Beyond VPN Metering: How On-Device AI Is Changing Panel Data Collection

For over a decade, VPN-based metering has been the default approach to capturing digital behavioural data from panel respondents. It works by installing a VPN on the panellist’s device, routing all network traffic through a monitoring layer, and exporting raw data to the cloud for processing.

The technology delivers genuine value. Full URL-level web browsing, app usage across every installed application, network traffic metadata — VPN metering gives panels deep visibility into what respondents do on their devices. For specific research projects requiring granular browsing data, it remains a powerful tool.

But the costs have been mounting for years, and panel operators know it.

The Growing Price of VPN Metering

Battery drain, device lag, and streaming interruptions are not edge cases — they are inherent to routing all device traffic through a VPN. Panellists notice. App store reviews reflect it. Churn follows.

This is why an increasing number of panel companies no longer install VPN metering on their own apps. Instead, they send respondents to separate third-party metering apps, fragmenting the experience and limiting coverage to the subset of panellists willing to download yet another application.

At the same time, the regulatory and platform environment is shifting against bulk data export. Apple and Google are tightening VPN capabilities on mobile — particularly on iOS. GDPR and CCPA data minimisation requirements make intercepting and storing comprehensive personal data increasingly complex. The architecture that made VPN metering powerful is the same architecture creating risk.

A Different Architectural Approach

On-device AI flips the model. Rather than intercepting traffic and exporting raw data to the cloud, an embedded SDK processes data directly on the respondent’s device using small language models and machine learning.

The privacy implications are significant. Sensitive personal information — a date of birth, a health metric, a financial transaction — never needs to leave the device. It stays as what DataSapien calls “Zero-Shared Data.” Only the inferences and consented insights need to be shared as “Zero-Party Data.” A panellist’s most sensitive data (e.g. date of birth) stays on their phone; their age category is what the panel receives.

This architecture also unlocks an entirely new category of data that VPN metering structurally cannot reach: personal context intelligence. Health and wellness behaviours, financial patterns, lifestyle signals, calendar data, location context — respondents will not share this raw data with cloud servers, and platforms increasingly prevent it. On-device processing means panels can generate insights from this data without ever collecting it.

What Changes for Panel Operators

The operational differences are immediate. An on-device SDK embeds directly within the panel’s own app — no separate download, no VPN activation, no fragmented experience. That means 100% of panel app users can participate, not just the subset willing to install a third-party metering app.

There is zero impact on device performance. No battery drain, no app conflicts, no streaming interruptions. The panellist experience is protected, and with it, the KPIs that matter: retention, engagement, app store ratings, and customer lifetime value.

Data quality improves through multi-source triangulation. On-device processing can cross-reference the same data point — say, a respondent’s location — across GPS, GeoIP, language settings, carrier data, timezone, and behavioural signals to generate a veracity score. This kind of validation is architecturally impossible when you can only observe network traffic from a single vantage point.

And the trajectory is favourable. Apple Intelligence and Android’s on-device AI investment signal clearly where mobile platforms are heading. On-device processing is aligned with that direction; VPN interception is working against it and becoming operationally constrained.

Complementary, Not Competitive

VPN metering and on-device AI observe fundamentally different layers of the respondent’s digital life. Panel operators do not need to choose one or the other. The strategic opportunity is to deploy on-device AI across the full panel base for personal context intelligence, engagement, and data quality — while continuing to use VPN-based solutions for specific projects that require deep network traffic analysis. Try out the sandbox app here (we charge a £0.40p fee as a KYC check).

Get the Full Comparison

Our white paper, VPN Metering vs Device Native AI, provides a detailed technology comparison across architecture, data capabilities, respondent experience, privacy and compliance, operational factors, and data veracity — including a summary of where each technology wins.

Download the white paper →

For more information or any questions, check out the Insight Panels Page on our website, or feel free to contact us. We’d love to hear from you.