Daniel is a professional, knowledgeable individual, that takes pride in the quality of his work. His reliability is second to none and he is always up to the challenge.
Kathy SongOperations Manager
Tolocal
A verification stalls, a document goes in and nothing follows, usage quietly drops. I build lifecycle systems that read those signals in real time and act on them, with every signal synced back to Salesforce so a human can follow the automation.
When I inherited lifecycle at a payments company, retention meant a shared MailChimp account serving three regions with no owner and no CRM sync. Sends went out on calendar dates to whoever was on the list. Nobody knew which accounts were stalling, because nothing was listening.
I rebuilt it on one rule: journeys trigger on account state and usage signals. A document submitted, a verification stalled, a first payment pending. Each of those is a customer telling you something, hours or weeks before they would ever write in. The $2M → $76M → $250M+ cross-border payments line depended on this repeat-usage engine. Marketing on that line was mine end to end; sales and finance ran their own sides of it, and my journeys fed them. Every journey I shipped carried a measurable job: registered → first payment → habitual use.
Before any cadence exists, every engagement signal gets a home. I sync opens, clicks, document submissions and usage events back into CRM scoring across HubSpot, Salesforce and Pipedrive, so account managers can see who's engaged, who's stalled, and who's gone silent after submitting documents. Churn risk surfaces before the customer says anything.
By where the account actually is. I built the segments around state: orientation for pre-KYC users, KYC-progress support during verification, activation after compliance approval. Each state has its own job, and an account moves segments the moment its state changes.
A document submitted, a verification stalled, a first payment pending. Each signal branches to its own cadence automatically. The engine I built ran as real-time automation at 100–300 new registrations a day, with no manual intervention and no weekly list pulls. If a save depends on someone remembering to check a report, it isn't a system.
Every cadence I ship carries its number, and the lowest performers go into my A/B queue. I use AI-assisted segment refinement and lead scoring to sharpen the loop over time. It is the same respond-before-they-churn muscle behind the 200+ workflows I built, which cut lead handoff from ~12 hours to 1–2 minutes, applied to keeping accounts instead of catching them.
The single biggest churn point was a verification that never finished. New registrants would start KYC, hit friction, and drift. I rebuilt the onboarding journeys around real-time account status: the moment a verification stalled or a document sat unprocessed, my journeys sent the right support message, and I wired the signal back into Salesforce so a human could follow the automation.
KYC submissions went from roughly 10% to 35–40%, and completion time dropped from 140 hours to 24–48 hours. The customers didn't behave differently. The system I rebuilt finally answered them on time.
Submissions ~10% → 35–40% · completion 140h → 24–48hAt a later company, the earliest churn signals were buried in support tickets, mixed in with sales ops requests, accounting questions and product bugs. I built an AI routing layer on the queue (GPT-4o mini plus Zapier) that classified and tagged every ticket on arrival. Misrouted sales ops, accounting and product work disappeared from the support queue, and my classifier's tags gave the first honest picture of what support actually spent time on: an engagement and workload signal no one had counted before.
With my classifier absorbing the triage, the same single rep went from replying to reviews on one platform to three. Trustpilot, G2 and Capterra were all covered, with no added headcount. The replies were her work; the hours were mine to give back. I never wired a dashboard for it, so I won't quote a deflection percentage. The queue got quieter and the replies got faster; that part I watched happen.
Review coverage 1 → 3 platforms · same single rep · zero added headcountDaniel is a professional, knowledgeable individual, that takes pride in the quality of his work. His reliability is second to none and he is always up to the challenge.
Kathy SongOperations Manager
Churn shows up in behaviour weeks before it shows up in revenue. The system watches the behaviour.