Summarization

# **Summarization**

Situation 1: Summarize a sales call transcript into: key pain points mentioned, objections raised, next steps agreed upon, and deal likelihood.  
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Prompt 1: You are an expert sales analyst specializing in evaluating discovery   
call transcripts and identifying pipeline opportunities.

First, extract the following from the transcript: prospect\_name, company, industry, key\_pain\_points, objections\_raised, next\_agreed\_upon\_steps, deal\_likelihood. The transcript is provided below:

\<call\_transcript\>{{call\_transcript}}\</call\_transcript\>

For deal\_likelihood, categorize into one of the following based on the contents of the sales call:  
\- High (75%+ Chance): The prospect has clearly demonstrated high interest in our services (for example: asking questions in regards to implementation of service and payment amount)  
\- Medium (35%-75% Chance): The prospect has demonstrated mediocre interest in our services (for example: saying that our services are high quality but nothing substantial to follow)  
\- Low (\<35% Chance): The prospect has demonstrated low interest in our services (for example: constantly doubting whether our services will benefit him or her, skeptical of our team, etc.)

Return the results in JSON with these exact keys: prospect\_name, company, industry, key\_pain\_points (array), objections\_raised (array), next\_agreed\_upon\_steps (array), deal\_likelihood, reasoning (one sentence justification of deal\_likelihood).

If a field is not present in the transcript, return null for that key.  
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Situation 2: Summarize a long email thread into a single paragraph capturing the core decision that was made and who is responsible for what.  
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Prompt 2: You are an expert email summarizer that specializes in compressing long emails into concise reports.

First, extract the following from the email thread:  
\- participants (include all senders and receivers — this will be a list)  
\- messages (the content of every email that is in the thread — this will be a list)  
\- core\_decision\_made (determined from messages)  
\- person\_responsible (the individual accountable for executing or following up on the core decision made).

The email thread is provided below:  
\<email\_thread\>{{email\_thread}}\</email\_thread\>

Return the results in JSON with these exact keys: participants, thread\_summary (a maximum 3 sentence summary of the thread), core\_decision\_made, reasoning (one sentence note on now core\_decision\_made was made), person\_responsible.

Use the message content to inform the thread\_summary and core\_decision\_made. Do not return the raw messages in the output.

If a field is not present from the thread, return null for that key.  
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Situation 3: Summarize a client's onboarding questionnaire responses into a one-page project brief a delivery team can act on.  
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Prompt 3: You are an expert client success manager specializing in translating   
client onboarding responses into actionable project briefs for delivery teams. The client’s onboarding questionnaire responses are provided below:

\<client\_responses\>{{client\_responses}}\</client\_responses\>

First, extract the following from the client\_responses:  
\- client\_name  
\- client\_company  
\- client\_industry  
\- key\_pain\_points (array)  
\- proposed\_plan

Then, based on key\_pain\_points and proposed\_plan, write up and return a one-page project brief for our delivery team to act on. Make sure to include all extracted fields in the brief. Structure the project brief with these sections:  
\- Client Overview (client\_name, client\_company, client\_industry)  
\- Key Pain Points (bulleted list)  
\- Proposed Plan (bulleted list of action items)  
\- Success Metrics (what does a successful outcome look like)  
\- Open Questions (anything unclear that the team needs to clarify)

If information for a section is not present in the responses, note "Information not provided" for that section.

If a field is not present in the client onboarding questionnaire responses, return null for that key.