On Day 9, we’ll use AI-powered coaching to help sales reps improve their pitch, objection handling, and closing techniques. AI will analyze past sales calls and provide real-time feedback and recommendations.
1. Why AI-Powered Sales Coaching?
✅ Personalized Training → AI listens to sales calls and suggests improvements.
✅ Identifies Strengths & Weaknesses → AI tracks closing techniques, persuasion, and tone.
✅ Automates Performance Reviews → No need for manual coaching sessions.
✅ Real-Time Insights → AI detects customer sentiment and flags objections.
2. How AI Coaching Works
- Sales Call Analysis → AI listens to recorded sales meetings.
- Objection Handling Feedback → AI flags common objections (e.g., price concerns).
- Tone & Sentiment Review → AI checks if the rep sounds confident or hesitant.
- Actionable Coaching Tips → AI provides suggestions to improve closing rates.
3. Installing NLP for Sales Coaching
Ensure GPT-4 and NLP sentiment analysis are installed:
npm install axios natural
4. Implementing AI Sales Coaching Feedback
✅ Step 1: Update gptService.js for Coaching
Modify src/api/gptService.js:
import axios from 'axios';
import { OPENAI_API_KEY } from '@env';
import Sentiment from 'natural/lib/natural/sentiment/SentimentAnalyzer';
const sentimentAnalyzer = new Sentiment('English', 'afinn');
export const analyzeSalesCall = async (salesCallTranscript) => {
try {
// Sentiment Score
const sentimentScore = sentimentAnalyzer.getSentiment(salesCallTranscript.split(' '));
const response = await axios.post(
'https://api.openai.com/v1/chat/completions',
{
model: 'gpt-4',
messages: [
{
role: 'system',
content: "You are an AI sales coach that analyzes sales call transcripts and provides performance feedback.",
},
{
role: 'user',
content: `Analyze this sales call:
${salesCallTranscript}
Provide:
- Overall sentiment score (-100 to +100)
- Key objections raised
- Areas where the salesperson performed well
- Actionable coaching suggestions`,
},
],
},
{
headers: { Authorization: `Bearer ${OPENAI_API_KEY}` },
}
);
return {
coachingFeedback: response.data.choices[0].message.content,
sentimentScore: sentimentScore * 100, // Convert to percentage
};
} catch (error) {
console.error('GPT Coaching Error:', error);
return { coachingFeedback: 'Error analyzing sales call.', sentimentScore: 0 };
}
};
5. Adding AI Coaching Insights to the App
✅ Step 1: Modify HomeScreen.js
import React, { useState } from 'react';
import { View, Text, Button, StyleSheet, ActivityIndicator, Alert } from 'react-native';
import VoiceRecorder from '../components/VoiceRecorder';
import { uploadAudio, transcribeAudio, getTranscriptionResult } from '../api/transcriptionService';
import { analyzeSalesCall } from '../api/gptService';
export default function HomeScreen() {
const [recordingUri, setRecordingUri] = useState(null);
const [transcription, setTranscription] = useState('');
const [coachingFeedback, setCoachingFeedback] = useState('');
const [sentimentScore, setSentimentScore] = useState(0);
const [isLoading, setIsLoading] = useState(false);
const handleRecordingComplete = (uri) => {
setRecordingUri(uri);
Alert.alert('Recording Saved', `Saved to: ${uri}`);
};
const handleAnalyzeSalesCall = async () => {
if (!transcription) {
Alert.alert('No Transcription', 'Please transcribe a voice memo first.');
return;
}
try {
setIsLoading(true);
const feedback = await analyzeSalesCall(transcription);
setCoachingFeedback(feedback.coachingFeedback);
setSentimentScore(feedback.sentimentScore);
} catch (error) {
Alert.alert('Error', 'Failed to analyze sales call.');
} finally {
setIsLoading(false);
}
};
return (
<View style={styles.container}>
<Text style={styles.title}>AI Sales Assistant</Text>
<VoiceRecorder onRecordingComplete={handleRecordingComplete} />
{transcription && (
<>
<Button title="Get AI Sales Coaching" onPress={handleAnalyzeSalesCall} />
{coachingFeedback ? <Text style={styles.feedback}>{coachingFeedback}</Text> : null}
{sentimentScore > 0 ? <Text style={styles.score}>Sentiment Score: {sentimentScore}/100</Text> : null}
</>
)}
{isLoading && <ActivityIndicator size="large" color="#0000ff" />}
</View>
);
}
const styles = StyleSheet.create({
container: { flex: 1, justifyContent: 'center', alignItems: 'center', padding: 10 },
title: { fontSize: 24, fontWeight: 'bold', marginBottom: 20 },
feedback: { marginTop: 10, fontSize: 16, fontWeight: 'bold' },
score: { fontSize: 18, color: sentimentScore > 0 ? 'green' : 'red' },
});
6. Example AI Coaching Feedback
🔹 Sales Call Transcript:
“The client was interested in our product but raised concerns about pricing. They also wanted to know if we offer a free trial. I emphasized our features and benefits, but they seemed unsure about committing.”
🔹 AI-Generated Coaching Insights:
📌 **Overall Sentiment Score:** +45/100
📌 **Key Objections:**
- Price concerns
- Free trial request
📌 **Strengths:**
- Sales rep highlighted product benefits
- Handled objections calmly
📌 **Coaching Tips:**
- Emphasize ROI to counter price objections
- Offer a trial period to increase engagement
- Use social proof (case studies, testimonials)
7. Preparing for Tomorrow: AI Sales Automation & Chatbots
Tomorrow, we’ll:
- Build an AI chatbot for real-time sales assistance.
- Automate responses to common customer queries.
8. Key Concepts Covered
✅ AI-powered sales coaching based on recorded sales calls.
✅ Sentiment analysis for evaluating rep performance.
✅ Actionable coaching tips for closing more deals.
9. Next Steps: AI Chatbots for Sales Assistance
Tomorrow, we’ll:
- Create an AI chatbot that helps answer sales queries in real-time.
- Automate lead nurturing via AI-powered messaging.
10. References & Learning Resources
11. SEO Keywords:
AI sales coaching, GPT sales training, AI-powered sales performance review, AI sales rep training, AI-driven sales improvement tools.
