Verum research · 2023 Census source year · Analysis prepared October 29, 2026
Custom computer programming establishments by state
The 2023 Census file counts 68,051 employer establishments in custom computer programming services across the 50 states and DC. California, Texas, Florida, Virginia and New York account for 43.87%. The fourth-place position of Virginia distinguishes the leading states in this category from the software-publisher category.
Our data
We selected 51 state-level rows for custom computer programming services, calculated each state's share of 68,051 establishments, and derived local employment-size comparisons. The CSV and JSON expose the same counts, source codes and missing-value status. These are computed public-data aggregates at the industry and state level.
Download the 51-row CSV · JSON dataset · Source checksums · Methodology
Source: Census Bureau 2023 County Business Patterns state bulk file. Industry filter: NAICS 541511; all legal forms; 50 states and District of Columbia. The five leading states sum to 29,851 establishments, or 43.87% of this geographic total.
Virginia changes the shape of the leading-state group
California leads with 10,962 establishments, followed by Texas with 6,411, Florida with 4,839, Virginia with 4,080 and New York with 3,559. Their combined count is 29,851. The table establishes Virginia's position in this particular industry distribution; explaining the concentration requires a separate causal investigation.
A causal explanation would need additional evidence about customers, contracts, business formation or employment patterns. This report supplies the geographic counts for that investigation. For an account-data team, the immediate use is simpler: check whether a custom-programming territory plan treats Virginia's measured footprint differently from a plan built for software publishers.
Custom programming and software publishing are separate filters
This report uses NAICS 541511. The companion software-publisher report uses 511210 and contains 18,425 establishments. We keep the two categories separate because they represent different industry definitions in the source file. A generic technology label can conceal that distinction in a CRM export.
The difference between 68,051 and 18,425 compares separate industry populations. Classifying subscription models, products and current programming services requires business-level research. Those commercial descriptions need business-level evidence. The statistical categories provide a starting classification for a customer-profile review.
The smallest local size band is a large majority
Establishments with fewer than five employees account for 72.02% of this selected industry. Adding the five-to-nine and ten-to-nineteen bands gives 60,654 establishments below 20 employees. All three inputs are numeric in each of the 51 rows, so the derived total has complete size-band coverage within this extract.
California has 9,882 under-20 establishments out of 10,962, or 90.15%. Texas has 5,706 of 6,411, or 89.00%. Florida has 4,509 of 4,839, or 93.18%. These are establishment-level sizes. A small office can belong to a larger company, and a company-level workforce figure requires a separate source.
Avoid translating establishment counts into contractor counts
The file covers employer establishments. Self-employed programmers, nonemployer businesses, individual workers and technical skills require their own population definitions and sources. A report titled as a count of all software developers would misrepresent this dataset.
If a staffing or services workflow needs those populations, it should define and obtain the appropriate source separately. A workforce estimate based on assumed staffing needs explicit assumptions and a separate label. This download can support a geographic review of employer locations in the chosen industry, which is a narrower and reproducible task.
Check classification before judging geographic coverage
Begin with internal accounts whose activity has been verified as in scope. Keep uncertain technology-category records in a separate queue. Then decide whether the internal numerator counts legal companies or offices. Only a location-level count with a compatible industry definition can be compared directly with the state establishment distribution.
Use a low internal share in a large state to prioritize a coverage investigation. Changes since 2023, deliberate customer exclusions, duplicated offices and parent-account consolidation can all alter the comparison. Document the explanation alongside the numbers so a later analyst can distinguish the diagnostic ratio from a measured accuracy result.
All state counts and derived shares
The table is ordered by total establishments. Shares use the full 51-jurisdiction denominator. Employment-size columns count establishments within each local size band. Use the horizontal scroll area on a narrow screen; the CSV is available above for filtering and analysis.
| State or DC | Establishments | Share of total | Under 5 employees | Under 20 employees | Under 20 share |
|---|---|---|---|---|---|
| California | 10,962 | 16.11% | 7,914 | 9,882 | 90.15% |
| Texas | 6,411 | 9.42% | 4,655 | 5,706 | 89.00% |
| Florida | 4,839 | 7.11% | 3,870 | 4,509 | 93.18% |
| Virginia | 4,080 | 6.00% | 2,858 | 3,498 | 85.74% |
| New York | 3,559 | 5.23% | 2,663 | 3,243 | 91.12% |
| New Jersey | 2,965 | 4.36% | 2,049 | 2,537 | 85.56% |
| Illinois | 2,838 | 4.17% | 2,085 | 2,527 | 89.04% |
| Georgia | 2,537 | 3.73% | 1,885 | 2,252 | 88.77% |
| Maryland | 2,176 | 3.20% | 1,455 | 1,854 | 85.20% |
| Colorado | 2,146 | 3.15% | 1,647 | 1,973 | 91.94% |
| Pennsylvania | 2,099 | 3.08% | 1,453 | 1,850 | 88.14% |
| Massachusetts | 1,736 | 2.55% | 1,140 | 1,470 | 84.68% |
| Ohio | 1,733 | 2.55% | 1,188 | 1,543 | 89.04% |
| North Carolina | 1,680 | 2.47% | 1,241 | 1,521 | 90.54% |
| Washington | 1,585 | 2.33% | 1,050 | 1,349 | 85.11% |
| Michigan | 1,374 | 2.02% | 877 | 1,180 | 85.88% |
| Minnesota | 1,343 | 1.97% | 1,029 | 1,222 | 90.99% |
| Arizona | 1,234 | 1.81% | 946 | 1,128 | 91.41% |
| Utah | 942 | 1.38% | 640 | 826 | 87.69% |
| Oregon | 819 | 1.20% | 607 | 756 | 92.31% |
| Delaware | 765 | 1.12% | 578 | 701 | 91.63% |
| Wisconsin | 759 | 1.12% | 534 | 678 | 89.33% |
| Indiana | 751 | 1.10% | 563 | 684 | 91.08% |
| Missouri | 733 | 1.08% | 507 | 651 | 88.81% |
| Nevada | 661 | 0.97% | 521 | 621 | 93.95% |
| Tennessee | 661 | 0.97% | 429 | 582 | 88.05% |
| South Carolina | 566 | 0.83% | 400 | 513 | 90.64% |
| Connecticut | 539 | 0.79% | 349 | 470 | 87.20% |
| Kansas | 395 | 0.58% | 264 | 351 | 88.86% |
| Alabama | 366 | 0.54% | 233 | 299 | 81.69% |
| Kentucky | 363 | 0.53% | 245 | 321 | 88.43% |
| Oklahoma | 360 | 0.53% | 256 | 331 | 91.94% |
| Iowa | 356 | 0.52% | 249 | 302 | 84.83% |
| District of Columbia | 352 | 0.52% | 200 | 274 | 77.84% |
| Louisiana | 352 | 0.52% | 226 | 309 | 87.78% |
| Idaho | 350 | 0.51% | 267 | 324 | 92.57% |
| Nebraska | 345 | 0.51% | 245 | 302 | 87.54% |
| New Hampshire | 318 | 0.47% | 210 | 286 | 89.94% |
| Arkansas | 242 | 0.36% | 164 | 211 | 87.19% |
| Wyoming | 234 | 0.34% | 208 | 227 | 97.01% |
| Montana | 216 | 0.32% | 170 | 196 | 90.74% |
| Maine | 191 | 0.28% | 142 | 180 | 94.24% |
| Hawaii | 180 | 0.26% | 142 | 173 | 96.11% |
| Rhode Island | 171 | 0.25% | 125 | 155 | 90.64% |
| New Mexico | 165 | 0.24% | 114 | 149 | 90.30% |
| Vermont | 139 | 0.20% | 100 | 126 | 90.65% |
| Mississippi | 116 | 0.17% | 80 | 103 | 88.79% |
| South Dakota | 108 | 0.16% | 83 | 96 | 88.89% |
| West Virginia | 88 | 0.13% | 60 | 78 | 88.64% |
| North Dakota | 80 | 0.12% | 50 | 73 | 91.25% |
| Alaska | 71 | 0.10% | 43 | 62 | 87.32% |
Method, missing values and reproducibility
- Selection. Select the 2023 CBP state bulk file, retain LFO '-' (all legal forms), the exact industry code and the 50 states plus District of Columbia. Do not add legal-form subgroups or industry children to their totals. Join state labels using Census FIPS codes preserved as two-character strings.
- Share calculation. Sum EST across the 51 rows. Divide each row's EST by that sum and multiply by 100 for geographic share. Sort by EST descending, then FIPS ascending to give ties a stable display order.
- Employment-size rule. For the under-20 count, add N<5, N5_9 and N10_19 only when all three are numeric. Otherwise retain a null result and the source N marker. Divide a known under-20 count by the same row's EST for its percentage. Round displayed percentages to two decimals; retain integer counts for reconciliation.
The Census state record layout for 2020–2023 defines the fields and the N marker for unavailable or non-comparable size-class counts. We preserve those markers rather than replacing them with zero. The official state FIPS reference supplies the geography labels.
The observation year is 2023; the report was prepared in 2026. The unit is an employer establishment in the chosen industry, not a unique company or contact. Nonemployer businesses are outside this extract's population. Employment-size categories describe local establishments rather than corporate parents. Geographic shares use only the 50 states and DC, excluding territories. A blank derived size value means unavailable, not zero. These descriptive aggregates do not establish current operating status, parent ownership, buying authority, revenue, purchasing intent or contact-list completeness. The category comparison does not measure missing businesses, subscription models or products. It cannot count all developers, contractors or technical skills, or explain the cause of a state's concentration.
The source archive and its extracted text have recorded SHA256 hashes. A retained subset contains the 255 source rows used across this five-industry series, including the original size-band values. The included calculation script can reproduce every exported row from that subset. CSV blanks correspond to JSON nulls; rounding can leave shares above or below exactly 100%.
The Census methodology page currently warns that its guidance is being updated. This report remains tied to the archived 2023 file and its published record layout, and leaves future release procedures for review against their own documentation. The industry-code reference identifies the 2017 NAICS classification used for this vintage.
This analysis and its prose were prepared with AI assistance. Verum is responsible for the report. Recheck the calculations when a source correction or new data vintage is adopted, and preserve the 2023 baseline as a dated version. The preparation date records this analysis; the business counts retain their original source year.
Related research and account-data methods
- Where software publisher establishments are concentrated
- Engineering service establishments across the states
For the next step, see market-sizing data work and how to define data-quality measures. Match the unit, industry scope and observation date before interpreting any ratio between your records and these aggregates.
Disclosure: Verum publishes this analysis and sells business data verification and enrichment services. Evaluating a vendor's accuracy, completeness or commercial performance requires a separate service assessment.