All posts by Tara McAdams

“Which City Has the Most Unpredictable Weather?”

“Which City Has the Most Unpredictable Weather?” is an article published on FiveThirtyEight that takes an interesting look at weather volatility across metro areas across the U.S., considering the unpredictability of temperatures, precipitation, and severe weather for each location.

Based on FiveThirtyEight’s scale, Rapid City, SD secured the top spot for the “Unpredictability Index” with a score of 84. Conversely, Honolulu, HI was the most predictable with a score of 30. Looking at major cities, Kansas City had the highest level of index at 76, while at the other end of the scale, San Diego registered a 31.

For many, these top and bottom rankings come as no surprise. What may be more eye-opening for retailers and other businesses that sell to consumers is the fact that the influence of weather changes on purchasing decisions is generally as significant in San Diego as it is in Kansas City and everywhere in between.

How is this possible? Planalytics’ work with businesses (we’ve analyzed trillions of sales transactions for over 40,000 products/services) shows that people acclimate to where they live and how they react to changes in temperatures, rain, snow, etc. is not the same as a person in another city. It really is all “relative” when looking at the weather’s influence on buying decisions.

As an example, let’s look at how weather-sensitive sales for Fleece are in different cities during the month of November. Some of these cities experience a high degree of weather variability and some see decidedly less. (Note: Planalytics’ measure or weather sensitivity indicates the percentage of a category’s sales that are directly related to changes in the weather.)

Between 14% and 17% of Fleece sales are weather sensitive in Kansas City (Unpredictability Index or UI = 76), Memphis (UI = 72), Phoenix (UI = 38), and Los Angeles (UI = 35). Minneapolis (UI = 74) and San Diego (UI = 31) – two cities with very different November climates – both see 10% of Fleece sales directly tied to the weather.

The bottom line for consumer-based businesses is that – like politics – all weather and its impact on purchasing is LOCAL. Just because from a pure stats standpoint the weather doesn’t change much in some western markets or Florida metros, doesn’t mean it isn’t significant from a consumer demand and sales perspective. Five degrees cooler may be barely noticed in Detroit but a shock to the system in Las Vegas.

Visit Planalytics to learn how weather-driven demand changes can be precisely quantified, enabling businesses to proactively plan for and manage sales opportunities and risks, better align inventories with shifting demand, and improve profitability.

To read the original article, Click Here.

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Dressing for Hot: How a Warming Planet Is Changing What We Wear

By Christopher Flavelle Illustrations by Josie Norton, The New York Times

A climate reporter in Washington set out to test clothes designed for keeping cool. He found a few good (but pricey) options, along with some questionable claims.

Shirts made from the same polymer as plastic bags. Jeans infused with crushed jade. Garments constructed using computerized knitting for superior ventilation, or made with cooling technology designed for astronauts by NASA.

As climate change brings more intense heat waves, the next frontier in climate resilience is the clothing we wear, with innovations that promise to cool and dry the hot and sweaty masses. They could make life more bearable for construction workers, farmers, soldiers, and others who can’t retreat indoors as days and nights get hotter. . . .

“. . . In the past five years, changes in weather alone have increased sales of shorts and sandals by half a percentage point, while reducing sales of fleece and outerwear by 1 percent, according to Evan Gold, executive vice president at Planalytics, a company that quantifies the impact of weather on consumer demand.”

Given the size of the market — Americans spend roughly $25 billion each month at clothing and shoe stores — those changes represent a significant amount of money, Mr. Gold said.” . . . . .

To read the original article, Click Here.


To learn more about demand analytics, or to get in touch, Contact Us.

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Warmer temperatures helped boost UK sales in July

A Sky News article (Retail sales boosted by warm weather but inflation worries loom) reported that UK retail sales in July increased by 2.3% according to the British Retail Consortium (BRC). “The summer heatwave prompted shoppers to spend more on summer clothes, picnic food and air conditioning in July, according to the latest figures.”

Planalytics’ Weather-Driven Demand metrics – which isolate and quantify the impact that the weather alone has on consumer purchasing – confirm that warmer temperatures did help lift spending for many summer season categories. For example, Suncare products, BBQ items, sandals, and skirts all saw +5 to +10% WDD gains on a like-for-like basis.

“But the figures are not adjusted for inflation and the consortium said they represented a fall in volume terms… Helen Dickinson, chief executive of the BRC, said that, with inflation over 9%, many retailers were still contending with falling sales volumes during what ‘remains an incredibly difficult trading period’.”

Paul Martin, UK head of retail at KPMG, said: “The summer could be the lull before the storm with conditions set to get tougher as consumers arrive back from summer breaks to holiday credit card bills, another energy price hike, and rising interest rates. With stronger cost-of-living headwinds on the horizon, consumers will have to prioritize essentials, and discretionary product spending will come under pressure.”

“Consumer spending was up 7.7% in July compared to a year earlier, figures from Barclaycard showed, boosted by sales of clothing, beauty products and staycations.”

Read the full SKY UK article here.

Visit Planalytics to learn more about predictive weather-driven demand analytics.

 

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The Predictive Demand Signal Among the Noise in 2022 Retail Performance

As we hit the end of the 1st half of the retail year, many retailers are noting various headwinds that are negatively impacting their results and profitability outlooks. High inventory levels due to inflation, supply chain disruptions, and increased costs of everyday items like food and gasoline have all led to a decrease in demand for seasonal apparel. This has prompted many retailers to ramp up markdown efforts to clear seasonal inventory in time for fall product arrivals.

In addition to these external variables is the embedded influence that the weather has had on seasonal apparel. Earlier this spring, the U.S. had the coldest March in 3 years following by the coldest April since 1999.

Weather sensitivity – the variability in sales directly attributable to the weather — is at its height during these months.  The cooler conditions this spring suppressed the year-over-year demand for Spring apparel by 90 basis points. For retailers, the financial impact was significant during the critical, high-volume months of March and April — a time when categories including sandals, short-sleeve shirts, shorts, sunglasses, and swimwear see between 9% and 15% of sales volumes directly influenced to the weather.

As temperatures have warmed in July, retailers were cutting prices on seasonal apparel at the exact same time when the weather is driving consumer demand for these items.  This has served as a ‘double whammy’ to profitability with many retailers discounting items at the exact time when the customer was looking to make a purchase!

While retailers can’t change the past, savvy businesses will leverage the power of predictive demand analytics to offset the negative impacts they just experienced. The holiday season is right around the corner and many retail executives are grappling with several ‘unknowns’, making it difficult to forecast the holidays.  The uncertainties of a recession, gas prices, interest rates, mid-term elections, COVID, labor availability, global conflicts, and other external variables will all influence the customer over the coming months and holiday season.

The weather, however, has known and measurable impacts. It is a measured demand signal that can and should be accounted for to better plan for retail sales as well as store traffic levels. Retail fall will have significant year-over-year demand opportunities as we are comping the same period in 2021 which was the 2nd warmest Q3 in 127 years. Of course, the timing and magnitude of these opportunities will vary. Regardless, retailers that leverage the power of predictive demand analytics to quantify the impact of weather for each product, time period, and location will help better plan for, allocate, and replenish seasonal apparel. The improvements to forecast accuracy and service levels will help to drive increased profitability and look to offset the uncertainties and headwinds retailers are facing.  The weather-driven demand signal is out there.  Which retailers are best positioned to hear it and act on it?


To learn more about how predictive predictive demand analytics can help your business., Contact Planalytics.

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