How to build a customer health scoring model in CRM: identifying which signals predict churn, assigning weights (product usage 35%, support 20%, relationship 20%, NPS 15%, commercial 10%), automating data collection from product analytics and support tools, CSM workflows triggered by score changes, and calibrating the model with churn retrospective analysis.
How CSMs use CRM: onboarding milestone tracking with automated task creation, building a composite customer health score model, managing renewals as a pipeline with automated 90-day triggers, CS platform options (Gainsight, ChurnZero, HubSpot Service Hub), and fixing reactive churn management and late renewal conversations.
How VPs of Sales use CRM: forecast review process and setup, pipeline coverage analysis (ratio, by segment, weekly monitoring), win/loss analysis at portfolio level, using CRM data for headcount capacity planning, and fixes for systematic forecast overestimation and full-looking pipelines that miss numbers.
How Account Executives should use CRM across the full deal cycle: stage-by-stage workflow and required fields, documenting discovery in structured fields (not free text), multi-stakeholder tracking with buying roles, pipeline review preparation, forecast accuracy discipline, and fixing sporadic CRM updates and poor discovery documentation.
CRM tools and workflows specifically for SDRs and BDRs: sequence management in HubSpot Sequences vs Outreach/Salesloft, lead importing with ICP tagging and email verification, qualification fields for the SQL handoff, SDR activity and outcome metrics, and fixes for poor handoff quality and low sequence reply rates.
The five reports sales managers actually need in CRM: forecast dashboard (daily), at-risk deals view (daily), rep performance dashboard (weekly), pipeline funnel by stage (weekly), and loss reason analysis (monthly) — with specific build instructions for HubSpot and Salesforce, and fixes for pipeline quality and report overload.
How sales managers use CRM data for coaching: building rep performance dashboards (activity, pipeline, outcomes), diagnosing the right coaching focus per rep (activity vs outcome mismatch, stage-specific stall, loss reason patterns), structuring data-driven 1:1s, using call recording for specific coaching, and fixing coaching that doesn't produce change.
How to connect sales enablement content to CRM workflows: content needs at each deal stage, CRM-native tools (HubSpot Documents, Sequences, Snippets; Salesforce Files), dedicated enablement platforms (Highspot, Seismic, Guru) with CRM integration, content architecture with deal-context tagging, and fixing the 'content exists but nobody uses it' problem.
How CRM conversation intelligence works: what CI platforms capture (transcript, talk ratio, topics, sentiment, next steps), Gong vs Chorus vs Fireflies.ai compared, what to sync to CRM vs keep in CI platform, using CI for deal review and portfolio coaching, and fixing rep discomfort with recording and verbose summaries.
How CRM sentiment analysis works: where it applies (support tickets, email, call transcripts, NPS), rule-based vs ML-based approaches, native features in Salesforce Einstein, Zoho Zia, and Gong, incorporating sentiment into customer health scores, deal risk detection in sales, and fixing false positive alert fatigue.