Dialbrew vs Apollo
Apollo is where many teams get data and send touches. Dialbrew is where the resulting work is rostered, measured, commissioned and billed.
This is a category-level comparison. We describe what each kind of tool is designed to do rather than claiming specific feature gaps, because we have not audited Apollo's current feature set. Check their documentation for specifics, and treat our own claims as describing Dialbrew only.
Data and sending vs operations
Apollo is best understood as a combination of a B2B contact database and an outbound execution layer — find companies and people, then sequence them.
Dialbrew is agnostic about where your data came from. It takes prospect lists per client project, however sourced, and runs the operation around them: reserving leads so two reps never dial the same company, logging every touch to one timeline, recording booking outcomes honestly, computing commission, and producing the client invoice.
The two sit at opposite ends of the same workflow. Apollo’s question is who should we contact and how do we reach them. Dialbrew’s question is given that the work happened, what did it produce, what do we owe the rep, and what do we charge the client.
What Dialbrew adds once the touches are sent
| Capability | Detail |
|---|---|
| Prospect lists per client project | Lists scoped to the client they belong to, with depletion alerting when one runs dry |
| Lead reservation | A soft lock with an expiry pins a lead to the SDR working it; a job releases stale holds |
| Import hygiene | Phone numbers normalise to E.164, duplicates collapse, client DNC entries are filtered |
| Unified activity log | Call, SMS, email and note on one per-lead timeline, streamed live over SSE |
| Booking outcomes | Held / no-show / no-show-with-reschedule as distinct recorded states |
| Commission | One row per completed booking, uniquely constrained, moving through approve → pay |
| Client billing | Billable bookings roll into a billing record and out to Procountor |
| Client portal | The client sees their own meetings, reports and billing — the same rows, not an export |
| Capacity | Bookings/hour per SDR per project, with overrides, for six-week forecasting |
On data quality
One place the two genuinely meet is phone data. Dialbrew tracks a phone-quality status and recomputes it, records phone origin on leads, and normalises everything to E.164 at import. That is not a contact database — it will not find you new numbers — but it does mean bad numbers get identified as a measurable property of your lists rather than a vague sense that “the data is rough”.
Who should pick which
If your bottleneck is finding people to contact, that is a data problem and a database is the answer.
If your bottleneck is proving and monetising the work your team already does for multiple clients, that is an operations problem. Use whichever data source you prefer, and put Dialbrew underneath the operation.