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AtlasRepo

An LLM agent that qualifies B2B leads from AmoCRM: notes from a production build

Описание и применение

LLM‑агент заменил ручную обработку входящих лидов в AmoCRM, сократив время квалификации с 40 до 8 минут, обеспечив ответ каждому лиду и увеличив долю лидов, переходящих к продажам, на 31%.

Задача

A B2B client had 50‑80 inbound leads per day and a single first‑touch sales manager who spent six hours daily answering repetitive questions, leading to uneven filtering and missed replies.

Результат

Lead qualification time reduced from 40 to 8 minutes, every inbound lead answered, and the share of leads reaching a sales conversation increased by 31%.

Рабочий процесс

  • Pull new leads from AmoCRM API v4 each morning
  • Classify request type (price question, materials request, etc.)
  • Open conversation in the originating channel (Telegram or WhatsApp via Wappi)
  • Qualify lead on six criteria (volume, budget, timing, ICP fit, etc.)
  • Move deal to appropriate pipeline stage and tag it
  • Provide admin panel for managers to view and override conversations

Доказательства

A B2B client came to us with 50 to 80 inbound leads a day and one first-touch sales manager. About six hours of that person's day went to the same questions: what are your prices, can you send the deck, do you work with our volume.

Источник

Qualifying a lead takes about 8 minutes instead of 40.

Источник

The share of leads that reach a sales conversation went up 31%. That came from consistency alone: the same questions, asked every time, with nothing forgotten.

Источник

Start from the CRM fields, not the prompt. Decide what a qualified lead looks like as data, then make the model fill exactly those fields.

Источник

Give people a visible override. The admin panel was one of the cheapest parts of the project, and it is the reason the team accepted the bot.

Источник

  • Дата записи: 2026-10-03T10:56:31.195Z