AI & CRM Insight

Coursera via Coursera

Go to class Write review

Overview

Google, IBM & Meta Certificates — All 10,000+ Courses at 40% Off

One annual plan covers every course and certificate on Coursera. 40% off for a limited time.

Get Full Access

Learn how artificial intelligence and CRM systems can support smarter decision-making and more efficient sales workflows. In this course, you’ll explore how sales professionals use CRM platforms to manage leads, track opportunities, and monitor pipeline performance. You’ll also learn how AI tools can assist with communication, data analysis, and sales preparation. The course introduces practical workflows that help sales teams organize customer information, track engagement, and identify opportunities more effectively. Through real-world examples, you’ll learn how CRM insights and AI-supported tools can improve productivity, support better client interactions, and help sales professionals prioritize the right opportunities. What makes this course unique is its focus on combining traditional CRM practices with emerging AI tools used in modern sales environments. Instead of focusing only on technology concepts, the course emphasizes how sales professionals apply these tools in daily workflows to improve communication, streamline processes, and make informed sales decisions

Syllabus

Develop Lead Tracking: Understanding the CRM Lead Lifecycle

In this module, you will build a clear mental model of how leads progress through a CRM—from initial capture to sales qualification. Through short videos, focused readings, and guided reflection, you will examine why accurate lead stages matter for sales execution, forecasting, and AI-supported decision-making. By the end of the module, you will understand lead tracking as a structured system that drives visibility, timing, and credibility in B2B sales workflows.

Develop Lead Tracking: Practicing Lead Tracking in a Sandbox CRM

In this module, you will move from conceptual understanding to hands-on execution. Through demonstrations, guided reflection, and applied practice, you will create and manage lead records in a sandbox CRM—entering leads, documenting sales context, and scheduling follow-ups that mirror real B2B sales workflows. The focus is on disciplined CRM habits that signal ownership, support negotiation readiness engagement readiness, and maintain clean data for forecasting and AI-driven insights.

AI Tools for Seller: Interpreting Buying Signals with AI Insights

You will examine how conversational-AI plugins provide real-time cues and sentiment insights to support better interpretation of buyer signals during discovery calls.

AI Tools for Seller: Interpreting Discovery Signals with AI

You will apply an AI meeting assistant to analyze a call recording and extract meaningful indicators of deal progress to support informed decision-making.

Automate CRM Nudges: Designing AI-Triggered CRM Nudges

You will design CRM workflows using AI-predicted churn signals to trigger timely, personalized follow-ups with clear entry and exit logic.

Automate CRM Nudges: Optimizing CRM Sequences Using Engagement Data

You will analyze engagement data to identify drop-offs and refine CRM sequences to improve response rates and overall performance.

Use AI During Calls: Real-Time AI Assistance In-Call

This module will help you use a conversational AI assistant during live calls to spot objection cues, especially pricing, right as they happen and respond confidently in the moment. You’ll practice turning AI prompts into action by reframing to ROI/value and securing a clear next step before the call ends.

Use AI During Calls: Measure Impact and Share Results

This module will let you turn your call data into proof—exporting outcomes, building a simple chart, and translating the numbers into a retro-ready story. You’ll quantify next-step lift, check the call-length tradeoff, and leave with a clear recommendation your team can act on.

Dashboard Win Drivers: Building a Win-Driver Dashboard

You will design a dashboard that visualizes win-rate by discount band, negotiation length, and AI sentiment to support sales decision-making.

Dashboard Win Drivers: Interpreting Win Drivers and Recommending Action

You will analyze dashboard insights to identify key predictors of win-rate and recommend concrete sales process improvements.

AI-Powered Sales Workflow Design Project

In this project, you will design an AI-powered sales workflow for a B2B software sales team. Your work will show how CRM processes, AI-supported selling activities, and analytics function as one connected system. You will create a workflow that improves data quality, supports timely follow-up, guides AI use during calls, and measures business impact through a clear performance framework. As part of this, you will define how AI insights are used during sales interactions and evaluate their impact by comparing call outcomes across AI-assisted and non-AI-assisted scenarios. You will also design analytics that help identify patterns in performance, including isolating key factors that influence win rates using dashboard data. You will create automated follow-up sequences and define how their effectiveness can be tested using A/B-style comparisons to determine which approaches improve engagement and deal progression. In addition, you will build a performance measurement framework that connects activity, AI usage, and outcomes, enabling continuous optimization of the sales workflow. This project reflects a real sales operations challenge where teams must not only implement systems but also measure what drives results. It focuses on integrating CRM, AI tools, and analytics into a continuous improvement loop where insights are tested, validated, and used to refine sales execution.