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What is Stella?

Stella is an innovative platform tailored for marketing measurement, offering marketers scientifically sound insights into which advertisements, campaigns, and media channels drive revenue growth. It includes three key features: Incrementality Testing, Always-On Incrementality, and Media Mix Modeling (MMM). With Incrementality Testing, Stella performs geo-holdout studies, commonly referred to as inverse holdouts, to determine performance variations between test and control regions, thereby isolating the direct effects of advertisements instead of relying solely on attribution techniques. This tool streamlines intricate statistical concepts like causal inference and confidence intervals, enabling users to grasp potential outcomes independent of any specific campaign, and revealing the true "lift" generated by each ad. Additionally, the Media Mix Modeling component utilizes a distinctive Bayesian method to analyze past marketing budgets alongside external factors, such as seasonality and promotional events, to accurately evaluate each channel's contribution to total sales. By employing these sophisticated strategies, Stella not only enhances the decision-making process for marketers but also ensures that the data they rely on is both precise and actionable. Ultimately, the platform stands as a vital resource for marketers seeking to optimize their advertising efforts effectively.

What is Robyn?

Robyn is an advanced, open-source tool for Marketing Mix Modeling (MMM) developed by the Marketing Science team at Meta with a focus on experimental applications. Its primary goal is to support advertisers and analysts in creating comprehensive, data-driven models that evaluate the influence of different marketing channels on key business outcomes, such as sales and conversions, while maintaining user privacy through the use of aggregated data. Rather than relying on the tracking of individual users, Robyn leverages historical time-series data by combining marketing spend or reach metrics—including advertisements, promotions, and organic outreach—with performance metrics to assess incremental effects, saturation levels, and carry-over dynamics. The tool employs a blend of traditional statistical methods and innovative machine learning techniques; it utilizes ridge regression to address multicollinearity in complex models, executes time-series decomposition to separate trends from seasonal variations, and applies a multi-objective evolutionary algorithm for optimization purposes. This cutting-edge methodology empowers businesses to achieve a deeper understanding of their marketing performance, enabling them to make data-driven decisions founded on solid analysis. As organizations increasingly prioritize data-driven strategies, tools like Robyn will play a crucial role in enhancing marketing effectiveness and driving growth.

Media

Media

Integrations Supported

Amazon
Facebook
Facebook Ads
Google Cloud Platform
Instagram Ads
Meta AI
Meta Pixel
Shopify
Snowflake

Integrations Supported

Amazon
Facebook
Facebook Ads
Google Cloud Platform
Instagram Ads
Meta AI
Meta Pixel
Shopify
Snowflake

API Availability

Has API

API Availability

Has API

Pricing Information

$2,000 per month
Free Trial Offered?
Free Version

Pricing Information

Free
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

Stella

Company Location

United States

Company Website

www.stellaheystella.com

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

facebookexperimental.github.io/Robyn/

Categories and Features

Categories and Features

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