Lead intake for a small B2B agency
A concept build that turns scattered inbound enquiries into a single, enriched pipeline — so no lead waits on someone remembering to copy it into the CRM.
One
pipeline instead of three inboxes
Internal build — describes the design, not a measured result
< 2 min
from enquiry to enriched CRM record
Internal build — design target, not a client result
Nothing
dropped without a logged reason
Internal build — describes the design, not a measured result
Problem
Enquiries arrive through a website form, a shared inbox and the occasional LinkedIn message. Someone has to notice each one, judge whether it is worth pursuing, look up the company, and paste it into a CRM. It happens late, or not at all, and there is no record of what was ignored.
Before — the manual workflow
- 01
New enquiry lands in a shared inbox
- 02
A team member notices it (eventually)
- 03
They manually research the company and contact
- 04
They decide, informally, whether it is worth a reply
- 05
Some enquiries are copied into the CRM; some are lost
Intervention
A single intake system that watches every channel, enriches each enquiry with public company data, scores it against a written definition of a good-fit lead, and creates a CRM record with a suggested next step. A person still approves anything before outreach — the system removes the busywork, not the judgment.
Why this build exists
This is an internal concept build, not a paid client project — and it is labeled that way on purpose. It shows how we think about a common, unglamorous problem: inbound leads that depend on a person remembering to act.
The numbers below are design targets for this build, not measured client outcomes. When we run this for a real company, the results section will say so and cite where each figure came from.
The system, in plain terms
Every channel feeds one intake step. Each enquiry is enriched and scored, then a CRM record is created with a recommended next step. A human approves outreach. The result is one legible pipeline instead of three places to check.
What we would watch in production
A system like this fails quietly rather than loudly, so the interesting work is in the instrumentation:
- Enrichment misses. Public data is incomplete for small companies. Anything the enricher cannot resolve goes to a human queue rather than being scored on missing fields.
- Score drift. A “good-fit lead” definition written in January is wrong by June. The score is reviewed against closed-won data, not left to run forever.
- Channel silence. If a shared inbox stops delivering, nothing errors — the pipeline just goes quiet. Each channel gets a heartbeat check so silence is itself an alert.