Aberrant AI

Case study

Sales Follow-up Automation

Follow-ups disappear in personal reminders and chat threads.

Operating problem

What keeps breaking.

Follow-ups depend on personal memory.

Sales aging is not visible.

Client response status is not tied to next action.

Managers ask for updates instead of seeing them.

Build model

The work becomes a clearer system.

Trigger follow-up tasks from CRM status, quote date, client response, and aging rules.

Operating path

Follow-ups trigger from lead status, quote age, client response, owner rules, and pipeline stage.

AI/product layer

Summarize the client signal, draft the follow-up, and recommend timing.

Reusable improvement

Winning follow-up patterns become reusable timing, message, and owner rules.

Workflow

The sequence becomes explicit.

Lead or quote tracked
Aging rule applied
Follow-up generated
Owner notified
Response logged
Pipeline updated

Capabilities

What the system needs.

Follow-up rules

Aging dashboard

Owner tasks

Response logging

Manager visibility

Connected tools

Where the system fits.

CRMQuotation systemEmailChatDashboards

Implementation path

More disciplined pipeline movement.

01

Step 1

Map sales stages

02

Step 2

Define follow-up rules

03

Step 3

Connect communication signals

04

Step 4

Review pipeline behavior weekly

Automate Sales Follow-up

Tell us where this work currently breaks. We will map the first useful AI/product build path.