AI course in sales – the power of artificial intelligence for sales and business process support

1. AI as support for modern sales

• the most important AI capabilities in the B2B sales process,
• overview of available AI models and tools used in sales,
• how to select AI tools for specific sales tasks,
• comparison of AI models in terms of quality, costs and business application possibilities,
• how to understand billing models and pricing of AI tools and properly budget their use,
• examples of AI application at individual stages of the sales funnel,
• case studies of AI use by sales teams,
• practical exercises using selected AI tools.

2. Lead Generation – searching for and qualifying potential customers

• use of AI to identify new customer segments and markets,
• building the ideal customer profile – ICP using AI,
• searching for companies meeting specified sales criteria,
• analysis of websites, company information, and available business data,
• creating lists of potential B2B customers,
• searching for decision-makers and determining their potential needs,
• automatic organizing and enrichment of lead information,
• Lead scoring – assessment of the customer’s sales potential with AI support,
• identifying buying signals and events that may initiate sales contact,
• prioritization of leads and determining the order of sales activities,
• exercise: preparation of a list of potential customers and a model of their scoring.

3. AI in preparing contact with the client

• use of AI to prepare for a sales conversation,
• quick client research before contact or a meeting,
• analysis of the client's business, its market, potential needs and problems,
• generating hypotheses regarding the client's business needs,
• preparation of sales arguments tailored to a specific recipient,
• personalization of communication depending on the industry, position and stage of the sales process,
• creating questions for the discovery conversation,
• preparation of a telephone conversation or meeting scenario,
• identification of the client's potential objections and preparation of responses,
• exercise: preparation of a complete brief before a meeting with the client.

4. Sales communication automation

• generating personalized prospecting messages,
• creating contact-initiating email messages,
• preparing follow-ups after conversations and meetings,
• creating contact sequences with a potential client,
• adapting the language of messages to the recipient's position and profile,
• personalizing communication with a larger number of clients,
• creating reminder and reactivation messages for inactive clients,
• automatically preparing meeting summaries and recommended next actions,
• using AI as a sales assistant in everyday work,
• exercise: preparing a multi-stage contact campaign with a B2B client.

5. Generating offers and sales materials using AI

• creating commercial offers based on information collected during a conversation with the client,
• personalizing offers to the needs of a specific company,
• transforming product and technical data into the language of business benefits,
• preparing value propositions for various client groups,
• creating descriptions of products and services,
• preparing sales arguments,
• generating comparisons of offer variants,
• creating sales presentations and materials supporting meetings,
• quality control of content generated by AI,
• exercise: preparing a personalized offer for a selected client.

6. Optimization of sales processes using AI

• identifying repetitive tasks that can be improved or automated,
• automation of work related to acquiring and handling leads,
• use of AI in customer relationship management,
• practical applications of AI in the CRM environment,
• automatic creation of notes, summaries and recommendations for further actions,
• classifying customer inquiries and determining their priority,
• supporting the sales team in task management and pipeline management,
• coordination of sales activities with the help of AI,
• designing simple processes automating the daily work of salespeople,
• exercise: analysis of a selected sales process and designing its improvement using AI.

7. Sales data analysis and forecasting

• use of AI for sales data analysis,
• asking questions to data in natural language,
• identifying trends, seasonality and changes in customer behavior,
• analysis of sales results by customers, products, regions and sales representatives,
• searching for relationships and anomalies in data,
• analysis of the sales funnel and the reasons for losing sales opportunities,
• customer segmentation based on historical data,
• sales forecasting with AI support,
• creating sales scenarios: optimistic, baseline and pessimistic,
• use of forecasts for planning resources, inventory and sales team activities,
• generating management reports and comments on results,
• exercise: preparation of sales data analysis and a forecast for the next period.

8. Chatbots and AI agents in sales support

• the role of chatbots and AI agents in the modern sales process,
• the most common scenarios for the use of chatbots in B2B sales,
• automatic handling of basic customer inquiries,
• lead qualification with the help of a chatbot,
• collecting information necessary to prepare an offer,
• supporting customers in choosing products or services,
• integration of chatbots with CRM and other organizational systems,
• example technologies and architectures of conversational solutions,
• analysis of chatbot effectiveness and basic performance indicators,
• the process of implementing a chatbot or AI agent in an organization,
• areas in which conversational automation can bring the greatest benefits,
• limitations and risks associated with automating customer contact.

9. Prompt engineering for salespeople

• how to formulate effective commands for AI,
• the structure of a good prompt: context, role, task, data and expected result,
• prompts for customer research,
• prompts for lead generation and scoring,
• prompts for preparing sales messages,
• prompts for analyzing customer needs,
• prompts for preparing commercial offers,
• prompts for data analysis and forecasting,
• building your own prompt library for the sales team,
• practical exercises based on real sales scenarios.

10. Security, privacy and responsible use of AI in sales

• rules for safe use of AI tools,
• what customer and organization data should not be provided to public AI tools,
• protection of commercial information and confidential data,
• protection of personal data and customer privacy,
• risk of incorrect or outdated information generated by AI,
• verification of content prepared by AI models,
• risk of bias and incorrect customer segmentation,
• transparency of AI use in communication with the customer,
• rules for responsible use of automation in sales and marketing,
• good practices regarding the use of AI by sales teams.