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ease
features
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support

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Description

Haus is a cutting-edge marketing science platform that provides brands with the ability to accurately assess the true business effects of their advertising campaigns, whether conducted online or offline, by utilizing automated incrementality experiments. It features innovative products such as GeoLift for geographic incrementality testing, Causal Attribution for regular incrementality assessments, and the soon-to-be-released Causal MMM for media mix modeling driven by incrementality. These advanced tools empower users to quickly design and execute experiments within minutes, receive results in as little as two weeks, and enhance their marketing strategies through daily incrementality insights. Furthermore, Haus is committed to offering privacy-conscious solutions that avoid the use of pixels, cookies, or any personally identifiable information, which ensures adherence to the latest privacy regulations. As the landscape of digital marketing continues to evolve, Haus remains at the forefront, equipping brands with the necessary tools to navigate these changes effectively.

Description

A no-code AI platform designed for enterprises transforms raw data into enhanced business insights. In the pursuit of valuable information within extensive data lakes, misleading correlations can contaminate findings, resulting in unreliable signals for organizations. CausaLake smartly identifies the most relevant data tailored to specific use cases, standing out as the sole technology capable of delving beyond correlated indicators in comparable datasets to pinpoint causal factors. Causal AI models illustrate the workings of various systems, encompassing economies, businesses, and biological entities. They offer a high level of trust and transparency, merging the strengths of human expertise with artificial intelligence. CausaLab represents the pinnacle of causal model discovery technology. The essence of AI transcends mere future predictions; it aims to actively influence outcomes. For AI to facilitate high-quality decision-making, it must grasp the human context alongside the goals and limitations of organizations. To address this challenge, we introduced decisionOS, which effectively connects predictions with actionable decisions, empowering organizations to optimize their strategies.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Haus

Founded

2021

Country

United States

Website

www.haus.io

Vendor Details

Company Name

causaLens

Country

United Kingdom

Website

www.causalens.com/causal-decision-making-ai-platform/

Product Features

Marketing Analytics

A/B Testing
Campaign Management
Channel Attribution
Customer Journey Mapping
Dashboard
Performance Metrics
Predictive Analytics
ROI Tracking
Social Media Metrics
Website Analytics

Product Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Decision Support

Application Development
Budgeting & Forecasting
Data Analysis
Decision Tree Analysis
Monte Carlo Simulation
Performance Metrics
Rules-Based Workflow
Sensitivity Analysis
Thematic Mapping
Version Control

Alternatives

Alternatives

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