Advanced Excel, AI-Powered Business Analytics and Strategic Sales Athens 16.Mar.2027 (103600666_83518)

Course Overview

The Advanced Excel, AI-Powered Business Analytics and Strategic Sales course is a five-day professional training programme designed to help participants transform sales, financial and customer data into reliable business insights and strategic decisions. It combines advanced Excel, business analytics, artificial intelligence and strategic sales management within one integrated learning experience.

Participants begin by learning how to structure, clean and validate business data before applying advanced formulas, lookup functions, conditional formatting and analytical techniques. They then use Excel to evaluate sales performance, revenue, products, customer accounts, invoices, outstanding receivables, ageing balances and payment behaviour.

The course progresses to PivotTables, PivotCharts, KPI design, data visualization and executive dashboard development. Participants also explore how AI can support data interpretation, detect patterns and anomalies, improve forecasting, analyse customers and accounts, automate reporting and generate management summaries. Responsible AI practices are addressed to help participants protect confidential business information and verify AI-generated findings.

The final stage connects analytical results with customer segmentation, pipeline analysis, strategic account planning and KPI-based decision-making. Throughout the programme, participants work on a progressive business case that moves from raw data to Excel analysis, AI-generated insights, sales strategy and a final management decision.

Target Audience

• Sales managers and supervisors
• Business development managers
• Commercial managers
• Key account managers
• Business and sales analysts
• Finance and accounting professionals
• Accounts receivable personnel
• Credit control professionals
• Revenue and performance analysts
• Professionals responsible for management reporting

Targeted Organizational Departments

• Sales and business development
• Commercial operations
• Finance and accounting
• Accounts receivable and credit control
• Business intelligence and analytics
• Revenue and performance management
• Customer relationship management
• Strategic planning
• Operations and performance reporting

Targeted Industries

• Banking and financial services
• Retail and consumer goods
• Manufacturing and industrial organizations
• Telecommunications and technology
• Logistics and transportation
• Energy and utilities
• Healthcare and pharmaceutical companies
• Hospitality and tourism
• Professional services
• Government and public-sector organizations

Course Offerings

By the end of this course, participants will be able to:

• Structure, clean and validate business datasets.
• Apply advanced Excel formulas and analytical functions.
• Analyse sales, revenue, products and customer performance.
• Evaluate invoices, outstanding balances and receivables ageing.
• Build PivotTables, PivotCharts and interactive dashboards.
• Design sales, financial and customer performance indicators.
• Use AI to interpret business data and identify patterns.
• Produce AI-assisted forecasts and management summaries.
• Validate AI-generated results against original business data.
• Segment customers and prioritize valuable accounts.

Training Methodology

The programme follows an applied, progressive learning methodology combining instructor-led explanations, guided Excel demonstrations, AI-assisted analysis, business discussions and an integrated case study.

Throughout the five days, participants work with a business dataset covering sales performance, customer accounts, products, invoices, outstanding receivables and related commercial information.

The case study follows this pathway:

Data → Analysis → AI Insights → Sales Strategy → Management Decision

The methodology includes:

• Instructor-led presentations and demonstrations
• Guided advanced Excel applications
• Business data cleaning and validation
• Sales, revenue and receivables analysis
• PivotTable, PivotChart and dashboard development
• AI-assisted data interpretation and forecasting
• Customer segmentation and account prioritization
• Sales opportunity and commercial risk identification
• Strategic account and pipeline analysis
• Management reporting and executive presentations
• Daily reflection and review
• Individual workplace action planning

Course Agenda

Day 1: Advanced Excel for Business Data Analysis

• Topic 1: Structuring Business and Sales Data
• Topic 2: Cleaning and Validating Excel Datasets
• Topic 3: Advanced Formulas and Logical Functions
• Topic 4: Lookup and Reference Functions
• Topic 5: Sorting and Filtering Large Datasets
• Topic 6: Data Tables and Conditional Formatting
• Reflection & Review: Preparing and validating the integrated business dataset

Day 2: Sales, Financial and Receivables Analysis

• Topic 1: Sales Performance by Product and Customer
• Topic 2: Sales Targets Versus Actual Results
• Topic 3: Revenue and Product Performance Analysis
• Topic 4: Customer Account and Balance Analysis
• Topic 5: Receivables and Debt Ageing Analysis
• Topic 6: Invoice and Payment Pattern Analysis
• Reflection & Review: Analysing sales, accounts and receivables data

Day 3: Dashboards and Management Reporting

• Topic 1: PivotTables for Business Analysis
• Topic 2: PivotCharts and Interactive Reporting
• Topic 3: Sales and Financial KPI Design
• Topic 4: Dashboard Layout and Data Visualization
• Topic 5: Monthly and Quarterly Performance Reporting
• Topic 6: Executive Sales and Receivables Dashboards
• Reflection & Review: Building a decision-ready management dashboard

Day 4: AI-Powered Business and Sales Analytics

• Topic 1: AI Applications in Business Analytics
• Topic 2: AI-Assisted Data Interpretation
• Topic 3: Pattern, Trend and Anomaly Detection
• Topic 4: AI for Customer and Account Analysis
• Topic 5: AI-Assisted Sales Forecasting
• Topic 6: Automated Reports and Management Summaries
• Reflection & Review: Generating and validating AI-assisted business insights

Day 5: Strategic Sales Analysis and Decision-Making

• Topic 1: Customer Segmentation and Account Prioritization
• Topic 2: Sales Pipeline and Conversion Analysis
• Topic 3: Identifying Growth Opportunities and Revenue Risks
• Topic 4: Strategic Account Planning with Analytical Insights
• Topic 5: Translating KPIs into Sales Actions
• Topic 6: Presenting Recommendations to Senior Management
• Reflection & Review: Delivering the final business analysis and strategic sales presentation

FAQ

What qualifications or prerequisites are required?

Participants should have a basic understanding of Microsoft Excel, including worksheets, data entry, cell formatting and simple formulas. Familiarity with sales, customer, financial or business data is helpful but not mandatory. No previous experience in advanced Excel, artificial intelligence or business analytics is required.

How long is the course?

The programme runs for five days. Each day generally includes approximately four to five hours of instruction, demonstrations, discussions and applied analytical activities, providing approximately 20–25 training hours.

Can AI-generated insights be used directly in management decisions?

AI-generated insights should not be used without verification. Findings must be checked against the original data, validated for accuracy and evaluated within the organization’s commercial and operational context. AI outputs should support, rather than replace, professional judgement.

How This Course Is Different

This programme goes beyond teaching isolated Excel formulas or producing standard dashboards. It presents business analysis as a complete decision-making process covering data preparation, sales and financial analysis, visualization, AI-assisted interpretation, strategic sales planning and executive reporting.

Participants analyse sales performance, customer accounts, products, invoices, receivables and payment patterns before translating their findings into actionable management information. They also learn to verify AI-assisted results, protect confidential information and maintain human oversight.

By working with the same integrated dataset throughout the five days, participants experience the complete analytical journey:

Raw Data → Excel Analysis → Interactive Dashboard → AI Insights → Sales Strategy → Management Decision