Data export

shortkit provides data export capabilities for custom analysis, data warehousing, and compliance with privacy regulations.

Export methods

Method	Best For	Access
On-demand export	Ad-hoc analysis, specific date ranges	API or Admin Portal
Scheduled export	Regular data pipeline feeds	Admin Portal
User data export	GDPR/CCPA subject requests	API

On-demand export

Via Admin Portal

Go to Analytics → Export Data
Select date range (max 30 days)
Choose data types to include
Select format (CSV or JSON Lines)
Click Export
Download when ready

Via API

Request an export:

curl -X POST https://api.shortkit.dev/v1/analytics/export \
  -H "Authorization: Bearer sk_live_your_secret_key" \
  -H "Content-Type: application/json" \
  -d '{
    "startDate": "2024-01-01",
    "endDate": "2024-01-31",
    "dataTypes": ["events", "quality"],
    "format": "jsonl"
  }'

Response:

{
  "data": {
    "jobId": "exp_abc123",
    "status": "processing",
    "estimatedSize": "250MB",
    "estimatedCompletion": "2024-02-04T12:30:00Z"
  }
}

Check status and get download URL:

curl https://api.shortkit.dev/v1/analytics/export/exp_abc123 \
  -H "Authorization: Bearer sk_live_your_secret_key"

Response when complete:

{
  "data": {
    "jobId": "exp_abc123",
    "status": "complete",
    "downloadUrl": "https://exports.shortkit.dev/...",
    "expiresAt": "2024-02-11T12:00:00Z",
    "fileSize": "245MB",
    "rowCount": 1250000
  }
}

Export parameters

startDate

string

required

Start date (ISO 8601 format: YYYY-MM-DD).

endDate

string

required

End date (ISO 8601 format: YYYY-MM-DD). Maximum 30 days from start.

dataTypes

string[]

default:"[\"events\"]"

Data types to include:

events - Engagement events (impressions, playStart, completion, etc.)
quality - Playback quality events (rebuffer, qualityChange, error)
ads - Ad events (impression, completion, click)

format

string

default:"jsonl"

Output format:

jsonl - JSON Lines (one event per line)
csv - Comma-separated values

filters

object

Optional filters:

Show properties

contentIds

string[]

Filter to specific content IDs.

userIds

string[]

Filter to specific user IDs.

eventTypes

string[]

Filter to specific event types.

Export formats

JSON Lines (recommended)

One JSON object per line, easy to process with streaming parsers:

{"event":"impression","contentId":"cnt_abc123","userId":"user_456","timestamp":"2024-01-15T10:30:00Z","data":{"position":0}}
{"event":"playStart","contentId":"cnt_abc123","userId":"user_456","timestamp":"2024-01-15T10:30:01Z","data":{"startupTime":250,"rendition":"720p"}}
{"event":"completion","contentId":"cnt_abc123","userId":"user_456","timestamp":"2024-01-15T10:30:46Z","data":{"watchTime":45.2,"looped":false}}

CSV

Tabular format for spreadsheet analysis:

event,contentId,userId,timestamp,position,startupTime,rendition,watchTime
impression,cnt_abc123,user_456,2024-01-15T10:30:00Z,0,,,
playStart,cnt_abc123,user_456,2024-01-15T10:30:01Z,,250,720p,
completion,cnt_abc123,user_456,2024-01-15T10:30:46Z,,,,45.2

Exported data schema

Engagement events

Field	Type	Description
`event`	string	Event type
`contentId`	string	Content identifier
`userId`	string	User identifier
`timestamp`	datetime	Event timestamp
`sessionId`	string	Session identifier
`deviceType`	string	ios, android, web
`data`	object	Event-specific data

Event-specific data

impression

{
  "position": 0,
  "entryPoint": "feed"
}

playStart

{
  "startupTime": 250,
  "rendition": "720p",
  "codec": "h264"
}

watchProgress

{
  "currentTime": 15.5,
  "duration": 45.2,
  "percentComplete": 34.3,
  "rendition": "720p"
}

completion

{
  "watchTime": 45.2,
  "looped": false,
  "loopCount": 0
}

swipe

{
  "fromContentId": "cnt_abc123",
  "watchTimeOnFrom": 12.5,
  "direction": "next"
}

Quality events

Field	Type	Description
`event`	string	rebuffer, qualityChange, error
`contentId`	string	Content identifier
`userId`	string	User identifier
`timestamp`	datetime	Event timestamp
`currentTime`	number	Playback position
`data`	object	Event-specific data

Scheduled exports

Set up automatic recurring exports:

Configure in Admin Portal

Go to Settings → Data Export
Enable Scheduled Exports
Configure:
- Frequency: Daily or weekly
- Data types: Select data to include
- Format: CSV or JSON Lines
- Delivery: Webhook URL or email

Webhook delivery

When an export is ready, a POST request is sent to your webhook:

{
  "event": "export.ready",
  "data": {
    "exportId": "exp_daily_20240204",
    "dateRange": {
      "start": "2024-02-03",
      "end": "2024-02-03"
    },
    "downloadUrl": "https://exports.shortkit.dev/...",
    "expiresAt": "2024-02-11T00:00:00Z",
    "fileSize": "45MB"
  }
}

User data export

For GDPR/CCPA data subject requests, export all data for a specific user:

curl -X POST https://api.shortkit.dev/v1/users/{userId}/export \
  -H "Authorization: Bearer sk_live_your_secret_key"

Response:

{
  "data": {
    "jobId": "usr_exp_abc123",
    "status": "processing"
  }
}

Exported user data

The export includes:

User profile (topic affinities, engagement summary)
All engagement events attributed to the user
Linked device IDs
Experiment assignments

Data deletion

To delete user data (right to erasure):

curl -X DELETE https://api.shortkit.dev/v1/users/{userId} \
  -H "Authorization: Bearer sk_live_your_secret_key"

This permanently deletes:

User profile
All engagement events
Topic affinity data
Device linkages

User deletion is irreversible. The user ID can be reused, but all historical data is lost.

Data retention

Data Type	Retention Period
Raw events	90 days
Aggregated analytics	2 years
User profiles	Until deletion
Export files	7 days

Best practices

Use streaming parsers for large exports

JSON Lines format allows processing line-by-line without loading the entire file:

const readline = require('readline');
const fs = require('fs');

const rl = readline.createInterface({
  input: fs.createReadStream('export.jsonl')
});

rl.on('line', (line) => {
  const event = JSON.parse(line);
  // Process event
});

Schedule exports during off-peak hours

Large exports can take time to generate. Schedule them for low-traffic periods.

Implement incremental processing

Rather than re-processing all data, track your last processed timestamp and export only new data.

Secure your export files

Export URLs are signed and expire after 7 days. Download and secure files promptly.

Integration examples

Data warehouse (BigQuery)

# Download export
curl -o events.jsonl "https://exports.shortkit.dev/..."

# Load to BigQuery
bq load --source_format=NEWLINE_DELIMITED_JSON \
  your_dataset.shortkit_events \
  events.jsonl \
  event:STRING,contentId:STRING,userId:STRING,timestamp:TIMESTAMP

Analytics pipeline (Python)

import pandas as pd
import requests

# Download export
response = requests.get(export_url)
with open('events.jsonl', 'wb') as f:
    f.write(response.content)

# Load to pandas
df = pd.read_json('events.jsonl', lines=True)

# Analyze
watch_time_by_content = df[df['event'] == 'completion'].groupby('contentId')['data'].apply(
    lambda x: sum(d['watchTime'] for d in x)
)

Platform

Integration

Export methods

On-demand export

Via Admin Portal

Via API

Export parameters

Export formats

JSON Lines (recommended)

CSV

Exported data schema

Engagement events

Event-specific data

Quality events

Scheduled exports

Configure in Admin Portal

Webhook delivery

User data export

Exported user data

Data deletion

Data retention

Best practices

Integration examples

Data warehouse (BigQuery)

Analytics pipeline (Python)

Next steps

Analytics

Analytics API

Platform

Integration

​Export methods

​On-demand export

​Via Admin Portal

​Via API

​Export parameters

​Export formats

​JSON Lines (recommended)

​CSV

​Exported data schema

​Engagement events

​Event-specific data

​Quality events

​Scheduled exports

​Configure in Admin Portal

​Webhook delivery

​User data export

​Exported user data

​Data deletion

​Data retention

​Best practices

​Integration examples

​Data warehouse (BigQuery)

​Analytics pipeline (Python)

​Next steps

Analytics

Analytics API

Export methods

On-demand export

Via Admin Portal

Via API

Export parameters

Export formats

JSON Lines (recommended)

CSV

Exported data schema

Engagement events

Event-specific data

Quality events

Scheduled exports

Configure in Admin Portal

Webhook delivery

User data export

Exported user data

Data deletion

Data retention

Best practices

Integration examples

Data warehouse (BigQuery)

Analytics pipeline (Python)

Next steps