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What is Causality Engine?

Numerous attribution tools can show which advertisements a customer engaged with before completing a purchase, highlighting correlation. However, Causality Engine goes a step further by revealing how much your revenue would have been affected if those advertisements had not been executed, thereby proving causation. By employing causal inference—akin to the statistical methods used in clinical drug studies—we evaluate the actual additional revenue produced by each marketing channel. This methodology guarantees that the outcomes are purely the result of marketing initiatives without any external influences or alterations. The calculations can be easily understood: for example, if Meta indicates a 4.2x ROAS, yet your total revenue remains the same after a 30% reduction in spending, it suggests those conversions would have occurred anyway. Causality Engine accurately quantifies this phenomenon. By integrating your GA4 and Shopify data, you can obtain your preliminary causal analysis in under five minutes. There’s no requirement for tracking pixels, cookies, or complex integrations—just upload your data to identify which channels are genuinely facilitating growth versus those that only take credit for existing gains. The service provides a one-time analysis for $99, and ongoing insights are offered for $299 each month, enabling businesses to continuously monitor their marketing performance and revenue contributions. This approach fosters a deeper understanding of marketing effectiveness over time, allowing for more informed decision-making.

What is CX.AI?

Seamlessly analyze text feedback with the accuracy of a human while enjoying the quick processing speed typical of computers. The incorporation of machine learning significantly boosts predictive precision, while causal machine learning tackles the biases and limitations found in conventional driver analysis. Our goal is to apply these innovative solutions for your advantage. Organizations cannot risk uncertain outcomes solely to save on costs. With the vast quantities of data at their disposal, an effectively crafted dashboard is critical for uncovering essential insights. The CX.AI simulator allows you to assess the impacts of different actions, shedding light on their effects on customer experience and financial results. By utilizing these resources, companies can make well-informed decisions that propel their growth and success. Ultimately, the combination of technology and strategy can transform a business's approach to customer engagement and operational efficiency.

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Media

Integrations Supported

Google Analytics
Meta Ads
Shopify

Integrations Supported

Google Analytics
Meta Ads
Shopify

API Availability

Has API

API Availability

Has API

Pricing Information

$99/month
Free Trial Offered?
Free Version

Pricing Information

$600 per model per month
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Causality Engine

Date Founded

2023

Company Location

Netherlands

Company Website

causalityengine.ai

Company Facts

Organization Name

CX.AI

Company Location

Germany

Company Website

www.cx-ai.com/vsl

Categories and Features

Marketing Attribution

Attribution Modeling
Audience Segmentation
Conversion Tracking
Cross-Channel Attribution
Customer Journey Mapping
Multi-Touch Attribution
Predictive Analytics
ROI Tracking

Categories and Features

Customer Experience

Action Management
Analytics
Customer Segmentation
Dashboard
Feedback Management
Knowledge Management
Multi-Channel Collection
Sentiment Analysis
Survey Management
Text Analysis
Trend Analysis

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