Why Integrating Weather-Driven Demand Analytics with
Promotion Management can improve Retailer’s Bottom Line
Often one of the first things people do is check the weather when starting their day. Weather plays a huge role in the clothes we choose to wear, the activities we do for the day, the food and drinks we consume, and even our emotional state.
Recent research has shown that weather has the second biggest impact on consumer behavior right after the state of the economy. Different weather states can determine how consumers shop, what they purchase, when merchants launch new lines, and when sales seasons begin.
With the power of advanced technology, retailers now have the ability to pair weather data with their strategies in an effort to meet their customers’ needs.
Throughout the article discover the impacts weather-driven demand has on promotion performance.
One of the major keys to a successful promotion is if it’s customer-centric. Today, top retailers follow these strategies to ensure their promotions align with their customer’s behaviors:
One area that is often overlooked? Understanding the weather’s impact on your customer’s priorities.
By combining both promotion management strategies and weather-driven demand analytics, retailers can further optimize their promotions by providing the right products, at the right price, in the easiest obtainable way for their customers.
Here are a few examples of how weather impacts promotion performance:
By including weather analytics in the forecasting stage, retailers are able to make even better predictions about purchasing patterns. Why? Because it can give accurate insight into a specific product or location that will be directly impacted by weather.
With more information comes more accuracy, meaning retailers can feel confident about what the demand will look like for the specific product, how much they will need to order, and ensure the promotion will be released to the right audience, at the right time, and to the right location.
Business weather intelligence can give retailers insight up to 2 weeks in advance of their promotion running. This allows merchants to adjust their promotion strategies if there was a shift in demand due to weather.
If there is a drastic change in weather from when previous promotions were run, retailers risk ordering too much (which can lead to waste), or not ordering enough (resulting in lost sales).
By layering specific predictive demand analytics onto current promotion solutions, retailers are able to see how changes in upcoming weather conditions will either increase or decrease demand and update their orders accordingly to avoid too much or too little inventory.
Now that we understand the impact weather has on promotion performance, let’s provide a few use-case examples of how weather analytics can work alongside a promotion management solution.
Tina works in buying and forecasts promotions for inline and online items. She is going to run a key wintertime promotion on a product and wants to forecast how many units she should purchase.
By utilizing business weather intelligence within her promotion solution, Tina is able to gain insight into the:
Through her analysis, she was able to see that where the weather had been favorable, the sales were higher than the promotional and weather lift suggested. This synergistic effect shows Tina that the product is highly sensitive (in a positive way) to weather and will perform even better when paired with a promotion.
By having access to this information, Tina is able to:
Phil, a category merchant for a grocer, has created a promotion on hotdogs to run throughout the heat wave in New Hampshire and submitted it for approval. Two weeks before the promotion is set to run, he receives an alert about drastic changes in the weather. The weather went from warm and sunny, to gloomy and heavy rain.
Since hotdogs are grilled outside, there has been a drop in demand than what was originally anticipated. Phil can either kill the promotion, reduce the amount of product, or run a different promotion on another product that will perform better.
An abnormal snowstorm is predicted to happen in Minneapolis, Minnesota when a grocery merchant plans on running a promotion for a fresh product. Though the merchant is running the same promotion across all of the stores in the US, the promotion in Minneapolis is no longer predicted to run as well.
With the help of weather analytics, merchants are able to see two weeks in advance the drastic drop in demand for that specific region. Because the product on promotion is fresh, they risk dealing with waste.
To avoid having too much product on hand, the merchant changes the amount that needs to be ordered ahead of time.
About Planalytics!
Planalytics’ predictive weather-driven demand analytics enable retailers to understand, precisely quantify, and proactively manage the most omnipresent external influencer of consumer buying decisions.
Weather-driven demand analytics apply advanced statistical methods and machine learning, mountains of sales data, and years of unmatched retail demand expertise to help retailers and other consumer-based businesses factor in the impact of weather to better anticipate demand, increase customer satisfaction, and improve financial performance.
About Cognira
About Cognira
Cognira is the leading artificial intelligence solutions provider for retailers. Cognira is passionate about helping retailers unlock valuable, transformative business insights from their data.
We know retail. We love data.
To learn more, check out our website at cognira.com or contact us today to get started.
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