Case Study

How a Fintech Startup Automated 60% of GTM Work and Freed 15 Hours Per Week Per AE

Industry
Fintech · Payments
Stage
Seed · $2.4M ARR
Timeline
8 Weeks
Team Size
5 AEs
The Situation

Founder-led sales was ending.
The chaos was just beginning.

This B2B payments infrastructure company had just closed a Seed round and brought on five account executives to take over a sales motion the founders had been running on gut instinct and sheer hustle. The problem: there was no motion to hand off.

Every AE was spending north of 15 hours per week on work that had nothing to do with selling: manual research before calls, copy-pasting contact data into the CRM, writing follow-up emails from scratch, and chasing calendar links back and forth with prospects. There were no sequences, no enrichment, no routing logic. Just five smart people buried in operational drag.

01 Zero lead enrichment on inbound. When a prospect filled out a form, AEs were manually digging through LinkedIn, Crunchbase, and company websites just to understand who they were talking to before a call. 45 minutes of research before every discovery call, every time.
02 No outbound sequences or personalization at scale. Outbound existed in theory. In practice, every email was written from scratch. AEs had no templates, no AI-assisted personalization, and no sequencing tool configured for their ICP. Volume was low and conversion was lower.
03 CRM was a graveyard, not a system. Deal stages were updated manually, or not at all. Meetings were booked through email tag and sometimes fell through entirely. Leadership had no real pipeline visibility. Forecasting was a weekly guessing game.
The Approach

Four moves. Eight weeks.
A sales team that could actually sell.

We didn't hand them a strategy deck. We got into their systems on week one and started building. Here's exactly what we did.

Step 01
GTM Audit
We mapped every manual touchpoint across the entire sales motion, from lead creation to closed-won. Every form fill, every research task, every CRM update, every email, every scheduling back-and-forth. We assigned time cost to each step and ranked by automation opportunity. Within three days, we had a complete picture of where the 15+ hours per AE per week were actually going, along with a prioritized build list.
Diagnostic · Process Mapping
Step 02
Enrichment Engine
We set up automated data enrichment triggered the moment a lead was created, pulling firmographic data (company size, revenue, industry, tech stack), contact-level data (title, seniority, LinkedIn, direct phone), and intent signals. By the time an AE opened a new lead in the CRM, the research was already done. Discovery calls went from "let me pull this up real quick" to leading with insight from the first sentence.
Clay · Enrichment · CRM Automation
Step 03
Sequence Architecture
We built role-specific outbound sequences with distinct tracks for CFOs, Heads of Finance, and Operations leads, combined with AI-generated personalized opening lines at scale. Each sequence pulled from enrichment data to reference the prospect's company, recent news, or relevant tech stack signal. What used to take an AE 30 minutes to write per email now happened automatically, at volume, without sacrificing relevance. Outbound finally became a system.
AI Personalization · Sequencing · Outbound
Step 04
Routing & Handoff Automation
We built automated lead routing based on ICP fit score and deal size, eliminating the informal "who's taking this one?" Slack threads. Calendly was integrated directly into sequences and confirmation emails, removing scheduling latency entirely. CRM stage updates were automated on key triggers (meeting booked, meeting completed, proposal sent) so deal hygiene happened without anyone touching it. For the first time, the pipeline actually reflected reality.
Lead Routing · Meeting Automation · CRM Hygiene
The Results

Eight weeks in,
the numbers did the talking.

0%
GTM Work Automated
More than half of every AE's weekly task load across research, data entry, follow-ups, and scheduling now runs without them touching it.
0hrs
Saved Per AE Per Week
10 hours returned to each AE every single week. That's a full working day redirected from admin to active selling.
0x
Outbound Volume
Same five AEs. Triple the outbound activity. Sequences, AI personalization, and enrichment removed the ceiling on what the team could send.
CRM data quality went from ~40% to 95%+ complete across all active pipeline records, giving leadership real-time forecast accuracy for the first time in company history.
Average time-to-booked-meeting dropped by 62% after integrating automated scheduling directly into outbound sequences, resulting in fewer touchpoints, faster conversion, less prospect drop-off.
Illustrative · Real data coming soon
In Their Words
“

Before zRev, I spent most of my week doing things that had nothing to do with revenue. Research, data entry, chasing scheduling links. It was endless. I knew it was broken, but we didn't have the time or expertise to fix it while also trying to hit quota.

The automation work alone saved my team 15 hours a week. But the bigger win was the clarity. We finally know what's working and why. Our CRM reflects reality. Our outbound is actually running. Our AEs are spending their time talking to prospects instead of building spreadsheets.

zRev didn't just give us tools. They gave us a system that runs itself. That's the difference.

PRIYA M.
Head of RevOps · Anonymous Fintech Startup
What This Means For You

Your team doesn't have a talent problem.
It has a system problem.

If your AEs are burying time in research, CRM updates, and manual follow-ups, that is recoverable time. We've done this before. We can map exactly where the drag is coming from and build the automation that eliminates it. In weeks, not quarters.

Book a 30-Min Call

No pitch. Just a straight conversation about your GTM.

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