Start with the list in front of you
Open a saved audience or search result, use the score and reason columns, then decide what deserves the next real action.
Define the score
Make the ICP explicit before reps start sorting.
AI-assisted scoring is most valuable when the team agrees on the inputs. Start with plain-language ICP, exclusions, personas, and current buying signals.
Work the reason, not only the number
Use the score as the priority layer. Use the reason and signal to choose call, email, sequence add, follow-up, or hold.
Keep the queue clean
Review which records reps worked, which records were parked, and which reasons need better signal or fit coverage.
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 rep 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 rep's 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 rep task lists until a material signal changes the timing or the fit profile improves.
Guided tracker
Keep the scoring run open while you work.
Start the tracker when you are ready to test one real audience. It stays pinned while you move through this guide and Apollo, so you do not have to scroll back to update progress.
Work-along mode
Run one audience through the score, task, and outreach decision.
Use this after you know the score definition and the search path. The tracker saves progress in this browser only. It does not update Apollo, change records, create tasks, or enroll anyone in a sequence.
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steps completed
Best use: keep the tracker open, work one audience in Apollo, and decide which records deserve same-day action.
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, rep 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 reps 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 rep task prioritization.