Badcock Home Furniture &more and Sonny’s BBQ
The Magic of the Media Analytics Process
How &Barr delivered a blueprint for maximizing media spend.
Data Collection, Correlations Analysis, Statistical Modeling, ROAS Optimization
By leveraging robust data analytics processes, including data collection and analysis, correlation analysis, statistical modeling, and ROAS optimization, &Barr’s DMA Team was able to provide valuable insights and recommendations for both Badcock Home Furniture &more and Sonny’s BBQ.
&Barr’s DMA team is dedicated to one thing above anything else: delivering results that make an impact for our clients. Two challenges had arisen: a reduced media budget from Badcock Home Furniture &more, and a decline in off-premise sales at Sonny’s BBQ. Badcock’s reduced budget meant finding a way to make every dollar work harder, and Sonny’s drop in sales raised questions on which channels were most effective.
THE DATA’S IN THE DETAILS
Both clients benefited from one thing: a history working with &Barr. For Badcock, the DMA team was able to work backwards over the past three years, analyzing decisions driven by various business and priority shifts. The team poured over the Sonny’s integrated media plan, double-and triple-checking accuracy and consistency between data sets. Conducting a correlation analysis for both clients helped to identify the media that had the highest impact on sales, allowing us to recommend a newly-optimized media investment plan.
RESULTS IN ROAS
Based on findings from statistical models and correlation analyses, &Barr’s DMA team was able to recommend strategies that optimized Return on Advertising Spend (ROAS) for both clients. Every decision made was backed by data. Our recommendations to Badcock maximized their spend, helping them reach the desired ROAS while driving in-store foot traffic and sales. Our suggested changes to Sonny’s digital media spend allowed them to achieve sales growth. While the two clients faced different challenges, &Barr’s media team’s ability to expertly analyze and interpret data meant we’d be able to navigate both of them with ease.