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A code-first alternative
to Qualtrics.

Qualtrics is the drag-and-drop standard. Fieldbase gives you the same depth (CBC, MaxDiff, quotas, SPSS export) with an in-platform code editor instead of a drag-and-drop canvas — plus AI that drafts the survey from a Word or PDF spec.

What Qualtrics does well

A broad drag-and-drop surface that covers nearly every survey pattern without typing. Massive feature set (XM, CX, EX suites). Enterprise sales, procurement, and compliance machine. If your team is non-technical or your company has already standardised on Qualtrics XM, that's a real moat.

Where Fieldbase differs

  • Code-first authoring in the browser. Surveys are YAML in - qid blocks with Python-like - script blocks for logic. You edit, save, and ship them from the Fieldbase editor — no file plumbing, no separate IDE. Readable, greppable, AI-assistable. See scripting →
  • AI drafts the code from a spec. Upload a questionnaire document (Word, PDF); the AI writes the survey, you review and accept. Days of programming compress into hours.
  • AI chat for live edits. Ask for changes in plain English — "make Q7 required if S2 is Male" — the AI proposes the edit, you accept. Works in any language your team speaks.
  • Export surface built for the analyst. SPSS (.sav and .dat+.sps pair), CSV with camelCase + BOM, Excel with proper type hints, fixed-width ASCII. Companion long CSVs for CBC/MaxDiff ship in the same pack. See export →
  • Pre-field Design Test for CBC/MaxDiff. Design Health and Precision scorecards with D-efficiency and implied-N — know the design will produce usable utilities before you field. See choice modeling →
  • Quotas that hold under concurrency. Real database locks on every completion — not a client-side counter. The Survey Simulator fires parallel completes against the actual production path to verify. See simulator →
  • Transparent, scoped pricing. In early access, free for founding teams. No per-response fees, no enterprise multi-year contracts. See pricing →

Side-by-side

  Fieldbase Qualtrics
Authoring
Authoring surface In-platform code editor (YAML) + Python-like - script blocks Drag-and-drop canvas with menu-driven logic
AI drafts the survey from a spec document Yes — upload a Word or PDF spec, AI writes the survey No — some AI-assisted question suggestions, not spec-to-survey
AI chat for live edits (any language) Yes — "make Q7 required if S2 is Male" in any language Limited — rule-based builders, not conversational edits
Learning curve for a programmer Hours — the DSL is YAML + Python-like syntax Days — different model (menus, flow blocks, embedded JS)
Learning curve for a non-programmer Steeper — code-first; AI chat helps Shallow — drag-and-drop is the strength here
Advanced research methods
CBC (choice, rating, ranking) First-class, three response modes supported Available in Conjoint add-on
MaxDiff + TURF analysis First-class; TURF built in Available in Conjoint add-on
Pre-field Design Test (D-efficiency, implied-N) Yes — Design Health + Precision scorecards in the editor No equivalent integrated workflow
In-app CBC utilities + share simulator Aggregate MNL part-worths + live share-of-preference Export-only (Sawtooth / R / other)
Card sort (open/closed/hybrid) Yes — first-class question type Add-on / third-party integration
Qualitative annotation (image heatmap, text intensity, video dial) First-class with in-app viewer Limited; image heatmap only
Fieldwork
Quota precision under concurrent load Row-level locks per completion — exact Soft-count buffering — occasional over-quota reported
Real-respondent survey simulator Fires parallel completes through the production path Preview / test-respondent flows (not concurrency testing)
Live-fielding quota edits Edit in place without a republish Supported with limitations
Per-language fielding (launch one language at a time) Yes — Test/Live/Paused/Closed per language Supported via translation + distribution workflow
Data & export
SPSS export .sav binary + .dat/.sps syntax pair, PSPP-verified .sav
Fixed-width ASCII export Yes — datamap-driven No
CBC / MaxDiff long-form companion CSVs Yes — cbc_long, maxdiff_long, design file, Design Health report in one pack Long form via custom export or external processing
Partial exports (date / row count / variable filter) Stackable filters at export time — no new variable needed Date filter + response-level filter via workflow
Datamap Designer (grid + text editor, templates) Yes — grid or text view, template per tracker Variable manager, no equivalent template layer
Mid-field data import (update columns on existing respondents) Yes — by respondentId, column-scoped Supported with limitations
Test / Live environment on same route (?env=) Byte-identical export for shared columns Separate test respondent workflow
Pricing & vendor
Pricing model Free in early access; transparent going forward Enterprise contracts — per-seat + per-response + modules
Starting cost (typical mid-size team) $0 (early access) Five to six figures / year
Procurement + legal Lightweight — direct contact Full enterprise procurement cycle
Best fit Teams with a programmer, or ones who'd rather have one Teams on drag-and-drop with enterprise XM/CX needs

When Qualtrics is still the right call

  • Your organisation has standardised on Qualtrics XM across multiple departments.
  • Your team has no technical users and doesn't want any.
  • You need the broader XM / CX / EX suite, not just the research tool.
  • You need enterprise procurement coverage (SOC 2 Type II, HIPAA BAA, FedRAMP) today.

FAQ

Is Fieldbase actually a Qualtrics alternative?

Yes — for the research use cases (CBC, MaxDiff, grids, quotas, SPSS export). We don't try to replace the XM/CX/EX suites.

Can my research team migrate from Qualtrics?

Email [email protected] — we'll walk you through what a migration looks like for your tracker (we can usually import a wave's data to validate column parity before you cut over).

Does Fieldbase handle CBC conjoint like Qualtrics does?

Yes — upload a Sawtooth-format design or a CSV of concept matrices, reference it with design: project://your_design_v2, and run aggregate MNL in-app. See choice modeling for the Design Test workflow.