FreightScout compared with ZoomInfo and Apollo for freight brokerage sales
ZoomInfo and Apollo are excellent general-purpose B2B databases. That is not a hedge before an attack, it is the actual starting point of this comparison. They are bigger than us, older than us, and better than us at the thing they are built for. The question is not which product is better. It is whether generic company data is what a brokerage sales floor is missing.
Last updated 20 August 2026. Competitor descriptions are quoted or paraphrased from each company's public pages on that date. Where a figure is not published, this page says so rather than estimating it.
What each one actually is, in its own words
| ZoomInfo | Apollo.io | FreightScout | |
|---|---|---|---|
| Self-description | "a go to market intelligence platform" / "the AI GTM platform that turns B2B intelligence into pipeline" | "AI sales platform" that "replaces your data provider, outreach platform, dialer, enrichment, and CRM" | Freight-native platform for brokerages, revenue and ops on one system |
| Database scale, as published | Not stated on the pages reviewed; 30,000+ customers cited | "240M+ contacts and 30M+ companies" | Not a contact database; built on freight and brokerage data |
| Industries served | Software, manufacturing, business services, healthcare named | Any; roles from SDR to founder | Freight brokerage only |
| Buying signals | "real time buying signals" | Visitor identification, form enrichment | Lane and shipper context, freight-side fit |
| Sequencing and dialing | Engagement tooling in platform | Multichannel campaigns, dialer, call summaries | Outreach plus coaching on real brokerage calls |
| Published pricing | Quote only | Free Starter tier; paid tiers compared on their pricing page | $750/mo platform incl. three seats, $250/mo per added seat, $1 per stage per load |
The actual difference: generic company data versus freight context
A generic sales intelligence platform knows companies. It knows a shipper's headcount, its tech stack, its org chart, who changed jobs last month, and often when someone on that team started researching a category. That is genuinely valuable and there is no freight-native equivalent of it at that scale.
What it does not know is freight. It cannot tell you which lanes that shipper actually runs, whether those lanes fit the capacity you already have, what you have historically been able to cover into that region, or whether this account looks like the accounts your floor already wins. To a general-purpose database, a manufacturer in Ohio is a manufacturer in Ohio. To a brokerage, the only question that matters is what moves, where it goes, and whether you can cover it profitably.
The second difference is coaching. Sales intelligence platforms increasingly summarize calls. Summarizing a call and coaching a broker are different jobs, and the gap is domain: knowing that a rep failed to ask about seasonal volume, or accepted a rate objection they should have held, or never established who signs, requires knowing how a brokerage sale works.
Where ZoomInfo and Apollo win, plainly
This is the section most vendor comparison pages leave out, which is exactly why it is worth reading.
- Prospecting outside freight. If a brokerage is selling anything other than freight services, or a parent company is running go-to-market across several businesses, a general database is the right tool and a freight-native one is not.
- Raw contact volume. Apollo publishes 240M-plus contacts and 30M-plus companies. If the requirement is breadth of contact records, buy breadth of contact records.
- Cross-industry buying signals. ZoomInfo's intent data covers a far wider surface than anything freight-specific.
- Consolidating a stack. Apollo's explicit pitch is replacing a data provider, an outreach tool, a dialer and enrichment with one bill. If your problem is five overlapping subscriptions, that is a real answer.
- Recruiting, marketing and ops teams. Both platforms serve functions well outside sales. A freight sales tool does not.
Where a freight-native system wins
- Lane-level context on a prospect, rather than firmographics that stop at the company record.
- Shipper fit scored for brokerage prospecting, which is a different question from company fit.
- Coaching built on real brokerage calls, where the model knows what a good discovery call in freight sounds like.
- Revenue and ops on one data foundation, so what the floor sold and what the operation delivered are the same record.
- Pricing you can read before a call. Ours is on the pricing page; both of the others are quote-led at the tiers a brokerage would buy.
Verdicts by situation
| If this is you | Buy | Why |
|---|---|---|
| You need contact records at volume, across every industry | Apollo or ZoomInfo | That is the product. No freight-native tool matches the breadth. |
| You are prospecting outside freight | Apollo or ZoomInfo | Freight context is irrelevant to the sale. |
| You want one bill instead of four tools | Apollo | Consolidation is its stated pitch. |
| Enterprise GTM with intent data across many segments | ZoomInfo | Breadth of signal is the strength. |
| Your reps have lists and still cannot tell which shippers fit your capacity | FreightScout | The missing input is freight context, not more contacts. |
| Your floor's performance varies and nobody can say why | FreightScout | Coaching needs to know what a brokerage call should sound like. |
| You want what was sold and what was delivered on one system | FreightScout | Revenue and ops share one foundation. |
They are not mutually exclusive, and pretending otherwise would be dishonest
Plenty of brokerages will run a general database for contact discovery and a freight-native system for fit, coaching and execution. Those are different line items solving different problems, and a floor that already pays for Apollo does not need to cancel it to get freight context. If a vendor tells you their product replaces a 240-million-record database, ask to see the records.
The thing underneath the comparison
Whatever you buy, the effect on a brokerage floor is the same and it is worth being clear-eyed about it. These tools take the friction out of the parts of selling where effort used to be invisible: building the list, writing the follow-up, remembering what was said on a call three weeks ago. When that friction goes, your strongest reps do several times the work they used to, and the difference between them and everyone else stops being a matter of opinion.
That is not AI replacing brokers. It is AI removing the cover that made an existing performance gap hard to see. The brokerages that do well out of this are the ones that give their A players the leverage and then act on what the rest of the picture is now showing them.