Generative AI for sales performance: strategies and tools for your sales teams

Duration : 7 hour

© AFI Expertise inc.

This intensive, hands-on training course, available in 7 hour formats, propels you into the practical use of AI tools to amplify your sales performance. After a targeted introduction to specialized AI tools for sales, you will directly experience their use through practical exercises based on real sales scenarios. The emphasis is on the immediate application of the knowledge acquired to your day-to-day sales challenges: prospecting, lead qualification, personalizing sales proposals and customer follow-up. You'll leave with a personalized toolbox and the confidence to integrate AI into your sales cycle, significantly boosting your sales productivity and conversion rates.

Audience

This training course is aimed at human resources professionals who want to understand and exploit artificial intelligence in their missions:

· Account managers and sales managers

· Inside sales and telemarketers

· Sales representatives

· Business developers

Prerequisites

Have a basic understanding of key concepts and terminology in artificial intelligence.

General Objectives

Identifying the right generative AI tools
Identify relevant AI tools, their key functionalities, appropriate contexts of use, and associated best practices.

Understanding how to use generative AI
Understand AI tools, interpret their results, distinguish appropriate use cases and classify the forms of assistance offered by AI in the workplace.

Applying good prompting practices in tools
Use AI tools independently, apply best practices, adapt prompts according to needs and daily work tasks.

Analyze and assess the quality of results
Evaluate the quality, relevance and effectiveness of AI tools, as well as diagnose problems and justify the use or non-use of AI depending on the situation.

Specific Objectives

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

Remember

· Identify the main AI tools relevant to their professional context

· Name the key functionalities of each tool presented

· Recognize the situations conducive to the use of each tool

· List best practices for using AI tools

Understand

· Explain the general operation of the AI tools presented

· Interpret the results produced by AI tools

· Distinguish the appropriate use cases for each tool

· Classify the different types of assistance that AI can bring to their work

Apply

· Use the AI tools presented independently

· Demonstrate correct use of the main functionalities

· Implement good AI interaction practices

· Adapt prompts and queries to specific needs

· Perform professional tasks with AI assistance

Analyze

· Examine the quality of results produced by AI

· Diagnose common problems in the use of tools

· Differentiate between situations where AI is relevant and those where it is not

· Analyze the effectiveness of different approaches to tool use

Evaluate

· Assess the suitability of an AI tool for a given task

· Judge the quality and reliability of the outputs generated

· Measure the efficiency gains brought about by the use of AI

· Justify the choice of whether or not to use AI for specific tasks

Create

· Develop customized prompts tailored to their needs

· Build their own customized AI toolbox

· Generate innovative solutions by combining different AI tools

Contents

Module: Introduction to LLMs and Generative AI (30mins)

• LLM definition and fundamentals
• Architecture and basic operation
• Model types and their characteristics
• Current capabilities and limitations
• Key concepts: tokens, embeddings, prompts
• Impact on different business sectors

Module: Security and confidentiality when using LLMs (30mins)

• Understanding confidentiality issues
• Good security practices
• Ethical communication with AI

Module: Producing text with an LLM (60mins)

• Basic principles of prompt engineering
• Content generation techniques
• Structure and format of effective prompts
• Tone and style control
• Optimizing results
• Best practices and pitfalls to avoid

Module: Analyzing and synthesizing text with an LLM (60mins)

• Text analysis and information extraction techniques
• Key information extraction
• Structural analysis
• Pattern identification
• Content classification
• Comparative analysis
• Summary structuring
• Adaptable synthesis levels
• Accuracy validation

Module: Transforming and formatting text with LLM (30mins)

• Rewriting techniques and reformulation
• Adapting style and language level
• Formatting for different media
• Conversion between formats
• Document structuring
• Checking and improving quality

Module: Translating and localizing with AI (30mins)

• Principles of machine translation
• Cultural adaptation and localization
• Preserving context and meaning
• Quality control
• Idiomatic expression management

Module: Analyzing visuals with LLM (30mins)

• Image recognition
• Visual content description and analysis
• Information extraction
• Image classification
• Object and scene detection
• Layout analysis
• Module: Analyzing data with AI (30mins)
• Data preparation and cleaning
• Statistical analysis techniques
• Data visualization
• Interpretation of results
• Trend identification
• Data-driven recommendations
• Module: Search (web and other) with the help of LLMs (30mins)
• Advanced search techniques
• Source validation
• Limits to LLM search capabilities

Module: Learning with the help of an LLM (30mins)

• Personalized learning
• Creating learning paths
• Self-assessment techniques
• Content adaptation
• Progress monitoring

Module: Ideation with LLM (30mins)

• Idea generation techniques
• Stimulating creativity
• Concept exploration
• Development of alternatives
• Idea evaluation
• Concept refinement