Historically, measuring the efficiency of creative has been challenging, due to the difficulty in isolating its impact from other factors, such as execution tactics or brand health. This landmark study proposes a technical Marketing Mix Modelling (MMM) methodology to help brands understand which creative elements have the biggest impact on marketing effectiveness.
We analysed brands in four sectors – automotive, cosmetics, insurance and hospitality – using 3 billion impressions from 2,300 campaigns with almost 23,000 individual creatives across three and a half years, and with a total spend of $8.9m USD. The 124 models in play encompassed multi-stage econometric modelling, and object and text detection (for example, logos, brand cues, products and copy). Critical to the methodology was the selection of both pre-trained and custom-trained Python models for optimal object and text detection performance, with the model selection itself requiring an understanding of the relative merits of when and which pre-trained models to use and how and when to create custom models.
The whitepaper reveals the most efficient features across the study, with sector insights too. But the real juice is in how brands can apply the methodology for themselves.
Download the whitepaper now to find out more.