How to Switch from ServiceTitan to BILT AI

Updated June 17, 2026

To switch from ServiceTitan to BILT AI: export your customers, jobs, and history to CSV (ServiceTitan exports can require admin access or a support request, so start there); map ServiceTitan's customer and job fields to BILT's pipeline; import a test batch first; rebuild active marketing and follow-up as BILT sequences and AI follow-up; reconnect your sending identities; and run both in parallel before cutting over. Many teams keep ServiceTitan for heavy field ops and use BILT only for the marketing and follow-up layer.

ServiceTitan is a deep, enterprise-grade field-service platform — dispatch, payroll, inventory, reporting, the works. For large operations that need all of it, that depth earns its keep. The flip side is real: it's expensive and complex, and a lot of shops use a fraction of what they pay for. BILT AI is far narrower on purpose — the marketing and follow-up layer: cold email, SMS, and AI follow-up that generate and book work.

Because of that gap in scope, this is rarely a clean one-for-one swap. The honest framing is either a downsize — leaving ServiceTitan's overhead for a leaner stack — or a layer, keeping ServiceTitan for field ops while BILT runs the demand generation it isn't built around. Here's how to move the data and stand up the engine either way.

The migration, step by step

  1. Decide: downsize or layer onFirst choose the model. If you genuinely use ServiceTitan's depth, keep it for field ops and add BILT as the marketing + follow-up layer. If you're paying for far more than you use, plan a downsize. The data steps below apply either way.
  2. Export your data to CSVExport customers, jobs, estimates, and history from ServiceTitan to CSV. Exports here can require admin permissions or a support request, so start this early and keep an untouched backup copy.
  3. Inventory marketing and follow-upList the marketing campaigns, reminders, and follow-up automations you actually run in ServiceTitan so you know what to rebuild in BILT — and what enterprise machinery you won't be carrying over.
  4. Map customers and jobs to BILTMap ServiceTitan's customer and job fields onto BILT's pipeline and contact model. Decide the mapping on paper first; ServiceTitan's data model is rich, so plan which fields are essential versus enterprise overhead you can retire.
  5. Import a test batchImport 25–50 records into BILT first and verify customers, job stages, tags, and custom fields all landed correctly before the full load.
  6. Import the full datasetOnce the test batch checks out, import your complete customer and job data into BILT.
  7. Build the marketing and follow-up engineSet up the demand-generation layer in BILT — cold email sequences, SMS, and AI follow-up that work replies and book jobs — before disabling anything in ServiceTitan.
  8. Reconnect sending identitiesSet up your sending domains, email authentication (SPF/DKIM/DMARC), and A2P 10DLC SMS registration in BILT, and send yourself a test to confirm deliverability.
  9. Run both in parallel, then cut overKeep ServiceTitan live for about a week alongside BILT so in-flight jobs have a safety net. Then cut over fully and archive, or settle into the keep-ServiceTitan-for-ops split you chose in step one.

Consolidation math

ServiceTitan is priced for enterprises that use its full depth. If you're a smaller shop paying enterprise rates for a slice of the platform, the cost case for a leaner stack is real — but be honest about what you'd lose. The narrower case is the marketing layer: where ServiceTitan's demand generation is an add-on, BILT's cold email, SMS, and AI follow-up are the core. Consolidating outreach onto BILT either replaces an underused platform or runs alongside one you still need.

Frequently asked

Is BILT AI a full replacement for ServiceTitan?

Honestly, for large field operations, no — ServiceTitan's dispatch, payroll, inventory, and reporting depth is built for scale BILT doesn't try to match. BILT is the marketing and follow-up layer: cold email, SMS, and AI follow-up. The fit is either downsizing off an underused enterprise platform or layering BILT on top for demand generation.

Why would I leave ServiceTitan?

Usually cost and complexity. ServiceTitan is expensive and feature-dense, and many shops use a fraction of it. If your gap is generating and booking work rather than enterprise field-ops depth, paying for the full platform may not pencil out — and a leaner stack with a real outbound engine can do more for that specific bottleneck.

How do I export my data from ServiceTitan?

ServiceTitan exports can require admin-level access or a support request depending on your plan, so start that early. Pull customers, jobs, estimates, and history to CSV, keep a backup, and import a test batch into BILT before the full load to confirm the field mapping.

Can I keep ServiceTitan and still use BILT?

Yes, and many do. Keep ServiceTitan for field operations and run BILT as the marketing and AI follow-up layer that fills the schedule. Just connect them at the data level so a booked job from BILT lands where your ops team works it, instead of living in two disconnected systems.

The takeaway

Switching from ServiceTitan to BILT AI is usually about cost and scope, not features for features' sake. ServiceTitan's enterprise depth is real; so is its overhead. Decide whether you're downsizing or layering BILT on as the marketing and AI follow-up engine, export your data early (it can need admin access), map carefully, test-import, and parallel-run. The win is a leaner, demand-generation-first stack — without pretending BILT matches enterprise field-ops depth it doesn't claim to.

Make the switch.

Bring your data; BILT brings the engine — LOIs, cold email, SMS, and AI follow-up working from one pipeline.