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From Export-Sales Lead Pool to Attributed Inquiry: The Tables a TG Phone Must Cross

Organize export-sales TG checking across provenance, cleanup, observation, permission, touch and inquiry tables for traceable attribution.

Updated 9/11/20263 minBy AppShai Research

Article summary

Organize export-sales TG checking across provenance, cleanup, observation, permission, touch and inquiry tables for traceable attribution.

The most common TG attribution error in export sales is counting “observed active” as “inquiry generated.” Activity is a platform observation; an inquiry is a business event. Between them are provenance, permission, touches and sales records. A phone needs at least six tables with distinct responsibilities.

Table one: the lead-provenance ledger

Store lead_id, source_type, source_campaign, captured_at, country_evidence and permission clues. A trade-show card, website form, customer referral and purchased list cannot all collapse into source=import.

Table two: the phone-cleanup workbench

Keep phone_raw, phone_normalized, format_rule, exception_reason and dedupe_group. Country-code conflicts, extensions, uncertain length and duplicate provenance receive separate treatment. Never pad digits to manufacture acceptance.

Table three: TG observation events

Task Main return Role in attribution
TG Registration Phone, registration observation Channel observation
TG Activity UserID, username, offline time, active days and related fields Queue support
TG Username Account-related observations Matching and review clues

Every result carries checked_at and batch_id and never overwrites provenance.

Table four: permission and suppression ledger

Record who agreed, by what mechanism, to which sender, channel and purpose, and when consent was withdrawn. TG registration or activity cannot create permission. A new observation cannot override an opt-out.

Table five: the touch event stream

Every human or automated contact records touch_id, lead_id, channel, content_version, sent_at and response_type. Without touch_id, the organization cannot distinguish number checking’s contribution to queue efficiency from the effect of content.

Table six: inquiries and opportunities

A request for price, sample request, meeting, quotation and closed deal are different events. Store inquiry_id, first_qualified_at, product_interest and sales_owner. An emoji response is not automatically a qualified inquiry.

How the tables link—and how they do not merge

Use internal lead_id and event keys. Do not use UserID, username or phone as a permanent universal key. One person with multiple phones, phone reassignment and shared operating accounts require one-to-many relationships and validity dates.

The TXT task crosses the narrowest channel

Export a TXT file with one phone per line from the cleanup table and retain a batch_row crosswalk. Name, country, product, permission and sales stage are not uploaded. Returned Excel lands first in the TG observation table.

Rates the export-sales funnel should report

  • Format acceptance rate: cleanup quality.
  • TG observation coverage: channel input.
  • Permitted queue rate: permission and operating rules.
  • Meaningful response rate: communication performance.
  • Qualified inquiry rate: sales outcome.

Where Number Checking truly contributes

It may reduce irrelevant channel attempts and make human queues more explainable, but it cannot claim sole attribution for a closed deal. Telegram’s Privacy Policy frames platform-data handling, while the organization’s event chain must prove inquiry attribution.

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