Haus

Measure the true impact of ads with geo-based randomized experiments

Freemium 4.0

Haus runs geo-based randomized experiments to measure the true incremental effect of ad spend, letting brands test channel budgets, creative strategies and pricing without relying on platform-reported conversions.

Key Features

Geo-based randomized experiments
Cross-channel budget testing
Creative strategy evaluation
Pricing strategy testing
Independent performance attribution

Pros

Breaks free from platform self-attribution bias
Provides objective incremental data
Helps optimize marketing budget allocation

Cons

Requires a certain scale of ad budget
Experiment design and execution require expertise

Use Cases

Testing budget allocation across different marketing channels
Evaluating the real effect of new ad creatives
Analyzing the true impact of price changes on sales

Editor's Note

A marketing-science tool that cuts through platform myths, helping you accurately assess the true value of every ad dollar.

FAQ

How does Haus differ from ordinary ad-platform attribution?

Ordinary ad platforms usually use their own-perspective attribution models that tend to overstate performance, whereas Haus measures the true incremental effect of ads through geo-based randomized experiments.

What kind of brands are best suited to use Haus?

It suits brands and e-commerce companies with a certain ad-budget scale that want to more accurately evaluate cross-channel marketing effectiveness.

Do I need a data science background to use Haus?

Although the platform simplifies the experiment process, it's still recommended that a team with marketing-experiment or data-analysis skills plan and interpret the results.