Although modern life increasingly seems more and more detached from nature, it is clear from the data that, fundamentally, the weather is still one of the greatest influencers of our behaviour - including crucially from an advertising perspective - impacting on our chosen activities and buying habits.

MediaMath has announced an integration for its DSP with IBM Watson's advanced Advertising Weather Targeting to offer contextualised online advertising - targeted at a post/ZIP code level (and crucially without the need for third party cookies) - based on predicted and actual weather conditions in the area. The solution includes complex data sets such as the relative contextual "feel" of the weather - i.e. where the same temperature may feel hot in one geography and unusually cold in another - and how this may impact consumer behaviour differently. On a worrying topical note, it can also pull together datasets such as the latest Covid-19 figures and predicted extreme weather events to forecast and predict potential consumer bulk buying patterns. 

Using weather conditions to predict consumer behaviour (and therefore target advertising accordingly) is not new, but developments such as this show real advancement in the precision and nuance of such targeting, pulling together a vast array of datasets to give a clear contextual picture for an advertiser. It also demonstrates the continued trend towards ever more sophisticated and creative contextual advertising solutions, as usage of traditional third-party cookie based solutions winds down.