Step 1: Enter the target username into FootprintIQ's Telegram search module. The system checks for exact matches, common variations (underscores, dots, numbers), and previously known aliases associated with the handle. Results are returned with confidence scores indicating the probability that each match represents the same individual.
Step 2: Review the Telegram profile's public information. Document the following data points: display name, bio/about text, profile and cover photos, account creation date (if visible), follower/following counts, public post history, and any linked external accounts or websites. Each data point serves as a potential correlation signal for cross-platform identity resolution.
Step 3: Initiate a cross-platform scan. Use the Telegram username as a seed for FootprintIQ's full 400+ platform scan. The system automatically tests the exact username and common variations across social media, forums, developer platforms, gaming networks, dating sites, and professional directories. Each hit is then labelled against a measured per-site baseline for how often that checker reports a match, because the same username often belongs to different individuals on different platforms.
Step 4: Investigate cross-platform metadata. Compare profile photos using reverse image search, analyse bio text for consistent personal details, and check posting patterns for timezone correlation. Document which signals support identity linkage and which suggest distinct individuals sharing a common username.
Step 5: Compile findings into an actionable report. For self-audits, prioritise remediation actions: delete unused accounts, update privacy settings, change reused usernames on sensitive platforms, and enable MFA. For professional investigations, structure findings using FootprintIQ's report generation tools, which produce compliance-ready documentation with evidence chains and confidence assessments.