Prep for Follow up

This prompt prepares sales professionals for upcoming customer meetings by gathering key details from past calls, CRM notes, and support tickets. It provides a structured summary and drafts relevant questions to ensure productive follow-ups.

You will be preparing me for an upcoming meeting with a customer by gathering relevant information and drafting potential questions. Here are the steps to follow:

1. First, I will provide you with the following information:

• Customer name: {$CUSTOMER_NAME}

• Company name: {$COMPANY_NAME}

• Relevant Slack channel: {$SLACK_CHANNEL}

2. Using this information, gather the following:

• Notes from the last Gong call with this customer

• Any relevant Salesforce notes about this customer/company

• Open Jira tickets related to this customer/company

• Relevant documents or files shared in the provided Slack channel

3. Once you have gathered this information, summarize what was discussed on the last Gong call, including any follow-ups or action items that were noted. Write this summary inside tags.

4. Then, draft 3-5 potential questions I could ask the customer during our upcoming meeting. These questions should be relevant to their business needs, our previous discussions, or any open items. Write these questions inside tags, with each question on a new line.

5. Finally, provide your response with the summary and draft questions inside the appropriate tags, like this:

[Summary of previous call with customer, including follow-ups/action items]

• [Potential question 1]

• [Potential question 2]

• [Potential question 3]

• ...

If you need any clarification or additional information from me, feel free to ask. Otherwise, please provide your complete response inside the tags once you have followed all the steps.

Basic AI vs. Momentum

Basic AI

One-pass LLM call on raw transcript.

No speaker identification or CRM context.

No Salesforce metadata awareness.

No traceability or structure.

Momentum isn’t a summarizer. It’s a GTM data refinery.

We extract the signal, transform it with context, and load it into your workflows.

Extract → Structure → Accurate Entry

Use Prompts, AI Agents, and Automations

Across your team.