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Campaign Measurement

Causal inference

for Sales Lift

Use Snowflake to understand the incremental sales generated from your campaigns with a causal inference analysis

 

Solution Overview

Opportunity

Accurately determine the incremental business driven by your ad campaigns. Using causal inference, isolate variables and understand exactly how your campaign created sales lift for your business. As a result, your optimized targeting strategy will show ads to only the most likely converters.

Solution

Use Snowflake Global Data Clean Rooms to connect an advertiser’s customer data to impression data from the campaign ad platform. With the connected data, the advertiser is able to build machine learning models to measure the incremental impact the campaign had on sales and aim the campaign toward those most likely to be influenced.

Solution Architecture

Data transferring graphics

Technical Detail

Join ad impression logs to sales data in a Snowflake Data Clean Room. Casual inference can then identify confounding variables and quantify sales lift. With a Snowpark UDF, consumers are scored based on predicted uplift.

Benefits

Measuring Sales Lift

Predicting Campaign Impact

Advertisers can  build machine learning models to score their target audiences based on attributes available from the campaign publisher, such as demographics and browsing behavior, allowing the publisher to optimize the advertiser’s ideal campaign outcomes.

Improved Targeting and Bid Optimization

Focus your targeting strategy on only those who are most likely to take action as a result of a campaign. Optimize your bidding strategy to bid more aggressively on your most ideal targets and suppress those who are not likely to convert, creating efficiencies in your bidding and buying strategy.

RESOURCES