Car damage can occur for several reasons, and we’re all vulnerable to it at any time or place. Weather events are a huge factor in vehicle wear and tear. Hail can be a death sentence for your car, and intense UV radiation and heat can gradually destroy your car’s interior and paint job. Areas that must salt roads in winter do so to keep us safe on the road, but unfortunately, salt also damages cars and breaks down roads, leaving behind dangerous potholes. The Grease Monkey researchers took all these factors and considered them together to create a ranking system to show us the states that do the most damage to cars. Each state in the U.S. is ranked based on the severity of vehicle risk and deterioration.

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The team notes that hail was one of the most significant factors in their weather analysis. The size of hailstones will determine the damage, and areas with more frequent hailstorms will increase the likelihood of significant damage, such as cracked windows and broken headlights. Snowfall, ice, and sleet also greatly increase the risk of car damage. Frozen mechanical parts are more likely to break, and icy road conditions lead to dangerous crashes. Humid weather in general leads to more rust, so frequent rainfall and salty coastal air can take a slow toll as well. Natural disasters like floods and tornadoes can destroy a vehicle, so the team counted how many of these events each state has experienced since 1953.

Poor roads were another important factor in the team’s analysis. They counted the total percentage of a state’s roads considered to be in “acceptable” condition. Potholes, rough roads, and debris wreck tires, rims, and undercarriage components. Bad roads often have loose rocks that can kick up to shatter a windshield or dent a car’s body. The team found that the states with the worst roads are Rhode Island, Hawaii, New Mexico, Connecticut, and Mississippi. The states with the highest percentage of roads in good condition are Indiana, Kansas, South Dakota, Wyoming, and Vermont.

Combining all of these factors, the Grease Monkey analysis shows us that these ten states will cause the most damage to a car:

– Texas
– Mississippi
– New York
– Delaware
– Oklahoma
– Missouri
– Minnesota
– Kansas
– West Virginia
– North Dakota

This map can help drivers determine what factors are most likely to damage their car based on where they live. While we can’t do much to affect the quality of a state’s roads, it’s a good reminder to be vigilant and slow down for potholes. Heat damage to a car’s interior can be prevented with a sunscreen in the windshield. Building a garage can help protect your car from hail, snow, ice, and rain. Defensive driving will help you to be safe from accidents. People figuring out a car-buying budget can also consider these factors, which drive up insurance premiums.

Customers have an abundance of choice in all industries these days. When customers switch to a new option, companies call this “customer churn.” Customer churn can be a major detriment to business. In nearly every industry, loyal repeat customers can make or break a business. The team at Qualtrics helps us understand the state of customer churn in the past year with 30 key statistics illustrating the landscape. They took a well-rounded approach to their research, using facts that reveal how many customers are leaving, which industries have high churn, and other factors that help us understand why customer churn happens and how to prevent it.

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Customer churn gives businesses a way to quantify how well they’re retaining customers. Churn rate is calculated by dividing the number of customers lost over a set period of time by the total number of customers at the start of that period. This calculation yields the number of customers who didn’t return to do business. High churn rates often signal poor retention strategies or a mismatch between what customers expected and received. We can’t underestimate competitor appeal, though. The team’s data shows that 71% of businesses list price increases as their number one reason for losing customers.

The data make it clear that churn rates vary widely across industries. 61% of retail companies say churn rates are one of the biggest challenges in their quest for success. This could be due to the high level of competition and vastly different prices found in the retail sector. Financial, cable, and credit companies experience high churn rates too, around 25%. We can conclude that spending and saving may have the greatest impact on churn, based on industry rates. The big-box electronics industry only has an 11% churn rate, possibly due to fewer choices, but it may have stronger brand loyalty. For example, you’ll rarely see an X-Box fan make the switch to PlayStation. Speaking of the gaming space, apps don’t enjoy the same low churn rate as consoles might. With a 27.7% churn rate, many people give up on gaming apps and try something new after 30 days.

Data might point the way to solutions to reduce customer churn. We can see subscription-based companies with an exceptionally low churn rate of 3.27%. Software and business subscriptions have lower churn rates than digital media and entertainment subscriptions, but they are still among the lowest we’re seeing. A subscription-based service works hard to keep its subscribers, so maybe other types of businesses could learn something from its strategies. For example, social media apps have an enormous churn rate of 93.3% over 24 months. It’s clear that whatever value customers hoped to get from the platform didn’t materialize.

This information-rich graphic leaves us with a lot to think about. By comparing churn rates across industries, we can reflect on key differences that affect these numbers. Perhaps the most important statistic to hold on to is that U.S. companies could save over $35 billion per year by reducing their churn rates.

AI is spreading rapidly, especially in the workplace. According to surveys, 46% of American workers have used AI a few times in the past year. As the AI industry rapidly expands, Ooma examined how quickly U.S. states are adopting artificial intelligence in the workplace with a data-driven snapshot of current usage and future expectations. Using U.S. Census Bureau survey data, the team’s work highlights geographic trends and broader implications for business as AI becomes more enmeshed in daily business dealings.

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The team’s research ranks states on two key metrics: current AI adoption (whether businesses have recently used AI tools) and projected adoption (whether businesses expect to use AI in the near future). These combined elements allow us to see not only where AI is already in use, but where momentum is building. The infographic provides a visual way to compare states and identify these patterns.

One of the most striking findings is that Colorado, Arizona, and Nevada lead the way in the current AI usage. Over one-fifth of his businesses have recently adopted AI. Colorado stands out as a top state, with 25% of businesses already using AI in some capacity. These tools can include machine learning, virtual assistants, natural language processing, and other AI capabilities, supplementing everyday business tasks such as data analysis, communication, and customer service.

The map also reveals that the same states dominate in projections for future AI use. Colorado and Arizona take top rankings once again. This suggests that early adopters are more likely to keep investing in AI and remain in their leadership positions. States like Utah and Texas ranked highly in future projections, indicating these are emerging areas for AI growth.

We can see states on the opposite end of the spectrum, lagging behind the leaders. West Virginia, Alaska, and parts of the Northeast report much lower levels of current and anticipated use. Even though it’s an economically robust and influential state, New York ranks low for adoption, showing that size and economic power don’t always indicate rapid AI growth.

The team’s work suggests that differences might be influenced by factors like industry composition, workforce skills, and access to tech infrastructure. States with strong technology sectors and a growing startup economy are the most likely to adopt AI quickly, while states with more traditional economies and heavy reliance on physical labor might have slower transitions.

Remember that AI adoption is still in the early stages. Even in leading states, only one in four businesses reports using AI, so there’s still a lot of room for growth. This aligns with broader trends showing AI is expanding rapidly, but it hasn’t yet reached saturation.

The article paints a picture of a fragmented but rapidly spreading AI landscape in the U.S. While some states lead the charge, widespread adoption is still rolling out and could shake up these rankings a lot in the coming years.