---
name: score-and-tier
description: Score accounts, bucket into tiers, and re-score as new signals come in
---
# Dynamic Account Scoring and Tiering
OpenFunnel runs thousands of signals daily, producing a universe of accounts with rich signal data (job postings, social posts, engagement, job changes). This skill scores that universe and buckets accounts into tiers so customers can operationalize it.
Customers do NOT think in terms of signals. They don't want to configure "hiring + socials + engagement." They want:
- **Pain-based scoring** (OpenFunnel recommended) — "What pain does your product solve?" → we score everything through that lens
- **Custom prompt** — customer describes their own scoring criteria in plain English
The signals are evidence the scoring reads. Not knobs the customer turns.
---
## Scoring Universe
The scoring universe is **all OF accounts**. This includes:
| Pool | Evidence available |
|---|---|
| **OF only** | Traits + signals (job postings, social posts, engagement, job changes) |
| **OF + CRM** | Traits + signals + internal CRM data (deal stage, outreach history, pipeline status). CRM data is already attached to OF accounts via CRM sync — V2 batch returns `crm_status` and `crm_details`. |
Accounts in the customer's CRM that have **zero OF signal coverage** do not enter scoring. OF's signal coverage (especially deep enriches running across thousands of signals) is robust enough that any account showing buying activity will be picked up.
### CRM Coverage Gap
Some high-priority CRM accounts may not have OF signals. This is a **coverage gap, not a scoring gap**. The skill should surface it:
> "X of your CRM accounts have no OF signal coverage. Want to import them for deep enrichment?"
**Import flow:** Customer provides a CSV of domains for accounts they want scored. These get deep enriched (15-30 min async per account), enter the OF universe with signal data, and then enter scoring alongside everything else.
This is manual and intentional — bulk deep enriching the entire CRM is too expensive and most CRM accounts are garbage. The customer picks the ones that matter.
---
## Part 1: First-Time Init Scoring
One-time setup: score the full account universe, bucket into tiers, create tier audiences.
### Step 1: Pick source audience
List audiences. Customer picks the one containing their account universe.
Optionally surface CRM coverage gap: check for CRM accounts with no OF signals and offer import.
### Step 2: Pick scoring model
> How would you like to score these accounts?
>
> 1. **Pain-based** (recommended) — scores each account based on how urgently they need what you sell
> 2. **Custom** — describe your own scoring criteria in plain English
### Step 3: Get the scoring lens
- Pain-based → "What pain does your product solve? Example: 'We help companies migrate off legacy ERPs to cloud-native'"
- Custom → customer provides their criteria
This is the lens. Every account's signals get read through it.
### Step 4: Score accounts
For each account in the audience:
1. Pull V2 batch data (inline signal content — actual job posting text, social posts, context, CRM details)
2. Pull timeline (chronological events)
3. Read all evidence against the scoring lens
4. Assign score (0-100) + reasoning (1-2 sentences)
### Step 5: Tier
Present the scored distribution. Customer defines tiers — either:
- Threshold-based: "Tier 1 = 80+, Tier 2 = 50-79, Tier 3 = below 50"
- Or customer tells us their bucketing logic
Output: every account has a score, reasoning, and tier.
### Step 6: Pipe to tier audiences
Create a new audience per tier. Each audience is named by tier (e.g. "Tier-1", "Tier-2", "Tier-3") and contains the account IDs that landed in that bucket.
Use `POST https://api.openfunnel.dev/api/v1/audience/create { audience_name, account_ids }` to create each tier audience.
---
## Part 2: Scoring New Accounts
Once accounts are scored, tiered, and assigned — they stay put. No re-scoring, no tier movement. New signals on existing accounts directly benefit the rep who owns them.
The continuous piece is **new accounts entering the OF universe**. Signals fire daily, producing new accounts that weren't in the last scoring run. These need to be scored, tiered, and assigned.
### Flow
Runs on a cron (e.g. daily). Uses the alerts API to detect new accounts.
1. **Poll alerts** — `GET https://api.openfunnel.dev/api/v1/insights/alerts { days, limit, offset }` filtered by `view_name` matching the master scoring audience. Returns newly discovered accounts since last check.
2. **Diff** — compare alert account IDs against already-scored accounts. The delta = new accounts to score.
3. **Score new accounts** — same lens (pain-based or custom prompt), same rubric, same four dimensions.
4. **Tier new accounts** — apply the same tier boundaries from init scoring.
5. **Add to tier audiences** — `POST https://api.openfunnel.dev/api/v1/audience/add-accounts { audience_id, account_ids }` for each tier.
6. **Enter assignment** — new accounts in each tier are available for assignment (round robin, etc.)
### What stays the same
- The scoring lens (set during init, doesn't change)
- The tier boundaries (set during init)
- Existing accounts in their tiers (don't move)
### What changes
- The source audience grows as OF picks up new accounts from signals
- New accounts need to be caught, scored, and placed
---
## How Scoring Works
**Time is the most important factor.** Pain has a shelf life. A perfect-fit signal from 90 days ago with nothing since is stale, not hot.
Read the timeline as a narrative, not a list. A single signal is a hint. A sequence over weeks is a story.
### Four dimensions (use judgment, not mechanical buckets):
**1. Pain Relevance**
Does this account show signs of having the pain described in the scoring lens?
- Job descriptions describing the problem (read the actual content, not just titles)
- Social posts discussing the pain area
- Tech stack that creates or relates to the pain
- Industry alignment
**2. Temporal Signal**
When did the pain surface? Is it still alive? This dimension can override everything else.
- Signal from 90 days ago with no follow-up = cold. Score LOW.
- Weaker signal from last week > strong signal from 3 months ago
- Velocity: signals clustering in recent weeks = active and building
- Decay: gaps in the timeline after initial signals = cooling off
- Trigger → follow-through: did the triggering event (new hire, funding, leadership change) lead to more activity? If yes = escalating. If no = stalled.
**3. Buying Window**
Can they act now?
- New leadership in relevant function
- Recent funding
- Active hiring in the area
- Multiple signal types pointing at same pain = high conviction
**4. Story Coherence**
Do signals tell a connected narrative?
- Isolated signal = maybe noise, score conservatively
- Connected signals across time = real pattern
- Example: Jan hired VP Eng → Feb posted about migration challenges → Mar hiring cloud engineers = escalating story
**The score should reflect: "If I were selling a solution to [pain], how excited would I be about this account RIGHT NOW — today?"**
---
## API Calls
| Step | Endpoint | Description |
|------|----------|-------------|
| Step 1 | `POST https://api.openfunnel.dev/api/v1/audience/get-audience-list { limit, offset }` | List audiences for customer to pick source |
| Step 1 | `POST https://api.openfunnel.dev/api/v1/audience/ { audience_id }` | Get account IDs from source audience |
| Step 4 | `POST https://api.openfunnel.dev/api/v2/account/batch { account_ids }` | Full details with inline signal content + CRM data |
| Step 4 | `GET https://api.openfunnel.dev/api/v1/account/{accountId}/timeline { days, limit, offset }` | Chronological events |
| Step 6 | `POST https://api.openfunnel.dev/api/v1/audience/create { audience_name, account_ids }` | Create tier audience (init) |
| Part 2 | `GET https://api.openfunnel.dev/api/v1/insights/alerts { days, limit, offset }` | Poll for new accounts in master scoring audience |
| Part 2 | `POST https://api.openfunnel.dev/api/v1/audience/add-accounts { audience_id, account_ids }` | Add new accounts to existing tier audience |
All endpoints require headers: `X-API-Key`, `X-User-ID`, `Content-Type: application/json`.
> **NOTE:** 3 API calls per account (summary + V2 batch + timeline). Large audiences (100+) will be slow.
Skills