Optimizing Your Campaigns For Weather Can Be As Easy As Watching The Weather Channel
Net Conversion utilizes an AI data-based feed to indicate when weather factors might impact our clients branches / business for optimization opportunities in campaigns.
Our construction based partners have 30+ branches across the continental US with diverse products and services offered. That being said, our clients business is highly driven by weather – a factor that is almost impossible to attribute in digital media efforts and business results. Given that we are a curious and analytics first company – we saw an opportunity to create a weather feed that would indicate optimization windows to optimize toward heavy demand spikes that coincided previously with weather.
- Mainstream a weather feed database – based on a precipitation API – to attribute weather changes with business results.
- Increase opportunities in incremental sales based on weather impacting events in business markets across all 30+ branches.
Net Conversion Advanced Analytics team created a database of rainfall across thousands of zip codes, pulling from a precipitation API. We applied our Region, Brand, and Branch lookups to group these zip codes for the purpose of being able to identify areas receiving rainfall within the next week (available forecasted weather). In a separate analysis of historical data, we found that at least 1 inch of rainfall is needed to yield a positive incremental lead impact. Therefore, our team was able to qualify our weekly alerts to those branches that are going to receive more than 1 inch of predicted rainfall within the next week.
Once we have a forecasted model of weather for each region / bucket of zip codes, and the alert is triggered for a specific location, we are able to re-flow the budget based on the supported anticipated demand per each region. If an alert is triggered for a branch, NC increases budgets in FB and overpaces for that week (specifically in basement & crawl services) by approx +10% daily spend. We quickly realized however most client leads would come a few weeks after rain occurred in their location. Therefore we would continue to monitor campaigns, but by the 3rd of 4th Monday post budget changes, we would reduce budgets once again for display and ensure we were pacing towards our normal budget.
Essentially by optimizing budget based on demand, we are able to up-bid in those specific brands/branches to account for the incremental sales from weather impacted business and services.
With our AI weather feed and budget alert system working hand in hand, we were able to ingest weather changes to previously ignored weather impacted areas, and derive higher quality leads and performance for our campaigns and client’s business. The increased spend resulted in +37% higher volume of platform leads and a -26% drop in CPL (cost per lead). Overall cost per appointment improved by -35% as appointment volume increased by +56%.
Our goal, using the learnings from this case study, is to continue to optimize our weather feed AI and insight process to identify opportunities for weather feed usage across multiple clients and industries that would have weather impacted services.