BI tools like Looker, Metabase, and Hex are powerful. If you have a data team and a well-maintained data warehouse, they're excellent for building custom dashboards and running complex analyses. But if you're a Series A–B SaaS company without a dedicated data engineer, a BI tool often creates more problems than it solves.
Here's an honest breakdown of when a BI tool makes sense and when Eru is a better fit.
The Core Difference
BI tools are general-purpose analytics platforms. You bring your data, write queries, and build dashboards. They're a blank canvas.
Eru is a purpose-built AI revenue intelligence platform for SaaS. You connect your tools, and it automatically maps your data, detects churn signals, identifies expansion opportunities, and surfaces metrics like NRR, GRR, and churn rate. No configuration required.
The difference is the same as buying a custom-built house versus buying one that's already built and furnished for exactly your needs.
Side-by-Side Comparison
| Factor | BI Tool (Looker, Metabase, Hex) | Eru |
|---|---|---|
| Setup time | Weeks to months (warehouse + ETL + dashboards) | 5 minutes (connect tools via OAuth) |
| Requires a data warehouse | Yes — you need Snowflake, BigQuery, Redshift, or similar | No — Eru connects directly to your tools |
| SQL required | Yes, for most queries and dashboards | None — AI maps and queries your data |
| Who can use it | Data analysts, engineers, technical users | RevOps, CS, finance — anyone on the commercial team |
| Churn detection | You build it from scratch (custom queries across tables) | Built-in — cross-system churn signals surfaced automatically |
| Expansion signals | You build it from scratch | Built-in — watchlists from usage patterns and plan utilisation |
| Revenue metrics | You build each metric as a dashboard | Live NRR, GRR, churn rate, LTV:CAC out of the box |
| Data integrity monitoring | Not typically included | Automated alerts for MRR mismatches, orphaned accounts, stale pipelines |
| Maintenance | Dashboards break when schemas change; someone has to fix them | AI agent adapts to schema changes automatically |
| Cost | Tool cost + data warehouse cost + person to run it | Fraction of the total BI stack cost |
| Best for | Custom analysis, ad-hoc exploration, data-heavy orgs | Revenue intelligence, churn detection, expansion signals for scale-ups |
The Hidden Cost of a BI Tool at a Scale-Up
The sticker price of Looker or Metabase isn't the real cost. The real cost is everything around it:
Data warehouse. Before you can query anything in a BI tool, your data needs to live somewhere queryable. That means setting up Snowflake, BigQuery, or Redshift, then building ETL pipelines to move data from Stripe, Salesforce, HubSpot, and your other tools into the warehouse. That's a data engineering project.
Pipeline maintenance. Schemas change. APIs update. New tools get added. Someone has to maintain the pipelines that keep your warehouse current. If nobody does, your dashboards quietly go stale — and you're making decisions on bad data.
Dashboard building. A BI tool gives you a blank canvas. Someone has to write the SQL, design the visualisations, and build every dashboard from scratch. For SaaS revenue metrics, that means joining billing data with CRM data with product usage data — across different schemas and naming conventions.
A person to run it all. Unless someone on your team is comfortable with SQL and data modelling, you'll need to hire someone. At which point you're back to the "hire a data analyst" scenario — $150K–$220K/year — plus the BI tool and warehouse costs on top.
For a Series A–B company with 50–500 customers, that's a lot of overhead to answer "what's our NRR?" and "which accounts are about to churn?"
When a BI Tool Is the Right Choice
BI tools earn their place when:
- You already have a data team and a well-maintained data warehouse
- You need highly custom analysis that goes beyond standard SaaS metrics
- Your data needs are broad — not just revenue intelligence, but marketing analytics, product analytics, finance, and operations all in one place
- You want full control over every query, visualisation, and data model
If you're a 200-person company with a 5-person data team, Looker or Hex is probably the right call. They're built for teams that have the resources to maintain a full analytics stack.
When Eru Is the Right Choice
Eru fits when:
- You're a SaaS scale-up ($3–10M ARR) without a data engineering team
- Your core need is revenue intelligence: churn signals, expansion opportunities, NRR, GRR
- You want answers now, not in 3 months after building a warehouse and dashboards
- Your commercial team (RevOps, CS, finance) needs self-serve access to metrics
- Your data lives across 6–12 tools that aren't connected
- You can't afford to hire a data analyst just to get basic revenue reporting
Eru doesn't replace a BI tool for companies that already have a mature data stack. It replaces the need to build one in the first place.
How Eru Works Compared to a BI Tool Workflow
Typical BI tool workflow: Set up a data warehouse. Build ETL pipelines for each tool. Write SQL to join tables across systems. Build dashboards for each metric. Maintain everything when schemas change. Train your team to use it. Repeat when you add new tools.
Eru workflow: Connect your tools via read-only OAuth (5 minutes each). Eru's AI agent discovers how your data relates across systems and builds a unified truth map. Churn signals, expansion opportunities, and revenue metrics appear automatically. Add new tools any time — Eru maps them into the existing model.
The difference is months versus minutes, and ongoing maintenance versus zero maintenance.
Can You Use Both?
Yes. Some companies use Eru for revenue intelligence and a BI tool for other analytics needs (marketing, product, finance). They're complementary, not mutually exclusive.
The question is whether you need a BI tool right now, or whether Eru gives you everything your commercial team needs while you're still scaling toward the point where a full analytics stack makes sense.
How to Get Started
Connect your tools — Stripe, Salesforce, HubSpot, Intercom, Segment, your database, or any system with an API. Read-only access, 5-minute setup, no data warehouse or engineering required.
Book a free churn audit to see what revenue signals are hiding between your tools — without building a single dashboard.
Book a churn audit →