Read In-Between the Lines with a "Sentiment Analysis"

Enter into ChatGPT:

Act as a psychological expert in understanding buyer behaviour and provide a sentiment analysis of my customer using the attached call transcript. Also, give me clear steps I can take to improve my chances of a successful sale with this buyer.

**Upload the transcript from your video call from Zoom or Microsoft Teams etc.

Imagine walking out of a sales call knowing exactly how your buyer felt—what excited them, what made them hesitant, and what they didn’t say out loud. That’s the power of sentiment analysis. By reviewing transcripts from your video calls, AI can break down tone, language, and emotional cues to uncover hidden signals in buyer conversations.

You'll spot enthusiasm masked as formality, concerns buried in vague answers, and trust starting to build through subtle word choices. More importantly, you get clear steps to respond, adjusting your proposal, addressing objections, or doubling down on what matters most to them. Sentiment analysis turns guesswork into guidance, leading to smarter follow-ups, stronger relationships, and more closed deals.

Example of Sentiment Analysis Report

From the provided transcript, John Smith's comments primarily convey a neutral to mildly positive sentiment. Here is a breakdown of his sentiment in context:

1. Neutral-Descriptive: John frequently describes processes, challenges, and operational details (e.g., double handling of data, dependency on weather conditions). His tone remains factual, focusing on sharing insights about their workflows and needs.
   
   

2. Mildly Positive: John expresses openness to collaboration and improvement, as seen in comments like, "Absolutely, I think at this stage we're more than happy to get you guys inside." This suggests a constructive approach to addressing issues.
   
   

3. Mild Frustration: Certain comments reveal underlying frustrations, such as challenges with current systems or inefficiencies (e.g., "That would automate a lot of things" or "It's easier to drive back to the office"). These sentiments are directed at operational constraints rather than people.
   
   

4. Engaged and Cooperative: John's willingness to explore solutions and accommodate site visits reflects a collaborative and engaged sentiment.
   
   

Overall, the sentiment is constructive and cooperative, with occasional frustration about system limitations and operational inefficiencies. His comments aim to guide discussions toward practical improvements.

No Hype. Just Help.