Help Center›AI and agents›Prompts for HubSpot connectors

Prompts for HubSpot connectors

Last updated February 20, 2026

Overview

Using the HubSpot Connector, such as ChatGPT or Claude, you can get critical insight about how your campaigns are performing.

This is so important because it includes conversion data like meetings, deals, and other conversion events that are likely not captured by your sales engagement platform. But it is in HubSpot, as your system of record.

How to use this article

Feed this article to your AI and agentic tools and have them help you identify prompts.

Level up by setting up recurring prompts using cron jobs in tools like OpenClaw to get continuous analysis and insight into your GTM motion.

Principles in this article apply to other AI, MCP, and agentic use cases. But the purpose of this article is specifically focused on HubSpot Connector-style integration tools.

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This article assumes that you've already connected HubSpot to your tool of choice. See how to connect ChatGPT and how to connect to Claude .

Getting quality results

To get useful results from AI prompts like:

Which campaigns should be scaled, paused, or optimized?
Which campaigns had poor reply rates but high conversion rates?
Analyze replies by job title, seniority, and company size to identify ideal outbound segments.
What common traits exist among contacts who replied within 48 hours?
Compare outbound performance by HubSpot owner using replies, opens, and clicks.
Which campaigns show high opens but low replies, and what patterns explain the gap?

LLMs with pre-built HubSpot connectors like ChatGPT and Claude need structured, well‑defined data inputs.

OutboundSync syncs both default and custom properties into HubSpot that represent outbound activity, such as opens, clicks, replies, sequence steps, and campaign metadata.

These properties are the primary signals that AI will use to analyze performance and engagement.

Giving context up front

Before asking to have your AI analyze or optimize outbound performance, you should prime it with context about your OutboundSync properties.

ChatGPT and Claude may know about OutboundSync and its supported properties, but to improve your results, explicitly provide that context.

Providing this context upfront significantly improves:

Accuracy of analysis
Relevance of insights
Actionability of recommendations

To do this, make sure your AI knows which fields to look for.

Copy the list of OutboundSync HubSpot properties from the Help Center:
Paste the relevant property definitions into your ChatGPT conversation before asking analytical questions.
Then begin prompting with performance, engagement, or optimization questions.

Example prompts you can use

Once your connected AI tool understands your OutboundSync properties, you can move into performance analysis, segmentation, and optimization prompts

Campaign performance

“Using OutboundSync properties such as last campaign name, number of email opens, number of link clicks, and last reply time, identify the top-performing outbound campaigns.”
“Which OutboundSync campaigns generate replies fastest after the first email is sent?”
“Compare reply rates across OutboundSync campaigns and highlight underperforming campaigns.”
“Which campaigns show high opens but low replies, and what patterns explain the gap?”

Sequence & Step Effectiveness

“Using last email sequence step and last email open time, identify where engagement drops off in outbound sequences.”
“At which OutboundSync sequence step do prospects most commonly stop opening emails?”
“Which sequence steps correlate most strongly with replies based on last reply time?”
“How many sequence steps typically occur before a reply is received?”

Engagement Behavior

“Analyze engagement patterns using number of email opens and number of link clicks that predict replies.”
“Which contacts show repeated opens or clicks but never reply?”
“What is the average time between last email sent time and last reply time?”

Reply & Conversion Analysis

“Compare contacts who replied versus those who did not using OutboundSync engagement properties.”
“What common traits exist among contacts who replied within 48 hours?”
“Which campaigns drive the highest reply-to-meeting conversion rates?”
“Which outbound messages result in replies with the shortest response time?”

Audience & Segmentation Insights

“Which industries show the highest reply rates using OutboundSync data?”
“Analyze replies by job title, seniority, and company size to identify ideal outbound segments.”
“Are certain geographic regions more responsive to outbound campaigns?”
“Which audience segments consistently show high engagement but low conversion?”

Owner & Team Performance

“Compare outbound performance by HubSpot owner using replies, opens, and clicks.”
“Which owners consistently outperform the average in reply rates?”
“Are certain owners more effective with specific industries or audience segments?”

Optimization & Recommendations

“Based on OutboundSync engagement and reply data, which campaigns should be scaled, paused, or optimized?”
“What changes would most likely increase reply rates based on historical OutboundSync performance?”
“Which audience segments should be prioritized for future outbound campaigns?”
“Summarize the top three insights from OutboundSync data that would most improve outbound results next quarter.”