Haus

"Optimizes marketing investments with data-driven experiments."

This company helps marketers figure out which marketing activities are really driving sales through data-driven experiments. They test marketing strategies to ensure money isn't wasted, aiming to boost growth and maximize returns on investment.
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Haus Stated Claims
Below are public claims our AI believes to have been made by Haus.
Superior science
Haus claims that they use cutting-edge measurement techniques grounded in econometric models, avoiding black boxes.
Fast & automated
Haus claims that you can design and launch experiments in minutes, and get results in as little as two weeks.
Comprehensive measurement
Haus claims that you can test incrementality across all your marketing channels and identify & measure impact everywhere you sell.
INCREMENTALITY TESTING
CROSS-CHANNEL A/B TESTING
OMNICHANNEL MEASUREMENT
OPTIMAL SPEND LEVEL
NEW CHANNEL LAUNCH

BlurbSTAR Case Study
Hexclad & Haus
Extended measurement reveals Meta ads' true efficiency for Hexclad.
56%
CPIA decreased by 56% in the normal ad spend group.
67%
CPIA dropped by 67% in the increased ad spend group.
1.
Situation
Hexclad's 12-piece pan set, priced at $699.99, faced a long customer consideration phase. The company needed to measure the incrementality of their Meta ad spend over this extended purchase journey, as traditional last-click attribution and platform reporting methods were insufficient.
2.
Task
Hexclad partnered with Haus to conduct an incremental impact test using geo-holdouts. They aimed to determine the optimal investment level in Meta ads and assess how the incrementality of these ads changed over the long consideration phase for a high AOV product.
3.
Action
Using GeoLift, Hexclad implemented a 3-cell optimal spend level test across the US, dividing it into three geographic groups. One had normal ad exposure, another had increased spend, and the control group had no ads. They analyzed sales on Shopify and Amazon over a two-week period, extending the measurement window by three weeks to capture lagging sales effects.
4.
Result
Initially, increased Meta ad spend showed less efficiency. However, after the extended observation, CPIA decreased by 56% in the normal spend group and 67% in the increased spend group. This highlighted the importance of a longer measurement period for high AOV products. Hexclad now plans to test other channels for comprehensive media mix optimization.
Keywords
INCREMENTALITY TESTING
GEOLIFT
META ADS
HIGH AOV PRODUCT
CUSTOMER CONSIDERATION PHASE
GEO-HOLDOUTS
OPTIMAL AD SPEND
HAUS
HEXCLAD
SHOPIFY SALES
AMAZON SALES
MULTI-WEEK PURCHASE JOURNEY
MEDIA MIX OPTIMIZATION
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Haus
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