SCOUT received two significant data updates during the second half of 2025: an updated drive-time engine and a refreshed demographic dataset. As a result, you may notice differences when comparing current drive-time trade areas, population counts, or other demographic metrics with results generated earlier in 2025.

The two updates affect SCOUT results differently:

These changes may appear independently or together. For example, the population reported within a 10-minute drive time could change because the drive-time polygon itself changed, the underlying demographic data changed, or both.

Updates introduced in January 2026 have stabilized drive-time calculations, and both drive-time and demographic data now follow an annual update cadence.

Buxton transitioned to a new drive-time engine during the second half of 2025. The previous engine and the current provider model road networks and traffic differently, which means the same address and drive-time duration may produce a differently shaped trade area.

The current engine is designed to account for real-world factors such as:

These differences can be particularly noticeable in dense urban environments, where realistic travel speeds can result in more conservative drive-time trade areas.

Buxton also refreshed the demographic dataset used throughout SCOUT during the second half of 2025. The updated dataset is the first version based on projections from the 2020 U.S. Census. Previous versions were based on projections from the 2010 U.S. Census.

Although many measures remain broadly similar, individual demographic fields can change between releases. Certain measures, including income-related metrics, may show more noticeable differences.

The effect you see in SCOUT depends on the geography and data used in your analysis.

Because demographic figures are calculated within a selected geography, a change to the drive-time polygon can also affect the demographic totals reported for that area. For example, a population difference within a 10-minute drive time does not necessarily indicate that the population data alone changed. The drive-time polygon may also cover a different geographic area than it did previously.

Buxton transitioned to a new drive-time engine during the second half of 2025.

The previous engine and the current drive-time provider model road networks and traffic differently. As a result, the same address and drive-time duration can produce differently shaped trade areas.

The current engine tends to produce more conservative trade areas in dense urban environments, where congestion, intersections, and traffic patterns reduce realistic travel speeds.

Because demographic values are calculated within the resulting polygon, changes to the size or shape of a drive-time area can also affect population and other demographic totals.

When the new drive-time engine was initially introduced, it used a continuously updating routing dataset.

As the provider refreshed its underlying road network and traffic models, drive-time results could change between report runs. Based on client feedback and the need for greater consistency in reporting and analysis, Buxton updated this approach in January 2026.

Buxton introduced two changes to improve the consistency of drive-time calculations.

Buxton's analytics team evaluated more than 12.6 million geographic grids across the United States while calibrating the updated drive-time engine. Adjustments were tested for logical consistency against trusted real-world benchmarks and account for factors such as urban density and roadway behavior.

With the transition to a static annual routing dataset, these calibrations remain consistent between annual updates rather than changing alongside continuously updated routing data.

The demographic dataset was updated separately from the drive-time engine.

The current demographic dataset is based on projections from the 2020 U.S. Census, while the previous dataset was based on projections from the 2010 U.S. Census.

As a result, demographic values can differ even when the geography being analyzed has not changed. While many measures remain broadly similar, some fields, including income-related measures, may show more noticeable differences between releases.

Both datasets now follow an annual update cadence:

Aligning these updates provides more predictable intervals for data changes rather than allowing the underlying drive-time information to update continuously.

If maintaining a mathematically consistent geography is important for historical comparisons, consider using mile-based trade areas. A mile-based geography is fixed. For example, a 5-mile radius represents the same geographic boundary regardless of changes to routing or drive-time models. Keep in mind that while mile-based geographies are not affected by drive-time engine updates, the demographic values reported within them can still change when demographic data is updated. Drive-time geographies remain consistent within the current annual data cycle but may change when the routing dataset is updated.

Not necessarily. The impact depends on the geography, data, location, and when the report was generated.

Drive-time updates affect SCOUT features that use drive-time geographies, including:

The demographic data update affects reports and features that use demographic fields.

No action is required. If you are conducting an analysis that relies on historical comparisons, consider whether changes to the drive-time geography, demographic data, or both could affect the results you are comparing.

For analyses that require a consistent geographic boundary across multiple time periods, a mile-based geography may be more appropriate.

Contact your Customer Success Manager if you need help interpreting differences in a specific report, location, or analysis. Your Customer Success Manager can review the results with you and, when appropriate, work with the Buxton analytics team to determine whether differences are related to the drive-time engine, demographic data update, or a combination of both.