To include only users from Brazil or Argentina, apply view filters that restrict sessions to the respective country codes: select filter expressions that match the GEOIP country field for Brazil (BR) and Argentina (AR) in your analytics platform. This approach ensures data inclusion is limited to visits from those two countries. The following sections explain how country-based filters work, how to configure them in common tools, and how to validate that your setup captures only Brazilian and Argentine traffic.
Core concepts for country-based filtering
GeoIP country filters rely on IP address mapping to determine session location. A filter configured to include Brazil and Argentina typically specifies a condition where the country code matches BR or AR. Understanding the data model is important: hits, sessions, and users can be attributed to a country based on IP, registration details, or explicit signals. When you apply these filters to a view, you exclude traffic from all other countries, reducing data volume and complexity for regional analysis. Note that accuracy varies by provider and can be influenced by VPNs or proxy usage.
How filters work at the data model level
At a high level, a view filter inspects each hit’s geographic metadata and either includes or excludes the session from reporting. Inclusion filters let through only matching events; exclusion filters block matching events. For Brazil and Argentina, you generally want an include filter on country equals BR plus an additional condition for AR, often implemented as a single expression that matches either code. Most platforms evaluate these rules before aggregation, so only sessions with those country codes contribute to metrics. Remember that filters are applied at view level and are irreversible for historical data, so implement them deliberately and test with sampled data first.
Practical implementation options
Implementation details depend on your analytics stack. Below are common patterns with concise examples and considerations. Choose the approach that matches your tooling and governance practices.
Google Analytics 4 configuration patterns
In GA4, you configure country filters using custom filters or audiences. Custom filters can include sessions where country dimension equals Brazil or Argentina. Audiences based on geo conditions allow reuse across reports and downstream integrations. Consider scope implications: session-level filters affect reporting, user-level filters shape long-term segments. Validate that the filter expressions use the correct dimension name and country codes. Keep a small holdout segment without the filter to compare coverage and detect data anomalies.
Google Analytics 4 filter expressions example
- Include country equals AR: country == AR
- Include country equals BR: country == BR
- Combined expression: country == AR OR country == BR
Adobe Analytics filter approach
In Adobe Analytics, create a report suite with a suite-level filter that includes geo country codes BR and AR. Use conversion variables and props to capture country, and optionally refine with VISTA rules if you need cross-hit persistence. Set up test groups to confirm that only expected traffic is recorded and that triggered events follow the intended regional logic.
Matomo and other on-premise platforms
Matomo allows you to define exclude or include IP ranges or country codes in the interface, and you can also use the GeoIP2 database for more consistent mapping. For self-hosted deployments, ensure your GeoIP dataset is updated regularly; outdated mappings can misclassify addresses and distort regional metrics. You can export server logs to verify that only BR and AR IPs appear in processed datasets.
Validation and ongoing monitoring
After you apply filters, run checks to confirm that sessions from Brazil and Argentina are captured as expected. Compare aggregated sessions before and after filter activation, inspect a sample of IP addresses, and verify that country codes align with expectations. Monitor for drops that could indicate incorrect filter logic, changes in traffic mix, or infrastructure shifts such as new CDN endpoints. Schedule periodic reviews of GeoIP accuracy if your use case is sensitive to small measurement errors.
Examples of common pitfalls and mitigations
Common issues include misconfigured country codes, overlapping filters that exclude desired traffic, and stale GeoIP databases. Users behind VPNs may appear in a different country, which can undercount true Brazilian or Argentine reach. To mitigate, combine country filters with additional signals when feasible, document filter logic and ownership, and maintain a fallback analysis without the filter to estimate undercoverage. If you manage multiple properties, ensure naming conventions make it clear which filters target Brazil and Argentina.
| Attribute | Verified Detail | Source Type |
|---|---|---|
| Country codes included | BR (Brazil), AR (Argentina) | Standard ISO 3166-1 alpha-2 |
| Filter type | Include by GEOIP country dimension | Platform configuration |
| Typical rule format | country == AR OR country == BR | Platform documentation |
| Data impact | Only sessions from BR and AR are retained | Platform behavior |
| Immutability note | View filters are irreversible for past data | Best practice guidance |
Advanced considerations for regional targeting
Beyond basic inclusion, you may need to distinguish between Brazilian states or Argentine provinces. While country-level filters are sufficient for many analyses, subnational breakdowns require regional dimensions or custom parameters. Be aware of regulatory differences that may affect measurement, consent flows, and data retention. Align your taxonomy so that naming conventions for Brazil and Argentina are consistent across properties and tools, making it easier to maintain and audit filters over time.
Operational best practices
Document filter logic in a central location and assign ownership for updates. Use version control for configurations when possible, and test changes in a test view before promoting them to production. Coordinate with data governance and analytics owners to ensure filters do not conflict with other reporting rules. Periodically verify that your regions of interest remain correctly mapped as IP databases and platform logic evolve.
Summary
To include only users from Brazil or Argentina, apply include view filters that match the GEOIP country dimension to BR and AR, using OR logic to capture both countries. Implement the filter in your analytics platform, validate with sampled checks, and monitor over time to ensure continued accuracy. Understanding limitations and combining country filters with additional signals when necessary helps maintain reliable regional measurement.