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Linkorite by GTMStack
Partner Management

Partner Activity Scoring

Continuously score link exchange partner engagement and activity levels to identify at-risk relationships and top-performing SEO collaborators

Trigger

Real-time scoring updated with each partner interaction, with daily recalculation of aggregate scores

Outcome

Up-to-date partner activity scores that drive prioritization in outreach, renewal, and relationship management workflows

Steps

1

Track Interaction Events

Log every partner interaction including messages, exchange completions, link verifications, and response times

Feature: Partner Database
2

Calculate Activity Score

Compute a weighted activity score based on recency and frequency of interactions, exchange completion rate, and link health

Feature: Domain Metrics Engine
3

Classify Partner Status

Categorize partners as highly active, engaged, cooling, or at-risk based on their activity score trends

Feature: AI Agent
4

Trigger Engagement Actions

Automatically initiate re-engagement workflows for partners whose scores drop below configurable thresholds

Feature: Exchange Tracker

Features Used

Partner Database Domain Metrics Engine AI Agent Exchange Tracker

Partner activity scoring provides a real-time pulse on the health of every link building relationship in your network. Rather than relying on periodic manual reviews, this automation continuously evaluates partner engagement and flags relationships that need attention.

The scoring system tracks every interaction event, from Slack messages and email responses to exchange completions and link health checks. Each event contributes to a composite activity score that reflects both the quantity and quality of recent engagement.

Score weighting is designed to reward consistent engagement over sporadic activity. A partner who completes one exchange per month reliably scores higher than a partner who completes three exchanges in a burst followed by months of silence. Recency weighting ensures that recent activity carries more influence than historical patterns.

The classification system groups partners into actionable categories. Highly active partners are prioritized for new exchange opportunities. Engaged partners receive standard workflow treatment. Cooling partners trigger soft re-engagement outreach. At-risk partners receive more assertive outreach and are flagged for team review.

The automatic re-engagement trigger is the most valuable component. When a previously active partner’s score drops below the threshold, the system initiates outreach before the relationship goes cold. This proactive approach to relationship maintenance consistently recovers partnerships that would otherwise be lost to natural attrition.

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