I know what you’re thinking—”Ryan, didn’t you just post a newsletter yesterday?” Yes. I did. But that was before I saw that HubSpot released a Deep Research connector for ChatGPT. This is such a big deal, that I am breaking my usual once-a-week schedule.
HubSpot is the first CRM to create a connector like this, which essentially lets you leverage your CRM data to create in-depth reports and analysis using ChatGPT’s Deep Research model. Teams that effectively leverage this tool will have a massive leg up on the competition—and will also have to navigate some interesting security questions.
I basically didn’t sleep last night because I was so fascinated with this tool, and I have come up with some innovative ways marketing, sales, and RevOps teams can put this connector to work. After that, I will dive into data privacy and try to answer the question of how concerned you should actually be.
6 Use Cases for HubSpot's ChatGPT Deep Research Connector
Go-to-market teams now have superpowers. This is especially true for small businesses, who likely don’t have data analysis resources in-house. ChatGPT is your new data analyst! Here’s 2 use cases each for Marketing, Sales, and RevOps.
Marketing Use Cases
1. Hyper-Personalized Campaign Segmentation & Content Strategy
Description: Identify what customer segments are the most likely to convert. Analyze complex behavioral patterns (What content did they consume? Which website pages did they visit? In what order?). Connect the dots between their actions, demographics, and conversion paths, and get super-tailored content and messaging strategies that speak directly to each unique group, boosting engagement and conversions.
HubSpot Data: Contacts, Companies, Deals (engagement activity, content views, lifecycle, firmographics).
Sample Prompt: Analyze our HubSpot contacts over the past 12 months. Identify the top 3 micro-segments of leads that converted to customers fastest, considering their lead source, specific content engagement (e.g., which blog topics, whitepapers, or webinars they consumed, and in what order), and company industry. For each segment, provide a detailed persona description, including their common pain points, interests, and preferred learning styles, and recommend a tailored content strategy, including specific themes, formats, and optimal distribution channels to accelerate future conversions.
2. Predictive Churn Identification & Proactive Retention Marketing
Description: Identify customers at high churn risk by analyzing HubSpot data, including support tickets (e.g., volume, sentiment), marketing engagement (e.g., email opens, website activity), account health, and historical deal data. The system flags at-risk accounts and suggests personalized re-engagement campaigns.
HubSpot Data: Contacts (engagement, CSAT, NPS), Companies (health score, deals, tickets, product usage), Tickets (volume, sentiment, resolution time), Deals (renewal dates, purchases, upsells).
Sample Prompt: From our existing customer base (lifecycle stage 'Customer'), identify the top 100 companies exhibiting early warning signs of churn over the last 6 months. Analyze their recent support ticket activity (e.g., increased volume, negative sentiment, specific categories, repeated issues), marketing engagement (e.g., decreased email opens, website visits, lack of interaction with new product announcements), and any associated account health scores. For each identified company, provide a summary of churn indicators and suggest a personalized retention strategy, including specific content, outreach cadences, and potential offers to re-engage and reinforce value, prioritizing based on potential revenue impact.
Sales Use Cases
3. High-Value Account Prioritization & Tailored Engagement Playbooks
Description: Identify high-potential enterprise accounts by analyzing firmographic data, tech stack insights, historical deal success, and engagement signals. Generate hyper-specific sales playbooks, identifying key decision-makers, likely business challenges, and successful messaging themes to optimize sales efforts.
HubSpot Data: Companies (firmographics, tech stack, contacts, custom strategic account properties), Deals (win/loss reasons, stage progression, products, sales activities, value, competitor data), Contacts (seniority, role, engagement, decision-making authority, activity history).
Sample Prompt: Analyze our HubSpot company data to identify the top 50 companies with the highest potential for enterprise expansion in the sector, based on their revenue, employee count, and identified technology stack. For the top 10 most promising companies, analyze past successful deals with similar profiles and suggest a tailored engagement playbook, including key decision-maker titles to target, their likely business challenges, and successful messaging themes that resonated with similar clients, along with recommended first outreach channels and content assets.
