Commissioned Research
Top 10 Best Traffic Counting Software of 2026

GITNUXSOFTWARE ADVICE

Business Finance

Top 10 Best Traffic Counting Software of 2026

Editorial roundup comparing traffic counting software tools like INRIX, Placer.ai, and Miovision for planning teams and traffic analysts.

20 min readUpdated Editorially scoped research
How we ranked these tools
01Editorial Scope

Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.

02Source Research

AI search agents find sources, extract figures with provenance, and aggregate written reviews. They also transcribe video reviews and podcasts.

Read our full methodology →

Framework: Features 40% · Ease 30% · Value 30%

Gitnux may earn a commission through links on this page — this does not influence rankings. Editorial policy

Traffic counting software underpins planning and enforcement by converting sensor or camera inputs into counts, turning movements, and mobility metrics for operations teams. This comparison helps evaluators weigh the decision tradeoff between turnkey roadway analytics and configurable data models that support API integration, automation, and deployment controls for multi-site counting.

INRIX is the best pick for GIS-first agencies doing recurring operational reporting because its roadway-referenced context keeps counts and speeds consistent across repeated segment and intersection outputs, while Countwise is a strong alternative for SMB survey teams since its validation-heavy intersection workflows help flag inconsistent entries before dependable exports.

Editor’s top 3 picks

Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.

Editor pick
1

INRIX

Roadway-segment and intersection context that keeps counts and speed aligned across repeated reporting cycles.

Best for: Fits when GIS-first agencies need consistent traffic volume and speed outputs for recurring operational reporting.

2

Placer.ai

Editor pick

Geofence-based traffic estimates from mobile location signals mapped to road-adjacent count locations.

Best for: Fits when teams need recurring traffic estimates for many geographies without installing roadway sensors.

3

Miovision

Editor pick

Validated intersection count workflows that convert raw detections into reviewable turning movement count outputs.

Best for: Fits when operations teams need repeatable intersection counts with validated traffic flow data exports.

Comparison Table

1
INRIXBest overall
enterprise
9.2/10
Overall
2
enterprise
8.9/10
Overall
3
enterprise
8.6/10
Overall
4
enterprise
8.4/10
Overall
5
8.2/10
Overall
6
7.8/10
Overall
7
7.5/10
Overall
8
7.0/10
Overall
9
vertical specialist
6.8/10
Overall
10
vertical specialist
6.7/10
Overall
#1

INRIX

enterprise

Mobility data software provides traffic volumes, speeds, travel times, and roadway performance measures.

9.2/10
Overall
Features9.5/10
Ease of Use9.0/10
Value9.0/10
Standout feature

Roadway-segment and intersection context that keeps counts and speed aligned across repeated reporting cycles.

INRIX is built around traffic flow data products that combine vehicle count and speed measurement with roadway-referenced delivery, so teams can keep dashboards aligned to the same segments and intersections over time. The workflow supports time-of-day aggregation and peak-hour analysis outputs that can feed annual average daily traffic style reporting and ongoing count validation.

A key tradeoff is that INRIX is strongest when the use case accepts its established roadway coverage and data products rather than building custom count geometries from raw sensor feeds. INRIX fits situations where multiple stakeholders need consistent traffic count outputs for recurring operational decisions, especially when GIS alignment reduces manual reconciliation work.

Pros
  • +Roadway-referenced outputs support consistent segment and intersection reporting
  • +Time-of-day aggregation supports peak-hour analysis without manual reshaping
  • +Count and speed outputs align for cross-checking traffic flow trends
  • +GIS integration reduces reconciliation work across count locations
Cons
  • –Custom count geometry creation from sensor feeds is limited
  • –Integration depth can require technical ownership for automation and governance
  • –Some workflows depend on accepting INRIX data product coverage
  • –Rapid experimentation may be slower than tools built for survey-only counts
Use scenarios
  • City transportation planning teams

    Peak-hour and time-of-day reporting

    Faster reporting cycles

  • Mobility analytics groups

    Cross-checking count and speed

    Lower data inconsistency

Show 2 more scenarios
  • Regional traffic operations

    Operational monitoring by count location

    Stable monitoring baselines

    Maintain consistent traffic count locations for dashboarding and change tracking.

  • GIS administrators

    Roadway mapping alignment

    Less reconciliation work

    Place outputs into GIS to reduce manual linkages between surveys and assets.

Best for: Fits when GIS-first agencies need consistent traffic volume and speed outputs for recurring operational reporting.

#2

Placer.ai

enterprise

Location analytics platform providing foot traffic and visitation counting for retail and commercial sites.

8.9/10
Overall
Features8.9/10
Ease of Use8.9/10
Value8.9/10
Standout feature

Geofence-based traffic estimates from mobile location signals mapped to road-adjacent count locations.

Placer.ai produces traffic volume measurement from mobile location signals and aggregates it onto count locations for retail, events, and venues. It supports roadway segment and intersection count use cases by mapping observed movement patterns to road-adjacent geofences and time windows.

The workflow centers on configuration of geographies and baselines, followed by time-of-day aggregation and export for analysis. API and automation features are geared toward recurring reporting and data validation across locations and periods.

Pros
  • +Mobile-signal coverage enables counting without site-based detectors
  • +API supports automated refresh across many count locations
  • +Time-of-day aggregation supports peak-hour analysis workflows
  • +Exports support downstream GIS and BI pipelines
Cons
  • –Road mapping accuracy depends on geofence configuration discipline
  • –Vehicle classification and speed measurement coverage is indirect
  • –Audit-level data lineage across transformations can require extra work
  • –Intersection turning movement count is not a direct native output
Use scenarios
  • Transportation and GIS planning teams

    Estimate roadway traffic time series

    Adds historical traffic context

  • Mall owners and leasing teams

    Assess catchment visitation and footfall

    Evidence for leasing decisions

Show 2 more scenarios
  • Retail portfolio analytics teams

    Benchmark visit trends across stores

    Consistent cross-location comparisons

    Teams compare performance changes across locations using standardized multi-site time aggregation.

  • Out-of-home media planning teams

    Plan proximity audiences and benchmarks

    Location-aware campaign KPI analysis

    Planners use visitation benchmarks and location footprints to pace and evaluate campaigns.

Best for: Fits when teams need recurring traffic estimates for many geographies without installing roadway sensors.

#3

Miovision

enterprise

Traffic data software supports intersection counts, turning movements, signal analysis, and transportation planning.

8.6/10
Overall
Features8.6/10
Ease of Use8.6/10
Value8.6/10
Standout feature

Validated intersection count workflows that convert raw detections into reviewable turning movement count outputs.

Miovision supports end-to-end traffic counting workflows that combine field data capture, validation, and distribution into traffic flow outputs for operational teams. The tool handles intersection count workflows that include vehicle counts and turning movement counts, which helps teams analyze demand beyond total volume. Time-of-day aggregation outputs support peak-hour and period comparisons for roadway segment and intersection reporting.

A tradeoff is that the intersection-focused workflow can require more setup effort than simpler segment-only counting tools. Miovision fits best when agencies need consistent counting data across multiple sites and when turning movement detail and time-of-day summaries are required for traffic studies and operational review cycles.

Pros
  • +Intersection count workflow supports turning movement capture and review
  • +Count data exports support integration into external analysis pipelines
  • +Configuration for count duration and time-of-day aggregation is straightforward
  • +Validation workflows reduce errors before traffic count survey deliverables
Cons
  • –Automation depth depends on how sensors and recorders are deployed
  • –Modeling complex count plans across many count locations takes planning
  • –Custom reporting requires more setup than basic hourly volume profiles
  • –Governance controls can feel limited for multi-team administration
Use scenarios
  • Traffic engineering analysts

    Peak-hour turning movement analysis

    Clear peak period insights

  • City transportation operations

    Road segment and intersection reporting

    On-schedule traffic reporting

Show 2 more scenarios
  • Intersection study project managers

    Vehicle counts plus turning movements

    More complete demand data

    Run integrated intersection workflows that combine vehicle totals with turning movement outputs.

  • Data quality and validation leads

    Consistent count validation

    Higher data reliability

    Apply built-in validation steps to reduce inconsistencies between captured and distributed traffic data.

Best for: Fits when operations teams need repeatable intersection counts with validated traffic flow data exports.

#4

Rekor

enterprise

Roadway intelligence software uses computer vision to classify vehicles and measure traffic activity.

8.4/10
Overall
Features8.4/10
Ease of Use8.5/10
Value8.3/10
Standout feature

Automated count generation from video scenes mapped to specific roadway segment or intersection count locations.

Rekor is a traffic counting software solution built around video-based detection and automated count generation for roadway corridors and intersection count locations. It supports outputs that can be used for time-of-day aggregation and count duration reporting, which helps when programs need predictable hourly volume profiles. The integration and automation surface is most useful when multiple locations must follow similar processing logic and exports feed GIS and traffic analysis workflows.

Pros
  • +Video-driven counting that produces consistent count outputs by count location
  • +Repeatable processing steps reduce variability across similarly configured sites
  • +Exports support downstream traffic flow data workflows and reporting
  • +Detection configuration can be tuned for intersection and roadway segment use
Cons
  • –Non-video sensor sources may require extra bridging work
  • –Setup tuning is sensitive to camera placement and operating conditions
  • –Advanced governance controls are limited compared with enterprise data platforms
Use scenarios
  • Traffic engineering teams

    Hourly volume reporting for intersections

    More consistent peak-hour estimates

  • Transportation analytics teams

    Roadway segment count program

    Faster multi-site reporting

Show 1 more scenario
  • GIS and planning analysts

    Seasonal comparisons by export data

    Quicker seasonal trend reviews

    Exports count data for validation steps and annual comparison workflows.

Best for: Fits when agencies need automated video-based vehicle counts feeding time-of-day reporting.

#5

StreetLight Data

enterprise

Mobility analytics software estimates vehicle, bicycle, and pedestrian volumes across road networks.

8.2/10
Overall
Features8.2/10
Ease of Use8.2/10
Value8.2/10
Standout feature

API-backed workflow for defining study geometries and running repeatable traffic count and speed outputs at scale.

StreetLight Data provides traffic flow data products built from aggregated mobility signals, which makes it distinct from systems that rely on fixed roadway sensors. The core workflow centers on defining roadway segment or intersection study areas, generating time-of-day traffic count and speed measures, and validating outputs with quality controls.

Pros
  • +Mobility-signal derived traffic flow outputs for roadway segments and intersections
  • +Repeatable results via an automation-first workflow with API access
  • +Quality controls and validation steps for count and speed measures
  • +Export options for feeding GIS and analytics pipelines
Cons
  • –Not a physical sensor management system for inductive loops or radar detectors
  • –Turn-by-turn turning movement detail is limited versus intersection-focused TMC workflows
  • –Roadway geometry setup can require iteration to match count locations
  • –Governance needs rely on customer process for access control and change review
Use scenarios
  • Transportation planning consultants

    Estimate volumes across large roadway networks

    Historical volume estimates for studies

  • Road safety analysts

    Prioritize safety reviews using mobility evidence

    GIS-ready evidence for prioritization

Show 2 more scenarios
  • Corridor operations teams

    Compare speed and volume trends over time

    Consistent corridor performance views

    Run repeatable count surveys across recurring windows to monitor corridor performance and movement patterns.

  • Retail real estate strategists

    Analyze movement trends around store zones

    Store-network comparisons for planning

    Use exported mobility counts to compare foot-traffic patterns across stores and catchment areas.

Best for: Fits when agencies or consultancies need fast traffic flow data coverage without installing sensor hardware.

#6

Countwise

SMB

People and vehicle traffic counting software using overhead thermal and video sensors.

7.8/10
Overall
Features7.8/10
Ease of Use7.8/10
Value7.8/10
Standout feature

Count session validation that highlights inconsistencies before exporting roadway segment and turning movement outputs.

Countwise targets traffic count survey workflows that need repeatable data collection across roadway segments and intersections. It focuses on field capture to produce vehicle count and time-of-day aggregation outputs, with validation to flag inconsistencies during review.

Pros
  • +Field workflow built around intersection and count location setup
  • +Validation checks help catch missing or inconsistent count entries
  • +Time-of-day aggregation supports peak-hour analysis prep
  • +Exports stay aligned to typical traffic flow data analysis pipelines
Cons
  • –Vehicle classification coverage can be limited depending on sensor or capture mode
  • –Turning movement count configuration requires careful mapping discipline
  • –Audit trails and governance controls are not as granular as enterprise RBAC needs
  • –Automations and API surface are thin for fully custom aggregation logic
Use scenarios
  • Municipal traffic engineering teams

    Run repeatable intersection turning counts

    More consistent counts

  • Transportation planning consultants

    Produce segment counts for studies

    Faster study deliverables

Show 2 more scenarios
  • Roadway survey managers

    Collect pedestrian and bicycle tallies

    Cleaner field verification

    Count location configuration ties non-vehicle tallies to defined survey points and review checks.

  • Data analysts for traffic models

    Export structured flow datasets

    Less cleanup work

    Exported traffic flow formats feed downstream analysis pipelines without manual reformatting.

Best for: Fits when traffic count survey teams need repeatable intersection workflows and dependable exports for analysis.

#7

Voxel51 FiftyOne

API-first

Open-source computer vision toolkit supporting custom object and vehicle counting model evaluation.

7.5/10
Overall
Features7.5/10
Ease of Use7.4/10
Value7.6/10
Standout feature

View-based dataset filtering and evaluation ties detection results back to specific frames and metadata for count validation.

Voxel51 FiftyOne ingests and labels vehicle and road-scene data, then turns it into analytics-ready datasets for counting workflows. The core capability centers on multimodal dataset management, view-based filtering, and evaluation tooling that connects detection outputs to vehicle count and traffic flow data products.

Pros
  • +Python API supports custom ingestion and transform pipelines
  • +View and filter workflow accelerates iterative count QA on subsets
  • +Dataset-centric operations keep frames, detections, and metadata aligned
  • +Built-in evaluation tooling supports validation of detection outputs
Cons
  • –Does not provide a native hardware counting stack like loop or radar integrations
  • –Traffic counting outputs require custom mapping from detections to counts
  • –Large video datasets can stress local storage and indexing throughput
  • –Operational governance like RBAC and audit logs is not a primary focus
Use scenarios
  • Traffic analytics engineers

    Convert detections into vehicle count reports

    Repeatable counting metrics across sites

  • Computer vision QA teams

    Audit detection errors affecting counts

    Fewer counting discrepancies

Show 2 more scenarios
  • Road safety research groups

    Evaluate models on traffic scenes

    More reliable traffic behavior studies

    Evaluation tooling links model outputs to counting targets for consistent traffic flow comparisons.

  • Systems integrators

    Automate ingestion from sensors and videos

    Faster integration to analytics

    A Python-first API ingests multimodal data and transforms it into analytics-ready datasets for counting pipelines.

Best for: Fits when traffic counting depends on video detection results that need dataset QA and automated reporting.

#8

Axis Communications Camera Station

enterprise

Video management software with integrated people and vehicle counting analytics for Axis network cameras.

7.0/10
Overall
Features7.0/10
Ease of Use7.0/10
Value7.0/10
Standout feature

Traffic-focused video workflows built around Axis camera and recorder control for repeatable count collection.

Axis Communications Camera Station pairs video management features with traffic use through its support for Axis video devices and analytics-oriented workflows. It enables roadway scene setup that turns camera views into vehicle count outputs for operational traffic monitoring and reporting.

Pros
  • +Works directly with Axis camera ecosystems for unified camera and recording control
  • +Video scene configuration supports repeatable vehicle count collection per roadway segment
  • +Reporting outputs fit CSV handoff workflows for standard traffic count survey processing
  • +Centralized management reduces operational overhead for multi-camera intersections
Cons
  • –Traffic detection and classification quality depends heavily on camera placement and lighting
  • –Extensibility is limited compared with platforms that offer direct API access to counts
  • –Setup time rises when tuning detection across multiple intersections and turning movements
  • –Audit and governance controls for count data are less granular than enterprise workflow systems
Use scenarios
  • Traffic operations analyst team

    Configure roadway scenes for vehicle counts

    Consistent traffic count outputs

  • Regional security administrators

    Manage traffic monitoring across sites

    Centralized multi-site oversight

Show 2 more scenarios
  • Physical security IT managers

    Onboard ONVIF cameras with Axis

    Shared monitoring workflow

    Teams add compatible third-party cameras through ONVIF to unify live monitoring and recording workflows.

  • Compliance and investigation teams

    Share traffic clips for reviews

    Portable evidence for review

    Teams export selected clips to document incidents and support stakeholder handoff.

Best for: Fits when teams already standardized on Axis cameras and need configuration-based vehicle count reporting.

#9

Eco-Counter

vertical specialist

Counting systems and software measure pedestrian, bicycle, and vehicle traffic at outdoor sites.

6.8/10
Overall
Features6.8/10
Ease of Use6.8/10
Value6.8/10
Standout feature

Session-based count management that ties device data to count location and duration settings for controlled surveys.

Eco-Counter is traffic counting software focused on field devices and count sessions tied to specific count locations and time windows. It handles vehicle count workflows with configuration for data validation and repeatable setup across surveys.

Pros
  • +Count sessions map cleanly to count locations and predefined durations
  • +Configuration supports repeatable surveys across multiple field deployments
  • +Export outputs fit common downstream analysis workflows
  • +Validation tooling reduces obvious collection errors during review
Cons
  • –Automation depth is limited for custom analytics pipelines
  • –Extensibility depends on how device integrations are packaged
  • –GIS workflows require consistent coordinate hygiene before import
  • –Admin governance for multi-team sharing is not as granular as enterprise needs
Use scenarios
  • Municipal traffic engineers

    Plan site counts across time windows

    Cleaner datasets for planning models

  • Consulting survey teams

    Run recurring surveys with consistent setups

    Faster survey turnaround

Show 2 more scenarios
  • GIS analysts and planners

    Export traffic flows for spatial analysis

    Quicker mapping and reporting

    Produces exports that support spreadsheet review and GIS-oriented workflows tied to count locations.

  • Road safety data managers

    Validate vehicle counts before sharing

    More reliable traffic statistics

    Applies data validation steps to reduce errors from field collection and organize outputs for review.

Best for: Fits when roadway teams need managed count sessions from device collection to validated exports.

#10

GoodVision Video Insights

vertical specialist

AI video analytics software counts vehicles, pedestrians, cyclists, and traffic movements from camera footage.

6.7/10
Overall
Features6.7/10
Ease of Use6.7/10
Value6.7/10
Standout feature

Detection-zone configuration for intersection-style counting from video scenes, with scheduled interval exports for traffic analysis.

GoodVision Video Insights is built around video traffic detection workflows that map detection regions to count outputs. Configurations cover vehicle presence over time, per-interval volume profiles, and structured results intended for downstream traffic analysis. Automation is centered on repeating the same camera setup across scheduled count windows to reduce manual rework.

Pros
  • +Video detection zones map directly to roadway and intersection counting
  • +Repeatable count windows support recurring traffic count surveys
  • +Time-of-day volume outputs fit peak-hour analysis workflows
  • +Exports integrate with GIS and reporting pipelines
Cons
  • –Scene illumination and camera angle can require frequent zone tuning
  • –Accuracy validation workflows take effort when scenes change
  • –Advanced classification depth can lag specialized axle or LPR systems
  • –Multi-site governance needs careful configuration standards
Use scenarios
  • Transportation planners

    Peak-hour analysis from fixed cameras

    Faster peak-hour reporting

  • Traffic survey coordinators

    Recurring count duration studies

    Consistent survey timelines

Show 2 more scenarios
  • GIS and reporting teams

    Roadway segment aggregation exports

    Reduced manual data wrangling

    Outputs structured counts that can be merged into GIS layers and time-of-day reporting formats.

  • Operations analysts

    Traffic flow data validation cycles

    Lower data rework

    Supports repeatable output generation that teams can review and adjust when video conditions drift.

Best for: Fits when traffic teams need repeatable video counts for fixed camera locations and interval reporting.

Conclusion

After evaluating 10 traffic counting software, INRIX stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.

Our Top Pick
INRIX

Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.

Frequently Asked Questions About Traffic Counting Software

Which traffic counting software is best for video-based intersection counts?
GoodVision Video Insights supports configurable detection zones, scheduled runs, and interval exports for repeated intersection counts. Rekor also processes video streams into count outputs, but its workflow requires attention to detection recalibration across new sites.
How do API and automation capabilities differ across traffic counting tools?
StreetLight Data provides programmatic access for defining study geometries, scheduling updates, and reusing datasets. Placer.ai supports API-based recurring reports, while Voxel51 FiftyOne uses a Python-first API for data ingestion, transformation, filtering, and report generation.
What integrations support GIS and downstream reporting?
INRIX links traffic outputs to roadway context and GIS-based count locations. GoodVision Video Insights, Eco-Counter, Countwise, Miovision, and StreetLight Data provide export workflows for GIS, spreadsheets, or downstream analytics, with the available format depending on the product.
What is the tradeoff between fixed sensors and mobility-signal data?
Eco-Counter manages device-based collection tied to count locations and survey durations, while Axis Communications Camera Station depends on Axis cameras and recorders. Placer.ai and StreetLight Data estimate traffic from aggregated mobility signals, reducing hardware deployment but changing the measurement model.
When should a team use dataset tooling instead of a field-counting platform?
Voxel51 FiftyOne fits workflows that already produce video or sensor-derived detections and require frame-level filtering, labeling, and evaluation. Countwise, Miovision, and Eco-Counter fit direct traffic count surveys with field capture, validation, and location-based session management.
What breaks if detection settings are not recalibrated for new sites?
Video systems can misclassify vehicles or miss movements when camera angles, lane geometry, or lighting change. Rekor identifies recalibration as a key configuration task, while GoodVision Video Insights uses detection-zone configuration to adapt intersection counts to each recorded scene.
Do these tools provide SSO, RBAC, audit logs, or compliance controls?
The listed product capabilities describe data collection, processing, exports, APIs, and configuration, but they do not specify SSO, RBAC, audit logs, or compliance certifications. Teams with identity or governance requirements must assess those controls directly for products such as INRIX, StreetLight Data, and Voxel51 FiftyOne.
How can teams migrate existing traffic count data into a new platform?
Migration starts with mapping location identifiers, timestamps, measurement units, and vehicle categories to the destination data model. Voxel51 FiftyOne supports ingestion and transformation for detection datasets, while Eco-Counter, Countwise, and Miovision focus on producing structured exports that can feed external analysis systems.

Tools reviewed

Primary sources checked during evaluation.

Referenced in the comparison table and product reviews above.

How to Choose the Right Traffic Counting Software

What separates traffic counting software is how each tool turns raw site inputs into dependable counts and how much control you get over configuration, output, and repeatability. In practice, the biggest differences show up in data import and validation, configuration transparency, and export formats.

Import and validation behavior

Why it matters

Import and validation behavior decides whether you trust counts after moving projects between sites or after changing devices. If the tool quietly repairs issues, you may never know what changed in your results.

How to check

Ask for a sample import workflow using a provided file, then check whether it flags gaps, time mismatches, or malformed rows instead of silently accepting them. In the output, look for an audit-style summary of what was corrected or rejected.

Counting configuration transparency

Why it matters

Counting configuration transparency matters because small setting changes can shift totals across hours and days. You need to reproduce counts when seasons or site conditions change.

How to check

During a demo, request to set up two similar counts with one variable changed (for example time window or detection method) and compare the resulting totals. Then ask where those settings are stored and how you can review the exact configuration later.

Time granularity output options

Why it matters

Time granularity output options determine whether the software matches how your team consumes results, from hourly views to daily summaries. If the tool over-aggregates early, it can limit later QA and reporting.

How to check

Export the same count for at least two time views and confirm the timestamps and rollups match what the interface shows. Ask whether you can re-export the same site data with a different time aggregation without reprocessing everything manually.

Quality review and exception handling

Why it matters

Quality review and exception handling affects how quickly you locate bad periods and how consistently you exclude them. This is where confidence is won or lost for long-running counts.

How to check

Request a workflow that marks or filters problematic intervals, then verify what changes in the exports. Look for a way to review exceptions by date/time and see the before/after impact on totals.

Export formats and field mapping

Why it matters

Export formats and field mapping matter when you need traffic counting software to fit into an existing reporting pipeline. Missing fields or inconsistent naming forces manual cleanup and increases error risk.

How to check

Export results from a demo project and inspect the column names, timestamp fields, and unit conventions. Ask if the mapping can be customized and whether exports stay consistent after edits to configuration.

Red flags

  • Validation accepts problematic imports without a clear change log.
  • Configuration can’t be reviewed later, so counts can’t be reproduced.
  • Exports hide or remap time fields in a way that doesn’t match the screen.

Fit by situation

  • If you regularly move count projects between sites, prioritize import and validation behavior.
  • If your team needs to reproduce totals after changing site settings, prioritize counting configuration transparency.
  • If your reporting depends on hourly-to-daily rollups, prioritize time granularity output options.
Commissioned Research

Funding and competing interests

This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.

They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.

Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →

Keep exploring

FOR SOFTWARE VENDORS

Not on this list? Let’s fix that.

Our best-of pages are how many teams discover and compare tools in this space. If you think your product belongs in this lineup, we’d like to hear from you—we’ll walk you through fit and what an editorial entry looks like.

Apply for a Listing

WHAT THIS INCLUDES

  • Where buyers compare

    Readers come to these pages to shortlist software—your product shows up in that moment, not in a random sidebar.

  • Editorial write-up

    We describe your product in our own words and check the facts before anything goes live.

  • On-page brand presence

    You appear in the roundup the same way as other tools we cover: name, positioning, and a clear next step for readers who want to learn more.

  • Kept up to date

    We refresh lists on a regular rhythm so the category page stays useful as products and pricing change.