At a Glance
Knowing the geographic origin of your users helps optimize targeting, reporting, and campaign strategies. In Apptrove, we determine user location using IP data, device metadata, and fallback logic when required.
Why User Location Matters
Geo-based targeting: Run campaign strategies or bidding adjustments by region.
Fraud detection: Spot suspicious behavior (e.g. installs from unexpected countries).
Regional reports & segmentation: Compare performance, retention, LTV by geography.
Ad compliance & region restrictions: Some campaigns or ad networks require location data.
How Apptrove Determines Location
Apptrove uses a combination of methods and data sources to map users to geographic regions. Below is how this generally works:
Method | Source of Data | How it is Used |
IP Geolocation | The user’s IP address at the time of click or install | Primary method: use IP → match against geolocation databases to get country, region, city |
Device / System Metadata | OS locale, network country code, SIM info (where available) | Helps refine or confirm geolocation in ambiguous cases |
Fallbacks / Defaults | Unknown or unresolvable IP, missing metadata | Mark location as “Unknown” or use best-available broader region (e.g. country-level) |
Priority & Overriding Logic
When both IP and device metadata are available, Apptrove may prefer the more reliable source (e.g. IP).
In locales where IP geolocation is less reliable (e.g. for VPNs or proxy), device metadata can help correct.
If neither source yields valid location, Apptrove defaults to a fallback (e.g. “Unknown”).
Temporal vs Click vs Install Location
Location is often determined at the time of click (if tracking link is used).
The install’s location may use the IP at install or first-open time.
Discrepancies can arise if the user moves (e.g. travels) between click and install.
Use Cases & Examples
Example 1: Campaign by Country
You run an ad campaign targeted at Country A. Apptrove tracks that only users whose IP resolve to Country A triggered installs. You can see install count by region after filtering location.Example 2: Mobile Users with Mismatched Metadata
A user connects to Wi-Fi abroad (IP place = Country B) but their SIM / network code is Country A. Apptrove might choose one source or mark fallback depending on confidence rules.Example 3: Unresolvable IP / VPN use
If the user’s IP is from a VPN or proxy, location might not map correctly. Apptrove may mark “Unknown” or use device metadata if available.
Best Practices & Limitations
Expect some “Unknown”: Despite best efforts, a portion of installs may lack location data—especially when IPs are masked.
Use broader time windows when analyzing location-based trends to smooth out anomalies.
Validate with external analytics: Compare Apptrove’s geo splits with your backend or BI system to identify systematic bias.
Avoid over-relying on city-level resolution: Country or region is usually more reliable; city-level may be noisy, especially in rural or less-mapped regions.
Be cautious with weighted decisions: Don’t base heavy bidding changes on small region segments unless sample sizes are strong.
Document expected variance: Have a tolerance threshold (e.g. ±5-10%) for geo mismatches between Apptrove and other sources.
We are delighted to have assembled a world-class team of experienced professionals who are ready to take care of your queries and answer any questions you may have.
Feel free to reach out to us at any time by emailing us at support@apptrove.com or by using the in-platform chat feature. We'd love to hear from you!
