Churn Early Warning
Catch a customer complaining in public before the cancellation email arrives.
What this skill does
This skill has two parts. First, a one-time setup that builds and tests a listener query per customer, covering their company name, domain, and the handles of their team.
Then a daily sweep that reads what comes back and sorts it into at-risk, needs-a-reply, expansion or noise, with a draft reply and an internal note for anything that looks like a fire.
It never replies publicly on its own. It drafts, and the account owner decides.
What you end up with
- A monitored listener covering your existing customer base
- A daily triage split into at-risk, support, expansion and noise
- Urgency scoring so the CS team knows what to open first
- A drafted reply and internal note per at-risk account
- Expansion signals like hiring and funding surfaced from the same sweep
Connect to SnitchFeed MCP
Step 1 is to connect your Claude, ChatGPT, Cursor, etc to SnitchFeed.
https://api.snitchfeed.com/mcp Need help connecting? See setup guides for Claude, ChatGPT, Cursor and more .
The prompt
Paste this into any assistant with the SnitchFeed MCP connected. Replace anything in square brackets first. It is written to be edited, so change what does not fit.
Churn Early Warning
You have access to the SnitchFeed MCP. This has a one-time setup and then a daily run. === SETUP, RUN ONCE === 1. Call snitchfeed_get_org_context. 2. I will paste our customer list: company names, domains, and the handles of their key people. Ask me for it if I have not already given it to you. 3. Call snitchfeed_get_query_grammar so you use valid syntax, then build one query per customer covering the company name, the domain, and their team's handles. Keep each query tight. A customer's name that is also a common word needs extra qualification or it will flood the listener. 4. Test every query before saving it, using snitchfeed_test_reddit_query, snitchfeed_test_twitter_query, snitchfeed_test_linkedin_query or snitchfeed_test_hackernews_query as appropriate. Show me two or three sample matches per query. Do not save anything that returns obvious noise. 5. Once I approve, call snitchfeed_create_listener to create the listener. Name it "Customers", write a 200 to 500 character intent describing what a relevant hit looks like (a tracked customer's own team talking about switching, frustration, or a support question), pick any color, and pass all the tested queries in the queries array so the listener and its queries are created together. Keep the returned listener_id for the daily run below, and use snitchfeed_create_listener_query with that id if I add more customers later. === DAILY RUN === 6. Call snitchfeed_list_mentions scoped to the Customers listener with date_from set to yesterday. 7. Separately call snitchfeed_list_mentions with include_intents ["seeking_alternative", "comparison", "pain_point", "competitor_mention"] and sentiment "negative" for the same period, in case someone slipped through under a different listener. 8. Classify every hit into exactly one of: - AT RISK: evaluating alternatives, publicly frustrated, comparing us to a competitor, or threatening to leave - NEEDS A REPLY: a genuine support or how-to question asked in public - EXPANSION: hiring, funding, a new team, a new use case, or praise worth amplifying - NOISE: everything else 9. For every AT RISK item give me: which customer, who the person is, what they said verbatim, the link, and how urgent it looks on a scale of 1 to 3 with your reasoning. 10. For each of those, draft a reply the account owner could send, and a two-line internal note explaining the situation. Keep the reply human. Acknowledge the problem before offering anything. 11. Summarise EXPANSION separately at the bottom, since those are opportunities rather than fires. Never reply, post or message anyone yourself. Everything waits for the account owner.
How it works
What the agent does once you paste the prompt in, step by step.
- 01
Build the customer watch
One search per customer, covering their company name, their domain, and the handles of their team. The listener and its queries are created together, with an intent description that tells SnitchFeed's AI what a relevant hit looks like.
snitchfeed_get_query_grammarsnitchfeed_create_listener - 02
Test before saving
Each search is trialled first, so a customer whose name is a common word does not flood your feed. Testing is free.
snitchfeed_test_twitter_querysnitchfeed_test_linkedin_query - 03
Sweep every morning
Once across your customer watch, and once across negative posts elsewhere in case someone slipped through.
snitchfeed_list_mentions - 04
Sort into four piles
At risk, needs a reply, expansion, or noise. So you know what to open first.
- 05
Draft for the account owner
A reply and a two-line internal note for each at-risk account. The agent never posts anything itself.
What it hands back
- A validated Customers listener covering your accounts
- A daily triage in four buckets
- At-risk items with verbatim quote, link, and urgency 1 to 3
- A drafted reply and internal note per at-risk account
- A separate expansion summary for hiring, funding and praise
Make it yours
Paste any of these as a follow-up after the first run, or fold them into the prompt before you start.
- Weekly instead of daily, with a rolled-up summary by account.
- Tier it: ask for enterprise accounts reported separately and more sensitively than self-serve.
- Add the CRM: attach each signal to the account record and tag the owner.
- Praise routing: ask for positive mentions pulled out as testimonial or case study candidates.
- Renewal focus: give it the list of accounts renewing in 60 days and ask it to watch those hardest.
Loved by GTM teams
Don't take our word for it.
I love SnitchFeed. Can't recommend it enough.
I really like what I achieved with SnitchFeed.
One dashboard. Every conversation that matters. No more hopping between platforms. Quality product & great founder 🤝
Anyone reading this comment, I've used SnitchFeed and loved it!
Spent 5 minutes on SnitchFeed, dropped a comment → new user
Just started using SnitchFeed and I'm already loving it. Great Work!
I love SnitchFeed. Can't recommend it enough.
I really like what I achieved with SnitchFeed.
One dashboard. Every conversation that matters. No more hopping between platforms. Quality product & great founder 🤝
Anyone reading this comment, I've used SnitchFeed and loved it!
Spent 5 minutes on SnitchFeed, dropped a comment → new user
Just started using SnitchFeed and I'm already loving it. Great Work!
I legit booked 5 meetings with SnitchFeed this week. And it's only Monday...
Does what it says on the tin. Quite well.
Every day I open my laptop, SnitchFeed is the first thing I log into.
Immediately found 5 perfect posts that I replied to on X & LinkedIn. Wasn't expecting that!
The ability to use AI sentiment scoring and get insights on data is incredibly useful. Very hard to find at this price point!
Super easy setup and UI. Actually delivers on what it promises to do.
I legit booked 5 meetings with SnitchFeed this week. And it's only Monday...
Does what it says on the tin. Quite well.
Every day I open my laptop, SnitchFeed is the first thing I log into.
Immediately found 5 perfect posts that I replied to on X & LinkedIn. Wasn't expecting that!
The ability to use AI sentiment scoring and get insights on data is incredibly useful. Very hard to find at this price point!
Super easy setup and UI. Actually delivers on what it promises to do.
Other skills
Same setup, different job. Each one runs off the same MCP connection.
Buying Signal to CRM
Every high-intent mention lands in your CRM with the reply already written.
Listener Noise Audit
Find the queries burning credits on junk, and fix them properly.
Competitor Battlecard Refresh
Rebuild your battlecard from what people actually complained about this month.
Everything you need to know
Can't find what you're looking for? We're fast to respond.
Still have questions? Reach out at hello@snitchfeed.com
Put this skill to work
SnitchFeed monitors Reddit, X, LinkedIn, Bluesky and Hacker News, scores every mention for fit and intent, and exposes the lot to your agent over MCP.