Pinterest Ads Integrations

Integrations linking Pinterest Ads with analytics platforms, CRMs, and data tools.

Overview

Pinterest Ads offers a comprehensive integration ecosystem designed to help advertisers measure performance, activate audiences, and optimize campaigns across the customer journey. With native integrations spanning e-commerce platforms, analytics tools, attribution partners, and CRM systems, Pinterest enables businesses to leverage visual discovery intent data for measurable business outcomes.

This guide covers all available Pinterest Ads integration options, including the Pinterest Tag, Conversions API, catalog feeds, partner integrations, and data export capabilities.

Integration Capabilities

Native Pinterest Integrations

Pinterest Tag

Client-side tracking pixel for web events
Base code deployment with event-specific tracking
Enhanced match for improved attribution
Automatic advanced matching when enabled
Custom event parameters for flexible tracking
Support for single-page applications (SPAs)

Pinterest Conversions API

Server-to-server event tracking
Privacy-compliant data sharing
Redundancy with Pinterest Tag for event deduplication
Real-time event transmission
Offline conversion tracking capability
Custom event and parameter support

Pinterest Business Hub

Centralized account management
Asset sharing across Pinterest accounts
Team collaboration and permission management
Linked account overview dashboard
Bulk account operations

Catalogs API

Product catalog synchronization
Automated feed updates (hourly, daily)
Inventory and pricing sync
Product attribute management
Multi-country catalog support
Feed validation and error reporting

Ads API

Programmatic campaign management
Bulk campaign creation and optimization
Automated bidding and budget management
Custom reporting and analytics
Audience management endpoints
Creative management and testing

Platform Requirements

Access Levels

Business account: Required for all advertising features
Admin access: Full campaign and billing management
Partner access: For agencies managing client accounts
API access: Requires developer approval and app review
Catalog access: Requires claimed website domain

Technical Prerequisites

Verified Pinterest business account
Claimed website domain (for catalog and conversion tracking)
Pinterest Tag properly implemented
Conversions API server endpoint (for server-side tracking)
Developer app credentials (for API access)

E-commerce Platform Integrations

Shopify

Integration Type: Official app integration Setup:

Install Pinterest app from Shopify App Store
Connect Pinterest business account
Automatic catalog sync begins
Pinterest Tag auto-installed via app
Enable Shopping Ads in Pinterest Ads Manager

Features:

Automatic product catalog sync (every 24 hours)
Real-time inventory and pricing updates
Pinterest Tag automatic installation
Conversion tracking without code
Product Pin creation from catalog
Shopify order attribution in Pinterest

Data Synced:

Product ID, title, description
Images and product variants
Price and availability
Product category and attributes
Custom labels for segmentation

Conversion Events Tracked:

Page visit
Add to cart
Checkout initiation
Purchase with order value

WooCommerce

Integration Type: Official Pinterest for WooCommerce plugin Setup:

Install Pinterest for WooCommerce plugin
Authorize Pinterest business account
Configure catalog feed settings
Map product attributes to Pinterest taxonomy
Enable automatic tag installation

Features:

Automated catalog feed generation
Dynamic product updates
Pinterest Tag deployment via plugin
Order tracking and attribution
Product group targeting
Rich Pins for products

Best Practices:

Use high-quality square images (1:1 ratio)
Complete all product attributes
Maintain inventory accuracy
Set up shipping and tax correctly
Use Google Product Category taxonomy

Magento

Integration Type: Extension marketplace Setup:

Install Pinterest extension from Magento Marketplace
Configure API credentials in extension settings
Map Magento attributes to Pinterest catalog fields
Set up cron job for automated sync
Deploy Pinterest Tag via extension

Features:

Scheduled catalog synchronization
Multi-store support
Attribute mapping customization
Bulk product upload
Conversion tracking integration

BigCommerce

Integration Type: Native app integration Setup:

Navigate to BigCommerce app marketplace
Install Pinterest app
Authenticate Pinterest account
Configure product catalog sync
Enable conversion tracking

Features:

One-click Pinterest Tag installation
Automated catalog feed updates
Product feed optimization
Category mapping tools
Order conversion tracking

Wix

Integration Type: Wix Marketplace app Setup:

Add Pinterest app from Wix App Market
Connect Pinterest business account
Select products to sync
Configure tracking settings
Publish to activate integration

Features:

Visual product selection interface
Simplified tag management
Basic conversion tracking
Manual and automatic sync options
Pin creation from products

Analytics Platform Integrations

Google Analytics 4

Integration Method: Pinterest Tag + UTM parameters Setup:

Deploy Pinterest Tag alongside GA4 tracking
Enable auto-tagging in Pinterest Ads Manager
Configure Pinterest as traffic source in GA4
Create custom dimensions for Pinterest campaign data
Set up conversion events in GA4 that mirror Pinterest events

UTM Structure:

utm_source=pinterest
utm_medium=cpc (or social, display)
utm_campaign=[campaign_name]
utm_term=[targeting_type]
utm_content=[pin_id]

Cross-Platform Tracking:

// Pinterest Tag with GA4 integration
<script>
!function(e){if(!window.pintrk){window.pintrk = function () {
window.pintrk.queue.push(Array.prototype.slice.call(arguments))};var
  n=window.pintrk;n.queue=[],n.version="3.0";var
  t=document.createElement("script");t.async=!0,t.src=e;var
  r=document.getElementsByTagName("script")[0];
  r.parentNode.insertBefore(t,r)}}("https://s.pinimg.com/ct/core.js");

pintrk('load', 'YOUR_TAG_ID', {em: '<user_email_address>'});
pintrk('page');

// Also track in GA4
gtag('event', 'page_view', {
  'pinterest_campaign': '[campaign_id]',
  'pinterest_source': 'organic_pin'
});
</script>

Available Data in GA4:

Pinterest traffic segmentation
Conversion path analysis with Pinterest touchpoints
User engagement metrics for Pinterest visitors
E-commerce transaction attribution
Audience overlap analysis

Adobe Analytics

Integration Method: Pinterest Tag + Adobe Launch Setup:

Deploy Pinterest Tag via Adobe Launch
Configure data elements for Pinterest variables
Map Pinterest events to Adobe Analytics events
Set up processing rules for data normalization
Create segments for Pinterest traffic analysis

Implementation Example:

// Adobe Analytics + Pinterest Tag integration
var s = s_gi('rsid');

// Pinterest conversion event
pintrk('track', 'checkout', {
  value: 49.99,
  order_quantity: 1,
  currency: 'USD'
});

// Mirror to Adobe Analytics
s.events = 'purchase';
s.products = ';Product Name;1;49.99';
s.eVar20 = 'Pinterest';
s.eVar21 = getPinterestCampaignId();
s.t();

Use Cases:

Multi-touch attribution modeling
Customer journey analysis
Lifetime value tracking by acquisition source
Campaign effectiveness measurement
Cross-channel performance comparison

Heap Analytics

Integration Method: Auto-capture + Pinterest event enrichment Setup:

Deploy both Heap and Pinterest Tag
Use Heap's autocapture for behavioral data
Send Pinterest attribution to Heap as user properties
Create funnels including Pinterest traffic
Analyze user behavior by Pinterest campaign

Benefits:

Automatic event capture without manual instrumentation
Retroactive analysis of Pinterest user behavior
Cohort analysis by Pinterest campaign
Session replay for Pinterest-driven sessions

Attribution and Measurement Partners

AppsFlyer

Integration Type: Mobile app attribution Setup:

Configure AppsFlyer SDK in mobile app
Enable Pinterest integration in AppsFlyer dashboard
Add Pinterest to attribution configuration
Map app events to Pinterest conversion events
Test attribution flow with test campaigns

Features:

App install attribution from Pinterest ads
In-app event tracking and optimization
Deep linking for app re-engagement
Cross-device attribution
Fraud prevention and validation
ROI and LTV measurement

Attribution Windows:

Click-through: 30 days (default, configurable)
View-through: 1 day (configurable)
Re-engagement: 30 days

Adjust

Integration Type: Mobile measurement partner Setup:

Integrate Adjust SDK in app
Enable Pinterest in Adjust dashboard
Configure callback URLs for Pinterest
Map conversion events
Set attribution windows

Features:

Multi-touch attribution
Fraud prevention suite
Audience segmentation for retargeting
Uninstall tracking
Revenue and event tracking
Real-time analytics dashboard

Branch

Integration Type: Deep linking and attribution Setup:

Implement Branch SDK
Configure Pinterest as ad partner
Create Branch links for Pinterest campaigns
Enable deferred deep linking
Set up conversion tracking

Features:

Deep linking from Pinterest to app
Deferred deep linking for new users
Web-to-app attribution
Cross-platform user journey tracking
People-based attribution
Campaign performance analytics

CRM and Marketing Automation Integrations

Salesforce

Integration Method: Pinterest offline conversions + CRM data upload Setup:

Export Pinterest exposure data via API or partner
Match to Salesforce leads/opportunities by email
Upload offline conversions back to Pinterest
Build custom audiences from Salesforce lists
Measure closed-loop attribution

Use Case Example:

import hashlib
import requests

def upload_offline_conversions_to_pinterest(access_token, ad_account_id, conversions):
    """Upload Salesforce conversions to Pinterest Conversions API"""

    url = f"https://api.pinterest.com/v5/ad_accounts/{ad_account_id}/events"

    headers = {
        "Authorization": f"Bearer {access_token}",
        "Content-Type": "application/json"
    }

    events = []
    for conv in conversions:
        # Hash email for privacy
        email_hash = hashlib.sha256(conv['email'].lower().encode()).hexdigest()

        events.append({
            "event_name": "lead",
            "action_source": "offline",
            "event_time": int(conv['timestamp']),
            "event_id": conv['opportunity_id'],
            "user_data": {
                "em": [email_hash]
            },
            "custom_data": {
                "value": str(conv['deal_value']),
                "currency": "USD"
            }
        })

    payload = {"data": events}
    response = requests.post(url, headers=headers, json=payload)
    return response.json()

Benefits:

Measure true ROI including offline conversions
Build lookalike audiences from high-value customers
Suppress existing customers from prospecting
Attribute revenue to Pinterest campaigns

HubSpot

Integration Method: Form tracking + list syncing Setup:

Deploy Pinterest Tag on HubSpot landing pages
Track form submissions as Pinterest lead events
Sync HubSpot contact lists to Pinterest audiences
Set up workflows based on Pinterest engagement
Report on Pinterest influence in HubSpot

Custom Audience Creation:

Upload HubSpot contact lists (hashed emails)
Segment by lifecycle stage
Build lookalikes from SQL/MQL lists
Suppress customers from acquisition campaigns
Target based on engagement scores

Klaviyo

Integration Type: Email marketing automation Setup:

Connect Klaviyo to Pinterest via integration
Sync email lists as Pinterest audiences
Track Pinterest-driven email signups
Build multi-channel campaigns
Measure cross-channel performance

Use Cases:

Retarget email subscribers on Pinterest
Suppress active email engagers from Pinterest ads
Build lookalike audiences from email converters
Create sequential messaging across email and Pinterest
Attribution analysis for email + Pinterest touches

Pinterest Conversions API Integration

Server-Side Implementation

The Conversions API enables server-to-server event transmission for improved accuracy and privacy compliance.

Authentication:

import requests
import hashlib
import time

class PinterestConversionsAPI:
    def __init__(self, access_token, ad_account_id):
        self.access_token = access_token
        self.ad_account_id = ad_account_id
        self.base_url = "https://api.pinterest.com/v5"

    def send_event(self, event_data):
        """Send conversion event to Pinterest"""

        url = f"{self.base_url}/ad_accounts/{self.ad_account_id}/events"

        headers = {
            "Authorization": f"Bearer {self.access_token}",
            "Content-Type": "application/json"
        }

        # Hash PII data
        if 'email' in event_data.get('user_data', {}):
            email = event_data['user_data']['email'].lower().strip()
            event_data['user_data']['em'] = [hashlib.sha256(email.encode()).hexdigest()]
            del event_data['user_data']['email']

        payload = {
            "data": [event_data]
        }

        response = requests.post(url, headers=headers, json=payload)
        return response.json()

Event Structure:

# Example purchase event
purchase_event = {
    "event_name": "checkout",
    "action_source": "web",
    "event_time": int(time.time()),
    "event_id": "order_12345",  # For deduplication with Pinterest Tag
    "event_source_url": "https://yoursite.com/checkout/success",
    "user_data": {
        "em": ["hashed_email"],  # SHA256 hash
        "ph": ["hashed_phone"],  # SHA256 hash
        "client_ip_address": "192.168.1.1",
        "client_user_agent": "Mozilla/5.0..."
    },
    "custom_data": {
        "currency": "USD",
        "value": "79.99",
        "content_ids": ["SKU123"],
        "contents": [{
            "id": "SKU123",
            "item_price": "79.99",
            "quantity": 1
        }],
        "num_items": 1,
        "order_id": "order_12345"
    }
}

Event Deduplication:

// Client-side Pinterest Tag with event_id for deduplication
pintrk('track', 'checkout', {
  value: 79.99,
  order_quantity: 1,
  currency: 'USD',
  order_id: 'order_12345',
  event_id: 'order_12345_' + Date.now()  // Unique event ID
});

// Server-side sends same event_id
// Pinterest automatically deduplicates

Enhanced Match:

// Pinterest Tag with enhanced match data
pintrk('load', 'YOUR_TAG_ID', {
  em: 'user@example.com',  // Automatically hashed by Pinterest
  ph: '+14155551234',
  ge: 'f',
  db: '19900101',
  ln: 'smith',
  fn: 'jane',
  ct: 'san francisco',
  st: 'ca',
  zp: '94102',
  country: 'us'
});

Product Catalog Integration

Catalog Feed Setup

Feed Specifications:

Format: CSV, TSV, XML
Encoding: UTF-8
Max file size: 1GB
Update frequency: Hourly (recommended for e-commerce)
Hosting: HTTPS-accessible URL or Pinterest upload

Required Fields:

id,title,description,link,image_link,price,availability,brand
SKU123,"Blue Widget","Premium blue widget",https://example.com/blue-widget,https://example.com/images/widget.jpg,29.99 USD,in stock,WidgetCo

Optional Fields for Better Performance:

google_product_category: Product taxonomy
product_type: Custom product hierarchy
gender: m, f, unisex
age_group: adult, kids
color, size, material: Product attributes
sale_price: Promotional pricing
additional_image_link: Multiple product images
custom_label_0 through custom_label_4: Campaign segmentation

Catalog API Implementation:

import requests

def create_catalog_feed(access_token, feed_url, country, default_currency):
    """Create a catalog feed via Pinterest API"""

    url = "https://api.pinterest.com/v5/catalogs/feeds"

    headers = {
        "Authorization": f"Bearer {access_token}",
        "Content-Type": "application/json"
    }

    payload = {
        "default_country": country,
        "default_currency": default_currency,
        "name": "Product Catalog Feed",
        "format": "TSV",
        "location": feed_url,
        "default_availability": "IN_STOCK"
    }

    response = requests.post(url, headers=headers, json=payload)
    return response.json()

Dynamic Retargeting

Setup:

Create product catalog feed
Implement Pinterest Tag on product pages
Send page_visit events with product_id
Create catalog campaign in Ads Manager
Set up dynamic retargeting audiences

Product Page Tracking:

// Track product page views
pintrk('track', 'pagevisit', {
  product_id: 'SKU123',
  product_name: 'Blue Widget',
  product_price: 29.99,
  product_category: 'Widgets'
});

Dynamic Ad Templates:

Carousel: Multiple products
Collection: Hero image + product grid
Single image: Individual product Pin
Video: Product in use

API Integration Patterns

Authentication

Pinterest API uses OAuth 2.0:

import requests

def get_access_token(client_id, client_secret, redirect_uri, authorization_code):
    """Exchange authorization code for access token"""

    url = "https://api.pinterest.com/v5/oauth/token"

    payload = {
        "grant_type": "authorization_code",
        "code": authorization_code,
        "redirect_uri": redirect_uri
    }

    response = requests.post(
        url,
        auth=(client_id, client_secret),
        data=payload
    )

    return response.json()['access_token']

Campaign Management

Create Campaign:

def create_campaign(access_token, ad_account_id, campaign_data):
    """Create a new Pinterest campaign"""

    url = f"https://api.pinterest.com/v5/ad_accounts/{ad_account_id}/campaigns"

    headers = {
        "Authorization": f"Bearer {access_token}",
        "Content-Type": "application/json"
    }

    payload = {
        "name": campaign_data['name'],
        "status": "ACTIVE",
        "lifetime_spend_cap": campaign_data.get('budget'),
        "daily_spend_cap": campaign_data.get('daily_budget'),
        "order_line_id": campaign_data.get('order_line_id'),
        "tracking_urls": {
            "impression": [],
            "click": [],
            "engagement": [],
            "buyable_button": [],
            "audience_verification": []
        }
    }

    response = requests.post(url, headers=headers, json=payload)
    return response.json()

Reporting API

Performance Metrics:

def get_campaign_analytics(access_token, ad_account_id, campaign_id, start_date, end_date):
    """Fetch campaign performance data"""

    url = f"https://api.pinterest.com/v5/ad_accounts/{ad_account_id}/campaigns/analytics"

    headers = {
        "Authorization": f"Bearer {access_token}"
    }

    params = {
        "campaign_ids": [campaign_id],
        "start_date": start_date,  # YYYY-MM-DD
        "end_date": end_date,
        "columns": [
            "SPEND_IN_MICRO_DOLLAR",
            "IMPRESSION_1",
            "CLICKTHROUGH_1",
            "TOTAL_CLICKTHROUGH",
            "TOTAL_ENGAGEMENT",
            "OUTBOUND_CLICK",
            "PIN_CLICK",
            "SAVE",
            "TOTAL_CONVERSIONS",
            "TOTAL_CONVERSIONS_VALUE"
        ],
        "granularity": "DAY"
    }

    response = requests.get(url, headers=headers, params=params)
    return response.json()

Data Export and Reporting

Export Options

Ads Manager Reports:

Manual CSV exports
Scheduled daily/weekly email reports
Custom date ranges
Campaign, ad group, and pin-level granularity
Conversion metrics by event type

API Reporting:

Real-time performance data
Historical data (up to 2 years)
Custom metric combinations
Hourly granularity available
JSON format for data pipeline integration

Data Warehouse Integration

BigQuery Example:

from google.cloud import bigquery
import requests

def sync_pinterest_to_bigquery(access_token, ad_account_id, project_id, dataset_id):
    """Load Pinterest performance data to BigQuery"""

    # Fetch from Pinterest
    analytics = get_campaign_analytics(
        access_token,
        ad_account_id,
        'all',
        '2024-01-01',
        '2024-01-31'
    )

    # Transform data
    rows = []
    for row in analytics:
        rows.append({
            'date': row['DATE'],
            'campaign_id': row['CAMPAIGN_ID'],
            'spend': row['SPEND_IN_MICRO_DOLLAR'] / 1000000,
            'impressions': row['IMPRESSION_1'],
            'clicks': row['CLICKTHROUGH_1'],
            'conversions': row['TOTAL_CONVERSIONS']
        })

    # Load to BigQuery
    client = bigquery.Client(project=project_id)
    table_id = f"{project_id}.{dataset_id}.pinterest_performance"

    errors = client.insert_rows_json(table_id, rows)
    if errors:
        print(f"Errors: {errors}")
    else:
        print(f"Loaded {len(rows)} rows")

Common Integration Issues

Issue 1: Low Pinterest Tag Match Quality

Symptoms:

Events firing but not appearing in Ads Manager
Low event match quality score
Poor conversion tracking accuracy

Causes:

Missing enhanced match parameters
Incorrect email hashing
Client-side tracking blocked by ad blockers
Domain verification not completed

Solutions:

Enable enhanced match with email and phone:

pintrk('load', 'TAG_ID', {
  em: 'user@example.com',  // Auto-hashed by Pinterest
  ph: '+14155551234'
});

Verify website domain in Pinterest Business Hub
Implement Conversions API for redundancy
Test with Pinterest Tag Helper browser extension

Issue 2: Catalog Feed Errors

Symptoms:

Products not syncing to Pinterest
Feed processing errors
Missing product attributes

Causes:

Invalid feed format
Missing required fields
Incorrect image URLs (non-HTTPS)
Price format errors

Solutions:

Validate feed format:
- Use Pinterest Catalog Feed Validator
- Ensure UTF-8 encoding
- Check all required fields present
Fix common errors:
- Use HTTPS for all image URLs
- Format price with currency: "29.99 USD"
- Ensure availability is "in stock" or "out of stock"
Monitor feed processing in Pinterest Business Hub

Issue 3: Conversions API Event Deduplication Issues

Symptoms:

Duplicate conversions counted
Inflated conversion metrics

Causes:

Missing or different event_id between Tag and API
Timing issues between client and server events
Incorrect event parameter matching

Solutions:

// Client-side: Generate consistent event_id
const eventId = `order_${orderId}_${timestamp}`;
pintrk('track', 'checkout', {
  value: 99.99,
  order_id: orderId,
  event_id: eventId
});

// Server-side: Use same event_id
conversions_api.send_event({
  event_name: 'checkout',
  event_id: eventId,  // Must match client-side
  event_time: timestamp,
  // ... other parameters
});

Issue 4: Attribution Discrepancies

Symptoms:

Pinterest reporting more conversions than GA4
Different conversion values across platforms

Causes:

Attribution window differences
View-through attribution in Pinterest
UTM parameter stripping
Time zone mismatches

Solutions:

Align attribution windows:
- Pinterest default: 30-day click, 1-day view
- GA4: Last click (typically)
Compare click-only metrics
Use consistent time zones (UTC recommended)
Accept 10-20% variance as normal
Focus on directional trends rather than exact numbers

Support and Resources

When to Contact Support

Pinterest Support:

Catalog feed processing errors
Tag implementation issues
API access problems
Account access and permissions
Contact: business.pinterest.com/support

Partner Support:

E-commerce platform sync issues (Shopify, WooCommerce, etc.)
MMP attribution problems (AppsFlyer, Adjust, Branch)
Tag management questions (GTM, Adobe Launch)

Additional Resources

Backlog & Opportunities

Explore Conversions API for improved iOS 14+ attribution and privacy compliance
Evaluate Enhanced Match implementation for better user matching without third-party cookies
Test API for Conversions for fully automated server-side event sending
Implement catalog feed optimization with dynamic pricing and inventory updates
Build custom audience segmentation using Pinterest API for granular targeting
Explore Pinterest Trends API for seasonal campaign planning
Integrate with customer data platforms (CDPs) for unified customer profiles
Test Pinterest Shop integration for native commerce experience