# Kochava integrations

> Connect Kochava's mobile measurement data to your entire marketing stack and get attribution automation running in real time.

**Canonical page:** https://tray.ai/connectors/kochava-integrations/
**Categories:** Marketing, Databases
**Documentation:** https://tray.ai/documentation/connectors/service/kochava

## Overview

Kochava is a mobile measurement and attribution platform that tracks app installs, in-app events, and campaign performance across every major ad network. Integrating Kochava with your CRM, data warehouse, and marketing tools cuts out manual data exports and keeps your attribution data flowing where it needs to be. With tray.ai, teams can build workflows that act on Kochava's attribution signals in real time — optimizing spend, suppressing audiences, and enriching customer profiles automatically.

## Use cases

### Real-Time Attribution Data Sync to Data Warehouse

Push Kochava attribution events — installs, re-engagements, and in-app purchase events — directly into your data warehouse (Snowflake, BigQuery, or Redshift) as they happen. No more waiting on scheduled CSV exports. Your analytics team gets fresh attribution data for LTV modeling and cohort analysis, and automated pipelines remove the risk of data loss from manual handling.

- Cut data latency from hours to seconds by eliminating manual CSV exports
- Maintain a complete, queryable record of every install and in-app event by campaign source
- Run LTV and cohort analysis without waiting for nightly batch jobs

### Automated Audience Suppression Across Ad Networks

When Kochava registers a successful conversion — an app install or first purchase — automatically suppress that user from active acquisition campaigns on Facebook, Google, or TikTok. You stop wasting spend on users who've already converted, and ROAS improves. tray.ai listens for Kochava postback events and fires the suppression workflow immediately.

- Stop serving acquisition ads to users who have already installed or purchased
- Cut wasted ad spend the moment a conversion is detected
- Keep suppression lists current without manual audience uploads

### CRM Enrichment with Mobile Attribution Data

Enrich your Salesforce, HubSpot, or Braze customer records with Kochava attribution data — capturing the exact campaign, ad set, and creative behind each app install or registration. Sales and lifecycle marketing teams get full visibility into which paid channels produce the highest-quality users. Connect install source directly to CRM deal records to tie downstream revenue back to specific campaigns.

- Attach first-touch attribution data to every contact or user profile in your CRM
- Give sales teams the context to prioritize leads from high-converting acquisition channels
- Close the loop between paid acquisition and downstream revenue reporting

### Fraud Alert Escalation and Reporting Automation

Kochava's fraud detection tools flag suspicious installs and invalid traffic in real time. With tray.ai, those fraud alerts automatically trigger Slack notifications to your marketing ops team, log flagged events to a Jira board for investigation, and pause associated campaigns via ad network APIs. The gap between fraud detection and action shrinks from days to minutes.

- Get instant Slack or email alerts when Kochava flags fraudulent install activity
- Auto-create Jira or Asana tickets for fraud investigation with full event context
- Pause campaigns on connected ad networks before budget is wasted

### Cross-Channel Campaign Performance Reporting

Aggregate Kochava campaign performance metrics — installs, CPIs, in-app events, and revenue — across all connected ad networks and push consolidated reports into Looker, Tableau, or Google Sheets on a set schedule. Instead of pulling reports from multiple ad network dashboards by hand, everything flows through Kochava's API and gets distributed automatically. Stakeholders get accurate, formatted performance digests without lifting a finger.

- Consolidate multi-network performance data into a single reporting destination automatically
- Schedule daily or weekly performance digests delivered directly to stakeholders
- Eliminate manual dashboard logins across multiple ad network portals

### User Lifecycle Trigger Automation via In-App Events

Use Kochava in-app event postbacks to trigger downstream lifecycle workflows. When a user completes onboarding, makes a first purchase, or hits a loyalty milestone, automatically fire a personalized push notification via Braze, update their segment in Amplitude, or create a follow-up task in your CRM. Kochava's behavioral signals connect directly to your engagement and retention stack — no engineering tickets required.

- Trigger personalized engagement campaigns the moment a key in-app event fires
- Update user segments and profiles across your stack in real time
- Reduce dependency on engineering for connecting attribution events to lifecycle tools

### Budget Pacing Alerts and Automated Bid Adjustments

Monitor Kochava's cost and install data against daily or monthly budget caps and automatically send pacing alerts when spend velocity goes off-track. When CPI thresholds are breached, tray.ai can call ad network APIs to adjust bids or pause underperforming campaigns. Your media budgets stay on track without someone manually checking dashboards all day.

- Get automated alerts when campaign CPIs exceed defined thresholds
- Trigger bid adjustments or campaign pauses automatically based on Kochava cost data
- Protect budget pacing without manual daily monitoring

## Templates

### Kochava Install Event → Snowflake Pipeline

Automatically captures every Kochava install postback and inserts structured attribution records into a Snowflake table, keeping your data warehouse in sync with real-time acquisition activity.

Connectors used: Kochava, Snowflake

### Kochava Conversion → Facebook Audience Suppression

When Kochava confirms an app install or purchase event, automatically adds the converted user's device ID or email to a Facebook Custom Audience exclusion list to prevent redundant acquisition spend.

Connectors used: Kochava, Facebook

### Kochava Fraud Alert → Slack + Jira Escalation

When Kochava's fraud protection engine flags an invalid install or suspicious traffic pattern, this template fires an instant Slack alert to the marketing ops channel and creates a Jira ticket with full event details for investigation.

Connectors used: Kochava, Slack, Jira

### Kochava In-App Event → Braze User Profile Update

Syncs Kochava in-app event data — tutorial completion, first purchase, subscription start — to Braze user profiles in real time, so lifecycle campaign triggers fire based on actual behavioral milestones.

Connectors used: Kochava, Braze

### Scheduled Kochava Performance Report → Google Sheets + Slack

Pulls daily campaign performance metrics from Kochava's reporting API each morning, writes them to a Google Sheet, and posts a formatted summary to a Slack channel so stakeholders have instant visibility without logging into the dashboard.

Connectors used: Kochava, Google Sheets, Slack

### Kochava CPI Threshold Breach → Campaign Pause via Google Ads

Monitors Kochava cost-per-install data against defined thresholds and automatically pauses corresponding Google Ads campaigns when CPI exceeds acceptable limits, protecting budget from underperforming placements.

Connectors used: Kochava, Google Ads, Slack

## Challenges Tray.ai solves

### Postback Data Arrives Across Dozens of Disconnected Systems

Kochava collects attribution signals from every major ad network, but getting that data into CRMs, data warehouses, CDPs, and lifecycle tools typically means custom code or brittle point-to-point integrations that break and need babysitting. Marketing engineering teams burn time debugging pipelines instead of doing growth work.

**How Tray.ai helps:** tray.ai's visual, low-code workflow builder connects Kochava postback webhooks to any downstream system without custom infrastructure. Teams can route, transform, and fan out attribution data to multiple destinations from a single workflow — and non-engineers can maintain these flows on their own.

### Fraud Detection Alerts Don't Automatically Trigger Action

Kochava surfaces fraud signals, but most teams rely on manual monitoring to act — which means campaigns can keep burning budget on invalid traffic for hours or days before anyone responds. That gap has a real dollar cost.

**How Tray.ai helps:** tray.ai turns Kochava fraud events into immediate automated actions. The moment a fraud flag arrives via webhook, tray.ai can notify your team on Slack, pause the relevant campaign via API, and log a ticket for investigation — all at once, in seconds.

### Attribution Data Is Siloed Away from CRM and Sales Tools

Mobile attribution data often stays locked inside Kochava and analytics dashboards, so sales and lifecycle teams have no visibility into which acquisition channels produce the most valuable users. Without that connection, tying downstream revenue back to specific campaigns just isn't possible.

**How Tray.ai helps:** tray.ai maps Kochava install and event data directly to CRM records in Salesforce or HubSpot, enriching contacts with campaign source, ad set, and creative details at the moment of acquisition. The loop between paid spend and pipeline closes without any manual data entry.

### Audience Suppression Lists Fall Out of Sync with Actual Conversions

Manually uploading converted users to exclusion audiences on Facebook, Google, or TikTok introduces delays of hours or days. During that window, acquisition ads keep running to users who've already installed or purchased — one of the most common sources of wasted programmatic spend.

**How Tray.ai helps:** tray.ai automates suppression list updates the instant a Kochava conversion postback fires. Converted users get added to exclusion audiences across connected ad networks in real time, with no manual uploads and no delay.

### Reporting Requires Manual Aggregation Across Multiple Ad Network Dashboards

Even with Kochava centralizing attribution data, getting performance reports to stakeholders still often means manual pulls, spreadsheet formatting, and copy-pasting into email or Slack. It's slow, error-prone, and gets worse as your channel count grows.

**How Tray.ai helps:** tray.ai schedules automated reporting workflows that query Kochava's reporting API, transform the data into stakeholder-friendly formats, populate Google Sheets or BI tools, and deliver summaries to Slack or email — replacing the manual reporting workflow entirely.

## Agent features

### Retrieve App Analytics Data (Data Source)

Pull aggregated performance metrics — installs, sessions, revenue — from Kochava to give an agent current context on app performance. Downstream workflows and reports can then act on real numbers instead of guesses.

### Fetch Campaign Performance Reports (Data Source)

Query Kochava for campaign-level attribution data including clicks, conversions, and ROI across ad networks. An agent can use this to surface underperforming campaigns or put together executive summaries.

### Look Up Attribution Data for Events (Data Source)

Retrieve attribution details for specific in-app events like purchases or sign-ups, tracing them back to their originating media source. Useful when an agent needs to answer which channels are actually driving user actions worth caring about.

### Query Audience Segments (Data Source)

Access defined audience segments in Kochava to see how users are grouped by behavior or attribution. An agent can use this to personalize downstream marketing actions or push audiences to other platforms.

### Monitor Fraud Detection Reports (Data Source)

Pull fraud detection and invalid traffic reports from Kochava to spot suspicious install or engagement activity. An agent can flag anomalies automatically and alert the right people or pause affected campaigns.

### Retrieve Cohort Analysis Data (Data Source)

Fetch cohort-based retention and monetization data to understand how different user groups behave over time. An agent can use this to pick out high-value cohorts and recommend where to reallocate budget.

### Create or Update Audience Segments (Agent Tool)

Programmatically create or modify audience segments in Kochava based on behavioral triggers or data from other connected systems. This lets an agent keep targeting audiences in sync with current user data.

### Register Custom Events (Agent Tool)

Send custom in-app event definitions to Kochava so new tracking points are properly configured. An agent can handle this setup automatically when new features or campaigns launch, cutting down on manual configuration work.

### Trigger Data Export Jobs (Agent Tool)

Kick off raw data export jobs in Kochava to pull granular event-level data into a warehouse or analytics pipeline. An agent can schedule or trigger these exports based on business schedules or how fresh the data needs to be.

### Update Postback Configurations (Agent Tool)

Modify postback or S2S (server-to-server) settings in Kochava to route attribution signals to the right advertising partners. An agent can handle updates automatically when new partners come on board or campaign structures shift.

### Pause or Activate Tracker Links (Agent Tool)

Enable or disable Kochava tracker links in response to campaign performance thresholds or fraud signals. An agent can take protective action on its own without a campaign manager having to step in.

### Sync Attribution Data to CRM (Agent Tool)

Push Kochava attribution and event data into a connected CRM or marketing platform to enrich user profiles with mobile engagement context. An agent can run this sync so sales and marketing teams always have accurate acquisition channel data to work from.

## Learn more

- Intelligent Integration: https://tray.ai/platform/intelligent-ipaas/
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- Agent Gateway for MCP: https://tray.ai/platform/agent-gateway/
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