8:42 AM - Inbox triage
I open my laptop and check Slack first. Three alerts overnight. One is just noise - a free trial signup from someone at a one-person shop, not our ICP. The second is interesting: Carol Reyes at Reyes Family Practice is asking about custom fields for their deal pipeline. The third is the kind that makes my stomach drop. Michael Chen, one of my first customers at Sterling Sales Group, has downgraded to the free plan.
I make a note to call Michael later. First, I need to move through the email queue.
Our AI prospecting agent prepped seven outbound emails last night. I open the draft folder in Gmail. Four are strong - personalized, specific references to recent LinkedIn posts from the VP Sales contacts, good hooks. One is generic enough that I rewrite it entirely. The other two are close but the tone is off for the industry. I revise them to sound less salesy and more consultative. I mark all seven as "ready to send" in our approval workflow, and they go out over the next hour via our automated cadence. It's 7:37 AM on the West Coast, so the timing should hit morning inbox checks.
I pull up the Deal Tracker dashboard to see yesterday's numbers. Seven new signups yesterday, three of them from the outbound pipeline. Two more in trial conversions from the first cohort we demo'd three weeks ago. Total revenue yesterday: $236. Not huge, but consistent. This month we're on track for about $1,840 new MRR if these conversions hold.
10:15 AM - A flagged conflict
Slack pings. Our automated system flagged something: a customer, James Park at Park & Associates, is two weeks into his trial but the deal tracking hasn't synced with his CRM all week. The system caught it because his login frequency just dropped from multiple times a day to nothing since Friday.
I open our admin UI and check the integration logs. Salesforce connection failed on Saturday afternoon - some kind of token refresh issue that our sync daemon didn't handle gracefully. It just silently stopped.
This is the kind of thing that kills trials. I open Linear and create a ticket for the integration bug, labeling it urgent. Then I do the manual operator work: I craft an email to James, acknowledge the issue, and let him know it's fixed and I'll re-sync his data this morning. I ask if he's free for a quick call to show him the feature he was trying to test. The email takes me maybe four minutes. Sending it manually instead of through our template system feels slower, but it feels personal. He needs to know a human noticed.
I run the re-sync through the admin panel. Twenty-two deals come through. I send James a follow-up in Slack with a screenshot of his freshly synced pipeline and a calendar link.
12:30 PM - Lunch and the metrics check
I grab a sandwich and open the metrics spreadsheet I maintain alongside Stripe. I pull our dashboard numbers for the first 35 days of month two.
Week-to-date we have forty-one customers. Eight converted from trial in the last seven days. Churn is low right now - only two downgrades (one was Michael Chen's downgrade this morning), no full cancellations. That keeps us clean.
But I need to be honest with myself about what today brought. Michael's downgrade stings. He was a clean customer, paid on time, we had good onboarding. I need to understand why.
I open Stripe and look at his account. Last login was six days ago. I check our internal notes. He tried to use the deal update feature to add activity notes and found the interface confusing. No support ticket. He just got frustrated and downgraded. I should have been watching for that signal. I wasn't.
I call him at 1:15 PM. His assistant puts me through after a minute.
Michael's direct. He says the tool is good but he didn't have time to learn it. His team is slammed in Q2. He might come back in the fall when things settle. I ask if I can do a 20-minute walk-through of the activity feature - it's simpler than he thinks. He says no, but not unkindly. He appreciates the call. I tell him I'll send him a quick video tutorial anyway and to reach out if things change.
After we hang up, I record a 3-minute screen recording walking through the exact feature he was stuck on and email it to him with a note that it'll be here whenever he's ready.
2:08 PM - The good one
Slack notification. "Hey, wanted to give you a shout-out. The deal tracking in your product just helped me close a deal I thought was stuck. Thanks."
It's from Carol Reyes. The same Carol who had the custom fields question this morning. Turns out she wasn't asking about custom fields because the tool was broken - she was asking because she wanted to track something additional. I'd misread the intent. But our tool's existing setup was enough to help her surface something she'd missed in her pipeline.
She closed the deal today. It's not our deal, but it's hers, and our tool helped. That's the entire product right there.
I respond in Slack and ask if she'd be open to a short customer interview call. The narrative that converts trials to paying customers isn't usually "the tool is perfect," it's "the tool helped me close a specific deal I was worried about." Those are gold. I want to hear the full story.
She replies within two minutes: "Absolutely. Tomorrow afternoon?"
3:45 PM - A billing question
Stripe alert. One of our customers, Victoria Chen at Northridge Sales, has failed their payment twice in the last week. Our automated retry logic tried again, and it still failed.
I open her Stripe record. The card is valid-looking, decent company, clean history. I search our support notes. Nothing flagged. The failing card is tied to an older corporate Amex. I send Victoria an email flagging it and asking if there's a card update needed, but I note that her trial converts her to month-to-month, so she's not in a hard billing cycle yet. I can give her 48 hours without escalation.
She replies at 4:12 PM - she's out of office but her finance person will handle it. Says to expect the corrected card by tomorrow morning.
4:30 PM - Pipeline review
I spend 20 minutes walking our current trial pipeline. Thirteen active trials running right now. Three are hot - these are VPs who've taken multiple logins, tested the deal sync, and asked good questions in onboarding. Two are medium. Eight are cold - they signed up but haven't logged in or haven't moved past the initial UI tour.
The system doesn't do this analysis automatically yet. I do it manually by hand in a Google Sheet, flagging which ones I think need outreach and which ones are likely dead. I send personalized emails to the three hot prospects - short, just checking in, asking if they want a call this week. For the eight cold ones, I set up a gentle automated re-engagement sequence that the AI handles.
5:50 PM - Closing out
I check Slack one more time. James Park replied to my re-sync message. "This is perfect. Really helpful. I'm going to use this more seriously the rest of the week."
Michael still hasn't watched the video I sent, but that's okay.
Carol confirmed tomorrow at 2 PM for the call.
I open Stripe one more time and export today's numbers. Five new signups, two conversions, Michael's downgrade, Victoria's card issue resolved, and my existing forty-one customer base churning slower than I expected. We're at $2,341 in recurring revenue for the month so far.
I think about what worked today and what felt hard. The prospecting emails that I reviewed and sent - that felt efficient. It's maybe two hours of work per week that's replacing what would be five or six hours of me cold-emailing all day. The AI is good at the volume and personalization layer. I'm good at the judgment calls, the tone edits, the timing.
What felt hard was the churn. Michael's downgrade reminds me that I'm not just a dashboard operator. I need to watch the metrics that tell me when customers are struggling. A customer who goes from four logins per day to zero in a week is a customer who's about to leave. I missed that signal.
I close the laptop at 6:15 PM. Tomorrow I'm going to add a daily "at-risk" alert to my morning routine. And I'm going to record a few more video tutorials. Turns out that's what people need from me on the support side.
The business is working. The growth is real. And the work is still real, too. The AI didn't make it invisible. It made it possible for one person to run.