BreezoMeter Launches Historical Insights

BreezoMeter’s Historical Insights offers historical data using the same accurate and granular environmental data format as our APIs such as air quality, pollen, and weather – with a historical perspective. No matter what the topic, one timeless truism is that the best decision techniques are based on the use of high-quality and reliable data.

Creative Use of Historical Data

In a recent survey, Gartner found that 65% of today’s decisions are more complex than they were only just two years ago. This complexity is even more prevalent when environmental data is concerned as accurate, reliable, and global air quality, pollen, and weather data have been difficult to come by – until now!

Introducing BreezoMeter’s Historical Environmental Data!

Today, climate change poses immense threats to our society as we know it. With polluted air and steadily rising temperatures linked to health effects, pollen counts and allergies on the rise, and wildfires destroying lives, properties, and ecosystems, it is crucial that we collect and use historical data to make smarter environmental decisions for the future of our planet. Until now, companies have had difficulties accessing quality environmental data but BreezoMeter is now offering a wide suite of high resolution, global historical data including air quality, pollen, and weather.

How Environmental Data Solves Business Problems

By looking at historical environmental data, we can see patterns and gather the information that might help us understand how we can use environmental data to solve critical problems and help us use analytical insights to form our business decisions.

Many of our customers have begun using historical environmental data for business and clinical research, building risk indices, and using historical data for advertising insights.

Business & Clinical Research

Finger pointing on transparent screen

As the environment is continually changing, clinical research and business often find the need to grasp a better understanding of what those changes mean for their individual businesses.

Using Historical Insights, some of our clients have compared their own sales and business data to environmental fluctuations to search for patterns providing a better understanding of which locations require different offerings at different times.

Using this approach, data analysts compare data sources so that companies can get verified analytic results to base their offerings on. For example, a pharmaceutical company can compare their data with BreezoMeter’s historical data to gain insights on how their patients have been affected by past environmental data or a business may use it to build sales predictions. The analysis can be used to make decisions related to production, merchandise location, and a variety of additional factors.

Building Risk Indices & Prediction Assessments

A risk index or prediction assessment looks at the indicators used to calculate the risk and attempts to understand future trends based on past occurrences. These are commonly used in the health, pharmaceutical, and insurance industries to forecast medical supplies, insurance rates, and health issues. AQ, pollen, and weather data are fundamental to building risk indices for various health conditions. Risk indices help understand the likelihood of a certain outcome and are represented as a percentage.

A risk index using historical data has multiple benefits. Until now, historical environmental data was difficult to locate but now it can be used as a risk or prediction index. Some of the benefits of a prediction index include:

  • Increasing awareness of a risk or hazard
  • Assisting others in recognizing or controlling specific risks
  • Enabling more appropriate insights or best practices to follow
  • Improve health or business risk
  • Reducing costs by encouraging people to be proactive rather than reactive

Getting Advertising Insights

Mobile phone open to Google advertising page

Historical Insights is often used by advertisers to gain insights into where and when it is best to advertise. Advertisers use historical data to research and locate the most polluted cities, past areas affected by wildfires, or any historical environmental data they can use to decide where and when to promote their goods or services. 

For example, a company that sells air purifiers might want to locate cities with the lowest air quality to advertise during periods of poor air quality. A pharmaceutical company may need Historical Insights to discover the specific cities and times to promote their allergy product. Using a range of historic data, decision-makers obtain a holistic view of past events and trends on which to base advertising strategy.

Using historical environmental data can help advertisers and their data analysts determine where their customers are located and when would be the best time to advertise their products. Many customers selling environmental-related products don’t have access to historical data on air quality, weather, or pollen which makes it challenging to learn from past patterns and trends. Using past data has solved many of the media challenges these customers were facing by enabling them to make data-driven decisions on how to locate the segments they seek to advertise to.

Ready to Try Historical Insights?

Historical Insights includes a full set of data with complete hourly historical air quality data, full pollutants listing, daily pollen & weather datasets from over 90 countries across the globe. Many of our clients are excited to begin accessing Historical Insights in addition to our full suite of current real-time and forecasted environmental intelligence data and insights provided by BreezoMeter.

For more information about BreezoMeter’s Historical Environmental Data and to request a data sample, click here.

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Amit Lesman

Director of B2B products at BreezoMeter. I define the B2B product vision & roadmap based on market needs while connecting the dots for different stakeholders, creating mockups and designs with the UX/UI teams, writing specs, (business & technical), and finally leading dev teams to the right execution. Can it get more fascinating than that?