Frequently Asked Questions

About Metopio

About the site.

Metopio is a cloud-based analytics as a service platform that offers curated, verified data and ridiculously easy tools to help you create decision-ready insights and plan meaningful actions for places and populations that matter to you. Ask your question, get an answer, and accelerate your impact.

Last modified: July 27, 2020

Metopio is the only start-to-finish solution providing analytics as a service regardless of skill level. Metopio empowers users to draw insights from curated, verified data, the ability to add proprietary data and go beyond layers on a map with sharper insights – without costly, time-intensive training or previous coding experience.

Last modified: July 27, 2020

Metopio comes from two Greek words, μετά (beyond) + τόπος (place), describing how our tools and visualizations take you deep into the interconnected factors that influence outcomes in different locations. It's pronounced meh-TOE-pee-oh, but you won't offend us if you make up another pronunciation.

Last modified: Feb. 4, 2020

Metopio’s co-founders are data scientists, healthcare executives and public health champions who needed a tool that could deliver and communicate actionable insights about places and populations to drive better policy and business decisions. The platform was built with the intention of liberating data so anyone could generate insights to guide their work.

Last modified: June 29, 2020

Metopio has data on hundreds of topics, from dozens of public and private sources, representing a very broad set of information about communities and places. All of our data is aggregated, in the form of statistics like the average and count of cases. We do not have data about individuals. We focus on aggregated data for several reasons:

  • It is more valuable. Often, individual data is primarily used to compute statistics like averages and counts. We simplify that process by calculating these things for you. As a result, every one of our millions of data points is meaningful, because it represents the experience of many individual people--not whether one person went to the hospital, but whether many people in the community are going to the hospital for the same reason.
  • It is cleaner. Individual data suffers from poor data quality in all but the most rigorous data systems. Sometimes individuals don't answer the question, or a topic doesn't apply to them, or the measurement is invalid. By focusing on aggregates, we guarantee that every single data point is relevant and meaningful.
  • It is easier to compare data across topics. Matching up individual data sets is extremely complex and difficult. Additionally, many of our datasets come from healthcare or other sensitive industries, and cannot be matched to other datasets because individual information has been stripped out. Other platforms solve this problem by presenting each topic in isolation, but we believe it's very valuable to look at multiple points of information about the same community.

Last modified: April 16, 2020

Metopio's visualizations are incredibly easy to use because we have prioritized your user experience at every step of building this platform. That's why they are custom-designed and built by Metopio, not licensed from another company, and it's what allows us to introduce new features ahead of competitors that are tied to old technologies.

Last modified: April 16, 2020

Resetting your password has never been easier!

If you are already logged in, and know your current password, follow this link to change your password.

By following the above link, you will be taken to our password change form. Simply follow the prompts on the screen to reset your password.

If you forgot your password, simply log out and reset your password here.

By following the above link, you will be taken to a new tab with our password reset form. By simply entering the email address linked to your Metopio account, an email will be sent to the same email address with a link to reset your password.

If you don’t receive this email within 5 minutes, please make sure you entered the email used by your Metopio account. For security reasons, our automated system is unable to confirm or deny what email account you used, but we can look that up for you upon request.

Contact us if you need further assistance.

Last modified: April 15, 2021

Billing

Our billing and payment processing guidelines and procedures.

Metopio is built for collaborative data work. Our subscriptions are geared toward people working in teams, such as a small company, or the Strategy or Marketing department at a larger organization. We recommend getting one subscription for each department because their needs are often different.

An Enterprise account lets you combine all of the teams at your company into one subscription, so that they can share datasets, custom regions, insights, and other work in a secure account. Contact us for more information about the Enterprise subscription.

If you are not part of a team, don't worry! You still get all the features of Metopio if you're the only one on your team.

Last modified: Sept. 15, 2020

When you start a subscription with a free trial, you can use Metopio without paying or providing a credit card. When the trial period is over, you'll be asked to submit payment information to keep using your subscription. You can cancel at any time before paying.

Last modified: Sept. 15, 2020

Yes, we offer subscriptions for individuals as well, though we find that Metopio is best for teams because it enables everyone who works with data to reap the benefits. Please contact us to learn more about our subscription options.

Last modified: Dec. 8, 2020

A seat is the spot taken up by a user - someone with their own login for Metopio. You can have more seats than users (if some seats are temporarily empty) but you can’t have more users than seats, because users are not allowed to share their login credentials.

Last modified: July 29, 2020

Subscriptions can be upgraded at any time, and we will pro-rate the change. If you downgrade your subscription, pro-rating may or may not apply. Please contact us to discuss your needs.

Last modified: Oct. 28, 2020

We prefer payment by check, but you can also pay using all major credit and debit cards. We use Stripe to process payments. We do not accept payments in Russian rubles from shadowy organizations, but chances are you're okay.

Last modified: Sept. 16, 2020

Yes, you can. When you cancel, you will have access for the remainder of your subscription but you won’t be charged again.

Last modified: July 27, 2020

Our data

How we collect, clean, aggregate, and display our data, and caveats for interpreting our data.

The standard error of a data point is a measure of its accuracy, equal to the standard deviation of the distribution of a large population of such data points. It is used to generate confidence intervals of the data points.

Because most data on Metopio is aggregated statistics and rates, the standard errors and confidence intervals are very important in communicating how well we know each data point. The smaller the standard error (or confidence interval), the more confident we are about where the true estimate lies. With large populations, standard errors let us provide good estimates without taking the time and expense to survey every single person.

Last modified: Nov. 21, 2018

A margin of error is calculated from the standard error and represents how much the true value might differ from the reported one (the estimate), given that the reported value is often based on a sample of individuals. The larger the margin of error, the wider the variability of the estimate. Confidence intervals are built by adding or subtracting the margin of error from the reported value.

In Metopio, all confidence intervals are at the 90% confidence level. The proper interpretation of this is as follows:

Under the system which produced this estimate, the confidence interval is the range in which the true value would fall 90% of the time.

In plain English, this means something like the following:

Our data estimate was produced by a certain system (asking a certain number of people in a certain way). If we knew the true value, it would probably be a little different from our estimated value because our sample would be 100% of the population, and every one of them would understand the question fully and tell us exactly what we want to know. However, we can create a confidence interval to represent the area where we believe that true value would fall, 90% of the time.

Last modified: April 10, 2020

Some of our data tracks the exact count of reported events (such as crimes, disease cases, or reports). Even though this count is exact--we know exactly how many events happened in the time period--it is given a standard error to describe how variable the process is that generates those reports. In technical terms, this treats the count as an observation in a Poisson distribution. The standard error gets smaller relative to the count as the count gets bigger.

Think about standard errors/margins of error as lines that mark what an "out-of-bounds" data point would look like. If you consistently see between 20 and 40 squirrels every day, and then one day you count 10,000, you can be pretty sure that something changed in the process that produces squirrels. Maybe it was totally coincidental, or maybe it was a squirrel convention. You would want your data analysis engine to flag that 10,000 value as "out-of-bounds" so you know something is different about it - even though you have exact counts of how many squirrels you saw on any given day, and no uncertainty about how many you saw.

This is what we do by applying standard errors to exact count data. Suppose that there were five events reported in a given year and the margin of error is 3.7. This suggests that, in any given year where the underlying factors are the same, we might expect between 1 and 9 events, just by random chance of when the events happen. If we saw 500 events the following year, that would indicate that something major had changed, because the chances of the same process producing 5 events in one year and 500 events in the following year is infinitesimally small.

Last modified: Feb. 4, 2020

All dollar-denominated topics in Metopio are adjusted for inflation to 2017-equivalent dollars. We adjust them because most topics reflect people's actual economic situation at the time that the data was collected, and adjusting for inflation accounts for the changing value of money. (Over the twenty years from 1999 - 2019, inflation has reduced the value of a dollar by more than one-third.) There is no importance to choosing 2017 as our baseline year, except that we started doing this in that year.

Adjusting for inflation is important because it shifts our view from the nominal dollar amount at the time to the actual value of those dollars, or what they can purchase. The median earnings for workers over time INB is a good example of why this matters. In nominal terms, earnings rose consistently over the ten years from 2005-2015, excepting only the year of the financial crisis:

Metopio image

However, after we adjust for inflation, we see that the purchasing power of workers' earnings actually steadily declined (in constant 2017 dollars):

Metopio image

As we use Metopio to tell the story of our communities and the challenges they face, it's crucial that our data reflect their actual experiences. Using constant dollars also makes it easier to understand the relative value of money by looking at what earnings from the past could purchase in today's economy.

Note: The inflation multipliers we used are from the Bureau of Labor Statistics' CPI inflation calculator, using June-to-June measurements.

Last modified: June 27, 2020

Race/ethnicity definitions vary widely, but we adhere to the guidelines set out in the OMB (Office of Management and Budget) Directive 15 from 1977. We did not invent these names or categories, and we are trying to use the most consistent available federal guidelines. The basic categories are:

  • White: equivalent to Caucasian plus those with Middle Eastern or North African origins.
  • Black or African-American: those with origins in Sub-Saharan Africa, not including White South Africans.
  • Asian or Pacific Islander: includes any part of Eastern or Southeastern Asia or Pacific islands.
  • Hispanic or Latino: those with origins in Mexico, the Caribbean, Central or South America, or any other Spanish-speaking culture, regardless of race. Hispanic and Latino are not synonyms and we generally mean "Latino", but the Census Bureau calls this category "Hispanic" while including both Brazilians and people from Spain.

Note that Hispanic or Latino ethnicity supersedes race, so that people identifying as Hispanic/Latino are coded that way whether they also identify as White, Black, Asian, or any other race. Hispanic/Latino is the only ethnicity included as a built-in stratification in Metopio. All data about "White" or "Black" people in Metopio means non-Latino and non-Hispanic White or Black. This also goes for Asian/Pacific Islander data in Metopio, which signifies "non-Latino and non-Hispanic Asian/Pacific Islander", although we do not use this name because it would be too long.

OMB 15 also recommends collecting data on Native Americans or Alaskan Natives. Those data are not included as built-in stratifications in Metopio because low sample sizes make it very difficult to make meaningful comparisons at small-geography levels. Some Metopio topics separately track the populations of Native Americans and some Asian races/ethnicities. We also do not stratify our data by people identifying as some other race or two or more races. If you are interested in such data, or in other race/ethnicity breakdowns, please get in touch.

Last modified: Feb. 24, 2020

When a user defines a custom region, Metopio weights the individual values for the places in that region by the size of each place to arrive at a weighted average for the entire region. It also calculates the 90% margin of error of this weighted value, where possible, to indicate how reliable the estimate is.

Last modified: March 6, 2020

At Metopio, we put extra effort into making data easy to explore and use, even if the original data was only published at the ZIP code level and you're interested in county statistics.

The way we do this is through a proprietary algorithm that calculates the data point for each place in one layer (such as each county) based on a weighted average of the places in the other layer that overlap it (such as ZIP codes). This weighted average is based on the distribution of people, housing units, or land, whichever is most appropriate for the topic we're calculating. To determine how people, housing units, and land in one place are divided into places in a second geographic layer, we use the US Postal Service’s Crosswalk Files.

We even go a step beyond this: for data about a specific population stratification, such as seniors, we further weight the calculation by the distribution of seniors from one place to another. This provides even greater accuracy in our modeled estimates.

All estimates produced in this way also include margins of error, which are based on the margins of error in the original layer’s data, with an additional margin to represent the inherent uncertainty involved in translating data between geographic layers.

The bottom line? Regardless of how the data was originally published, to the extent that we can responsibly do so, we provide data at all other layers we possibly can. Several government datasets are made available only for Census tracts; we take this data and calculate it for more than ten other geographic layers using our best-of-its-kind algorithm. This means you can focus on your analysis, regardless of what geographic layer interests you, and be confident that the data you’re using is the best available. And it means that Metopio often has more data available, at more layers, than any other service could provide.

Last modified: Feb. 18, 2021

Nearly all data to which you have access in Metopio can be downloaded in bulk using our Data Download feature. This includes all data in our Curated Data Library, any data that you upload yourself, and even data provided by third parties that you can see. The exceptions are some datasets provided by third parties that place restrictions on their download in bulk.

If your team has an active subscription, you are able to download data 500 times in every thirty-day period, or up to 6,000 times a year. A download is defined as data for a specific topic, population, and time period, so if you download data for 13 topics at once, or download data about the same topic for 13 separate time periods, it would count as 13 downloads either way. The number of data points in each download does not matter - only the number of topics (as shown on the Download page). The thirty-day period is based on today, not on a fixed date each month, so your download limit is recalculated each day.

The following downloads do not count against this limit:

  • Data owned by your team - download your own data as much as you want
  • Downloads that are empty (no available data)

If you have special circumstances (such as a once-a-year project requiring more data than the limit), please get in touch.

Last modified: July 29, 2020

For best results, use your computer's screenshot tool to take pictures of scatterplots. On Windows, this is the Snipping Tool. Mac computers and mobile phones also have ways to take screenshots. These tools will let you save an image of the visualization exactly the way it looks to you.

You can also click on an "Export" or "Save image" button near the visualization to download an image, but be aware that this tool may distort your image in some ways, and will not capture any highlights or other changes you've made to the visualization. This tool may not work on Internet Explorer.

Last modified: Oct. 28, 2020

Your security

How Metopio protects your privacy.

Metopio has been tested and should work on all major web browsers (Chrome, Firefox, Edge, Safari, Internet Explorer, and others). It also works well on mobile and tablet devices and their major browsers. If you notice a potential bug, please let us know on our Contact page.

Note: While Metopio works on Internet Explorer, some of its visualizations are not optimized for that browser. Microsoft has discontinued support for Internet Explorer. If you notice that Metopio is very slow on Internet Explorer, consider trying it in another web browser such as Microsoft Edge.

Last modified: July 27, 2020

Yes, in a limited way. As you use the website, we collect and store information such as what pages you visit. This information lets us customize your experience and improve our recommendation engine for you and other users. Other users are not able to know your individual activity, and we do not share this information with anyone who is not on the staff of Metopio. This sort of tracking is standard for websites trying to provide a customized user experience.

Last modified: Oct. 28, 2020

We do not share any information about you, or your use of Metopio, with any third parties, with the exception of Google Analytics and Sentry, discussed below. By "third parties", we mean any entity not owned by Metopio, and this includes social media companies like Facebook and Twitter. We do not track you across the internet, install cookies to track your usage of any website other than Metopio, or sell information about you to advertisers. If this sort of thing concerns you, we invite you to check Metopio yourself using a tool like webbkroll, which will tell you what data Metopio is telling others about you. (Try checking other sites too.)

We use Google Analytics to collect data about you and how you use the website. We use this information to learn how our users in general are using Metopio, such as what browsers and states they are accessing it from, so that we can optimize the site for those factors. This information includes what pages you visit, what type of devices you use to access the website, and how long you spend on the website. None of this information is tied to your real name, address, IP address, or any other personal information that identifies you individually, and we do not attempt to identify you through this anonymized usage activity. More information is provided at the web page “How Google uses data when you use our partners’ sites or apps”. You can opt out of this tracking by installing the Google Analytics Opt-Out Browser Add-On, and you won’t hurt our feelings if you do so.

We use Sentry, an automated error-tracking tool, to track bugs and errors on the platform, and in doing so we send them your user ID when you encounter an error. This helps us prioritize fixing issues that have a high impact and also lets us reach out to you if you encountered a bug that affected your experience. You can't opt out of this, as far as we know, but you can review Sentry's privacy policy.

See our privacy policy for more information.

Last modified: June 29, 2020

No private data

Our browser cookies contains only the information we need to keep you logged-in to Metopio and ensure the integrity of your form submissions. This is done through unique hashes that cannot be used to identify you. We do not store information about you and share that with other websites you visit, nor do we track what websites you visit and use that information to show you ads. (Nor do we have ads.)

Some empty map layers

To improve the speed of our visualizations, we store some empty map layers in your browser, if your browser lets us. For instance, we may store a blank county-level map layer, and use that layer to build your map rather than requesting the layer from Metopio every time you open a map. This conserves your bandwidth and improves rendering speed. These layers contain no data and are auto-deleted after a month if they are not used.

You can clear all Metopio data in your browser at any time with no effect on your experience.

Last modified: Oct. 28, 2020

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