BIGM vs Apollo
An honest side-by-side from the team that built BIGM. We use Apollo ourselves; this page tells you when to pick them over us, and the specific cases where the BIGM architecture is structurally better.
You need the B2B database as much as the outreach tooling, your team is 10+ across multiple channels, and you'd rather have one platform than three best-of-breed.
You have a data source already, your LinkedIn channel is the leverage point, and you want a tool that's built specifically for the LinkedIn restriction-resistance + reply-rate optimization problem rather than one platform that does ten things average.
What Apollo does well
All-in-one B2B sales platform combining a massive prospect database (~270M contacts), sequencing, dialer, and engagement tracking. Best known for data quality, deep filters, and the breadth of what's in one tool.
Pricing: Per-seat from ~$49 to $149/user/month for the standard tiers; enterprise pricing custom. Free tier exists but is data-limited.
- Teams that need a B2B database AND outreach in one bill
- Sales orgs running multi-channel sequences at scale (email + LinkedIn + dialer)
- Companies where data quality is the bottleneck, not channel execution
Where BIGM is structurally better
BIGM isn't a "Apollo replacement" in the generic sense. It's a LinkedIn-outbound specialist with a pool architecture built for restriction-resistance + reply-rate optimization. Specifically:
- You already have a data source (Sales Nav, ZoomInfo, internal CRM) and you're paying Apollo mostly for the outreach layer
- Your LinkedIn outreach specifically is underperforming and a generic multi-channel sequencer isn't the fix
- Restriction risk on LinkedIn is a real number for your team (it isn't, for Apollo)
- Reply rate is the limiting metric, not data volume
Side-by-side
| Dimension | Apollo | BIGM |
|---|---|---|
| What it is | Database + multi-channel outreach platform | LinkedIn outbound specialist |
| Prospect data | Built-in ~270M contact database | Bring-your-own (Sales Nav, ZoomInfo, list) |
| Account architecture | 1 account per seat | Aged-account pools |
| LinkedIn restriction protection | Standard guardrails | Pool rotation + per-account volume capping |
| Per-prospect message AI | Token-based personalization | Full per-profile rewriting |
| Best for | Multi-channel sales orgs needing data + execution | LinkedIn-first teams optimizing reply rate |