Weather-dependent performance analysis
Analyze advertising performance by matching it with weather data (weather type, temperatures...)
Objective
Analyze advertising performance by correlating it with weather data, including weather types, temperatures, and other meteorological factors. This analysis helps advertisers understand how weather conditions impact consumer behavior and purchasing patterns, allowing for more targeted and effective advertising strategies. By identifying weather-related trends, advertisers can optimize their campaigns to capitalize on favorable conditions and mitigate the impact of unfavorable weather on sales.
Key benefits
Improved campaign targeting
Seasonal trend optimization
Inventory management enhancement
Localized marketing strategies
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How it works
Correlate advertising performance with weather data across retail media networks and marketplaces. Identify weather-related trends to optimize campaign targeting, adjust bids automatically, and capitalize on favorable conditions for increased ROI.
Data integration
Use mimbi COLLECT to import advertising performance data (impressions, clicks, conversions, sales) from multiple retail media platforms. At the same time, integrate historical weather data for relevant locations and time periods from a dedicated weather data connector.
Data alignment and enrichment
Leverage mimbi TRANSFORM to align advertising performance metrics with corresponding weather data. Enrich your dataset by adding relevant weather attributes (e.g., temperature ranges, precipitation levels, weather types) to each data point.
Correlation analysis and pattern identification
Conduct advanced statistical analyses, identify correlations between weather conditions and advertising performance metrics. Discover patterns such as which product categories perform better in specific weather conditions or how temperature changes affect conversion rates.
Strategy implementation and automation
Based on the insights gained, create automated rules and adjustments for your advertising campaigns. For example, automatically increase bids for winter clothing when temperatures drop or boost visibility for outdoor products during sunny forecasts.
Product ROI bucket analysis
Weather-dependent performance analysis
ACOS and TACOS correlation analysis
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