Real Impact
Real Impact causal modelling tool allows us to prove the correlation between two disconnected data sets.
CASE STUDY
END. – Dynamic Product Feed Ads with Meta to Generate Full-Funnel Growth, with proven incremental impact
Objective
END is a global online fashion retailer. Tug was appointed to implement dynamic product feed ads on Meta, generate full-funnel growth, and verify their incremental impact. The objective was to prove the efficacy of social advertising without cannibalising organic traffic and deliver measurable e-commerce results. Tug runs a successful SEO campaign for END and was tasked with proving that we wouldn’t cannibalize organic traffic.
Challenge
END runs paid search in-house but did not have the resources to test paid social. Tug was briefed to deliver a three-month test. Tug already runs a successful SEO campaign for END and was also tasked with proving that paid social efforts would not cannibalise organic traffic.
Solution
At launch, Tug ensured all client data was robust and accurately fed into Meta’s platform, providing a continuous data feedback loop for real-time campaign optimisation. Leveraging the latest machine learning technology and a dynamic product feed, Tug delivered individualised ads to customers and lookalike audiences in real time across END’s entire product range. Tug then deployed Real Impact, its causal measurement tool, after the test period to measure the true impact of the social media campaign on e-commerce sales.Results
+34%
Increase in average basket size.
126%
ROAS in the first 4 weeks.
87%
Confidence in attributable incremental revenue directly from the paid social test.
Tug Labs
