoding completes, triggering the enrichment pipeline Webhooks
Auto-process via REACH and AI Agents — the webhook handler submits the entry for captioning, translation, and AI-generated metadata REACH, Agents Manager
Webhook fires on task completion when captions and metadata are ready, confirming enrichment is complete Webhooks
Player fires playback events as viewers watch the content — play, quartile, seek, and buffer events flow automatically into analytics Events Collection
Analytics accumulate over the monitoring window — plays, watch time, engagement rate, drop-off patterns build up in the reporting pipeline [Analytics Reports]
Scheduled report check runs report.getTable to evaluate content performance against thresholds — if engagement rate falls below target, send an alert via Messaging [Analytics Reports], Messaging
Compare enriched vs. non-enriched metrics — pull reports for entries with and without captions/AI-metadata to quantify the ROI of automated enrichment [Analytics Reports]

# Step 7: Scheduled performance check — flag underperforming content
#   topContentCreator (reportType=38) ordered by plays, filtered to recent uploads
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$MONITORING_START" \
  -d "reportInputFilter[toDate]=$MONITORING_END" \
  -d "reportInputFilter[entryIdIn]=$RECENT_ENTRY_IDS" \
  -d "order=-count_plays" \
  -d "pager[pageSize]=100" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

# Step 8: Compare engagement for captioned vs. uncaptioned entries
#   Run the same report for each group and compare avg_view_drop_off and sum_time_viewed
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getTable" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportType=2" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$MONITORING_START" \
  -d "reportInputFilter[toDate]=$MONITORING_END" \
  -d "reportInputFilter[entryIdIn]=$CAPTIONED_ENTRY_IDS" \
  -d "pager[pageSize]=100" \
  -d "pager[pageIndex]=1" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|"

15.17 Cross-Guide Workflow: CRM Integration Pipeline¶

This pipeline connects event engagement data to CRM systems for sales follow-up, combining user registration, gamification-based lead scoring, playback analytics, and automated data export.

Register attendees via the User Profile API and capture registration metadata (company, title, interest areas) User Profile
Configure gamification rules that assign point values to high-intent actions — watching product demos earns more than watching keynotes, booth visits earn more than passive viewing Gamification
Playback events collected automatically as attendees watch sessions — the player reports play, quartile completion, and seek events to the analytics pipeline Events Collection
Custom engagement events tracked via analytics.trackEvent — CTA clicks, resource downloads, meeting requests, and demo sign-ups Events Collection
Lead scoring report classifies attendees into Hot/Warm/Cold tiers based on cumulative gamification score — Hot leads (top 10%) are flagged for immediate sales outreach Gamification
User Reactions Report (ID 4021) provides per-attendee interaction detail — poll responses, Q&A questions, reactions — enriching the CRM contact record [Analytics Reports]
Push to CRM via CSV export or webhook — getUrlForReportAsCsv generates a downloadable file for batch import, or a webhook endpoint receives real-time score updates [Analytics Reports], Webhooks
Ongoing sync — replay viewers continue accumulating engagement, and scheduled report runs update CRM records weekly [Analytics Reports]

# Step 6: Per-attendee interaction detail for CRM enrichment
#   User Reactions Report (ID 4021) provides poll answers, reactions, Q&A data
curl -X POST "$KALTURA_SERVICE_URL/service/report/action/getCsvFromStringParams" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "id=4021" \
  -d "params=from_date=$EVENT_START;to_date=$EVENT_END;virtualeventid=$VIRTUAL_EVENT_ID"

# Step 7: Bulk export for CRM import
#   Generate a CSV with engagement data for all event attendees
CSV_URL=$(curl -s -X POST "$KALTURA_SERVICE_URL/service/report/action/getUrlForReportAsCsv" \
  -d "ks=$KALTURA_KS" \
  -d "format=1" \
  -d "reportTitle=CRM+Lead+Export" \
  -d "reportText=Event+Engagement+for+CRM" \
  -d "headers=User,Name,Email,Plays,Minutes,Unique+Sessions,Engagement+Score" \
  -d "reportType=38" \
  -d "reportInputFilter[objectType]=KalturaEndUserReportInputFilter" \
  -d "reportInputFilter[fromDate]=$EVENT_START" \
  -d "reportInputFilter[toDate]=$EVENT_END" \
  -d "reportInputFilter[virtualEventIdIn]=$VIRTUAL_EVENT_ID" \
  -d "responseOptions[objectType]=KalturaReportResponseOptions" \
  -d "responseOptions[delimiter]=|" | tr -d '"')
curl -o crm_lead_export.csv "$CSV_URL"

16. Best Practices¶

Date handling. All API v3 report filter dates use Unix timestamps in seconds (not milliseconds). For example, Math.floor(Date.now() / 1000) in JavaScript or int(time.time()) in Python.

Pipe-delimited parsing. Always set responseOptions[delimiter]=| for consistency. Parse the header field to map column positions dynamically rather than hardcoding column indices — columns may vary by report type and account configuration.

Multi-request for dashboards. Batch getTotal + getGraphs + getTable in a single KalturaMultiRequest to reduce round trips. This is the standard pattern for building analytics dashboard views.

CSV vs API tradeoffs. Use report.getTable for real-time dashboard queries with pagination. Use report.getUrlForReportAsCsv for bulk exports, scheduled ETL jobs, and BI tool ingestion. Use report.getCsvFromStringParams for specialized reports (IDs 4021, 6000-6002, 3006-3008) that are not available via the standard filter interface.

Polling intervals for live. Follow the recommended intervals in section 11.3. Polling faster than recommended wastes resources without improving data freshness. Polling slower may miss transient issues.

Reports Microservice polling. Always use statusOnly: true for the polling loop to avoid downloading the full CSV on every check. Only omit statusOnly for the final download request after status shows completed.

Cross-service analytics. Use appId:<name> in KS privileges to tag analytics per-application. Use virtualEventIdIn to scope reports to specific events. Use categoriesIdsIn to scope by content library. See the Session Guide for KS privilege syntax.

Session Guide — appId:<name> KS privilege tags analytics per-application; userId ties analytics to a user
AppTokens — Scoped tokens for analytics-only access
Player Embed — Player v7 fires ~45 playback events that feed analytics automatically
Events Collection — Report custom playback and application events back to analytics
Events Platform — virtualEventIdIn filter scopes reports to a specific event
User Profile — reports/eventDataStats for attendance stats; registration reports via Reports Microservice
Messaging — message/stats for delivery statistics
REACH — entryVendorTask.list for task monitoring; exportToCsv for batch CSV
Upload & Delivery — baseEntry.exportToCsv for bulk content export; thumbnail generation for report dashboards
User Management — ANALYTICS_BASE role permission gates analytics access
Webhooks — Trigger automated reporting on content events
eSearch — Enrich analytics data with entry metadata, tags, categories
Captions & Transcripts — Caption coverage auditing (eSearch + captionAsset.list for accessibility dashboards)
Categories & Access Control — categoriesIdsIn filter for content library scoping
Gamification — Analytics events feed the gamification rules engine
Multi-Account Management — Cross-account analytics with multi-account report types (20001+)
Distribution — Distribution status tracking via analytics reports
Embeddable Analytics — Analytics dashboards via iframe + postMessage

Kaltura Analytics Reports API¶

1. When to Use¶

2. Prerequisites¶

3. Authentication¶

4. Report Response Format¶

4.1 Table Response¶

4.2 Totals Response¶

4.3 Graphs Response¶

4.4 Parsing Pattern¶

5. report.getTable¶

5.1 Filtering by Entry¶

5.2 Filtering by Category¶

5.3 Filtering by Virtual Event¶

6. report.getTotal¶

7. report.getGraphs¶

8. Multi-Request Batching¶

9. CSV Exports¶

9.1 report.getUrlForReportAsCsv¶

9.2 report.getCsvFromStringParams¶

User Reactions Report (ID 4021)¶

KME Room Data (ID 6000), Attendee Data (ID 6001), Breakout Sessions (ID 6002)¶

Enriched Reports (IDs 3006, 3007, 3008)¶

10. Reports Microservice¶

10.1 Two-Step Generate/Serve Pattern¶

10.2 Report Types¶

10.3 Chat & Collaboration (C&C) Reports¶

11. Live Analytics¶

11.1 liveReports.getEvents¶

11.2 Stream Health via beacon.list¶

Health Beacons (Alerts)¶

Diagnostics Beacons (Encoder Data)¶

11.3 Recommended Polling Intervals¶

11.4 Realtime Report Types¶

12. Report Types Reference¶

12.1 VOD / Historical Reports¶

12.2 Webcast / Events Platform Reports¶

12.3 Multi-Account Variants¶

13. Filter Fields Reference¶

14. Error Handling & Permissions¶

14.1 Analytics Permissions¶

14.2 Common Errors¶

14.3 Reports Microservice Errors¶

15. Common Integration Patterns¶

15.1 Event ROI Dashboard¶

15.2 Content Performance Optimization¶

15.3 Live Stream Operations Dashboard¶

15.4 Compliance Training Verification¶

15.5 Per-User Event Engagement Report¶

15.6 Multi-Account Analytics¶

15.7 BI Pipeline / Data Warehouse Integration¶

15.8 Geographic Analytics¶

15.9 Device and Technology Analytics¶

15.10 Accessibility Coverage Reporting¶

15.11 Lecture Capture & LMS Analytics¶

15.12 Investor Relations Webcast Analytics¶

15.13 Thumbnail A/B Testing¶

15.14 Webhook-Triggered Automated Reporting¶

15.15 Cross-Guide Workflow: Full Event Lifecycle¶

Pre-Event Setup¶

During the Event¶

Post-Event Follow-Up¶

15.16 Cross-Guide Workflow: Analytics-Driven Content Automation Pipeline¶

15.17 Cross-Guide Workflow: CRM Integration Pipeline¶

16. Best Practices¶

17. Related Guides¶