How Job Change Intent Scorer Automates Intent Scoring

Your champions change jobs. Be the first call they take. That single sentence captures a workflow gap that costs customer success teams hours every week. The manual process behind what Job Change Intent Scorer automates is familiar to anyone who has worked in a revenue organization: someone pulls data from Hubspot, Slack, copies it into a spreadsheet or CRM, applies a mental checklist, writes a summary, and routes it to the next person in the chain. Repeat for every record. Every day.

Three problems make this unsustainable at scale. First, the process does not scale. As volume grows, the human bottleneck becomes the constraint. Whether it is inbound leads, deal updates, or meeting prep, a person can only process a finite number of records before quality degrades. Second, the process is inconsistent. Different team members apply different criteria, use different formats, and make different judgment calls. There is no single standard of quality, and the output varies from person to person and day to day. Third, the process is slow. By the time a manual review is complete, the window for action may have already closed. Deals move, contacts change roles, and buying signals decay.

These are not theoretical concerns. They are the operational reality for customer success teams handling intent scoring and contact management workflows. Every hour spent on manual data processing is an hour not spent on the work that actually moves the needle: building relationships, closing deals, and driving strategy.

This is the gap Job Change Intent Scorer fills.

Three Agents. Two Phases. Zero Missed Champions.

Job Change Intent Scorer is a 20-node n8n workflow with 3 specialized agents. Each agent handles a distinct phase of the pipeline, and the handoff between agents is deterministic — no ambiguous routing, no dropped records. The blueprint is designed so that each agent does one thing well, and the overall pipeline produces a consistent, auditable output on every run.

Here is what each agent does:

• The Tracker (Tier 1 Reasoning): Detects job change signals via web_search — new employer, title, start date, public announcements.
• The Analyst (Tier 1 Reasoning): Scores Re-engagement Potential (RPS 1–10) across 4 weighted criteria: relationship warmth (30%), new company ICP fit (25%), timing signal (25%), and new buying power (20%).
• The Briefer (Tier 1 Reasoning): Drafts an actionable re-engagement brief and writes 6 custom HubSpot contact properties — new company, new title, RPS score, brief summary, change detected date, and last scored timestamp.

When the pipeline completes, you get structured output that is ready to act on. The blueprint bundle includes everything needed to deploy, configure, and customize the workflow. Specifically, you receive:

• 20-node n8n workflow (.json) — you own it
• 3 production-ready agent system prompts
• 8 SDC inter-agent schemas
• Error handling matrix (34 failure modes documented)
• HubSpot custom field setup guide (6 fw_ properties)
• Dependency matrix with ITP-measured costs
• README setup guide (10 minutes)

Every component is designed to be modified. The agent prompts are plain text files you can edit. The workflow nodes can be rearranged or extended. The scoring criteria, output formats, and routing logic are all exposed as configurable parameters — not buried in application code. This means Job Change Intent Scorer adapts to your specific process, terminology, and integration requirements without forking the entire workflow.

Understanding how the pipeline works helps you customize it for your environment and troubleshoot issues when they arise. Here is a step-by-step walkthrough of the Job Change Intent Scorer execution flow.

Step 1: The Tracker

Tier: Tier 1 Reasoning

Detects job change signals via web_search — new employer, title, start date, public announcements. Confirms or rules out a change with a confidence score. No change detected? Pipeline terminates here. Zero Phase 2 cost.

This stage is critical because it ensures that downstream agents receive structured, validated input. Each agent in the pipeline trusts the output contract of the previous agent. If The Tracker identifies an issue — a missing field, a low-confidence score, or an unexpected input format — the pipeline handles it explicitly rather than passing garbage downstream. This is the difference between a prototype and a production-grade workflow: every handoff is defined, every edge case is documented.

Step 2: The Analyst

Tier: Tier 1 Reasoning

Scores Re-engagement Potential (RPS 1–10) across 4 weighted criteria: relationship warmth (30%), new company ICP fit (25%), timing signal (25%), and new buying power (20%). Only runs when a job change is confirmed.

This stage is critical because it ensures that downstream agents receive structured, validated input. Each agent in the pipeline trusts the output contract of the previous agent. If The Analyst identifies an issue — a missing field, a low-confidence score, or an unexpected input format — the pipeline handles it explicitly rather than passing garbage downstream. This is the difference between a prototype and a production-grade workflow: every handoff is defined, every edge case is documented.

Step 3: The Briefer

Tier: Tier 1 Reasoning

Drafts an actionable re-engagement brief and writes 6 custom HubSpot contact properties — new company, new title, RPS score, brief summary, change detected date, and last scored timestamp. Optional Slack alert for high-RPS contacts.

This stage is critical because it ensures that downstream agents receive structured, validated input. Each agent in the pipeline trusts the output contract of the previous agent. If The Briefer identifies an issue — a missing field, a low-confidence score, or an unexpected input format — the pipeline handles it explicitly rather than passing garbage downstream. This is the difference between a prototype and a production-grade workflow: every handoff is defined, every edge case is documented.

The entire pipeline executes without manual intervention. From trigger to output, every decision point is deterministic: if a condition is met, the next agent fires; if not, the record is handled according to a documented fallback path. There are no silent failures. Every execution produces a traceable audit trail that you can review, export, or feed into your own reporting tools.

This architecture follows the ForgeWorkflows principle of tested, measured, documented automation. Every node in the pipeline has been validated during ITP (Inspection and Test Plan) testing, and the error handling matrix in the bundle documents the recovery path for each failure mode.

All values below are from ITP testing — not estimates, not projections. Measured across 20 test contacts spanning confirmed job changes, no-change scenarios, and edge cases.

The primary operating cost for Job Change Intent Scorer is the per-execution LLM inference cost. Based on ITP testing, the measured cost is: Cost per Contact (Full Pipeline): $0.29/contact (full pipeline) | $0.21/contact (no change). This figure includes all API calls across all agents in the pipeline — not just the primary reasoning step, but every classification, scoring, and output generation call.

To put this in context, consider the manual alternative. A skilled team member performing the same work manually costs $50–75/hour at a fully loaded rate (salary, benefits, tools, overhead). If the manual version of this workflow takes 20–40 minutes per cycle, that is $17–50 per execution in human labor. The blueprint executes the same pipeline for a fraction of that cost, with consistent quality and zero fatigue degradation.

Infrastructure costs are separate from per-execution LLM costs. You will need an n8n instance (self-hosted or cloud) and active accounts for the integrated services. The estimated monthly infrastructure cost is $5–15/month, depending on your usage volume and plan tiers.

Quality assurance: BQS audit result is 12/12 PASS. ITP result is 18/20 PASS (90%). These are not marketing claims — they are test results from structured inspection protocols that you can review in the product documentation.

9 files. Workflow, 3 system prompts, error handling, and complete documentation.

When you purchase Job Change Intent Scorer, you receive a complete deployment bundle. This is not a SaaS subscription or a hosted service — it is a set of files that you own and run on your own infrastructure. Here is what is included:

• job_change_intent_scorer_v1.json — The 20-node n8n workflow (conditional 2-phase pipeline)
• README.md — Setup guide (10 minutes)
• CHANGELOG.md — Version history
• LICENSE.md — Usage terms
• dependency_matrix.md — Required services, API keys, ITP-measured costs
• error_handling_matrix.md — 34 failure modes mapped to recovery paths
• system_prompts/tracker.txt — Tracker agent system prompt (job change detection)
• system_prompts/analyst.txt — Analyst agent system prompt (RPS scoring)
• system_prompts/briefer.txt — Briefer agent system prompt (re-engagement brief)

Start with the README.md. It walks through the deployment process step by step, from importing the workflow JSON into n8n to configuring credentials and running your first test execution. The dependency matrix lists every required service, API key, and estimated cost so you know exactly what you need before you start.

Every file in the bundle is designed to be read, understood, and modified. There is no obfuscated code, no compiled binaries, and no phone-home telemetry. You get the source, you own the source, and you control the execution environment.

Job Change Intent Scorer is built for Customer Success teams that need to automate a specific workflow without building from scratch. If your team matches the following profile, this blueprint is designed for you:

• You operate in a customer success function and handle the workflow this blueprint automates on a recurring basis
• You have (or are willing to set up) an n8n instance — self-hosted or cloud
• You have active accounts for the required integrations: HubSpot CRM, Slack workspace
• You have API credentials available: Anthropic API, HubSpot API, Slack Bot Token
• You are comfortable importing a workflow JSON and configuring API keys (the README guides you, but basic technical comfort is expected)

This is NOT for you if:

• Does not access LinkedIn API — uses web_search to surface publicly available job change signals (no LinkedIn OAuth required)
• Does not send outreach emails — output is HubSpot property updates + optional Slack alert
• Does not monitor contacts in real time — runs on-demand per contact
• Does not create new HubSpot contacts — enriches existing records only

Review the dependency matrix and prerequisites before purchasing. If you are unsure whether your environment meets the requirements, contact support@forgeworkflows.com before buying.

Deployment follows a structured sequence. The Job Change Intent Scorer bundle is designed for the following tools: n8n, Anthropic API, HubSpot. Here is the recommended deployment path:

1. Step 1: Create 6 HubSpot custom contact properties. Create 6 custom contact properties with the fw_ prefix in HubSpot: fw_new_company, fw_new_title, fw_rps_score, fw_reengagement_brief, fw_change_detected_at, fw_last_scored_at.
2. Step 2: Configure webhook and credentials. Import the n8n workflow JSON and configure your Anthropic API key, HubSpot Private App token, and optional Slack Bot token.
3. Step 3: POST contact data and receive RPS + brief. Send contact data to the webhook endpoint. Receive either a no_change_detected response or a full RPS score with re-engagement brief.

Before running the pipeline on live data, execute a manual test run with sample input. This validates that all credentials are configured correctly, all API endpoints are reachable, and the output format matches your expectations. The README includes test data examples for this purpose.

Once the test run passes, you can configure the trigger for production use (scheduled, webhook, or event-driven — depending on the blueprint design). Monitor the first few production runs to confirm the pipeline handles real-world data as expected, then let it run.

For technical background on how ForgeWorkflows blueprints are built and tested, see the Blueprint Quality Standard (BQS) methodology and the Inspection and Test Plan (ITP) framework. These documents describe the quality gates every blueprint passes before listing.

Ready to deploy? View the Job Change Intent Scorer product page for full specifications, pricing, and purchase.