Build an inbound lead scoring rubric your team will actually use
Replaces inbound chaos with a four-bucket rubric — hot, work, nurture, discard — a rep can apply in 30 seconds. It ranks your conversion sources by true buying intent, defines the minimum enrichment before routing, and hands you implementable if-then routing logic with speed-to-lead targets per bucket.
You are a marketing operations specialist who has cleaned up inbound chaos at dozens of B2B companies. You know the two ways inbound handling fails: either every form-fill gets a sales call (reps burn out chasing students and tire-kickers, then start ignoring all leads), or scoring becomes a 30-field model nobody trusts. Your rubrics are deliberately simple — something a rep can apply in 30 seconds from the lead record alone — because a rubric that requires a data science degree gets bypassed by Friday. Build my inbound scoring rubric. Produce: 1. THE FOUR-BUCKET RUBRIC: route every inbound lead to HOT (call within 5 minutes), WORK (personalized follow-up within 4 hours), NURTURE (automated sequence), or DISCARD — with crisp, checkable criteria for each bucket based on fit and the intent of the converting action. 2. SOURCE INTENT LADDER: my conversion points ranked by real buying intent (demo request beats pricing-page visit beats webinar signup beats ebook download), with scoring implications for each. 3. THE ENRICHMENT MINIMUM: which 3-4 data points must be appended before routing (company size, industry, role seniority) and where to get them cheaply. 4. SPEED RULES: response-time targets per bucket and what happens when they're missed — because a hot lead worked in a day is a warm lead. 5. ROUTING LOGIC: the if-this-then-that rules ready to implement in my CRM, marketing automation, or an n8n workflow. Before you write anything, interview me. Ask me these questions ONE AT A TIME, waiting for my answer each time: 1. What do you sell, and what does your ICP look like? 2. List every way an inbound lead currently reaches you (forms, demo requests, chat, content downloads, referral intros). 3. Roughly how many inbound leads arrive monthly, and what fraction are obviously bad fits? 4. What happens to a new inbound lead today, step by step, honestly? 5. Who is available to respond, and how fast can they realistically move? Once you have my answers, produce the rubric. Calibrate the bucket thresholds so the HOT bucket matches my team's actual capacity to respond fast.
How to use it
- 1
Copy the prompt into Claude, ChatGPT, or any LLM.
- 2
Audit your real inbound flow before answering question 4 — the gap between assumed and actual handling is usually the biggest finding.
- 3
Implement the routing logic in your CRM or an n8n workflow the same week, starting with just the HOT bucket rules.
- 4
Track speed-to-lead per bucket from day one; the rubric only pays off if hot leads actually get called fast.
- 5
Review a sample of DISCARD-bucket leads monthly to confirm the rubric isn't throwing away revenue.
Best practices
Rank sources by intent, not volume — one demo request outweighs fifty ebook downloads, and your routing should reflect that.
Keep the HOT bucket small enough that a five-minute response is achievable; a hot bucket nobody can service on time is a fiction.
Enrich before routing, not after — a demo request from an unknown domain might be your best lead this month or a student.
Resist criteria creep: every added rule makes the rubric slower to apply, and speed is the entire point of inbound.
Example: what this looks like in practice
A marketing manager at a payroll software company gets 350 inbound leads monthly across demo requests, a pricing calculator, and gated content — all of which currently trigger the same generic email and an eventual SDR touch, days late. The rubric routes demo requests and calculator completions from 20+ employee companies to HOT with a 5-minute call target, solid-fit content downloaders to a personalized WORK follow-up, students and micro-businesses to NURTURE or DISCARD. The enrichment minimum is company size and role via a cheap append step in n8n. First month's results: SDRs handle 60% fewer leads, hot-lead response time drops from 9 hours to 6 minutes, and demo-request-to-meeting conversion doubles.
Best fit
This prompt is one gear in a bigger machine. We orchestrate 20+ tools into outbound systems our clients own — and guarantee the results.
Apply for a Pilot Spot → →Frequently asked questions
Inbound leads arrive with intent already displayed — the question is how much. Score primarily on the converting action (a demo request signals near-purchase intent; an ebook download signals curiosity) combined with company fit. Outbound scoring is mostly fit-based because you initiated contact. The other difference is speed: inbound value decays in hours, so scoring must route instantly, not batch overnight.
More icp, targeting & lead scoring prompts
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Design a lead scoring model with firmographic and behavioral points
Produces a complete, implementable lead scoring model: firmographic fit points, behavioral intent points with decay and negative scoring, threshold bands tied to actions, and a monthly validation loop. It caps complexity at 12 criteria and adapts to what you can actually track, so the model ships instead of dying in a spreadsheet.
Build a negative ICP: who to actively avoid and why
Turns your worst-customer war stories into a formal negative ICP: hard disqualifiers, stacking yellow flags, and the false-positive profile that keeps fooling your team. Includes list-building exclusion filters and a polite decline template, so avoiding bad fits becomes operational instead of a lesson everyone relearns quarterly.