Guide referral partners from signup to their first sale
A rental business used an AI-built partner platform to coordinate onboarding, training, referral codes, and activation tasks, while staff focused on partners who needed help or showed progress.
How this works
A rental business used an AI-built partner platform to coordinate onboarding, training, referral codes, and activation tasks, while staff focused on partners who needed help or showed progress.
Coordinate partner activation through observable milestones, from registration to verified referral activity. Separate training completion, sales attribution and reward approval so an enthusiastic interaction or referral code alone does not establish an earned bonus.
Before you start
Defined operating scope
Referral partners require training, codes, activation tasks, and reviewed evidence before rewards.
Required source material
Obtain Partner registration; Training content and tasks; Referral codes and sales records. If connectors are unavailable, use authorized files with the same fields.
Decision and exception rules
A sale uses a code assigned to multiple partners. Hold attribution and resolve code ownership history.
Prepare the inputs
- partner_registration
- Required
Partner ID and approved terms
Verify eligibility and contact preferences.
- training_path
- Required
Materials, tasks and assessment rules
Define objective completion evidence.
- referral_mapping
- Required
Unique codes and assignment history
Prevent duplicate or reassigned-code ambiguity.
- sales_records
- Required
Transactions, status and reward policy
Use confirmed eligible sales and refund handling.
Implementation, step by step
Establish the working record
- Confirm the selected records, effective versions and responsible owner.
- Check partner_registration, training_path, referral_mapping, sales_records before beginning. Record the source version and the selected scope; an unavailable value stays unknown rather than becoming an inferred fact.
Checkpoint: The input record identifies the selected partner_registration and any missing required fields.
Register partners and guide them through training and a short assessment
- Register the partner and present the relevant training sequence, retaining completion and assessment evidence.
- Reconcile referral codes, eligible transactions and reward calculations independently.
Checkpoint: A saved intermediate result for: Register partners and guide them through training and a short assessment.
Issue referral codes and show concrete activation tasks
- Issue or record an authorized referral code and show concrete activation tasks with clear completion conditions.
- Check that each activation milestone has the required evidence rather than a chatbot interaction count.
Checkpoint: A saved intermediate result for: Issue referral codes and show concrete activation tasks.
Collect completion evidence and sales activity in the CRM
- Connect submitted evidence and referral activity to the correct partner in the CRM, distinguishing pending from verified events.
- Reconcile referral codes, eligible transactions and reward calculations independently.
Checkpoint: A saved intermediate result for: Collect completion evidence and sales activity in the CRM.
Have staff review evidence, support activation, and approve earned bonuses
- Give staff a review queue for activation support and reward eligibility; payout remains a separate authorized action.
- Check that each activation milestone has the required evidence rather than a chatbot interaction count.
Checkpoint: A saved intermediate result for: Have staff review evidence, support activation, and approve earned bonuses.
Package the result and unresolved work
- Validate attribution and reward eligibility before paying. AI helped build the platform; the source does not establish AI-driven partner scoring or autonomous bonus approval.
- Do not infer partner potential or approve bonuses autonomously.
Checkpoint: A partner activation pipeline with attributable sales and progress records. Unresolved items remain visible in the review record.
Decisions along the way
A sale uses a code assigned to multiple partners.
Hold attribution and resolve code ownership history.
A referred sale is refunded or not yet eligible.
Keep reward pending or apply the approved reversal rule.
Training completion has no evidence.
Request the missing assessment or task result rather than awarding completion automatically.
What you will produce
activate-community-referral-partners-result.json
JSONA partner activation pipeline with attributable sales and progress records. Label proposed and completed states separately.
Include: partner_id · training_status · activation_tasks · referral_code · attributed_sales · reward_status · staff_action · status · evidence_reference · review_note
activate-community-referral-partners-review.md
MarkdownKeep the evidence and unresolved decisions needed to apply this result, including exceptions involving sales_records.
Include: source_reference · question · owner · next_action
Check the result
- Reconcile referral codes, eligible transactions and reward calculations independently.
- Check that each activation milestone has the required evidence rather than a chatbot interaction count.
- Inspect partner_registration and training_path in both the original and output; confirm that record identity and interpretation survived the transformation.
- Validate attribution and reward eligibility before paying. AI helped build the platform; the source does not establish AI-driven partner scoring or autonomous bonus approval.
When something goes wrong
A sale uses a code assigned to multiple partners.
Hold attribution and resolve code ownership history. Retain the affected evidence and recovery status.
A referred sale is refunded or not yet eligible.
Keep reward pending or apply the approved reversal rule. Retain the affected evidence and recovery status.
Training completion has no evidence.
Request the missing assessment or task result rather than awarding completion automatically. Retain the affected evidence and recovery status.
A worked example
SYNTHETIC EXAMPLE · NOT A REPORTED BUSINESS RESULT
Request
Guide referral partners from signup to their first sale for the following bounded example; prepare the result for review.
Inputs
Synthetic example: Partner P-7 completes training and refers sale S-9 using code R-7. The sale is paid but remains within the policy’s refund window.
Expected result
Synthetic expected result: Record training complete and referral attributed, with reward pending eligibility. Do not mark the bonus payable until the stated conditions are met.
Run a small pilot
Start small
Trial a representative batch containing the ordinary case and the exception demonstrated above.
Record the baseline
Record current preparation time, review effort and correction types for the same records.
Agree success criteria
Agree acceptable review and error limits; measure time to first verified activation; training completion and incorrect bonus approvals.
Stop or revise
Training completion has no evidence. Pause affected records and apply this recovery: Request the missing assessment or task result rather than awarding completion automatically.
Keep the scope clear
- Do not infer partner potential or approve bonuses autonomously.
- Changes to rewards, payouts or partner terms require the responsible owner’s authorization.
Check before using
Validate attribution and reward eligibility before paying. AI helped build the platform; the source does not establish AI-driven partner scoring or autonomous bonus approval.
Business activities
- Run sales conversations and proposals
- Onboard customers, partners, and members
FROM A RECIPE TO YOUR WORKFLOW
Bring the company context together.
This workflow needs reliable inputs before it needs a better prompt. Moat8 Vault brings working information into a readable archive for the AI tools you use.
For this recipe: Partner registration · Training content and tasks · Referral codes and sales records
Start with one recurring task, agree which sources to use, and review the first result with your team.
Discuss this workflow