Bring cohort review, attribution context, and revenue analysis into one workflow so your team can make decisions with clearer signal and less tab switching.
Many teams wait too long to understand downstream value, compare disconnected reports, and make budget decisions without a shared attribution view.
From integration to clearer decision-making
Integrate your ad platforms, analytics, and revenue sources in minutes. One SDK, all data.
Every click, view, install, and purchase is captured with sub-50ms latency.
ML models process your data to predict LTV, attribute conversions, and identify patterns.
Get actionable insights to reduce CAC, improve ROAS, and scale profitable campaigns.
Everything you need to understand and optimize user value
Review early value signals before long payback windows fully mature.
Slice your data by acquisition source, date, campaign, creative. See true ROI per cohort over time.
Last-click is dead. See the full customer journey and attribute value across every touchpoint.
End-to-end tracking from click to purchase to repeat buy. Connect ad spend directly to revenue.
Keep install, event, and postback workflows close to campaign reporting and optimization.
Use consent-aware identity signals to understand broader customer journeys across touchpoints.
Use early cohorts, revenue events, and attribution context to build faster feedback loops.
Review core attribution workflows side by side with campaign and revenue reporting.
| Feature | AdBid | AppsFlyer/Adjust |
|---|---|---|
| Install Attribution | Available | Varies by setup |
| SKAdNetwork Support | Supported | Often separate configuration |
| Deep Linking | Available | Plan dependent |
| Raw Data Export | Available | Often gated |
| Custom Events | Flexible | Plan-based limits |
| Fraud Prevention | Workflow support | Often add-on |
Use one workspace for campaign reporting, attribution context, and downstream value analysis.
Compare models side-by-side to find what works for your business
100% credit to final touchpoint
100% credit to first touchpoint
Equal credit across all touchpoints
More credit to recent touchpoints
40% first, 40% last, 20% middle
ML-based credit distribution
Illustrative ways teams use analytics inside AdBid
"Used cohort views to compare channels earlier and align spend reviews with downstream revenue signals."
"Centralized campaign, revenue, and attribution views so weekly optimization reviews happened in one place."
"Compared cohorts by creative and source to spot which acquisition paths looked strongest over time."
AdBid surfaces early behavioral and revenue signals so teams can review likely value trends sooner. Final outcomes still depend on tracking quality, product economics, and campaign structure.