Perser provides a platform that analyzes partner interactions across calendars, calls, and CRMs to offer predictive insights into revenue outcomes. It scores partner fit and engagement based on behavioral data, enabling organizations to optimize partnership activation and scale their go-to-market strategies.
Funding
Funding not disclosed
Founders
Product
Problem
Partner-led go-to-market strategies often suffer from a lack of visibility into partner engagement and potential, leading to stalled growth and inefficient resource allocation. Teams struggle to identify which partners are actively contributing to revenue and which require intervention, resulting in missed opportunities and wasted effort.
Solution
Perser is a platform that automatically ingests and interprets signals from partner interactions across calendars, calls, and CRMs to provide predictive insights into revenue outcomes. By analyzing real behavioral data, Perser scores partner fit and engagement, offering actionable recommendations to optimize partnership activation. This enables organizations to scale their go-to-market efforts by systematically identifying, nurturing, and activating high-potential partners. The system provides a clear view of partner activity, allowing teams to focus on those driving tangible results and proactively address underperforming relationships.
Target Audience
Perser targets revenue and partner operations teams within organizations that rely on partner ecosystems for go-to-market strategies, particularly those looking to scale their partner programs efficiently.
Features
- Automated ingestion of partner interaction data from calendars, call logs, and CRM systems, eliminating manual data entry.
- Signal interpretation engine that classifies and analyzes nuances in partner communications, including shared timelines, co-marketing interest, and sales confidence.
- Predictive partner modeling that scores Fit and Engagement based on observed behavior rather than subjective assessment.
- Activation layer that generates context-aware recommendations for partner follow-up, escalation, enablement, or pausing activities.
- Real-time detection of partner intent, confidence, and objections derived from meeting behavior, call transcripts, and agenda data.
- Portfolio scoring and prioritization tools to identify growth-ready partners, stalling relationships, and those needing support.
- Automated trigger mechanisms for recommended actions, such as follow-ups or re-engagement campaigns, based on recent signals.
- Scalable tracking and qualification capabilities for a large volume of low-touch partners without manual oversight.