Why should weather be included in MMM?

Weather doesn’t just decide whether we grab an umbrella or throw on a pair of sunglasses—it shapes how we shop. From surprise cold snaps to scorching summer heatwaves, weather has the power to instantly sway consumer behavior, either fueling demand or putting it on ice across industries like fashion and grocery retail. Traditionally, Marketing Mix Modeling (MMM) zeroes in on the message (what you're advertising) and the channels (where you're advertising). But often overlooked are the external forces, like weather, that can make or break marketing performance.

But don’t worry—MMM can be enhanced with the power of weather data! In this article, we’ll explore how weather drives consumer behavior and why incorporating this data set into your MMM will help you to explain ups and downs of your efforts in marketing.

Why is it Important to Analyze Weather’s Impact on Marketing Effectiveness?

Weather has a direct and sometimes profound impact on consumer behavior. On hot summer days, consumers are more likely to purchase cold beverages, lightweight clothing, or book vacations. Meanwhile, colder temperatures might drive people indoors, boosting demand for winter wear, comfort foods, and indoor activities. Understanding these shifts can help marketers make smarter decisions when allocating budgets and adjusting campaigns.

However, one key aspect of analyzing the impact of weather is to differentiate between long-term seasonality and short-term weather changes. While seasonality is already accounted for in MMM models, short-term weather variations — such as a sudden heatwave or an unseasonably an unseasonably chilly weekend — can lead to significant deviations in consumer behavior that aren’t captured by seasonality alone.

Certain industries are particularly sensitive to weather fluctuations, seeing significant changes in consumer demand based on temperature, precipitation, and other weather-related factors. Grasping these shifts is a game-changer for businesses aiming to fine-tune their marketing strategies and get the most out of their budgets. When you can anticipate how weather influences consumer behavior, you unlock the ability to not just react, but proactively adjust your campaigns and spending to maximize impact. Here are a few key sectors where weather plays a major role:

Fashion Retail: Weather has a direct influence on fashion choices, making this industry highly reactive to sudden changes in temperature. For example a cold snap can lead to an increase in demand for jackets, scarves, and boots, as consumers seek warmth and comfort. On the other hand, an unexpected warm fall might destroy planned campaigns for winter jackets, hats and gloves and it has nothing to do with the media-mix that you have been planned to boost the campaign.

Sports Apparel: Outdoor sports are heavily dependent on favorable weather conditions, making sports apparel another sector impacted by weather changes. When warm weather arrives unexpectedly, it can drive a boost in sales for running gear, cycling outfits, and other outdoor sports equipment. Conversely, colder conditions may prompt an increased interest in indoor workout apparel, as consumers shift to indoor fitness activities.

Travel: The travel industry is also significantly affected by weather patterns. Sunny and mild weather often triggers a rise in vacation bookings, as people look to escape for outdoor adventures. However, during rainy or cold periods, consumers may prefer indoor getaways or trips to warmer destinations. Understanding these trends allows travel companies to adjust their marketing plans accordingly and capitalize on favorable weather conditions.

Grocery Retail: Weather can also dramatically influence consumer behavior in the grocery sector. During cold weather, consumers may stock up on comfort foods, soups, or hot beverages, leading to increased demand for these products. Warmer weather, on the other hand, often sees a rise in purchases of fresh produce, cold drinks, and items for outdoor grilling or picnics. Sudden storms or extreme weather events can also drive last-minute demand for essentials like bottled water and non-perishables, as people prepare for potential disruptions.

How Weather Data Improves the Accuracy of MMM?

Incorporating weather data into MMM can supercharge its ability to analyze short-term shifts in demand. Imagine a sudden temperature drop sparking a surge in winter coat sales, or a stretch of hot, sunny days triggering a rush for swimwear and air conditioners. On the flip side, an unusually chilly summer could slow down sales of outdoor furniture or seasonal accessories as shoppers adjust to cooler-than-expected weather.

Below is a conceptual representation of your sales calendar for the year. Imagine red bars representing products associated with hot weather (e.g., swimwear, outdoor furniture) and blue bars representing cold weather products (e.g., winter coats, boots). Each month will feature varying heights for the red and blue bars, depending on weather patterns and consumer demand. Keep in mind, this is just an example because weather can be pretty unpredictable 😉.

For example:

• January and February: Taller blue bars as cold weather boosts winter product sales, while red bars are short or non-existent due to low demand for hot weather items.
• May to August: Red bars rise significantly as warmer weather increases demand for summer products, and blue bars drop or dissapear.
• November and December: Blue bars rise again, showing a peak in cold weather product sales.

If you integrate the weather data in your model then it can accurately capture these short-term shifts in consumer behavior. This improves both the predictive accuracy of the MMM and the better-informed budget decisions because you can anticipate and respond to fluctuations driven by weather changes.

Challenges in Adding Weather Data to MMM

While adding weather data to your MMM can significantly enhance its performance, there are some challenges to consider:

What to Measure: Weather data is rich with variables—temperature, precipitation, humidity, wind speed, and more. The challenge lies in identifying which factors will most impact consumer behavior. Temperature and precipitation are typically the most influential, as they have immediate effects on what people buy—whether it’s coats for the cold or ice cream for a sunny day.

Which Signals to Look For: For: Instead of relying on average weather conditions, focus on extreme or unusual deviations from the norm. A typical winter might already be factored into seasonal trends, but an unseasonably warm winter or a sudden heatwave will significantly alter consumer habits. These unexpected deviations in weather provide crucial signals that your MMM should track to understand short-term shifts in demand.

Understanding Product Categories: One of the biggest hurdles is recognizing that not all products are affected equally by weather changes. For example, a cold snap may increase demand for winter wear but might have no effect on electronics sales. To truly maximize the value of weather data, you must use product-category-specific models that capture the unique weather sensitivities of each product line, allowing for more tailored and precise forecasts.

Weather Helps Explain the Base

There are times when sales may drop or spike unexpectedly, and without incorporating weather data, these movements may appear random. Weather helps bridge the gap between what would otherwise be unexplained changes in consumer behavior and real-world environmental factors. For example, a sudden drop in sales during a rainy season or a sharp increase during an unusually hot period becomes more understandable when weather data is part of the equation.

Moreover, integrating weather data gives you a more precise analysis of base demand versus short-term deviations. Understanding how specific weather conditions impact consumer purchasing habits means you can refine your baseline forecasts. In turn, this improves the accuracy of your model’s uplifts (or the incremental effects of your marketing spend), because your MMM can now account for external factors that influence consumer decisions. As a results your model becomes better at predicting both base sales and the impact of marketing activities. If you want to learn more about calibrating your MMM you can read about it here.

Integrating Weather Data

Obtaining weather data for MMM is a relatively straightforward thanks to a variety of providers, such as Open-Meteo , who offer historical and real-time weather datasets through flexible, subscription-based models. To fully leverage weather data, it is critical to move beyond using “average” weather conditions, as these are already largely accounted for by the seasonality components of most MMM frameworks. Instead, the key lies in focusing on deviations from normal weather patterns—such as anomalously warm winters or unexpectedly cold summers. These deviations are where the true explanatory power resides because this way you can gain insights into short-term demand fluctuations that cannot be captured through seasonal trends alone.

Moreover, integrating weather data effectively needs a nuanced understanding of how specific weather variables interact with consumer behavior across different product categories. Simply adding temperature as a linear factor might not be enough because the relationship between weather and demand often varies in complexity and intensity depending on the sector. For example, a few degrees’ deviation might have a significant impact on sales of winter apparel, while the same variation might barely affect demand for indoor home goods. Essentially, when incorporating weather data into MMM we must carefully examine both product-specific sensitivities and the timing of weather anomalies in order to be able to optimize the predictive accuracy of the MMM.

Conclusion: Weather—The Untapped MMM Superpower

Integrating weather data into your MMM can unlock deeper insights and better predictive accuracy. Whether it’s understanding the base or capturing short-term deviations, weather data offers a crucial layer of analysis that helps you stay ahead of consumer behavior shifts. To fully capitalize on its power, focus on tracking the right weather variables, analyzing deviations from the norm, and customizing your approach by product category.

Ready to take on weather with your MMM tool?

Make it rain! ☔