Advertisers have one common objective: Reach the customer with the right product message at the right time at the right place. Obviously, this goal is related to weather as customers’ interest varies by weather. Sales for chocolate increase on cold days while cold beverages soar on hot days. While this relationship is not novel, properly determining the weather index based on data however remains critical as weather effects greatly vary by product, season, day and region.
How can we utilize the weather dependency of products to improve programmatic advertising? Dr. Christian Schneider, Senior Machine Learning Expert at wetter.com, will explain (a) how to combine weather and product data with data science methods to create regional product weather indices and (b) how these indices can be automatically applied to foster the efficiency of digital campaigns using used common ad-tech solutions.