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Weather for Analytics

Are you looking for weather data for analytics (i.e., weather data at the ZIP Code or even the Lat/Lon level)?  OnPoint from Weather Source is what major organizations utilize to analyze their data (energy, sales, etc.) with the granularity to make your results meaningful. Most other sources are weather reporting stations like airports. If you or your clients live next to an airport, then you are good to go. However, this is usually not the case. OnPoint Weather utilizes 15 data sources to determine accurate weather readings (temperature, dew point, humidity, wind speed, etc.) by zipode or lat/lon.

Most of our weather analytics clients obtain 3 to 5 years of historical weather data. With the historical weather they can utilize various statistical methods to help discover patterns and relationships between weather and their data. Our clients can also analyze the historical weather data and their own historical data to “forecast the past”. Forecasting the past is a necessary part of the process. Without this knowledge, you are just making assumptions. Granted, you may assume correctly on obvious relationships, but it’s the subtle data relationships that can be discovered and become the most useful. Once these relationships are understood, then applying current and forecast information can be beneficial to your organization’s bottom line.

In a nutshell, analyzing the relationship between weather and your data can assist in:

  • Adjusting and optimizing logistics
  • Adjusting and optimizing marketing strategies
  • Reducing waste
  • Increasing ROI
  • Improving the bottom line.

Our OnPoint data is available in CSV format or through using the OnPoint API. OnPoint Weather is brought to you by the team at Weather Source – the experts in historical weather data, and trusted by numerous Fortune 500 companies to provide their past weather needs, including:

  • AT&T
  • Mastercard
  • Target
  • PepsiCo
  • DHL
  • Comcast

Weather for Business Intelligence (BI) enables businesses to discover and learn how weather affects their sales, energy, product distribution, organizational performance, and more through weather analytics.

Sales: sales@weathersource.com

Weather Source
1 Stiles Road #201
Salem, NH 03079
844-813-2617 (toll-free)
Fax: 866-703-7505

How can historical weather data help your business?

Society, in general, is very adept at using weather forecasts and past experiences to make near-term personal or business weather impact decisions.

We have all seen how weather can impact an organization’s operations. Many organizations have plans in place to deal with weather. For instance, schools close when needed and add extra days to the school calendar in response. Many grocery stores staff based on expected weather and customer demand, but in general the overall impact to grocery stores is a time-shift of customer purchases and therefore the impact is lessened somewhat (http://www.federalreserve.gov/pubs/feds/2000/200008/200008pap.pdf). Unfortunately, many other businesses like restaurants are impacted by weather and have no substantial way to recoup the lost business due to events like snowstorms and rain.

What if you could better understand the impact of weather and use the insight to take advantage of opportunities or cut costs? Today’s technology will let data scientists analyze weather and other datasets at levels of granularity that are amazing. The starting point is by looking at historical weather first. Historical weather information can be used in analytical models to help determine patterns and relationships with other datasets (like sales, energy usage, etc.). It is easy to understand how energy usage is affected by weather (especially temperature), but other patterns and correlations can also be discovered. One widely mentioned example of unexpected discovery with weather events and retail is a dramatic increase in strawberry Pop-Tarts at Walmart stores ahead of a hurricane (http://www.adweek.com/adfreak/hurricane-coming-get-pop-tarts-21329).

To do these correlations, a data scientist or analyst will use many different methods to help them understand the relationships and patterns between different datasets. Once these patterns and relationships are better understood, current and/or forecast weather can be incorporated to help predict sales, usage or other impacts. This is how historical weather data can benefit a business. Is this process beyond your capabilities? There are a number of independent data scientists and business analytic experts that can assist smaller organizations who don’t have the staff to perform the analytical functions.

Since weather is local, it is imperative that organizations offering or performing the analytical services use the proper weather data for their analyses. In the past, historical weather data has been only available from weather reporting stations, many of which are located near airports. Weather data from stations 10 to 50 miles away may not be very useful, especially if elevation or coastal influences are common. Technology is such that historical weather data down to the ZIP Code or Latitude/Longitude level is now available making it possible to correlate weather with specific locations. After these correlations are understood, it is then possible to use this intelligence in many ways. At the very least, the knowledge of how last year’s sales or energy usage was impacted by weather can assist in making decisions about what to do this year. By using weather forecasts, the same correlations can be applied and actionable decisions can be made for the near-term. Some long-range forecasts (15-90 days out) are granular enough that they can also be used especially if temperature extremes impact your business.