Customer Success Manager - Core (sales & Service) Clouds

Salesforce Salesforce · Enterprise · Toronto, Canada, Canada

Salesforce is seeking a Customer Success Manager to help high-value customers achieve ROI with their AI CRM platform. The role involves acting as a trusted advisor, managing customer relationships, driving adoption of features, and addressing technical and business concerns. A key aspect is leveraging AI tools for tasks like meeting summaries, data collection, and sentiment analysis, and staying updated on AI capabilities.

What you'd actually do

  1. Serve as the single point of customer accountability responsible for the delivery of all Signature deliverables, the overall customer experience, and renewal and expansion.
  2. Coordinate all deliverables the customer is entitled to, overseeing the experience throughout the Signature lifecycle
  3. Apply the correct processes to address customer needs and ensure value is delivered through the Signature offer.
  4. Successfully align with and manage both Business and Technical Stakeholders, focusing on aligning Business Value and Technical Goals to the Signature offer.
  5. Prioritize the most urgent work activities, organize tasks to avoid missing key steps, and create basic plans to focus time, taking responsibility for assigned tasks.

Skills

Required

  • Experienced business professional, preferably with 3+ years of relevant industry expertise in Customer Success, SaaS platform use, or related fields.
  • Strong consulting skills and demonstrated ability to drive business value, facilitate discussions, handle objections, and influence C-level co

Nice to have

  • AI Literacy: Proficiency in using AI agents to automate routine tasks such as meeting summaries, QBR data collection, and initial health monitoring.
  • Prompt Engineering Basics: Ability to use natural-language commands to guide AI agents in retrieving accurate customer data and generating first drafts of success plans.
  • AI Engagement Monitoring: Using AI-driven sentiment and intent analysis to flag early customer concerns for human intervention.
  • Collaborative Learning: Actively seeking out "Agentblazer" training and certifications to stay current on autonomous agent capabilities.
  • Learning & Development: Apply product knowledge and expertise to address technical concerns, use this knowledge to ask effective diagnosis questions, and align platform features with customer priorities and roadmaps.

What the JD emphasized

  • AI Literacy
  • Prompt Engineering Basics
  • AI Engagement Monitoring
  • Agentblazer training