When building user-segmentation tools or cleaning contact databases, developers often look for signals that indicate whether a Telegram account is "active." Within the TG Validator ecosystem, the activedays field provided in bulk activity and profile checks is a key metric. However, interpreting this signal correctly is essential for building robust, data-driven applications.

What is activedays?

In the context of bulk asynchronous tasks, activedays represents the number of days since a user’s last recorded activity on the platform. It is an approximate metric. Because Telegram may hide exact last-seen timestamps for privacy reasons, this value should be treated as a heuristic rather than a precise, real-time presence indicator.

It is critical to distinguish between a registration signal and an activity signal. A registration check simply confirms that an account exists at the time of the check. An activity check provides additional context, but it does not guarantee that a user is currently online or available to receive messages.

Implementation Checklist for Bulk Activity Checks

Before integrating bulk activity or profile checks into your pipeline, ensure your architecture handles the asynchronous nature of these tasks correctly:

  • [ ] Task Lifecycle Management: Bulk tasks are asynchronous. Ensure your system is designed to submit a file (CSV or TXT), poll for completion, and then retrieve the final result file. Avoid assuming synchronous responses for bulk operations.
  • [ ] Polling Discipline: When polling for task status, maintain a non-aggressive interval. The API documentation specifies a recommended polling frequency; ensure your implementation respects this to avoid unnecessary load.
  • [ ] Data Minimization: Per GDPR Article 5(1)(c), ensure that the data you are requesting is relevant and limited to your specific business purpose. Only request profile or activity data if it is strictly necessary for your segmentation logic.
  • [ ] Handling Approximations: Build your application logic to treat activedays as a relative window rather than an absolute timestamp. For example, filtering accounts with activedays > 90 is a useful segmenting strategy, but do not rely on the exact integer for time-sensitive operational triggers.
  • [ ] Avatar Estimates: If you are using tg_profile_batch or tg_username_profile_batch, remember that age, gender, and skin-color fields are estimates derived from avatars. These are not verified identity documents and should not be used as the sole basis for high-stakes identity verification.
  • [ ] Security and Credentials: Always store your API keys securely using environment variables. Never hardcode keys in your source code or expose them in client-side applications. Use the X-API-Key header for REST API requests.

Operational Boundaries

Remember that TG Validator does not provide live online presence, private message history, or contact lists. The signals provided are snapshots based on public platform data. When designing your user-segmentation tool, treat the results as a way to prioritize or filter your outreach efforts, not as a definitive map of a user's current intent or availability.

For specific details on request concurrency and timeout configurations, always refer to the official API documentation.

This article was drafted with AI assistance and reviewed before publishing.