This whitepaper focuses on a rich meta-analysis focused and uses MMM and machine learning techniques to analyze the performance of over 16,000 Facebook campaigns and how execution decisions such as Format, Audience, Reach and Objectives have impacted the business KPI’s delivered.
With spend on Social Media advertising increasing it is more important than ever to study this topic in detail and by comparing performance across a wide sample we have answered key questions on Facebook effectiveness:
Social media plays an important role in the lives of individuals and businesses. Whilst individuals use these platforms to connect to friends and consume content, businesses rely on advertising through them to reach those consumers, build presence and boost their sales.
Advertising on Social Media platforms is generally increasing and one of the reasons behind this growth is the level of execution control they provide to brands. Tools like Facebook Ads Manager allow brands to customize who sees their ads, what they look like and how often they are seen. This also creates a level of detail not seen in traditional media channels, such as TV, Press and Radio.
Execution options make each campaign unique but unfortunately, much of this detail is lost when the impacts of campaigns are assessed together through measurement approaches such as Marketing Mix Modelling. This loss of information means brands don’t truly understand what is driving the results they see and impacts their ability to improve performance in the future.
This paper explores this topic in detail for campaigns activated on Facebook platforms. Utilizing a set of past client econometric models covering over 16,000 campaigns and $81m of investment we have deep dived into Facebook performance to guide brands with simple and actionable best practices to boost performance in the future.
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