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Agentforce Sales Consultant

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Agentforce Sales Consultant Study Checklist

  • Platform Administrator
  • Platform App Builder
  • Platform Foundations
  • Platform Developer
  • Platform Administrator II
  • Agentforce Sales Consultant
  • Agentforce Service Consultant
  • Platform Data Architect
  • Platform Development Lifecycle and Deployment Architect
  • Platform Identity and Access Management Architect
  • Platform Integration Architect
  • Platform Sharing and Visibility Architect
  • Heroku Architect
  • B2C Solution Architect
  • Experience Cloud Consultant
  • Agentforce Field Service and Operations Consultant
  • Agentforce Nonprofit Consultant
  • Data 360 Consultant
  • Omnistudio Consultant
  • CRM Analytics and Einstein Discovery Consultant
  • Platform User Experience Designer
  • Platform Strategy Designer
  • B2C Commerce Developer
  • JavaScript Developer
  • Omnistudio Developer
  • Platform Developer II
  • Marketing Cloud Engagement Administrator
  • Marketing Cloud Engagement Specialist
  • Marketing Cloud Engagement Consultant
  • Agentforce Sales Foundations
  • Business Analyst
  • Marketing Cloud Engagement Developer
  • Marketing Cloud Engagement Foundations
  • Agentforce Specialist
  • Agentforce Life Sciences Consultant
  • B2B Commerce Administrator AP
  • B2B Commerce Developer AP
  • Agentforce Consumer Goods AP
  • Agentforce Financial Services AP
  • Agentforce Health AP
  • Agentforce Manufacturing AP
  • MuleSoft Integration Foundations
  • MuleSoft Developer
  • MuleSoft Developer II
  • MuleSoft Platform Integration Architect
  • MuleSoft Platform Architect
  • Tableau Desktop Foundations
  • Tableau Data Analyst
  • Tableau Consultant
  • Tableau Server Administrator
  • Tableau Architect
  • Slack Administrator

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0/195Learned

Given business requirements, metrics, key performance indicators, or business challenges, determine the optimal solution in Agentforce Sales

0/6

Goal-first SMART success metrics for an Agentforce Sales rollout

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Activity measures versus outcome measures in sales KPIs

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One key sales metric, pipeline viability and monthly measurement

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Matching business needs to core Agentforce Sales capabilities

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Reducing rep data entry and manual activity logging

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Supporting sales teams that work from anywhere

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Given a scenario, discuss common sales and marketing processes and anticipate key implementation considerations

0/11

  • Sales process versus sales methodology
  • Common sales cycle stages from research to relationship building
  • B2B versus B2C selling models and Person Accounts considerations
  • Lead capture channels and auto-response planning
  • Lead qualification criteria and lead picklist design
  • Marketing-to-sales lead handoff and marketing automation alignment
  • Lead sharing model choices for controlling lead visibility
  • Opportunity stage design with exit criteria and Path guidance
  • Campaign attribution and ROI tied to opportunities
  • Aligning sales, marketing and finance stakeholders on process changes
  • Rollout success team roles and early end-user involvement

Identify when to use Agentforce Sales features and related products such as Sales Engagement, Salesforce Inbox, Enterprise Territory Management, Opportunity Forecasting, Agentforce Sales Einstein, and generative/predictive AI

0/10

  • Salesforce Inbox versus Einstein Activity Capture versus base email integration
  • When to recommend Sales Engagement for high-volume outreach
  • Sales Engagement standard cadences, quick cadences and automated actions
  • Sales Territories versus role hierarchy and account teams for territory-aligned access
  • Territory planning, models and account assignment rules
  • Salesforce Forecasting versus pipeline reports for revenue projection
  • Choosing Salesforce Forecasting forecast types for how the business sells
  • Matching a sales need to predictive, generative or agentic AI
  • Choosing among Agentforce Sales agents for prospecting, deal management and coaching
  • Agentforce Engagement agent versus rep-worked Sales Engagement cadences

Identify ways to transform business outcomes and sales KPIs into reports and dashboards

0/13

  • Mapping business questions to trackable sales metrics
  • Designing data capture so sales KPIs are reportable
  • Reports versus dashboards for sales KPI visibility
  • Core dashboards sales leaders rely on
  • Report types and cross filters for relationship-based KPIs
  • Report formats and summary formulas for calculated sales KPIs
  • Dynamic dashboards and running user for role-based KPI views
  • Embedding report charts and dashboards where reps work
  • Reporting pipeline change over time
  • Forecast and quota attainment reporting
  • Activity KPI reporting with Einstein Activity Capture
  • AppExchange dashboard packs to accelerate KPI reporting
  • Reviewing and iterating KPI dashboards with the business
  • Assessing the current sales process and user experience before build
  • Executive sponsorship and stakeholder alignment before build
  • Defining success metrics from key business questions
  • Systems change management planning and governance
  • Anticipating user resistance and designing for acceptance
  • Super users and change champions in adoption planning
  • Communication plan timing and launch message content
  • Training strategy goals and user expectations
  • Training methods and role-based content for a sales rollout
  • Placing readiness activities in the implementation lifecycle
  • Building in a sandbox versus changing production directly
  • User acceptance testing and sandbox choice before go-live
  • Change sets versus other tools for moving configuration between orgs
  • Application lifecycle management and production change governance
  • Deployment timing and release scheduling
  • Pilot groups versus a single big-bang launch
  • Placing deployment activities in the implementation lifecycle
  • Adoption usage metrics after go-live
  • Data quality patterns as signals of adoption problems
  • Post-launch feedback collection and user satisfaction
  • Matching the remedy to the root cause of low adoption
  • Recognition and peer success stories to sustain adoption
  • Validating business outcomes against pre-launch benchmarks
  • Managing user access changes after go-live
  • Handling changing requirements and enhancement requests after go-live
  • Long-term systems roadmap for continuous improvement
  • Evaluating Salesforce seasonal releases for new value
  • Placing post-go-live activities in the implementation lifecycle
  • Project lifecycle phases and where artifacts and activities belong
  • Waterfall versus Agile for an Agentforce Sales implementation
  • Salesforce Adaptive Methodology stages, roles and kickoff
  • Statement of work content and accurate project scoping
  • Project management plan purpose, contents and template sizing
  • Defining in-scope and out-of-scope requirements to prevent scope creep
  • Scope changes, phased delivery and schedule-budget trade-offs
  • Identifying and responding to project risks
  • Monitoring project progress, governance and issue escalation
  • Implementation schedule and go-live milestones
  • Researching a customer's business before discovery
  • Stakeholder analysis and discovery workshop participants
  • Choosing elicitation techniques for sales requirements
  • Uncovering the business need behind a requested feature
  • Process maps, journey maps, and system overview diagrams in discovery
  • Reviewing an existing Salesforce org's usage and constraints in discovery
  • Current-state versus future-state gap analysis
  • User stories and acceptance criteria for sales requirements
  • Fit-gap analysis when translating requirements into an Agentforce Sales design
  • Co-creating a solution vision through storyboarding
  • Prioritizing use cases by business value and effort
  • Business analysis activities across the implementation lifecycle
  • End-to-end lead-to-close process design from a process map
  • Lead conversion design and custom field mapping
  • Translating a sales methodology into opportunity stages
  • Placing sales activities in the lead-to-close stages
  • Path guidance and key fields for stage-by-stage coaching
  • Enforcing required information at opportunity stage transitions
  • Opportunity contact roles for the buying committee
  • Discount approval routing before quote delivery
  • Kanban and Pipeline Inspection for opportunity pipeline reviews
  • Standard features, then configuration, then customization for sales requirements
  • Requirements that justify custom development over declarative tools
  • AppExchange solutions versus custom-built functionality
  • Another Salesforce product versus custom build or third-party app
  • Experience Cloud partner sites for channel selling and deal registration
  • Email and calendar integration options for Outlook and Gmail users
  • Inside-sales productivity tools for cadences, calling and in-browser prospecting
  • Slack integration for deal collaboration and sales team communication
  • Salesforce mobile app for field reps versus custom mobile development
  • Org-wide defaults as the baseline for sales record access
  • Role hierarchy for sales management visibility
  • Owner-based versus criteria-based sharing rules
  • Account Teams versus Opportunity Teams for collaborative selling
  • Account and opportunity team access considerations
  • Matching a sales record-access requirement to the right sharing feature
  • Permission sets versus profiles for sales object and field access
  • Permission set groups and muting for sales job personas
  • Permissions that override sharing for delegated sales operations
  • Products, the standard price book and price book entries
  • Custom price books for segment-specific pricing and access
  • Opportunity products, sales price and opportunity amount
  • Product schedules for revenue and quantity over time
  • Multiple quotes per opportunity and quote syncing
  • Quote templates and customer-facing quote PDFs
  • Retiring products and price books: deactivate, archive or delete
  • Corporate, personal and record currency with conversion rates
  • Multi-currency enablement implications for an existing org
  • Advanced currency management and dated exchange rates
  • Currency-specific price book entries on multi-currency opportunities
  • Campaign hierarchy and campaign types for performance roll-up
  • Campaign member statuses for tracking responses
  • Campaign Influence versus primary campaign source attribution
  • When to use leads versus direct contacts and opportunities
  • Lead capture with Web-to-Lead and lead imports
  • Lead routing with assignment rules and queues
  • Lead Status values and lead processes
  • Enforcing qualification criteria before lead conversion
  • Multiple sales processes with opportunity record types
  • Opportunity splits for shared revenue credit
  • Scoping which legacy sales data to migrate
  • Cleansing and mapping legacy data before migration
  • Choosing a data import tool for a sales data migration
  • Migration load sequence and preserving record relationships
  • Handling automation and validation rules during bulk data loads
  • Test loads, backups and cutover for a data migration
  • System of record and master data across integrated systems
  • Real-time versus batch integration with back-office systems
  • Data quality across integration extraction, transformation and consumption
  • Workload and design factors that affect org scalability
  • Report and list view performance on large data volumes
  • Data tiering with archiving and external objects
  • Account data skew from overloaded parent records
  • Lookup skew and lock contention on heavily referenced records
  • Ownership skew from a single generic record owner
  • Role hierarchy design for scalable record access
  • Sharing recalculation impact of ownership and hierarchy changes
  • Large data load planning to avoid lock contention and slow sharing
  • Automation complexity and batch timing at scale
  • Business impact of poor sales data quality
  • Assessing sales data quality across its core dimensions
  • Data management plan standards and data ownership
  • Validation rules versus required fields for enforcing sales data standards
  • Streamlining sales data entry to improve completeness and consistency
  • Matching rules and fuzzy matching for duplicate detection
  • Duplicate rule actions when reps create sales records
  • Resolving existing duplicates across the org
  • Data enrichment from trusted third-party sources
  • Ongoing data quality monitoring and stewardship after go-live
  • Assistive Agentforce actions versus autonomous sales agents
  • Record summaries and daily briefings for seller preparation
  • Sales Emails versus Agentforce for drafting customer emails
  • Agentforce actions for closing and prioritizing deals
  • Buying committee and relationship insight actions
  • Get Forecast Guidance for sales manager pipeline reviews
  • Agentforce Sales Management for pipeline and account work
  • Generative features within Einstein Conversation Insights
  • Agentforce Engagement for lead generation and nurturing
  • Agentforce Sales Coach for rep role-play and feedback
  • Standard sales prompt templates versus custom Prompt Builder templates
  • Prerequisite Sales features behind standard Agentforce sales actions
  • Einstein Lead Scoring for lead prioritization
  • Einstein Opportunity Scoring for deal prioritization
  • Einstein Activity Capture and its AI insights
  • Einstein Deal Insights and AI in Pipeline Inspection
  • Einstein Forecasting predictions for forecast accuracy
  • Einstein Conversation Insights for call analysis
  • Data readiness for Einstein predictive features
  • Ethical risk categories of generative AI in sales
  • Applying Salesforce Trusted AI Principles to sales AI use cases
  • Salesforce guidelines for responsible generative AI
  • Safeguards against inaccurate AI-generated sales content
  • Einstein Trust Layer protections for sales data
  • Human oversight and judgment with AI sales agents
  • Honesty and transparency in AI-driven sales outreach
  • Bias and fairness in predictive lead and opportunity scoring
  • Explainability of Einstein predictions for sales users

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