Tag Archives: weather analytics

Good Weather Data Is Hard to Come By; It Doesn’t Mean Much without Analytics

Compiling and implementing strong data practices to analyze can certainly help to improve strategic decision-making and mitigate risk. It could also help to optimize customer experience and increase process efficiencies across the board. However, while there are certainly many benefits to having data, data does not give you the insights or answers to make quality business decisions. Weather data is one source that many companies use, but struggle to understand. This is why weather analytics is more effective to use when evaluating business weather impacts.

The Problem with Collecting Quality Data

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Translating weather data is difficult enough for any organization. What do you do with all of that data? Many organizations throw tons of weather data at their employees when weather “hurts” the business. But weather data doesn’t provide the answers or insights to how weather is impacting your business.

How Weather Analytics Can Help You Connect the Dots

This is where accurate climate analytics comes in. Trying to do it on your own can be costly, take away from other strategic initiatives, and could create incorrect decision-making based off inaccurate analysis.   What do we mean when we talk about weather analytics to solve this problem? It is a multi-disciplinary, multi-faceted approach that takes into account all of the factors that drive changes in customer behavior due to the weather. Leading weather analytics providers analyze a company’s history sales data along with historical weather data to identify the weather drivers specific to their business. Weather is notoriously volatile as it only repeats itself year-to-year about 15-20% of the time. Business Weather Intelligence from Planalytics can help organizations bridge the gaps of knowledge to achieve a better understanding of how the weather really affects sales.

Therefore, many companies might find it beneficial to enlist Planalytics to help them gain a better understanding of how weather is driving their business sales. Getting clean weather data is difficult enough; knowing what to do with it is a whole other matter altogether.  When companies measure weather’s impact and create a weather-adjusted baseline for planning, retailers improve forecast accuracy and typically recapture 20-100 basis points of profit through inventory optimization improvements alone.

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A Final Look at December Retail Sales and Why Retailers Can’t Wait for Spring

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If retailers have a vested interest in whether or not Punxsutawney Phil sees his shadow or not, you can’t blame them. According to recently released data from the National Retail Federation, retail sales in the months of November and December only rose 3%. Before the holiday season started, it forecasted 3.7% growth. Specialty apparel stores were among those hit the hardest, losing close to $600 million in revenue over the course of the season. Department stores and other major stores were not included in this number.

In a Fortune.com article detailing holiday season results on major retailers in the country, many stores suffered setbacks in holiday sales. Macy’s, for example, took a 5.2% loss in comparable sales. Gap and Best Buy also experienced a significant loss in sales compared to other years, forcing them to reassess their operations and marketing plans in the next quarter. So the question then becomes how did this happen? According to the National Retail Federation, there were several factors in play.

 

Warm Weather, Early Promotions, and More Online Spending

 

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In his assessment of the holiday seasons sales report, NRF President Matthew Shay said the following: “Make no mistake about it, this was a tough holiday season for the industry. Weather, inventory challenges, advances in consumer technology and the deep discounts that started earlier in the season and that have carried into January presented stiff headwinds.”

In many areas in the country the weather was warmer this holiday season than ever before. In the Democratic Presidential Primary Debate, Bernie Sanders even remarked how it was significantly warmer in Burlington, Vermont than it had ever been before. He is not wrong. The second, third, and fourth weeks of December were the warmest in over 55 years for the New England region, while the Mid-Atlantic, East North Central, and West South Central regions all had 2 out of the 5 weeks trend warmest in 55+ years. Macy’s attributed 80% of its holiday sale losses to the weather. The Burlington Coat Factory experienced poor winter clothing sales and is now only showing figures that exclude its coat sales.

Because of this clothing retailers will need to heavily discount their winter clothing to make up sales and reduce inventory. Although Old Man Winter has recently made his presence known in New England and the Mid-Atlantic, retailers are gearing up their spring inventory planning. Spring inventory is typically seen in February and March. Therefore, they must discount their winter inventory to make room for spring items.

In addition to the weather, early promotions and consumer shopping behavior all impacted sales. Many shoppers stayed at home and shopped online or shopped early when they saw heavily discounted items. These discounts had a great impact on margins, which hurt sales for retailers even further.

 

What Lesson Should Retailers Learn from This Holiday Season?

 

In short, retailers who experienced losses during the holiday season will have to take better care to use weather analytics to determine how weather affects their sales. While retailers eventually caught on and responded accordingly with sharp discounts and other promotions to encourage people in the doors, the damage was already done. The fact that some companies attribute weather as 80% of the reason why they lost sales shows the importance of weather trends in future strategic plans.

 

 

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Why 90° Doesn’t Mean It’s Hot Outside for all Consumers

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Every consumer experiences weather conditions differently. A “hot” day for someone in Buffalo, NY doesn’t affect a resident of Atlanta, GA the same way.. There aremany variables in play that affect perception of the weather, such as location, time of year, and recent weather experiences. This is important for retailers to understand because weather volatility can affect how we shop and what we shop for. Therefore, businesses that understand how the weather shapes consumer behavior and the benefits of weatherization will be best suited to handle weather’s effect on the consumer.

 

The holiday season is in full swing, which means winter is just around the corner. Although much of the country has been experiencing warmer temperatures this November, cold snaps this time of year can have a dramatic effect on consumer behavior. One very “cold” (temperature is all relative) day in November can drive consumers to make those cold weather purchases such as apparel and hot beverages.

 

To that same end, the same temperature a consumer experiences in November has a very different affect in early March. That same weathercould drive consumers to start thinking about making warm weather purchases as they have undergone a whole season with colder temperatures. The two examples highlight just a few of the many factors that go into weather perception.  The time of year, your location, and previous weather experiences have an impact on how you feel. 60 degrees in New York City in June would feel a lot differently than 60 degrees in San Antonio. Weather  is relative depending on the variables.

 

Using Weatherization Tools to Better Predict Consumer Response to Weather Volatility

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Retailers that want to understand how variances in weather can affect customer behavior must invest in business intelligence tools that focus on weather analytics. Looking at weather data does not provide the answers to how weather is impacting your business.

 

Weather analytics from Planalytics can help organizations enhance strategies to effectively leverage the opportunities and mitigate risk associate with weather volatility.  While perception of the weather may be relative, preparation should not be.

 

Weather volatility, like all other external variables impacting a business, should be managed. Investing in a sophisticated solution like predictive analytics software can allow organizations to improve their merchandising, marketing, labor, logistics, finance, facilities management, and other business areas to support customer demand. Weather analytics removes weather volatility from sales history to create a deweatherization baseline to more effectively align plans.

 

Given the complicated nature of weather perception, retailers that can best utilize weather analytics to adjust internal processes to maximize profit. Learn more about weather analytics today by visiting www.planalytics.com.

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How the Mere Threat of a Hurricane Can Disrupt (and Benefit) Businesses

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When there is a threat of a hurricane, most people affected will take it very seriously. A hurricane can produce very unwelcome consequences – from damaged homes due to the high winds to flooding and power loss. Fears of these results can create a panic just by the mere mention of a hurricane. Therefore, even if a hurricane does not directly hit a region, it can have major consequences that can affect businesses of all kinds.

Take, for example, some of the headlines we saw in the media for Hurricane Patricia. “Biggest Potential Storm Ever” and “Dangerous Hurricane Patricia” were two phrases that stood out. The best, though, was from Doyle Rice of USA Today: “Patricia’s 200-mph winds will turn planes, vehicles into airborne missiles.” Understandably, residents, travelers, and business owners decided to heed on the side of caution and travel as far inland as possible. The potential consequences of a natural warzone were enough to get them to leave even if it caused some disruption in their lives. Luckily, there wasn’t a panic as meticulous planning and past experience enabled those affected to respond quickly and efficiently.

 

Hurricanes and Hysteria

 

In a blog post for PsychCentral, psychiatrist, John M. Grohol, outlined some fears that could lead to a panic. First and foremost, there is the fear of the unknown. The trajectory of a hurricane can change very quickly, which can create anxiety among those who may be wondering whether or not the storm will make landfall and how hard it will hit. In the case of Patricia, Mexico was for the most part spared. The storm regressed into a tropical depression and landed in a mountainous area of Mexico where the typography was able to sustain it. Still, anyone within the scope of Patricia’s projected path was affected in one way or another.

Then there is the fear of what happens if the worst does occur. A hurricane that directly hits a region could cause extreme damage, leave the area without power, and cause many to wonder whether or not they have enough food and water. What if Patricia didn’t slow down and landed somewhere where the winds would have produced more damage?  What if it had hit a populous area or an area with utilities and other potential hazards? We saw how Sandy disrupted the lives of those in the Mid-Atlantic and New England. What impact would an even more powerful storm have on a region?

 

How Can Businesses Respond to Extreme Weather?

 

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Because of these fears, consumers are more likely to act on the side of precaution when there is a threat of a major storm like a hurricane. They will likely fill up on gas, purchase the necessary food and water rations, and consider getting disaster recovery products, like generators and duct tape, to ensure that they will be ready if the storm does hit.

Notice that the key word in the previous sentence is “if.” When consumers are asking the question of “if?”, then businesses will be affected whether or not the storm actually does hit. This is why companies of all sizes that have locations where hurricanes can hit must consider investing in Weathernomics tools and services to help them plan for consumer demand during hurricane season.

An investment in Weathernomics allows businesses to see how and why customers make purchases because of the weather. Weather data is not enough because it does not tell the whole story. What if there was an aberration in sales during a week several years before, but the weather data showed that there wasn’t a significant weather event during that time? Weather analytics can provide a deeper picture to see whether or not there was the threat of a storm and how consumer behavior changed because of it.

By using Weathernomics, businesses can better plan before the season and update plans in-season due to changes in weather. Businesses can not only make changes in inventory, but also amend marketing plans, logistics, labor, and other operations planning to stay ready for whatever the season may bring.

In the event of a storm, most people will usually prepare for the worst. The weather can produce an emotion-based response in how people shop and what they shop for. Businesses, however, must have a logical response to the weather. They must provide the products and services their customers need based off whatever the weather forecast is. The best way to understand how their business could be affected by the mere threat of a major storm like a hurricane is by including Weathernomics in their higher order strategic planning.

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Why Weather Facts Aren’t Enough – the Case for Weather Analytics

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Data is great for businesses. It gives insights into customer demographics, what products perform best, and staffing needs– to name a few. However, data doesn’t provide the answers to help improve your business’s higher strategic planning to boost sales and mitigate risks.

 

Companies who solely use weather data find it extraordinarily difficult to utilize because there are so many variables which makes data aggregation problematic. In the past several years, more organizations have looked at weather data to help them understand how the weather will affect or have affected the sales. Unfortunately, so few know what to do with it. In the end, many executives have an excess of weather data, but little understanding of how to improve their bottom line. Here are several reasons why solely using weather data is unsuccessful:

 

There Are Regional Variances: Temperature is absolute. How temperature feels is relative. For example, it’s the end of summer right now in the Mid-Atlantic region of the United States. If the temperature were to drop to 55⁰ in New York City, that would feel very cold to consumers and they would start buying outerwear and hot chocolate. However, if the temperature were to drop to 55⁰ in Fairbanks, Alaska right now, it wouldn’t have a significant impact on consumer behavior since that is the normal temperature this time of year.

 

There Are Temporal Variances: To that same end, if there was a high of 55⁰ in Philadelphia in September, consumers would feel very cold and look to purchase sweaters or fire logs. However, if the temperature were to hit 55⁰ in the middle of February, consumers would be reaching for their shorts as it would feel like spring. The temperature may be the same in the same location, but the time of year will create major differences in consumer behavior too.

 

Businesses that have weather data but have no idea how to translate that data into weather intelligence are encouraged to check out Planalytics’ business forecasting tools. Planalytics provides weather analytics, actionable intelligence companies need to manage weather’s impact on business and improve their bottom line.

 

Contact us today to learn more about why weather analytics matters.

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Using FlashWeather to Make Better Weather-based Business Decisions

What was the weather like last week in your markets? While you can easily find this weather data, can you use the information to identify sales opportunities? Probably not. This is where weather analytics has been revolutionizing how businesses leverage the weather to improve their sales.  Understanding the weather and leveraging analytics to forecast sales and its effect on consumer behavior is an untapped resource that businesses are only beginning to understand. For example:

It’s 85 degrees in New York City in May. What does this mean for customers there, and how do purchasing trends differ here on a hot day in spring than for customers in Phoenix?

It was a warmer winter last year. How do businesses quantify the impacts and build an effective sales plan for the upcoming winter?

Scenarios like these are commonplace in retail, food service, and other industries, and determining how consumer behavior is affected by the weather by region and by season can greatly impact your bottom line. Planalytics was founded to help companies measure and manage the impact of weather on their business and leverage Business Weather Intelligence® to make smarter business decisions. We differ from others out there because we provide data in a context that managers can use to explain sales and manage their business. We have helped a variety of Fortune 500 companies across a spectrum of verticals use weather intelligence throughout their organization.

Below is a snippet of our FlashWeather report which provides clients with weather analytics and trends of the past week to help them gain a better understanding of what is going on now in their region and industry.  The full FlashWeather report doesn’t just tell the weather, it provides companies with predictive analytics to how weather will affect their bottom line.

For more information about all of our weather intelligence offerings, please contact us today to speak with a Planalytics representative.

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