If you’re a Series A or B SaaS company hitting $3–10M ARR, you’ve probably started feeling the pain: investor board decks need real numbers, churn is happening but nobody can explain why, and every data question turns into a two-week project. The instinctive move is to hire — a GTM engineer, a data analyst, maybe a RevOps lead.
But hiring isn’t the only option anymore. AI-powered tools like Eru can now handle much of the work that used to require a dedicated data hire. Here’s an honest comparison of both approaches.
What a GTM Engineer or Data Analyst Actually Does Day-to-Day
Before comparing, it helps to understand what these roles look like in practice at a scale-up.
A GTM engineer or data analyst at a $3–10M ARR company typically spends their time on: pulling ad-hoc data for leadership (“What’s our NRR by cohort?”), building and maintaining dashboards in a BI tool, writing SQL to join data across systems, cleaning up CRM data and fixing discrepancies, setting up integrations between tools, creating board-ready reports, and investigating why the numbers don’t match.
Industry data suggests roughly 60% of their time goes to ad-hoc requests — one-off data pulls that are urgent, repetitive, and low-leverage. The remaining 40% is spent building systems, dashboards, and processes.
Side-by-Side Comparison: Eru vs a Data Hire
| Factor | Hiring a GTM Engineer / Analyst | Using Eru |
|---|---|---|
| Annual cost | $150K–$220K (salary + benefits + tools) | Fraction of a hire — pricing scales with integrations |
| Time to value | 2–4 months (recruiting + onboarding + ramp) | 5 minutes (connect tools, AI maps your data) |
| Ad-hoc data requests | Handled manually, 60% of their time | Eliminated — metrics are live and self-serve |
| Churn detection | Requires building custom pipelines and dashboards | Built-in — cross-system churn signals surfaced automatically |
| Expansion signals | Requires correlating usage, billing, and CRM data manually | Built-in — expansion watchlists generated from usage patterns |
| Revenue metrics (NRR, GRR, churn rate) | Built manually in a BI tool, maintained by the hire | Live and always up-to-date, pulled from connected tools |
| Data integrity | Hire has to spot-check discrepancies | Automated alerts for MRR mismatches, orphaned accounts, stale pipelines |
| Maintenance | Dashboards break, schemas change, someone has to fix it | Eru’s AI agent adapts to schema changes automatically |
| Scales with complexity | One person can only do so much — you’ll need to hire again | Handles additional tools and data sources without added headcount |
| Strategic thinking | A great hire brings judgment, context, and strategic insight | Eru handles the data plumbing; your team makes the decisions |
Where Eru Wins
Instant time to value
Recruiting a good GTM engineer takes 2–3 months. Onboarding takes another month. Building the first useful dashboard takes another month after that. You’re looking at 4–5 months before you get the reporting you need.
Eru connects to your tools in 5 minutes, maps your data automatically with AI, and surfaces churn signals and revenue metrics from day one. The 60% of ad-hoc data work that would consume a hire’s time is eliminated immediately.
Cross-system intelligence that’s hard for humans to maintain
A GTM engineer can build a dashboard that shows Stripe MRR alongside Salesforce pipeline data. But maintaining that integration — handling schema changes, new tools, data freshness issues — is a grind. And correlating signals across 8–12 tools simultaneously (usage drops + support spikes + billing changes + CRM gaps) is genuinely difficult for one person to do reliably.
Eru’s AI agent monitors all your connected systems continuously and correlates signals at the account level. It catches patterns that a human would miss simply because the data lives in too many places.
Cost
A GTM engineer in the US or UK costs $150K–$220K in total compensation. Plus the tools they’ll need (BI platform, data warehouse, ETL tool). Eru costs a fraction of that, and you don’t need to layer additional tooling on top.
Where a Hire Wins
Strategic judgment and context
Eru surfaces signals and metrics. It tells you which accounts are at risk, where expansion opportunities exist, and what your NRR looks like. But it doesn’t sit in your leadership meeting and argue for a pricing change based on churn patterns. It doesn’t design your go-to-market motion or decide which customer segment to prioritise.
A great GTM engineer or data analyst brings strategic judgment — the ability to interpret data in the context of your specific business and make recommendations that go beyond what any tool can do.
Custom, complex analysis
If you need a one-off deep dive into why a specific cohort of customers from Q2 2024 churned at 3x the normal rate, and you need to factor in seasonality, pricing changes, and a product incident — that’s a job for a human analyst. Eru handles the repeatable, ongoing monitoring. The truly novel, context-heavy analysis still benefits from a person.
Building processes and culture
A hire can build data literacy across your organisation. They can train your CS team to use dashboards, create self-serve reporting for your sales team, and establish data governance practices. Eru gives you the data infrastructure, but building a data-informed culture is a human job.
The Hybrid Approach: When Companies Use Both
Some scale-ups use Eru to handle the data infrastructure and monitoring, then hire a more senior, strategic person (a Head of RevOps or a data-minded Chief of Staff) who focuses purely on interpretation and strategy rather than pipeline plumbing.
This approach works particularly well because it lets the hire focus on the 40% of high-leverage strategic work instead of spending 60% of their time on ad-hoc data pulls. Eru handles the connective tissue; the hire provides the brain.
Questions to Help You Decide
Ask yourself:
Is the core problem that you don’t have data connected and visible? Eru solves this faster and cheaper than a hire.
Is the core problem that you don’t have someone to interpret the data and make strategic decisions? You probably need a hire — but consider using Eru first to give that hire a running start.
Are you under investor pressure to have solid reporting by next board meeting? Eru delivers in days. A hire delivers in months.
Is your team drowning in ad-hoc data requests? Eru eliminates these. If that’s 60% of what a hire would do, the math is clear.
How to Get Started With Eru
Connect your tools — Stripe, Salesforce, HubSpot, Intercom, Segment, your database, or any system with an API. Read-only access, 5-minute setup, no engineering required. Eru’s AI agent maps your data and starts surfacing churn signals, expansion opportunities, and revenue metrics immediately.
Book a free churn audit to see what you’re missing before you commit to a $200K hire.
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