The client, a leading media agency in North America, specializes in running multiple online ad campaigns for FMCG and electronics brands across the world. As a creative and technology partner for these brands, the media agency helps them to make strategic campaign management decisions in the modern marketing landscape.
The client wanted to analyze the effectiveness of online campaigns — for brands they manage — on sales in physical stores. The client partnered with 10+ brands that have physical stores across major cities in the US. For instance, one partner, Hewlett-Packard, has more than 100 retail stores across the US.
The online campaigns predominantly focused on video and display content delivered through video and social platforms. Nabler’s task was to design and develop a methodology to measure their advertising success with ROAS.
Nabler conducted extensive data discovery sessions, exploratory data analysis, and Design of Experiments to collect the best data for modelling quickly and efficiently. Nabler’s Data Science Consulting team then developed and deployed a framework for ROAS measurement. The implementation was executed in two phases by setting up test and control Randomized Control Trials (RCTs):
Nabler used historical time series of sales data and demographics data for the Designated Market Areas (DMAs). Upon selecting the test and control DMAs using time series correlation, Nabler launched the campaigns in test DMAs while restraining control DMAs.
Sales in control DMAs were used as regressors to generate a counterfactual estimation to predict sales in test DMAs without a campaign. Since highly correlated test and control DMAs were selected in the pre-campaign phase, Bayesian structural time series models were used to conduct the analysis. The difference between the predicted value and the actual sales value in the test DMAs provided an estimate of the lift in sales due to the campaign.