Open the current queue
Start in the saved audience or search result your team trusts. Use score as the priority layer, then inspect the reason before you act.
Frontline start path
Start with the scored work already in front of you.
Open the saved search, list, or audience your team already uses. Use score, reason, and signal to decide who gets the next action today.
Choose the next action
Use the reason and signal age to decide whether the record needs a call, email, sequence add, follow-up, nurture path, or hold.
Keep weak records out of the day
Park records when the reason is unclear, stale, or not actionable. Keep the day focused on records with fit, timing, and a usable angle.
Find audiences
Build audiences from fit plus reason, not score alone.
A high score should tell the team why the account matters. Use the reason cluster to pick the audience, message, and sequence path.
Score and prioritize
Separate ICP fit from buying timing.
Daily work should come from the overlap: strong fit and strong current signal. Everything else should be routed deliberately instead of sitting in one flat list.
A-tier: work today
High fit and strong signal. Create a same-day call, email, or LinkedIn task with the reason surfaced.
B-tier: work this week
High fit with softer signal, or strong signal with one missing fit proof. Schedule follow-up and watch for movement.
C-tier: nurture
Good market match but no near-term trigger. Add to a light nurture audience and revisit on new signal.
D-tier: park
Weak fit or bad timing. Suppress from active work unless a meaningful new signal appears.
Score output
The useful output is not only a number.
- 1Score: total score plus fit and signal drivers.
- 2Reason: why this account or person fits the ICP.
- 3Timing: why this should be worked now.
- 4Action: task, audience, or nurture recommendation.
Work the tasks
Turn scores into the next best action.
The score should route the day. Each tier gets a clear task policy so high-value work does not compete with generic list activity.
Daily work queue
Call or email today. Lead with the highest-confidence signal and ask AI Assistant for the outreach angle.
Weekly follow-up
Schedule work this week. Ask AI Assistant what signal would move the account into the daily queue.
Nurture audience
Add to a relevant audience by reason cluster: new leader, funding, hiring, competitor, dormant, or expansion.
Park or suppress
Keep out of active task views until a material signal changes the timing or the fit profile improves.
Scoring run checklist
Keep a six-step checklist open while you work.
Pick one live list, task queue, or audience. The checklist stays pinned while you move through Apollo, and progress is saved in this browser only.
Choose a run
Start with the Apollo work in front of you.
Use the checklist when you are ready to prioritize one real list, clean one task queue, or route one scored audience. It will not update Apollo or change records.
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steps completed
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Prompt library
Copy-ready prompts for the full scoring loop.
Use the filters to move from setup to daily execution. Every prompt asks AI Assistant to return a clear next action, not just research.
Improve the model
Treat scoring as a weekly operating system.
Scores should move as markets move. Review tier movement, data quality, signal age, team feedback, and audience performance before changing the primary score.
Measure by tier
Compare replies, meetings, opportunities, pipeline, and wins by A, B, C, and D tiers.
Watch signal to touch
Track how quickly A-tier records receive a real first action after the score or signal changes.
Review false positives
Ask the team which high-scoring records should not have been prioritized and feed that back into criteria.
Find missing data
Flag records that cannot be scored well because email, phone, title, account fit, or signal coverage is incomplete.
Caveat for teams: AI Assistant works within available Apollo filters, signals, data, permissions, and plan access. If a signal is not available, log the gap instead of scoring from guesswork.
Resources
Source links and reference material.
These source links support search, score filters, and AI Assistant prospecting. Score owner setup sources live in the bottom admin materials control.
Configuration references
Use these when you manage scoring configuration.
Most day-to-day work happens in the playbook above. If you help maintain scoring setup, these references support custom score configuration and primary score review.
Score setup references Open references
Create or refine the custom score
Use the official score setup source to confirm score type, criteria, and configuration behavior before changing what users see in Apollo.
Check the active scoring model
Confirm which people score and company score should guide search, sorting, list triage, and task prioritization.