Make.com Timezones explained and AI Automation for accurate workflows breaks down the complexities of timezone handling in Make.com scenarios and clarifies how organizational and user-level settings can create subtle errors. For us, mastering these details turns automation from unpredictable into dependable.
Jannis Moore (AI Automation) highlights why using AI for timezone conversion is often unnecessary and demonstrates how to perform precise conversions directly inside Make.com at no extra cost. The video outlines dual timezone behavior, practical examples, and step-by-step tips to ensure workflows run accurately and efficiently.
Make.com timezone model explained
We’ll start by mapping the overall model Make.com uses for time handling so we can reason about behaviors and failures. Make treats time in two layers — organization and user — and internally normalizes timestamps. Understanding that dual-layer model helps us design scenarios that behave predictably across users, schedules, logs, and external systems.
High-level overview of how Make.com treats dates and times
Make stores and moves timestamps in a consistent canonical form while allowing presentation to be adjusted for display and scheduling purposes. We’ll see internal timestamps, organization-level defaults, and per-user session views. The platform separates storage from display, so what we see in the UI is often a formatted view of an underlying, normalized instant.
Difference between timestamp storage and displayed timezone
Internally, timestamps are normalized (typically to UTC) and passed between modules as unambiguous instants. The UI and schedule triggers then render those instants according to organization or user timezone settings. That means the same stored timestamp can appear differently to different users depending on their display timezone.
Why understanding the model matters for reliable automations
If we don’t respect the separation between stored instants and displayed time, we’ll get scheduling mistakes, off-by-hours notifications, and failed integrations. By designing around normalized storage and converting only at system boundaries, our automations remain deterministic and easier to test across timezones and DST changes.
Common misconceptions about Make.com time handling
A frequent misconception is that changing your UI timezone changes stored timestamps — it doesn’t. Another is thinking Make automatically adapts every module to user locale; in reality, many modules will give raw UTC values unless we explicitly format them. Relying on AI or ad-hoc services for timezone conversion is also unnecessary and brittle.
Organization-level timezone
We’ll explain where organization timezone sits in the system and why it matters for global teams and scheduled scenarios. The organization timezone is the overarching default that influences schedules, UI time presentation for team contexts, and logs, unless overridden by user settings or scenario-specific configurations.
Where to find and change the organization timezone in Make.com
We find organization timezone in the account or organization settings area of the Make.com dashboard. We can change it from the organization profile settings section. It’s best to coordinate changes with team members because adjusting this value will change how some schedules and logs are presented across the team.
How organization timezone affects scheduled scenarios and logs
Organization timezone is the default for schedule triggers and how timestamps are shown in team context within scenario logs. If schedules are configured to follow the organization timezone, executions occur relative to that zone and logs will reflect those local times for teammates who view organization-level entries.
Default behaviors when organization timezone is set or unset
When set, organization timezone dictates default schedule behavior and default rendering for org-level logs. When unset, Make falls back to UTC or to user-level settings for presentation, which can lead to inconsistent schedule timings if team members assume a different default.
Examples of issues caused by an incorrect organization timezone
If the organization timezone is incorrectly set to a different continent, scheduled jobs might fire at unintended local times, recurring reports might appear early or late, and audit logs will be confusing for team members. Billing or data retention windows tied to organization time may also misalign with expectations.
User-level timezone and session settings
We’ll cover how individual users can personalize their timezone and how those choices interact with org defaults. User settings affect UI presentation and, in some cases, temporary session behavior, which matters for debugging and for workflows that rely on user-context rendering.
How individual user timezone settings interact with organization timezone
User timezone settings override organization display defaults for that user’s session and UI. They don’t change underlying stored timestamps, but they do change how timestamps appear in the dashboard and in modules that respect the session timezone for rendering or input parsing.
When user timezone overrides are applied in UI and scenarios
Overrides apply when a user is viewing data, editing modules, or testing scenarios in their session. For automated executions, user timezone matters most when the scenario uses inline formatting or when triggers are explicitly set to follow “user” rather than “organization” time. We should be explicit about which timezone a trigger or module uses.
Managing multi-user teams with different timezones
For teams spanning multiple zones, we recommend standardizing on an organization default for scheduled automation and requiring users to set their profile timezone for personal display. We should document the team’s conventions so developers and operators know whether to interpret logs and reports in org or personal time.
Best practices for consistent user timezone configuration
We should enforce a simple rule: normalize stored values to UTC, set organization timezone for schedule defaults, and require users to set their profile timezone for correct display. Provide a short onboarding checklist so everyone configures their session timezone consistently and avoids ambiguity when debugging.
How Make.com stores and transmits timestamps
We’ll detail the canonical storage format and what to expect when timestamps travel between modules or hit external APIs. Keeping this in mind prevents misinterpretation, especially when reformatting or serializing dates for downstream systems.
UTC as the canonical storage format and why it matters
Make normalizes instants to UTC as the canonical storage format because UTC is unambiguous and not subject to DST. Using UTC internally prevents drift and ensures arithmetic, comparisons, and deduplication behave predictably regardless of where users or systems are located.
ISO 8601 formats commonly seen in Make.com modules
We commonly encounter ISO 8601 formats like 2025-03-28T09:00:00Z (UTC) or 2025-03-28T05:00:00-04:00 (with offset). These strings encode both the instant and, optionally, an offset. Recognizing these patterns helps us parse input reliably and format outputs correctly for external consumers.
Differences between local formatted strings and internal timestamps
A local formatted string is a human-friendly representation tied to a timezone and formatting pattern, while an internal timestamp is an instant. When we format for display we add timezone/context; when we store or transmit for computation we keep the canonical instant.
Implications for data passed between modules and external APIs
When passing dates between modules or to APIs, we must decide whether to send the canonical UTC instant, an offset-aware ISO string, or a formatted local time. Sending UTC reduces ambiguity; sending localized strings requires precise metadata so receivers can interpret the instant correctly.
Built-in date/time functions and expressions
We’ll survey the kinds of date/time helpers Make provides and how we typically use them. Understanding these categories — parsing, formatting, arithmetic — lets us keep conversions inside scenarios and avoid external dependencies.
Overview of common function categories: parsing, formatting, arithmetic
Parsing functions convert strings into timestamp objects, formatting turns timestamps into human strings, and arithmetic helpers add or subtract time units. There are also utility functions for comparing, extracting components, and timezone-aware conversions in format/parse operations.
Typical function usage examples and pseudo-syntax for parsing and formatting
We often use pseudo-syntax like parseDate(“2025-03-28T09:00:00Z”, “ISO”) to get an internal instant and formatDate(dateObject, “yyyy-MM-dd HH:mm:ss”, “Europe/Berlin”) to render it. Keep in mind every platform’s token set varies, so treat these as conceptual examples for building expressions.
Using format/parse to present times in a target timezone
To present a UTC instant in a target timezone we parse the incoming timestamp and then format it with a timezone parameter, e.g., formatDate(parseDate(input), pattern, “America/New_York”). This produces a zone-aware string without altering the stored instant.
Arithmetic helpers: adding/subtracting days/hours/minutes safely
When we add or subtract intervals, we operate on the canonical instant and then format for display. Using functions like addHours(dateObject, 3) or addDays(dateObject, -1) avoids brittle string manipulation and ensures DST adjustments are handled if we convert afterward to a named timezone.
Converting timezones in Make.com without external services
We’ll show strategies to perform reliable timezone conversions using Make’s built-in functions so we don’t incur extra costs or complexity. Keeping conversions inside the scenario improves performance and determinism.
Strategies to convert timezone using only Make.com functions and settings
Our strategy: keep data in UTC, use parseDate to interpret incoming strings, then formatDate with an IANA timezone name to produce a localized string. For offsets-only inputs, parse with the offset and then format to the target zone. This removes the need for external timezone APIs.
Examples of converting an ISO timestamp from UTC to a zone-aware string
Conceptually, we take “2025-12-06T15:30:00Z”, parse it to an internal instant, and then format it like formatDate(parsed, “yyyy-MM-dd’T’HH:mm:ssXXX”, “Europe/Paris”) to yield “2025-12-06T16:30:00+01:00” or the appropriate DST offset.
Using formatDate/parseDate patterns (conceptual examples)
We use patterns such as yyyy-MM-dd’T’HH:mm:ssXXX for full ISO with offset or yyyy-MM-dd HH:mm for human-readable forms. The parse step consumes the input, and formatDate can output with a chosen timezone name so our string is both readable and unambiguous.
Avoiding extra costs by keeping conversions inside scenario logic
By performing all parsing and formatting with built-in functions inside our scenarios, we avoid external API calls and potential per-call costs. This also keeps latency low and makes our logic portable and auditable within Make.
Handling Daylight Saving Time and edge cases
Daylight Saving Time introduces ambiguity and non-existent local times. We’ll outline how DST shifts can affect executions and what patterns we use to remain reliable during switches.
How DST changes can shift expected execution times
When clocks shift forward or back, a local 09:00 event may map to a different UTC instant, or in some cases be ambiguous or skipped. If we schedule by local time, executions may appear an hour earlier or later relative to UTC unless the scheduler is DST-aware.
Techniques to make schedules resilient to DST transitions
To be resilient, we either schedule using the organization’s named timezone so the platform handles DST transitions, or we schedule in UTC and adjust displayed times for users. Another technique is to compute next-run instants dynamically using timezone-aware formatting and store them as UTC.
Detecting ambiguous or non-existent local times during DST switches
We can detect ambiguity when a formatted conversion yields two possible offsets or when parse operations fail for times that don’t exist (e.g., during spring forward). Adding validation checks and fallbacks — such as shifting to the nearest valid instant — prevents runtime errors.
Testing strategies to validate DST behavior across zones
We should test scenarios by simulating timestamps around DST switches for all relevant zones, verifying schedule triggers, and ensuring downstream logic interprets instants correctly. Unit tests and a staging workspace configured with test timezones help catch edge cases early.
Scheduling scenarios and recurring events accurately
We’ll help choose the right trigger types and configure them so recurring events fire at the intended local time across timezones. Picking the wrong trigger or timezone assumption often causes recurring misfires.
Choosing the right trigger type for timezone-sensitive schedules
For local-time routines (e.g., daily reports at 09:00 local), choose schedule triggers that accept a timezone parameter or compute next-run times with timezone-aware logic. For absolute timing across all regions, pick UTC triggers and communicate expectations clearly.
Configuring schedule triggers to run at consistent local times
When we want a scenario to run at a consistent local time for a region, specify the region’s timezone explicitly in the trigger or compute the UTC instant that corresponds to the local 09:00 and schedule that. Using named timezones ensures DST is handled by the platform.
Handling users in multiple timezones for a single schedule
If a scenario must serve users in multiple zones, we can either create per-region triggers or run a single global job that computes user-specific local times and dispatches personalized actions. The latter centralizes logic but requires careful conversion and testing.
Examples: daily report at 09:00 local time vs global UTC time
For a daily 09:00 local report, schedule per zone or convert the 09:00 local to UTC each day and store the instant. For a global UTC time, schedule the job at a fixed UTC hour and inform users what their local equivalent will be, keeping expectations clear.
Integrating with external systems and APIs
We’ll cover best practices for exchanging timestamps with other systems, deciding when to send UTC versus localized timestamps, and mapping external timezone fields into Make’s internal model.
Best practices when sending timestamps to external services
As a rule, send UTC instants or ISO 8601 strings with explicit offsets, and include timezone metadata if the receiver expects a local time. Document the format and timezone convention in integration specs to prevent misinterpretation.
How to decide whether to send UTC or a localized timestamp
Send UTC when the receiver will perform further processing, comparison, or when the system is global; send localized timestamps with explicit offset when the data is intended for human consumption or for systems that require local time entries like calendars.
Mapping external API timezone fields to Make.com internal formats
When receiving a local time plus a timezone field from an API, parse the local time with the provided timezone to create a canonical UTC instant. Conversely, when an API returns an offset-only time, preserve the offset when parsing to maintain fidelity.
Examples with calendars, CRMs, databases and webhook consumers
For calendars, prefer sending zone-aware ISO strings or using calendar APIs’ timezone parameters so events appear correctly. For CRMs and databases, store UTC in the database and provide localized views. For webhook consumers, include both UTC and localized fields when possible to reduce ambiguity.
Conclusion
We’ll recap the dual-layer model and give concrete next steps so we can apply the best practices in our own Make.com workspaces immediately. The goal is consistent, deterministic time handling without unnecessary external dependencies.
Recap of the dual-layer timezone model (organization vs user) and its consequences
Make uses a dual-layer model: organization timezone sets defaults for schedules and shared views, while user timezone customizes per-session presentation. Internally, timestamps are normalized to a canonical instant. Understanding this keeps automations predictable and makes debugging easier.
Key takeaways: normalize to UTC, convert at boundaries, avoid AI for deterministic conversions
Our core rules are simple: normalize and compute in UTC, convert to local time only at the UI or external boundary, and avoid using AI or ad-hoc services for timezone conversion because they introduce variability and cost. Use built-in functions for deterministic results.
Practical next steps: implement patterns, test across DST, adopt templates for your org
We should standardize templates that normalize to UTC, add timezone-aware formatting patterns, test scenarios across DST transitions, and create onboarding notes so every team member sets correct profile and organization timezones. Build a small test suite to validate behavior in staging.
Where to learn more and resources to bookmark
We recommend collecting internal notes about your organization’s timezone convention, examples of parse/format patterns used in scenarios, and a short DST checklist for deploys. Keep these resources with your automation documentation so the whole team follows the same patterns and troubleshooting steps.
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