Orphex

Develop by Orphex Tech Limited

$199-$999

/ Month

Digital Marketing & User Behavior Analytics Platform

Multi-platform integration

Creative performance analysis

User behavior insights

Automated reports

Team assignments

Data-driven recommendations

Actionable recommendations

About Orphex

Launched Jun 26, 2024

Built by Orphex Tech Limited

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Description

Unified ad and analytics data. Optimize budget spend and product performance with AI-driven insights

Orphex unifies 30+ marketing and measurement channels—Google Ads, Meta, TikTok, GA4 and more—into one dashboard. AI surfaces cross-channel product, keyword and user analyses, highlighting best‑selling SKUs, creative wins and funnel leaks. Smart budget optimization flags underperforming spend to maximize ROI. Real-time anomaly alerts catch CPC, CPM or conversion spikes before they drain profit. Save hours with automated reports via email or Slack. 5‑min setup; flexible plans for every store.

Unified cross-channel insights reveal ROI across 30+ platforms
Product analytics spotlight best-selling SKUs and funnel friction points
Automated AI analyses and reports streamline decision‑making workflows
Creative insights and scoring pinpoints images, videos and assets that convert
Weekly digests via email or Whatsapp summarize wins, leaks and next step actions

Pros

Integrates with many popular analytics platforms such as Google, Meta, GA4, Tiktok, Adjust, Youtube, etc
Gathers all marketing and sales data into one place, simplifying data management and analysis
Advanced machine learning algorithms provide clear, data-driven recommendations for optimizing campaign budgets and maximizing ROI
Offers valuable insights by examining user behavior and preferences
Allows analysis of the performance of all creatives on various platforms
Supports creation of automated, custom performance reports
Enables assignment of recommendations to team members for streamlined action
Provides clear and concise recommendations to facilitate decision-making

Cons

Repeated description content may indicate limited descriptive variation
Potential reliance on machine learning algorithms may require supervision and validation
Integration complexities might arise with lesser-known or unsupported platforms
Data privacy and security concerns need to be managed due to aggregation from multiple sources
May require a learning curve to fully leverage all features and functionalities