Facebook has added a new Experiments section in Ads Manager that includes multiple types of tests previously available from Test and Learn, and Split Test.
Testing is an important tool for marketers that lets them make better decisions by finding out what works better for them, what doesn’t, and where they can find new opportunities for growth.
To help marketers run tests with their Facebook ads, Facebook is launching a new Experiments section in Ads Manager that brings together multiple types of tests formerly labeled as Test and Learn and Split Testing.
The new section includes the ability to run four types of tests – A/B Tests, Holdout Tests, Brand Surveys, and Campaign Budget Optimization Tests.
A/B tests lest marketers compare their creative and audience strategies and other variables in order to find out what works best for them. This will allow them to optimize their next campaigns. A/B tests help them answer questions, such as: Which creatives perform better? Which CTAs perform better with a particular audience?
Key Metrics: Cost per Result, Cost per Conversion Lift
Holdout tests make it easier for marketers to measure conversions that are driven by their ads. The way they work is rather simple, as Facebook compares conversion rates of people who saw the ads with those of people in a holdout group. Members of the holdout group are never shown the ads. The test uses this information to calculate lift in conversion events like purchases.
Key Metrics: Conversion Lift
Brand Surveys help marketers understand the brand impact from their ads. The idea is to find the effect on things like awareness, perception, recall and more. Brand surveys work by polling people who’ve seen an ad and polling a holdout group who hasn’t. Facebook then aggregates and compares results, thus making it easier to measure how ads impacted a brand objective. This also helps marketers confirm whether they’re investing in the right strategy.
Key Metrics: Brand Lift
Campaign Budget Optimization Test
Campaign Budget Optimization tests allow marketers to test campaigns using budget optimization versus others that aren’t, measuring the difference between the two. The test automatically randomizes an advertising audience to determine which of the two strategies works better.
Key Metrics: Cost per Result
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