Die Herausforderung
Manuelle Interessenten-Recherche bremst die Pipeline
The 12-person sales team was spending over 3 hours per day on manual prospect research. Each rep had to scour LinkedIn, Crunchbase, news sites, and CRM records to build a basic prospect profile before any outreach could happen. The result: slow pipeline velocity, frustrated reps, and missed quotas.
With a growing target list and flat headcount, the team needed a way to scale research without scaling costs. The sales director had tried ChatGPT for ad-hoc research, but results were inconsistent and nothing connected back to their CRM.
Die Lösung
Wie JieGou die Recherche automatisierte
The team installed the Sales Starter Pack on day one. The Prospect Research Brief recipe immediately became the most-used workflow — reps paste a company name and get a structured brief with firmographics, recent funding, tech stack, and personalized talking points in under 2 minutes.
By week one, the team added the Follow-Up Sequence workflow to automatically draft multi-touch email sequences based on the research brief. Connecting Salesforce via the onboarding integration step meant prospect data flowed directly into existing deal records.
Die Ergebnisse
Messbare Ergebnisse
Research time per prospect
Weekly team hours saved
Pipeline velocity increase
Payback period
Einführungszeitplan
Von der Installation zur vollständigen Einführung
Tag 1
Installed Sales Starter Pack. Ran Prospect Research Brief on 5 real prospects during lunch. Entire team saw the output quality.
Woche 1
All 12 reps using the tool daily. Added Follow-Up Sequence workflow. Connected Salesforce for CRM sync.
Monat 1
Research-to-outreach cycle dropped from 2 days to 30 minutes. Pipeline coverage increased 3x. Exploring Marketing Pack for content collaboration.
"We went from dreading prospect research to looking forward to new leads. What used to take 45 minutes now takes less time than making coffee."
This case study represents a typical adoption scenario based on the types of teams JieGou is designed for. Results may vary based on team size, workflow complexity, and usage patterns.