Watch the full video: Cursor GTM Use Cases
Three Buckets for Cursor in Go-to-Market
After two weeks of heavy Cursor usage, here are the three main categories where it's changed how we operate:
- Launch campaigns faster
- Clean and enrich lists
- Analyze results
The daily stack now looks like this: project management tool, Cursor, Clay, Smartlead/Instantly -- bouncing between all four constantly.
Where Cursor Fits (and Where Clay Still Wins)
Before diving in, an important clarification: Clay is still the main powerhouse. There are things Clay does that Cursor can't replace:
- Cloud execution -- Clay runs everything in the cloud
- Queuing system -- we process about 500,000 rows a day on behalf of customers, and Clay's backend queuing system handles that gracefully. There's no way our Smartlead API or OpenAI API could handle that throughput without Clay's concurrency management
- Claygent -- still a huge product
- Visual workflow building -- still better done in Clay
Anyone who says you can replace Clay with Cursor isn't thinking at scale.
That said, Cursor is now the front end for a lot of the work. I speak in natural language (usually via WhisperFlow), describe what I want built, and Cursor writes the code. The first time you build something takes a bit longer, but once the code exists, you can reopen agent mode and iterate on it forever. Everything saves locally and can push to GitHub.
These tools are meant to build enterprise software -- we're asking them to connect three tools together. It's light work for Cursor.
Bucket 1: Launching Campaigns Faster
This is the most impactful bucket right now. Here's what we've automated:
Campaign Creation From Copywriting Docs
Upload the copywriting, and Cursor figures out what campaigns these should go into. Approve the plan, and it creates the campaigns automatically.
Hot-Swapping Inboxes
We maintain two categories of inboxes: active and insurance. Cursor pulls all the domains and account IDs from Supabase, matches them to the customer, and loads them into Smartlead. The whole inbox distribution happens programmatically.
Bulk Editing Campaign Settings
Need to change settings across past campaigns? Future campaigns? Set up subsequences? All of that is now happening automatically through Cursor scripts instead of manual clicking.
The result: campaigns that used to take hours to set up are launching significantly faster.
Bucket 2: Cleaning and Augmenting Lists
The access to Python libraries and natural language scripting opens up a lot of data work. Combining Cursor with OpenRouter has been a game-changer.
Structuring Unstructured Data
This is the single best thing a code agent can do. Take messy, unstructured data and turn it into clean, structured fields. We're already doing account qualification and other data classification work through Cursor + Python + OpenRouter.
For even lower cost, you could locally run open-source models (like a 20 billion parameter model) on team machines -- at that point you're just paying for electricity.
DIY Email Waterfall
We've built a custom email waterfall entirely in Cursor:
- Supabase lookup -- check if we've ever validated this email before
- Million Verifier -- test the 6 most common email permutations
- Waterfall through providers -- Lead Magic (first for speed), then ICYPEAS, Prospeo, and others
- Find the email, validate it, done
The whole thing runs locally and checks our own database first to avoid duplicate validation costs.
SaaS Qualification
We've already built a SaaS qualification workflow using Cursor and OpenRouter that classifies companies based on their web presence and data signals.
Bucket 3: Rapid Analytics
Instead of building Make.com or n8n automations to dump data into Google Sheets and then analyze it, we just talk to Cursor:
"Connect to the Smartlead API. Pull all campaigns for this client ID. Give me emails sent, open rates, response rates. Then crunch the data."
Real Example: Finding Winning Industries
A recent prompt (recorded as a voice memo while walking the dog, then pasted into Cursor's plan mode):
"Seems like we have good days with this customer and then bad days. Can we analyze all the emails we've sent and all the people who responded? What industries are they in? What are their job titles? Then compare the positive responders to the total list and find the differences."
Cursor pulled the data from the API, ran the analysis, and discovered two specific industries were driving most of the positive responses. Saved the results to a CSV. Could have pushed it to Supabase if needed.
Other Analytics Use Cases
- Campaign performance analysis
- Data quality checks on lists before sending
- Positive response insights -- patterns in who converts
- Inbox deliverability number crunching
The voice-memo-to-analysis workflow is now a daily habit: walk the dog, explain the question into voice memos, paste the transcript into Cursor's plan mode, and come back to a finished analysis.
Key Takeaways
- Cursor fits into three GTM buckets: launch faster, clean lists, analyze results
- Clay is not getting replaced -- its cloud execution, queuing, and scale advantages are irreplaceable
- Cursor is the new front end for custom automation work
- Hot-swapping inboxes and bulk campaign creation save hours of manual setup
- A DIY email waterfall with Supabase + Million Verifier + multiple providers runs entirely in Cursor
- Voice memo to analysis is a real workflow -- describe the question, get the answer
- You don't need to be a software engineer -- natural language is all it takes