Built with data from the world’s most accurate forecaster overall¹ and combined with industry-leading IBM AI technology, IBM Watson Advertising Weather Targeting enables marketers to build a weather strategy that anticipates and responds to consumer behaviors and emotions based on the proven impacts of weather.
Putting weather into action can help brands:
- Understand shifts in consumer behaviors and predict their needs
- Tell their stories at the most relevant moment
- Personalize messages without using traditional identifiers
- Earn consumer confidence by partnering with IBM Watson Advertising and The Weather Channel, one of America’s most trusted brands
In weather, nothing is more important than an accurate and complete understanding of the data and the science behind it, which is why we analyze past, present, and future weather information to establish differentiated seasonal baselines.
The results are actionable targeting insights into how people’s activities, health and buying behaviors are influenced by weather conditions, allowing for hyperlocal ads that encourage consumer action based on the current weather’s impact on moods and behaviors in that specific area.
Updated every 15 minutes:
Over 30 weather variables across 44,000 zip codes within their respective 6 seasons.
Because weather is local and feels different based on location and time of year, we also divide the data into seven conditional ranges that vary by season.
Normalized data based on what is considered typical for time of year in 6 “seasons.”
Recent, current, forecast and seasonal data to add context. Meaning, is there suddenly a big shift from one point in time to another that can contribute to the experience.
Relative-conditions-based triggers activate on various forms of weather, including current condition mixes for inclement weather, hot and humid weather, air quality, pollen count and more.
Activity-based triggers connect with consumers during known condition mixes that align with desired behaviors, such as in-store shopping, outdoor activity and food delivery.
Product-based triggers are built from third-party sales data from sources like iRi and Nielsen to identify the optimal mix of conditions that lead to sales.
Reach likely health & wellness consumers based on privacy-forward signals, such as anonymized patient reports, sales data, academic journals and medical reports.
IBM technology analyzes weather variables, sales data and anonymized third-party data across over 41,600 zip codes in the United States—and an increasing number of international territories—to identify patterns of relevant consumer behaviors.
The insights developed from this data analysis reveal a dynamic picture of consumer responses to weather and create campaign triggers based on those understandings.
These triggers activate media in near-real time across zip codes experiencing the optimal mix of conditions that influence consumer behaviors and drive outcomes.
An automated, targeted data solution that is predictive, privacy-forward and accessible across the advertising ecosystem.
Footnotes
¹Global and Regional Weather Forecast Accuracy Overview, 2017-2020 (commissioned by IBM)