Introducing NurtureHub: The Lead & Contact Data Schema Powering Everything

v1.0.0 | Foundation Release

Every great product starts with a solid foundation. For NurtureHub — the AI-powered lead nurture platform built exclusively for UK property agents — that foundation is a carefully designed database schema for contacts and leads. Version 1.0.0 ships that schema, and with it, the backbone that every feature from AI email generation to hot lead alerts will rely on.

This post explains what was built, why each decision was made, and what it enables next.

The Problem We're Solving

Property agents — lettings, estate, and property management — manage a wide range of contact types simultaneously: active landlords, prospective sellers, buy-to-let investors, commercial landlords, and more. Each contact type has different needs, different timelines, and different signals of intent.

Most CRM tools treat all contacts the same. NurtureHub doesn't. From the moment a contact enters the system, it is assigned one of 12 predefined lead categories, and that category determines the AI-generated nurture sequence, the engagement tracking approach, and the intent scoring model applied to it.

But before any of that can happen, the data has to be right.

What Was Built in v1.0.0

A Contacts Table Built for Property Agents

The contacts table stores the essential record for every lead or client in the system. It captures:

Name, email, phone, and address — the core identity fields every agent already works with
Source — how the contact entered NurtureHub, whether manually added or imported from a CRM
Organisation ID (orgId) — ensuring every contact is cleanly scoped to the agency that owns it, supporting multi-agency deployments from day one

12 Lead Categories — Fixed, Intentional, Powerful

One of NurtureHub's core design principles is radical simplicity. Rather than asking agents to define their own contact types or build their own segments, NurtureHub provides exactly 12 predefined categories that cover the full spectrum of property contacts:

Seller
Landlord
Buyer
Tenant
Buy-to-Let Investor
Active Tenant
Prospective Landlord
Prospective Seller
Vendor
Applicant
Property Investor
Commercial Landlord

These aren't arbitrary labels. Each category maps directly to a distinct nurture strategy. A Prospective Landlord needs different messaging cadence and content than an Active Tenant. A Buy-to-Let Investor has different intent signals than a Seller. By hardcoding these 12 types into the schema as an enum, NurtureHub ensures the AI layer always has the unambiguous context it needs to generate relevant, personalised email sequences.

Category Assignments with Full Timestamp Tracking

The lead_category_assignments table is the link between a contact and their category. It doesn't just record what category a contact is in — it records when they were assigned, with full timestamp tracking.

This unlocks a set of future capabilities that will make NurtureHub increasingly intelligent over time:

Re-categorisation history — understanding when and how often a contact's status changes
Time-based triggers — firing nurture sequences based on how long a contact has held a particular category
Lifecycle tracking — observing a contact's journey from Applicant to Buyer to Owner over months or years

CRM Source Tracking

NurtureHub is designed to integrate natively with agentOS and via open API with Reapit, Alto, Street, and Loop. For that to work reliably, the schema needs to know where every contact came from.

CRM source tracking fields record the originating CRM system and the external record ID for each contact. This enables:

Deduplication — preventing the same contact from being created twice if they exist in both a CRM and NurtureHub
Bidirectional sync — knowing which external record to update when data changes in NurtureHub
Audit clarity — always being able to trace a contact back to its source of truth

Why This Matters

This release ships no user-facing features. There is no UI, no AI sequence, no email send. What it ships is the data layer that makes all of those things possible — and possible correctly.

Getting this schema right at the start means:

AI sequence generation will always know the contact's category without ambiguity
CRM sync will never lose track of where a contact originated
Intent scoring will have clean, structured data to work from
Hot lead alerts will fire against reliable, consistent records

The 12-category enum is a deliberate constraint. It keeps the product focused, keeps the AI context clean, and keeps the agent experience simple. An agent shouldn't need to think about taxonomy — they should pick a category and let the platform do the rest.

What's Next

With the contact and lead schema in place, the next releases will build the application layer on top of it:

AI nurture sequence generation — producing three-email sequences tailored to each lead category and the agency's brand voice
Review and approval workflow — presenting generated sequences to agents before any email is sent
CRM sync integrations — connecting to agentOS, Reapit, Alto, Street, and Loop
Engagement tracking and intent scoring — measuring open rates, click behaviour, and surfacing hot leads in real time

Every one of those features starts with a contact, assigned to a category, with a known source. That's what v1.0.0 delivers.