How to effectively learn AI Prompting, with the 'AI for Global Heads of Sales (Prompt Course)'?

Start here: Build an AI playbook for global sales growth

This course gives Global Heads of Sales a practical, repeatable way to apply AI and ChatGPT across the full revenue engine. It converts leadership goals-growth, predictability, margin, and customer loyalty-into clear prompt workflows that your teams can run every week. You will learn where AI adds the most value, how to set standards that scale across regions, and how to turn outputs into decisions you can defend in the boardroom.

What you'll learn

• Sales Performance Analysis: Turn raw activity and results data into insights about productivity, conversion, cycle time, and quota coverage. Identify what is working, what is waste, and what to fix now versus later.
• Market Segmentation: Build actionable segments by industry, firmographics, buying center, behavior, and region. Prioritize high-yield clusters and connect them to pipeline plans.
• Sales Forecasting: Improve forecast quality with scenario comparisons, risk flags, and sensitivity reviews. Convert qualitative manager feedback into structured signals AI can use.
• Customer Relationship Management (CRM): Clean, enrich, and structure CRM data. Standardize notes, highlight next-best actions, and reduce rep admin time while improving data completeness.
• Competitor Analysis: Systematically scan public information, customer feedback, and win/loss notes to spot moves, pricing shifts, and product gaps.
• Pricing Strategy Development: Explore price bands, discount guardrails, and value messaging by segment. Link price guidance to win probability and margin goals.
• Sales Channel Optimization: Allocate effort across direct, partners, marketplaces, and digital. Compare cost-to-serve, reach, and ramp speed by country or segment.
• Sales Training and Development: Turn top-performer behaviors into repeatable coaching scripts, role-plays, and skill checklists. Keep enablement tied to pipeline bottlenecks.
• Lead Generation Strategies: Prioritize sources and messages that convert. Create repeatable prospecting routines aligned with ICP and segment pain points.
• Product Performance Analysis: See which products win in which segments and why. Identify attach opportunities and sunset candidates.
• Digital Sales Strategy: Coordinate web, content, product-led motions, and outreach. Map digital signals to sales actions and measure lift.
• Cross-Selling and Up-Selling Techniques: Use usage, success metrics, and lifecycle triggers to propose relevant expansions.
• Sales Incentive Plans: Test compensation scenarios for fairness, focus, and profitability. Stress-test for gaming risks.
• Customer Feedback Analysis: Convert voice-of-customer into prioritized actions for product, pricing, service, and sales messaging.
• International Market Entry: Assess entry candidates, routes to market, localization needs, and regulatory considerations with structured comparisons.

How the modules connect into one system

These modules are built to work together so your teams aren't running disconnected experiments. You get a coherent operating rhythm that links inputs, decisions, and outcomes:

• Segmentation → Lead Gen → Channel → Forecast: Use the same segment definitions across prospecting, coverage models, and projections, reducing conflict between marketing and sales.
• Performance Analysis → Training → Incentives: Target enablement and compensation where the data shows the biggest gaps, then re-measure impact.
• CRM → Cross/Up-sell → Retention: Standardize notes and signals so expansion plays trigger at the right time, with measurable lift in NRR.
• Competitors → Pricing → Product: Move from ad-hoc reactions to clear price and packaging updates backed by evidence.
• Product Performance → Digital → Channel: Match product-market fit to the most effective route to buyers in each region.
• Market Entry → Forecast → Incentives: Set realistic plans and pay structures for new countries, then adjust as early signals come in.

Using the prompts effectively

Prompts in this course follow a consistent structure so you can trust the outputs and scale them across regions and teams. Here's how to get the most from them:

• Start with a clear objective: State the decision you need, the time frame, and the metric you care about. This keeps outputs crisp and comparable.
• Provide context and guardrails: Include segment definitions, sales stages, product names, currencies, and time zones. Set constraints (e.g., margin floors, legal limits) to avoid rework.
• Structure inputs and outputs: Use consistent column names, tags, and formats. Ask for outputs that fit directly into your CRM or planning sheets.
• Regional nuance and language: Call out local buying norms, holiday calendars, and compliance. The prompts support multilingual use; specify language where required.
• Transparency and review: Request assumptions, key drivers, and sources so managers can audit and challenge conclusions.
• Validation loops: Compare AI summaries with a sample of raw records. If mismatches appear, refine the instructions and rerun.
• Bias and fairness checks: Test prompts for unintended bias by segment, region, or rep. Document adjustments.
• Data privacy: Use approved datasets and remove sensitive fields. The course includes guidance on anonymization and redaction.
• Operational integration: Align outputs to task queues, dashboards, and QBR templates so insights lead to actions without manual rewriting.
• Version control: Store prompt variants, date them, and keep a short rationale so teams can revert if performance drifts.
• Team collaboration: Encourage managers and reps to submit feedback on clarity, accuracy, and usefulness. Incorporate the best improvements centrally.

Outcomes and value for a Global Head of Sales

• Higher forecast reliability: Better risk visibility and mid-quarter course corrections.
• More productive pipeline: Cleaner ICP targeting, improved conversion, and shorter cycle times.
• Improved margin discipline: Clear discount guardrails and value-based pricing guidance.
• Stronger retention and expansion: Timely cross-sell and up-sell prompts based on real usage and feedback.
• Faster strategic moves: Quicker responses to competitor changes and new market opportunities.
• Consistent execution across regions: Shared definitions, shared dashboards, and shared playbooks.
• Lower overhead: Less manual analysis and admin; more time on coaching and deals.

Who should take this course

This course is built for senior sales leaders, sales operations leaders, enablement leaders, and regional heads who need a common AI approach across multiple countries or business units. It suits both B2B and B2C models, direct and indirect channels, and organizations at different stages of AI adoption.

How the course is structured

You'll progress through focused modules that map to core sales decisions-performance, segmentation, forecasting, CRM, competition, pricing, channel strategy, training, lead generation, product fit, digital strategy, cross/upsell, incentives, feedback analysis, and international expansion. Each module explains the goal, the data you'll need, how to run and reuse the workflows, how to review outputs for quality, and how to connect results to your planning and execution cadence.

Data, tools, and prerequisites

• Data readiness: Basic CRM hygiene and access to pipeline, activity, and revenue data. Optional enrichment sources improve results but are not required.
• Tooling: Any mainstream CRM, spreadsheet, and BI toolset works. The course remains vendor-neutral.
• Skills: Familiarity with sales stages, segmentation, and forecasting. No prior AI expertise is required.

Governance, risk, and compliance

• Privacy: Clear rules for handling PII and customer-sensitive fields.
• Security: Guidance on approved data paths and redaction procedures.
• Accuracy: Methods to detect hallucinations, ensure source traceability, and document assumptions.
• Fairness: Routine audits to prevent biased outputs across regions or customer groups.
• Auditability: Versioned prompts, change logs, and decision records that stand up to internal and external reviews.

Measuring ROI and scaling adoption

• Baseline first: Capture pre-course metrics (conversion, cycle time, forecast error, discount rates, rep time on admin).
• Pilots in two regions: Compare results to control groups before global rollout.
• Scorecards per module: Tie each workflow to a measurable KPI and a clear owner.
• Quarterly refresh: Retire low-value workflows; invest in those with proven impact.
• Enablement cadence: Add the most valuable workflows to new-hire training and manager coaching.

Time commitment and pacing

The course is self-paced. Most leaders complete the core modules in a few hours and then roll them out in phases, starting with two or three quick wins. Teams can operationalize the full set over a quarter with weekly check-ins.

Why this course stands out

• Built for global operations: Prompts and workflows account for regional nuance, currencies, languages, and varied routes to market.
• Outcome-first: Every module ties to a leadership decision and a measurable KPI.
• Repeatable and scalable: Standard structures minimize variance across teams and systems.
• Balanced and realistic: Clear about limits, data needs, and review steps so you can trust what you deploy.

What you gain by the end

You finish with a complete AI sales playbook: consistent workflows for analysis, decision-making, and execution that run across markets and business units. Your teams will know how to use AI responsibly, how to check outputs, and how to connect insights to daily actions-so growth plans are clearer, risks are visible earlier, and wins stick.