---
name: data-export-formats
description: Use when exporting data for ad platforms (Google Ads, Meta) or working with project datasets. Documents exact CSV formats for Enhanced Conversions, Customer Match, and project data schemas.
---

# Data Export Formats

Use this skill when creating CSV exports for ad platforms or when you need to understand the project's data schemas.

## Google Ads Export Formats

### Enhanced Conversions CSV

For uploading offline conversion data to improve Smart Bidding.

**Required columns:**
```
Email,Phone,Conversion Name,Conversion Time,Conversion Value,Conversion Currency
```

**Format requirements:**
- **Email**: SHA256 hash (32 hex chars, lowercase)
- **Phone**: SHA256 hash (32 hex chars, lowercase)
- **Conversion Name**: String matching your Google Ads conversion action
- **Conversion Time**: ISO 8601 UTC format (`2024-11-15T14:32:00Z`)
- **Conversion Value**: Numeric, no currency symbol
- **Conversion Currency**: 3-letter code (`USD`, `EUR`, etc.)

**Example:**
```csv
Email,Phone,Conversion Name,Conversion Time,Conversion Value,Conversion Currency
ed8e83c2f4cb7b9f43cdc75c148b0b09,628923b3c489bda7dd9ebba89cb5b46c,paid_subscription,2025-11-03T00:00:00Z,2388.0,USD
1bffb899c9248b28e37cda02dbd59444,0dd03c9dc463ab5efcd15f3343035ffa,paid_subscription,2025-10-31T00:00:00Z,2189.0,USD
```

**Google Ads upload path:**
`Tools & Settings → Conversions → Upload conversions → Import`

---

### Customer Match CSV (Retargeting Audiences)

For uploading audience lists to Google Ads.

**Minimal columns (email only):**
```
Email
```

**Extended columns (better match rate):**
```
Email,Phone,First Name,Last Name,Country,Zip
```

**Format requirements:**
- **Email**: SHA256 hash (32 hex chars, lowercase) OR plaintext (Google hashes it)
- **Phone**: SHA256 hash OR E.164 format (`+14155551234`)
- **First Name / Last Name**: Plaintext, lowercase, trimmed
- **Country**: 2-letter ISO code (`US`, `GB`, etc.)
- **Zip**: 5-digit US or local format

**Example (hashed):**
```csv
Email,Phone
ed8e83c2f4cb7b9f43cdc75c148b0b09,628923b3c489bda7dd9ebba89cb5b46c
1bffb899c9248b28e37cda02dbd59444,0dd03c9dc463ab5efcd15f3343035ffa
```

**Google Ads upload path:**
`Tools & Settings → Audience Manager → Customer Match → Email list`

---

### Meta Custom Audiences CSV

For uploading to Meta Ads Manager.

**Columns:**
```
email,phone,fn,ln,country,zip
```

**Format requirements:**
- **email**: SHA256 hash (lowercase hex) OR plaintext lowercase
- **phone**: Digits only, no formatting (`14155551234`)
- **fn / ln**: Lowercase, trimmed
- **country**: 2-letter ISO lowercase (`us`)
- **zip**: 5-digit

**Example:**
```csv
email,phone,fn,ln,country,zip
ed8e83c2f4cb7b9f43cdc75c148b0b09,14155551234,john,doe,us,94105
```

---

## Project Data Schemas

### users.csv (~5,000 records)

User master file with acquisition data.

| Field | Type | Description | Example |
|-------|------|-------------|---------|
| user_id | UUID | Unique identifier | `208763df-9843-4c82-b4f1-bc6382a44acf` |
| email | String | SHA256 hash (32 chars) | `0f9f75d98cacdbd135ccbf18f1aa2e54` |
| phone | String | SHA256 hash (32 chars) | `eb18808fce984c7887799fe9e45f3d66` |
| signup_date | Date | Registration date | `2024-11-15` |
| traffic_source | String | Acquisition channel | `organic`, `paid_search`, `paid_social`, `direct`, `referral` |
| utm_source | String | UTM source | `google`, `facebook`, `linkedin` |
| utm_medium | String | UTM medium | `cpc`, `organic`, `social`, `referral` |
| utm_campaign | String | Campaign ID | `google_ads_q4`, `fb_retargeting` |

---

### events.csv (~57,000 records)

Event stream with funnel progression.

| Field | Type | Description | Example |
|-------|------|-------------|---------|
| event_id | UUID | Unique event ID | `22794184-df27-4329-86b1-acccd60b79b2` |
| user_id | UUID | FK to users | `a0505dd5-4327-4f86-82cc-bf39ba62c92e` |
| event_name | String | Event type | `page_view`, `pricing_view`, `checkout_start`, `form_submit`, `conversion` |
| page_url | String | Page path | `/`, `/pricing`, `/checkout`, `/success` |
| timestamp | DateTime | ISO 8601 UTC | `2024-11-15T14:32:00Z` |
| session_id | UUID | Groups session events | `80ea1bd9-d628-4ef6-bf26-64d928490205` |
| conversion_value | Numeric | USD (conversions only) | `150.00` or empty |

**Funnel stages (event_name values):**
1. `page_view` - Landing page visit
2. `pricing_view` - Viewed pricing page
3. `checkout_start` - Started checkout
4. `form_submit` - Submitted form
5. `conversion` - Completed purchase

---

### daily_metrics.csv (~60 records)

Daily aggregated metrics with engineered anomalies.

| Field | Type | Description |
|-------|------|-------------|
| date | Date | Metric date |
| sessions | Integer | Daily sessions |
| users | Integer | Unique users |
| conversions | Integer | Daily conversions |
| revenue | Numeric | Daily revenue (USD) |
| conversion_rate | Numeric | Conversions / users |
| avg_order_value | Numeric | Revenue / conversions |

**Engineered anomalies:**
- Nov 15: -63% sessions (signup flow bug)
- Nov 21: +99% conversions (onboarding improvement)
- Nov 28-30: -72% conversion rate (activation issue)

---

### trial_users.csv (~500 records)

Trial user conversion data (Demo 4).

| Field | Type | Description |
|-------|------|-------------|
| user_id | UUID | Unique identifier |
| signup_date | Date | Trial start date |
| plan_type | String | Always `free_trial` |
| converted | Boolean | Whether converted to paid |
| conversion_date | Date | When converted (nullable) |
| days_to_convert | Integer | Days from signup to conversion |

---

### feature_usage.csv (~2,500 records)

Feature adoption events (Demo 4).

| Field | Type | Description |
|-------|------|-------------|
| user_id | UUID | FK to trial_users |
| feature_name | String | Feature used |
| first_used_date | Date | First usage date |
| usage_count | Integer | Total uses |
| days_since_signup_first_use | Integer | Days from signup to first use |

**Key features:**
- `create_form_onboarding` - Created first form
- `publish_form` - Published a form
- `embed_form` - Embedded form on site
- `configure_integration` - Set up integration (**aha moment**)
- `view_analytics` - Viewed form analytics

**Aha moment pattern:** Users who `configure_integration` within 3 days convert at 70% vs 19% baseline (3.7x lift).

---

### utm_data.csv (~12 records)

Campaign UTM data with intentional inconsistencies (Demo 5).

| Field | Type | Description |
|-------|------|-------------|
| url | String | Landing page URL |
| utm_source | String | Source parameter |
| utm_medium | String | Medium parameter |
| utm_campaign | String | Campaign parameter |
| session_count | Integer | Sessions with this UTM |

**Engineered issues:**
- Source fragmentation: `linkedin` vs `LinkedIn` vs `LINKEDIN`
- Typos: `product_upd_dec` instead of `product_update_dec`

---

## Common Export Patterns

### High-Value Converters (Enhanced Conversions)

```sql
SELECT
  u.email AS Email,
  u.phone AS Phone,
  'paid_subscription' AS "Conversion Name",
  e.timestamp AS "Conversion Time",
  e.conversion_value AS "Conversion Value",
  'USD' AS "Conversion Currency"
FROM users u
JOIN events e ON u.user_id = e.user_id
WHERE e.event_name = 'conversion'
  AND e.conversion_value > 100
ORDER BY e.conversion_value DESC
```

### Retargeting Audience (Customer Match)

```sql
WITH pricing_views AS (
  SELECT user_id, COUNT(*) as view_count
  FROM events
  WHERE event_name = 'pricing_view'
  GROUP BY user_id
  HAVING COUNT(*) >= 2
),
checkout_starters AS (
  SELECT DISTINCT user_id FROM events WHERE event_name = 'checkout_start'
),
converters AS (
  SELECT DISTINCT user_id FROM events WHERE event_name = 'conversion'
)
SELECT u.email AS Email, u.phone AS Phone
FROM users u
JOIN pricing_views pv ON u.user_id = pv.user_id
JOIN checkout_starters cs ON u.user_id = cs.user_id
LEFT JOIN converters c ON u.user_id = c.user_id
WHERE c.user_id IS NULL
```

---

## File Locations

| File | Location | Records |
|------|----------|---------|
| users.csv | `data/users.csv` | ~5,000 |
| events.csv | `data/events.csv` | ~57,000 |
| daily_metrics.csv | `data/daily_metrics.csv` | ~60 |
| trial_users.csv | `data/trial_users.csv` | ~500 |
| feature_usage.csv | `data/feature_usage.csv` | ~2,500 |
| utm_data.csv | `data/utm_data.csv` | ~12 |

## BigQuery Location

**Project:** `agents-webinar-2025`
**Dataset:** `webinar_demos`
**Tables:** `users`, `events`, `daily_metrics`, `trial_users`, `feature_usage`


---
Source attribution: FunnelEnvy
Original project: https://github.com/FunnelEnvy/agents_webinar_demos/blob/1804741b8131a0e7baca1a3f060922273225b8e4/.claude/skills/data-export-formats/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Dave AI.

## Upstream license notice

MIT License

Copyright (c) 2024 Arun Sivashankaran

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Dave AI resource metadata

Creator / publisher: FunnelEnvy
Original project: https://github.com/FunnelEnvy/agents_webinar_demos/blob/1804741b8131a0e7baca1a3f060922273225b8e4/.claude/skills/data-export-formats/SKILL.md
Attribution basis: Recovered original package and original project license at a pinned revision

Fields of work: Data & Analytics, Marketing
Roles: Advertising Specialist, Data Analyst, Growth Marketer, Marketing Analyst, Product Marketer
Specialties: API, Database
Tools: Google Ads, Meta Ads
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: d18e2d23721ebdeb8c5d8f618126270b6a1c6273f246d481e8aad4a0fd576ef1
Metadata reviewed: 2026-10-27
This metadata supersedes earlier Dave AI catalog attribution. Original instruction and supporting files are preserved.