battles / Analytics
Kochava vs Northbeam
Kochava ($1,500/mo/mo, vibe code 3/10) vs Northbeam ($2,500/mo/mo, vibe code 3/10). Northbeam is the easier one to rebuild yourself — here is what you lose either way.
Analytics
$1,500/mo/mo
- MVP
- 3 weeks
- Full replacement
- 18+ months, limited by MMP network certifications
Analytics
$2,500/mo/mo
- MVP
- 3-4 weeks
- Full replacement
- 12-18 months
easier to rebuild
get the build prompt →price gap / year
$12,000/mo
running both / year
$48,000/mo
our call
Start with Northbeam — highest vibe code, weakest moat.
Kochava
Kochava's underlying event tracking and attribution logic are straightforward to code, but you cannot replicate its Mobile Measurement Partner (MMP) status. Major ad networks like Meta, Google, and Apple only transmit fine-grained install attribution data to certified MMPs.
you can rebuild
- Custom rule-based attribution modeling (last-touch, first-touch, multi-touch)
- Raw event ingestion and client-side event payload validation
- Cohort retention and customer lifetime value (LTV) dashboarding
- UTM and custom referral link parameter parser engine
- Data warehouse exporter to Snowflake or BigQuery
what you lose
- Official MMP status with Meta, Google, TikTok, and Snap for SAN data access
- Cryptographically validated Apple SKAdNetwork / AdAttributionKit decoding pipeline
- SmartLinks cross-platform dynamic deep linking framework for iOS Universal Links and Android App Links
- Real-time SDK spoofing and ad click-flooding fraud detection algorithms
- Pre-configured server-to-server postbacks to thousands of ad networks
real moats
- Official MMP partner accreditation with Self-Attributing Networks (SANs)
- Device footprint and proprietary identity resolution graphs
- Widespread mobile SDK deployment across thousands of high-profile apps
open source escape hatches
- PostHog MIT
- RudderStack AGPL-3.0
- Snowplow Analytics Apache-2.0
Northbeam
Building a simple ROAS dashboard takes two days. Building a resilient, enterprise-grade multi-touch attribution platform that ingests raw clickstream data, survives Safari ITP, runs high-volume ClickHouse aggregations, and stitches identities across channels takes years of data engineering.
you can rebuild
- Standard UTM-based First-Touch, Last-Touch, and Linear attribution reporting dashboards.
- Basic Shopify purchase webhook aggregation and sales visualizers.
- Creative-level performance tables matching UTM content tags to Shopify orders.
- Basic Meta/Google Ads spend ingestion and CAC/ROAS summary cards.
what you lose
- Proprietary Apex conversion signal enrichment for Meta and Google Ad algorithms.
- Integrated Media Mix Modeling (MMM+) engines with weekly Bayesian calibration.
- Dedicated Human Media Strategists and agency-level channel calibration.
- Deterministic view-through attribution engines for non-click ad impressions.
- Cross-brand benchmark insights across thousands of DTC merchants.
real moats
- Multi-year identity mapping databases connecting cross-device click IDs to real purchase histories.
- Direct integration partnerships for Meta CAPI (Apex) feed optimization.
- Proprietary machine learning models for fractional multi-touch attribution and weekly media mix modeling calibration.
Questions people ask
Which is easier to rebuild with AI, Kochava or Northbeam?
Northbeam. It scores 3/10 on vibe code with a moat of 7/10, so an AI-assisted MVP takes about 3-4 weeks and a full replacement about 12-18 months.
Which one costs less, Kochava or Northbeam?
Kochava at $1,500/mo/mo for a typical mid-market store. The gap between the two is about $12,000/mo a year.
What do I lose if I replace Kochava?
Official MMP status with Meta, Google, TikTok, and Snap for SAN data access Cryptographically validated Apple SKAdNetwork / AdAttributionKit decoding pipeline SmartLinks cross-platform dynamic deep linking framework for iOS Universal Links and Android App Links
What do I lose if I replace Northbeam?
Proprietary Apex conversion signal enrichment for Meta and Google Ad algorithms. Integrated Media Mix Modeling (MMM+) engines with weekly Bayesian calibration. Dedicated Human Media Strategists and agency-level channel calibration.
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