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Here we are in 2015. The 2010 Census is five years behind us and the 2020 Census is five years away. Have you wondered about the next Census? How will data be collected? Will the questionnaire catch up with current technology? What happens to non-responders? Since much of our demographic data is based upon the results from each Census (whether from the Census Bureau or demographic vendors like Experian), I went looking on the Census Bureau's web site for a preview of coming attractions. And I found a page at A cost-effective 2020 Census answering my questions. The decennial Census is mandated by the U.S. Constitution. If you answered the Census in 2000, you took black/blue pen to paper for either a short or long-form questionnaire. No Internet access back then. In 2010 you still used a black/blue pen on paper and answered 10 simple questions even though the Internet was integrated in much of our day-to-day life. Are we relegated to a black/blue pen on paper to answer the 2020 Census Questionnaire? Based on information at census.gov, the next Census will encourage self-response via the Internet. Nice! And for those who do not respond, other existing governmental data may be used as a supplement. This equates to cost reductions with fewer physical offices, fewer staff and less followup with non responders. In 2010 there were 500+ Census offices and more than 750,000 staff on the ground. The 2020 Census may have as few as 150 Census offices and 200,000 staff on the ground. Technology may also influence another component of the U.S. Census - the Topologically Integrated Geographic Encoding and Referencing (TIGER) database. These are reference maps, created for the Census, used to visualize geographic and statistical data. Maps are the basis for companies such as TomTom who offer enhanced versions for licensing and inclusion in navigation products. Alteryx users can find mapping layers in the Map Input, Reporting and Browse tools as backdrop references for spatial objects. As referenced on census.gov, existing maps and address lists may be updated using technology, data and GPS to collect interviews efficiently. In the past enumerators walked EVERY block in EVERY neighborhood in the United States gathering responses and information. You can read more about the Census Bureau's 155-year history of mapping here: 155 years of mapping From what I read, these changes have the potential to save taxpayer dollars, maintain a high level of accuracy and make responding to the Census easier. So what happens next? Testing these new processes began this year on a small-scale and national basis. On April 1, 2017, Congress will be delivered the 2020 Census "topics." On April 1, 2018, "question wording" will be delivered. April 1, 2020 is Census Day! On December 31, 2020 apportionment counts are delivered to the President. Results of the Census were historically not instantaneously available but were released over a period of a few years. But who knows what WILL be available in another 5 years. http://census.gov/ is an excellent resource for information on the Census, American Community Survey (ACS), geographies, news and events.
Question Are seasonal population figures included in total population counts?
Answer It is very important to note that the CAPE ‘Seasonal Population’ only refers to the proportion of the population that is temporarily living in housing units that are defined as ‘For seasonal, recreational, or occasional use’. The CAPE ‘Seasonal Population’ therefore needs to be combined with the permanent ‘Residual Population’ to estimate the overall level of the population in each area by quarter.
We are trying to understand the difference between employees and daytime population. It looks like some of the population may be double counted. Can you explain what rows are used for the 2014 Total Daytime population #.
Methodologies are different for Employees and Daytime Population.
Employees & Establishments in Business Summary are sourced from the D&B Business list and summarized to a geographic level although delivered in the Experian CAPE release. The employee counts are as accurate as the D&B employee value but are also subject to block centroid allocation used for population.
Employment fields from the Occupation & Employment folder are based upon the American Community Survey, modeled to a current year value and are part of CAPE.
Daytime Population is sourced from Experian and are compiled values using several CAPE fields. The excerpt below is pulled from the Tech Overview delivered to clients.
Daytime PopulationDaytime Population – Current Year Estimates (CYE)
The Daytime Population database is created using a variety of methodologies applicable for different subsets of the Total Daytime Population. These subsets are then added together to create the Total Daytime Population.
The process starts by identifying key subsets of the residential population that are assumed to stay in or close to their home location during the day. In particular, the following subsets of population are assumed to remain in the same Block Group during the day as the Block Group in which they live (or reside):
Residential Population : Children aged less than or equal to 2
Residential Population : Civilian aged 16+ population that are unemployed
Residential Population : Civilian aged 16+ population that work at home
Residential Population : Population aged 65+ who are retired
Residential Population : Population aged 16+ who are homemakers
Residential Population : Population aged 16+ who are in the Armed Forces
All of the above variables can be directly obtained from previously calculated CAPE – Demographics – Current Year Estimate (CYE) residentially-based variables, except for the ‘Residential Population : Population aged 16+ who are homemakers’. This variable is calculated by applying suitable localized proportions to the existing ‘larger population’ variable of the ‘Civilian aged 16+ population who are ‘Not in Labor Force’. Applying these proportions determines the subset of this ‘larger population’ that are estimated to be homemakers.
Once these initial subsets of Daytime Population who are assumed to stay in their residential Block Group during the daytime are defined and accounted for, then the daytime location of other population types are modelled. It is assumed that these remaining population types are much more likely to travel out of their residential Block Group to reach their typical daytime location than is the case for the population groups previously accounted for. However, flows from home address to daytime address that occur completely within the same Block Group are also possible for these types.
First, the estimate of daytime population at place of work that has already been modelled for the Mosaic Workplace database is accounted for. This variable is:
Daytime Population, Civilian 16+, at WorkplaceAfter the above, the main population groups left to be modelled are:
Within the work to create Mosaic Workplace, this variable is estimated using Census Tract-to-Tract flows of workers from residence to workplace, and National Business Database data to update these flows and allocate them from Tract level to Block Group level.
Daytime Population, Students : Prekindergarten to 8th grade
Daytime Population, Students : 9th grade to 12th grade
Daytime Population, Students : Post-secondary students
Daytime Population: Any remaining Civilian aged 16+ population that are ‘Not in Labor Force’ and have not yet been accounted for.
All of the three student populations are modelled using a variety of data from the National Center for Education Statistics (NCES) and also information from key institutions (i.e. universities/colleges) themselves. After making allowance for students registered at an institution but very unlikely to travel to that institution on a typical day (for example, students undertaking online courses), this information is compiled and modelled to create an initial estimate of the typical number of students that spend the day at the location (or campus) of each institution. These figures are then calibrated so that the initial estimates of students who spend a typical day at the location of each institution, and those who stay within their residential Block Group during a typical day, are balanced to equal the national number of students within each category (i.e. Prekindergarten to 8th grade, 9th grade to 12th grade, Post-secondary students).
Once all students have been accounted for, current estimates of each relevant daytime population sub-group are tallied and compared to the national estimate of ‘Residential Population: Civilian aged 16+ population that are Not in Labor Force’. The above work does not yet account for a proportion of this population group. The, as yet unaccounted for, proportion of this group is therefore calculated and assumed to spend a typical day within the Block Group in which they live.
Having allocated all of the relevant subsets of residential population to either the Block Group in which they reside, or to another Block Group which they are estimated to travel to in order to spend a typical day, then the two final variables in the database are calculated:
Daytime Population Aged 16+
Total Daytime Population (i.e. all ages)
Households or individuals may be excluded from the ConsumerView file for multiple reasons. If an example list of names is provided to email@example.com, they can be validated with Experian. Otherwise, here are examples of exclusions:
Households at addresses may be renters with no deed information available
Household only has cell phones and is not in the phone book white pages
Privacy - many people see to it their name is never on any kind of mailing list when doing business with companies
Below is an excerpt on Experian's privacy & Compliance:
Experian Marketing Services’ Approach to Privacy
EMS is a steward of the information it collects, maintains, utilizes and shares. Our stewardship is anchored in a values-based approach to privacy. Our information values focus squarely upon the protection of information in our care and the safeguarding of consumer privacy through appropriate and responsible use. For more information regarding our approach to privacy, please visit our web site at http://www.experian.com/privacy/index.html .
Direct Marketing Association
As a member and Board of Directors participant of the Direct Marketing Association (DMA), EMS drives the adoption of, and subsequently abides by, and encourages its clients to adhere to, the DMA’s Privacy Promise and Guidelines for Ethical Business Practices. The Privacy Promise is a public assurance to American consumers that DMA members follow specific practices to protect consumer privacy. Specifically, the Privacy Promise requires member companies to:
Provide notice of consumers’ ability to opt-out
Honor consumer opt-out requests
Maintain an in-house opt-out suppression file
Use the DMA Preference Service suppression files (e.g., MPS, TPS, e-MPS)
Promote industry-wide compliance with DMA self-regulatory guidelines
Why are some people not contained in the Experian ...
For additional information, contact firstname.lastname@example.org
If you can't find the ZIP code you are looking for, it is likely that it is a ZIP point, ZIP codes are assigned to military basis, college campuses and other large facilities. These ZIP Codes are not registered by default, to be added to Allocate they have to be registered. For this you will need to have Admin rights to your computer to do this. If you don't, you could try right clicking on the Allocate product and selecting Run as administrator. If this does not work, you will need your IT to register the file for you. First, open the stand alone Allocate product (outside of Alteryx): Choose the dataset you are using in the first window: Next, go to the Pick Geography tab and go to File > Manage Virtual Geographies… The below window will pop up, click on Register: Go to the Program Files (x86)AlteryxDataProductsPortfolio[your dataset]Data folder (or the folder for the dataset you are using): And select the ZIPs with Points VGF files, click Open: You will see that the Zip Codes w/Points is now loaded in the list, click OK: Allocate will say it needs to restart, click OK. Once open again, go to the Pick Geography tab and the Zip Codes w/Points is now selectable and will also be available in the Allocate tool within Alteryx.
Census data is calculated based on census designated boundaries which range in increasing size from Blocks - Block Groups - Tracts - Counties - etc. However, when solving most business issues, custom polygons are often used. Since custom polygons almost never perfectly mirror Census Blocks, a method to subdivide Blocks must be created. Block Centroid Retrevial
Alteryx utilizes Block Centroid Retrieval when allocating demographic data to irregular polygons such as custom radii, ZIP Codes, and custom trade areas. For the US datasets, this retrieval is based on the centroids of the US Census 2010 Blocks. Each record is tagged with the percent of the household and population it represents as a fraction of its associated block group. Development changes in the years since the census are not reflected in this inventory of block centroids.
To address this requirement, Alteryx designed a methodological approach to update block groups to reflect areas of growth. By utilizing the Experian household database of 127 million U.S. consumer households in conjunction with the Census Bureau, Alteryx has created additional points, within the block inventory dataset, utilized by Allocate to represent population and household growth during the time since the previous census.
In June of 2012, the USPS made a change to how a P.O. Box operates. That change now allows for a street address to be used in lieu of a P.O. Box. This format, known as a P.O. Box Street Address (PBSA), is actually the address of the post office of where the P.O. Box is located. How does this affect Alteryx? One client brought to our attention that this could potentially affect address and demographic analysis. Let's say a user has a small list of competitors and they want to run a competitive analysis. The only issue is that several of these records are using a PBSA. The demographics for these records will revolve around the post office, not the actual business. How do we combat this? The first thing to keep in mind is that Alteryx is perfect for this sort of scenario. The USPS has posted a list of their post office locations as a .txt file. Attached to this post you will find an Alteryx Zip Package that informs you of where you can find the file (hint: here) and parses it. Once it is parsed, one option would be to merge that with the D&B Business Matching Macro to validate or invalidate your list of businesses. Another option would be to take your business list and compare it to this file to find out if any businesses are using a PBSA. Either way, we have options! One final note is that it is important to remember that these are valid street addresses. While the Alteryx Street Geocoder will mark a P.O. Box as invalid, it will see these and most likely geocode them all the way to the street level. If you would like to read more about this USPS feature, click here. Until next time! Chad Follow me on Twitter! @AlteryxChad
Also, HUGE THANKS to John H. for his help with this post!
ata Inventory Public Data Datasets that are available for use in the Public Gallery and in Private Studios are listed below: Demographic Data 2010 Census SF1 Data – includes Geographic boundaries and demographics from the 1990, 2000, and 2010 Census. 2010 Census SF1 Data with Telco Boundaries – includes the same offering as the 2010 Census SF1 Data with additional Telco boundary coverage limited to Florida for demonstration purposes. Drivetime Data Tom Tom US - will accurately create drive time polygons and calculate point to point drive distances by exclusively following the actual road network. This dataset is updated two times per year. Map Display Tom Tom US - enables the presentation of cartographic map information of over 50 layers throughout the U.S. and Canada for map creation. This dataset is updated two times per year. DigitalGlobe Aerials with Streets - enables the presentation of satellite imagery in combination with the street layers from Tom Tom for map creation. This dataset is updated two times a year. DigitalGlobe Aerials - enables the presentation of satellite imagery for map creation. This dataset is updated two times per year. Geocoding Tom Tom US - enables the assignment of a latitude and longitude and point to an address within the U.S. This dataset is updated four times per year. CASS – standardizes and cleanses address data. This dataset is updated 6 times per year. Private Data Datasets that are only available for use in Private Studios are listed below: Demographic Data Experian Demographics, Mosaic segmentation system and Simmons Syndicated Survey Data - Integrated industry-specific data from leading providers augments the existing demographic and firmographic data in the standard product. Service providers can use it to identify and rank high-value market and customer prospects for network planning, new services, competitive analysis, and regulatory activities. This dataset is updated two times per year. Experian Demographics Communications addition – includes the same offering as the Experian dataset explained above with the additional Telecommunications US boundary coverage including: Wire Centers, Rate Centers, LATAs, NPAs, Cable/MSO serving areas, Cellular Market Areas (CMA), Major Trading Areas (MTA), Basic Trading Areas (BTA) and Public Safety Answering Points (PSAP). This dataset is updated two times per year. List Data D&B Business Location/Firmographics Analytical File – contains more than 125 million business records and variables include: Business Name, SIC code, NAICS code, Sales Volume and Employee Counts. This dataset is updated four times per year. Experian ConsumerView Household Analytical File – contains more than 113 million households and variables include: Mosaic Household, mail order buyer preferences, mortgage/home purchase, median family income, estimated income, dwelling type, presence of children under 18. This dataset is updated four times per year. Experian ConsumerView Individual Analytical File – contains more than 235 million consumers and variables include: marital status, gender, education, and occupation group. This dataset is updated four times per year.