# Attribution

> Attribution (attributionapp.com) is a multi-touch marketing attribution platform that binds ad spend to individual user journeys across sessions and channels, supports first touch, last touch, linear, time decay, and position-based models across configurable modes, joins ad platform spend to CRM and payment revenue from HubSpot, Salesforce, Stripe, Shopify, and Segment, and exports full visit-level raw data to Snowflake, BigQuery, Redshift, S3, and other warehouses so every reported number can be traced back to the touchpoints that produced it.

- Category: GTM Analytics (https://saastracker.org/categories/gtm-analytics)
- Website: https://www.attributionapp.com
- Starting price: $199 per month (Shopify plan), $399 per month (Pro)
- Free plan: None; the trial is the evaluation path.
- Free trial: 14 days
- Founded: 2014, HQ: San Francisco, California, United States, Ownership: Privately held and independent
- Profile last reviewed: 2026-08-22
- Canonical profile: https://saastracker.org/products/attributionapp

## Overview

The problem Attribution is built around is stated bluntly on its own homepage: when Meta's API says a campaign generated eight dollars in revenue, it claims credit for every conversion that touched that campaign, even if Google also touched the same user. Every ad platform does this, which is why the sum of platform-reported revenue routinely exceeds actual revenue by a wide margin. Attribution's answer is to stop asking the platforms and instead bind spend to individual user journeys itself, tracking each user across sessions and channels and allocating cost and credit once rather than once per platform.

The design principle that follows from that is auditability. Every metric traces back to the underlying visits, touchpoints, and cost allocations, with no modelling layer between the raw data and the reported number. That is a deliberate contrast with data-driven attribution in GA4 and with the machine-learning attribution most vendors now market, and it is the reason Attribution appeals to people who have to defend a budget reallocation to a finance team rather than merely feel confident about it.

Model support is the deepest in this category at the price. Five models (first touch, last touch, linear, time decay, and position based) each run across four configurable modes, including a mode built for product-led and trial-based businesses where visits after signup should not receive attribution credit. That last detail is a small thing that tells you who built the product: it is the kind of configuration only someone who has actually tried to attribute a PLG funnel would think to add.

Commercially it sits in an unusual spot. The Pro plan is $399 a month for up to 10,000 monthly tracked visitors with overages at $10 per additional 1,000, a Shopify plan is $199, and a Custom tier adds account-based attribution, offline and broadcast tracking, and warehouse tooling. That is far more than a web analytics tool and far less than the quote-only B2B attribution platforms, and unlike most of them there is a published price and a 14-day trial. Managed onboarding exists at $2,500 to $5,000 but is optional rather than mandatory, which matters.

## How it works

1. You install Attribution's tracking on your site, or send data through an existing Segment or RudderStack pipeline, which is the fastest path for teams already running a CDP. Attribution then binds each visit to a user, following that user across sessions, devices where identity allows, and channels rather than treating each session as an independent event.

2. Ad platform connectors pull spend and campaign structure from Google, Meta, LinkedIn, TikTok, Pinterest, Reddit, Quora, Microsoft, and others. Because Attribution has both the spend and its own view of the journey, it allocates cost to users rather than accepting each platform's self-reported conversion count, which is what stops the same conversion being counted three times.

3. Revenue comes from the systems that actually hold it: HubSpot, Salesforce, and Pipedrive on the CRM side, Stripe, Recurly, and Zuora for subscriptions, and Shopify or BigCommerce for ecommerce. Joining spend to real revenue rather than to form fills is what turns the output into a CAC and ROAS number instead of a cost-per-lead number.

4. Reporting runs the five models across their configurable modes so you can see how the picture changes between first touch and position based rather than being handed one answer. Every figure drills back to the underlying visits and cost allocations, an MCP server lets Claude and other assistants query the data conversationally, and raw visit-level exports feed Snowflake, BigQuery, Redshift, S3, Azure, or Google Cloud Storage for teams that want to model it themselves.

## Best for

B2B SaaS, subscription, and ecommerce companies spending real money on multiple ad channels who need to reconcile platform-reported ROAS against actual revenue, and who want an auditable model comparison rather than a black-box number they cannot defend in a budget meeting.

## Not the right fit for

- Anyone spending little or nothing on ads; at $399 a month, attribution across a handful of monthly conversions produces expensive anecdotes rather than statistics.
- Teams that want a general analytics dashboard; this is an attribution tool and it will not replace your traffic reporting, your product analytics, or your GA4 property.
- Small sites tempted by the visitor allowance; 10,000 monthly tracked visitors is the Pro plan ceiling and overages run $10 per additional 1,000, so a 100,000-visitor site is a very different conversation.
- Buyers who need EU data residency, SSO, and a completed compliance package on a published plan; those questions land in the Custom tier rather than the self-serve one.
- Businesses with no CRM or payment system to connect; without a revenue source to join to, Attribution degrades into a more expensive way of counting form fills.

## Features

### Attribution modelling

The reason to buy this rather than trust the ad platforms.

- **Five attribution models**: First touch, last touch, linear, time decay, and position based, all available on the Pro plan rather than gated to an enterprise tier, which is more model coverage than GA4 now offers at any price.
- **Four configurable modes per model**: Each model runs across four modes to suit different business shapes, so a subscription business and an ecommerce store are not forced through the same credit logic.
- **Product-led growth mode**: A configuration specifically for trial-based and PLG businesses where visits after signup should not receive attribution credit, which is a distinction most attribution tools ignore entirely.
- **User-level cost binding**: Ad spend is bound to individual users across sessions and channels, so a conversion touched by three platforms is credited once rather than three times, which is the specific arithmetic error Attribution exists to fix.
- **Custom lookback windows**: Attribution windows tuned to your sales cycle rather than fixed at a platform default; custom windows are a Custom-tier feature.
- **Account-based attribution**: Credit rolled up to the account rather than the individual for B2B buying committees, available on the Custom plan.

### Auditability and data integrity

No black box, which is the whole editorial position of the product.

- **Visit-level drill-down**: Every metric traces back to the underlying visits, touchpoints, and cost allocations, so a disputed number can be opened rather than defended on faith.
- **No modelling layer**: The vendor's explicit claim is that there is no black-box modelling between raw data and reported numbers, in deliberate contrast with GA4's data-driven attribution and with machine-learning attribution vendors.
- **Model comparison**: Seeing the same spend under first touch and under position based side by side is how you discover whether your channel mix conclusion is robust or an artefact of the model you happened to pick.
- **Cost reconciliation against platforms**: Platform-reported revenue and Attribution's own allocation sit next to each other, which is the report you take into the meeting where someone insists Meta is working.

### Data sources and connectors

Spend from the ad platforms, revenue from the systems that hold it.

- **Ad platform connectors**: Google, Meta, LinkedIn, TikTok, Pinterest, Reddit, Quora, Microsoft, and additional networks, pulling spend and campaign structure rather than relying on each platform's conversion claims.
- **CRM integrations**: HubSpot, Salesforce, and Pipedrive, so attribution reaches closed pipeline rather than stopping at the form fill; HubSpot and Salesforce are named as primary integrations on the Pro plan.
- **Subscription and payment sources**: Stripe, Recurly, and Zuora, which is how recurring revenue and expansion enter the model instead of only first purchases.
- **Ecommerce platforms**: Shopify and BigCommerce, with a dedicated $199 Shopify plan for stores that do not need the full B2B feature set.
- **CDP and analytics integration**: Bidirectional Segment integration plus RudderStack, Amplitude, and Heap, so teams already running a CDP can route existing event streams in rather than adding another tracker.
- **Offline and broadcast channels**: TV and broadcast tracking and offline channel tracking on the Custom plan, for businesses where a meaningful share of spend never touches a browser.

### Data ownership and export

Full-fidelity raw data out, which is rare at this price.

- **Warehouse exports**: Visit-level raw data delivered to Snowflake, BigQuery, Redshift, AWS S3, Azure Blob Storage, and Google Cloud Storage, so your attribution data is not trapped in the vendor's interface.
- **Full-fidelity export**: Exports are visit-level rather than aggregated summaries, which means an analyst can rebuild or challenge the vendor's model in their own warehouse.
- **Data warehouse tooling**: Additional warehouse tooling on the Custom plan for teams treating Attribution as one source in a larger data stack.
- **MCP server**: A native Model Context Protocol server lets Claude and other MCP-compatible assistants query attribution data in natural language, which is a genuinely useful way to interrogate a model comparison without building a report.
- **AI reports and recommendations**: Agentic analytics that surface performance shifts and suggested reallocations rather than requiring you to go looking for them.

### Plans, limits, and administration

Published pricing in a category that mostly refuses to publish any.

- **Tracked visitor metering**: The Pro plan covers up to 10,000 monthly tracked website visitors, with overages billed at $10 per additional 1,000, so the meter is visitors rather than events or pageviews.
- **Dedicated Shopify plan**: A $199 plan for Shopify stores, which prices ecommerce attribution below the full B2B product.
- **Optional managed onboarding**: Vendor-led implementation at $2,500 to $5,000, offered rather than required, which distinguishes Attribution from platforms that mandate a paid onboarding.
- **Custom seats and support tiers**: Seat counts, visitor limits, and support level are negotiated on the Custom plan rather than fixed.
- **14-day free trial**: A real self-serve trial in a category where most competitors will only show you a demo.

## Use cases

- **Ecommerce brand spending $50,000 a month across Meta and Google**: Meta claims $180,000 in revenue, Google claims $120,000, and Shopify recorded $210,000. Somebody is wrong and the media buyer wants more budget. Outcome: Attribution binds spend to users, credits each conversion once, and joins to actual Shopify revenue, producing a single reconciled ROAS per channel. The model comparison then shows whether the conclusion survives moving from last touch to position based, which is the difference between a defensible reallocation and a guess.
- **B2B SaaS marketer defending budget to a CFO**: The CFO does not accept platform-reported numbers and wants to see how a channel's contribution was calculated before approving next quarter's spend. Outcome: Visit-level drill-down means every figure opens into the touchpoints and cost allocations behind it, and HubSpot or Salesforce revenue joining means the number being defended is closed pipeline rather than MQLs.
- **Product-led SaaS company with a free trial**: Attribution keeps crediting post-signup visits, so the branded search that trial users perform on their way back into the app looks like the best-performing channel. Outcome: The PLG mode excludes post-signup visits from attribution credit, which removes the single most common distortion in trial-based funnels and stops the team from over-investing in branded search.
- **Data team that wants to model attribution themselves**: The analysts do not want a vendor's opinion, they want the underlying visit and cost data in their warehouse. Outcome: Full-fidelity visit-level exports land in Snowflake or BigQuery, and the vendor's own models become one reference point to check the internal model against rather than the only available answer.

## Pricing

Per-plan subscription metered on monthly tracked website visitors, with per-1,000 overages, a cheaper dedicated Shopify plan, and a quote-only Custom tier for account-based, offline, and warehouse requirements.

- **Shopify**: $199 per month. Built for Shopify stores; All five attribution models; Digital ad connectors; Email support; 14-day free trial. The cheapest way into a real multi-model attribution product if you sell on Shopify.
- **Pro**: $399 per month, up to 10,000 monthly tracked visitors. First touch, last touch, linear, time decay, and position based across four modes; HubSpot, Salesforce, and Twilio Segment integrations; All digital ad connectors; Raw data export to Snowflake, BigQuery, Redshift, and cloud storage; MCP server and AI reports. Overages are $10 per additional 1,000 tracked visitors, which is the number to model before signing.
- **Custom**: Custom quoted. Account-based attribution; TV, broadcast, and offline channel tracking; Custom lookback windows; Data warehouse tooling; Custom visitor limits, seats, and support tier; Managed onboarding included.

Add-ons:

- Managed onboarding ($2,500 to $5,000 one-time): Optional on Pro and Shopify, included on Custom.

Billing notes:

- Annual billing takes 16 percent off, so Pro at $399 monthly comes to roughly $335 a month equivalent on a yearly commitment.
- The meter is tracked website visitors, not pageviews or events. A site with 100,000 monthly pageviews will typically have far fewer unique visitors, but a busy consumer site can still blow well past 10,000 and add hundreds of dollars in overages at $10 per 1,000.
- Managed onboarding at $2,500 to $5,000 is optional rather than mandatory, which is a genuine cost advantage over attribution vendors that require a paid implementation before the tool works.
- Account-based attribution, offline and broadcast tracking, and custom lookback windows all live on the quote-only Custom tier, so B2B buyers with buying committees should price that conversation rather than assuming $399 covers them.

Value assessment: Against the quote-only B2B attribution market, $399 with a published price, a 14-day trial, and optional rather than mandatory onboarding is a strong offer, and the five-model, four-mode coverage with visit-level auditability is deeper modelling than most platforms charging several times more. Against a general analytics budget it looks expensive, because it does one job and does not replace anything else you are running. The deciding number is ad spend: at $50,000 a month, $399 is under one percent of media budget for the ability to stop double-counting conversions, which is trivially worth it. At $3,000 a month of spend it is not, and the honest recommendation is to use the ad platforms' own numbers with appropriate scepticism until the spend justifies the tool.

## Strengths

- Five attribution models across four configurable modes, which is deeper model coverage than GA4 offers at any price after it removed most of its models in 2023.
- Visit-level auditability with no black-box modelling layer, which is what makes the output usable in a budget argument rather than merely interesting.
- User-level cost binding across sessions and channels directly addresses the double-counting that makes platform-reported ROAS unusable.
- A dedicated product-led growth mode that excludes post-signup visits from credit, which almost no competitor models correctly.
- Published pricing, a self-serve 14-day trial, and optional rather than mandatory onboarding, in a category where nearly every competitor is demo-gated.
- Full-fidelity visit-level exports to Snowflake, BigQuery, Redshift, S3, Azure, and Google Cloud Storage, so the data is genuinely portable.
- Broad connector coverage across ad platforms, CRMs, subscription billing, ecommerce, and CDPs, including a bidirectional Segment integration.
- A native MCP server, so attribution data can be queried conversationally from Claude rather than through a report builder.

## Limitations

- At $399 a month with a 10,000 tracked visitor ceiling and $10 per 1,000 overages, this is expensive for high-traffic sites and unjustifiable for low ad spend.
- It is a single-purpose tool: no general web analytics, no product analytics, no dashboards for anything other than attribution, so it adds to your stack rather than consolidating it.
- Account-based attribution, offline and broadcast tracking, and custom lookback windows are Custom-tier features, which means B2B buyers with buying committees usually need a quote after all.
- It requires a CRM or payment system to be genuinely useful; without a revenue source to join to, you are paying $399 to count form fills more carefully.
- Tracking users across sessions means cookies and identity, so this is not a no-consent-banner tool and post-ATT mobile attribution is subject to the same platform limits everyone else faces.
- Data residency, SSO, and formal compliance attestations are not published self-serve features, which will slow a European or security-heavy procurement process.
- A small, independent company with no significant disclosed venture funding, so the vendor is stable in the bootstrapped sense rather than large.

## Comparisons

- **Attribution vs Dreamdata**: Dreamdata is the operational B2B attribution platform: account-level journeys, EU processing, audience and conversion sync back to ad platforms, and a genuinely free tier, with paid pricing quote-only. Attribution is the analytical one, with more models, four modes each, and visit-level auditability at a published $399. B2B teams who want to activate audiences pick Dreamdata; teams who want to defend the numbers pick Attribution.
- **Attribution vs HockeyStack**: HockeyStack is the enterprise version of this idea, with every attribution model, lift reporting, AI agents, and no-code dashboards at quote-only pricing reported around $2,200 a month. Attribution costs a fifth of that with a published price and a trial, and trades the analytics workbench for a tighter focus on auditable model comparison. Companies with a RevOps function pick HockeyStack; teams who want the models without the sales cycle pick Attribution.
- **Attribution vs Triple Whale**: Triple Whale is Shopify-native, priced against your GMV, and built for DTC with creative analytics, marketing mix modelling, and its own pixel. Attribution's $199 Shopify plan does the modelling side more rigorously and more cheaply but without the creative cockpit or the ecommerce operating-system ambitions. DTC brands who live in Shopify take Triple Whale; brands who want auditable model comparison take Attribution.
- **Attribution vs Usermaven**: Usermaven bundles website analytics, product analytics, and a lighter multi-touch attribution layer for $199 a month, which is better value if you need all three. Attribution does only attribution and does it far more rigorously, with five models, four modes, and visit-level drill-down. Buy Usermaven to consolidate tools; buy Attribution when the attribution number itself has to survive scrutiny.
- **Attribution vs Supermetrics**: Supermetrics moves marketing data from ad platforms into Sheets, Looker Studio, or a warehouse from €49 a month, and it does not attribute anything: it faithfully reproduces each platform's self-reported numbers, double-counting included. Attribution is what you buy when you have concluded those numbers are wrong. Teams often run both, with Supermetrics handling reporting plumbing and Attribution handling the credit question.

## Implementation

- Setup time: A few days to a couple of weeks. The tracking install is quick, especially through an existing Segment or RudderStack pipeline, but connecting ad accounts, CRM, and payment systems and then agreeing which model and mode reflect your business is genuine configuration work.
- Learning curve: Moderate to high, and unavoidably so. The tool asks you to make real modelling decisions about credit allocation and lookback windows, and a team that does not understand the difference between first touch and position based will misread the output regardless of how good the interface is.
- Onboarding: Self-serve on Shopify and Pro with a 14-day trial. Managed onboarding is offered at $2,500 to $5,000 and included on Custom, but it is genuinely optional rather than a required implementation fee.
- Migration: Attribution is additive rather than a replacement: it sits alongside GA4, your web analytics, and your ad platforms rather than displacing them. Historical data does not migrate in, so the model needs a few months of collected journeys before its conclusions carry weight, which is worth knowing before you evaluate it against a single month of data. Raw visit-level exports mean leaving later does not strand your history.

## Platform, API & security

- Platforms: Web app, JavaScript tracking, Segment and RudderStack pipelines, MCP server
- API: Data access through full-fidelity visit-level exports to Snowflake, BigQuery, Redshift, AWS S3, Azure Blob Storage, and Google Cloud Storage, plus a native MCP server for conversational querying from Claude and other assistants.
- Compliance: GDPR data processing, CCPA
- Data residency: Not published as a self-serve regional option; raise residency requirements in the Custom tier conversation.
- SSO: Not published on the self-serve plans; negotiated on Custom.
- Security notes: Attribution tracks users across sessions and channels, which means identity and cookies are part of the architecture, so it is not a no-personal-data tool and a consent banner is required in Europe. The compensating strength is that raw data is exportable in full fidelity, so customers can hold their own copy rather than depending on the vendor's retention.

## Support

- Channels: Email support on Pro and Shopify, Custom support tier on the Custom plan, Optional managed onboarding
- Documentation: Public documentation covering tracking installation, the model and mode configurations, connector setup, and warehouse exports, alongside a blog focused on attribution methodology.
- Community: No large user forum; the company's presence is through its own content and the growth and analytics consulting world its founder comes from.

## Company

- Founded: 2014
- Founders: Ryan Koonce (founder and chief executive)
- Headquarters: San Francisco, California, United States
- Ownership: Privately held and independent
- Employees: Small; an independent team
- Funding: No significant disclosed venture funding; the company operates independently on subscription revenue.

Timeline:

- 2014: Attribution is incorporated in San Francisco to build multi-touch attribution that binds ad spend to individual user journeys rather than trusting platform-reported conversions.
- 2016: Ryan Koonce takes the company forward as founder and chief executive, positioning it around auditable attribution for growth teams.
- 2020: Connector coverage broadens across ad platforms, CRMs, subscription billing, and ecommerce, with a bidirectional Segment integration for teams already running a CDP.
- 2024: Full-fidelity visit-level warehouse exports to Snowflake, BigQuery, Redshift, and cloud storage make the raw data portable rather than vendor-locked.
- 2026: A native MCP server and agentic AI reporting ship, letting Claude and other assistants query attribution data conversationally; the customer list is cited at more than 1,000 companies including Calendly, Replit, and Stanford University.

## Integrations

Google Ads, Meta, LinkedIn, TikTok, Pinterest, Reddit, Quora, and Microsoft Advertising, HubSpot, Salesforce, and Pipedrive, Stripe, Recurly, and Zuora, Shopify and BigCommerce, Twilio Segment (bidirectional) and RudderStack, Amplitude and Heap, Snowflake, BigQuery, Redshift, AWS S3, Azure Blob Storage, and Google Cloud Storage, MCP server for Claude and other AI assistants

## FAQ

### What is Attribution (attributionapp.com)?

Attribution is a multi-touch marketing attribution platform that binds ad spend to individual user journeys across sessions and channels, then joins that to real revenue from your CRM, payment system, or ecommerce platform. It supports first touch, last touch, linear, time decay, and position-based models across four configurable modes each, and every reported number drills back to the underlying visits and cost allocations.

### How much does Attribution cost?

The Pro plan is $399 a month for up to 10,000 monthly tracked website visitors, with overages at $10 per additional 1,000. There is a dedicated Shopify plan at $199 a month, and a Custom tier for account-based attribution, offline and broadcast tracking, and warehouse tooling. Annual billing takes 16 percent off and there is a 14-day free trial. Managed onboarding is available at $2,500 to $5,000 but is optional.

### Do I need a cookie consent banner with Attribution?

Yes, in the EU and UK. Attribution's entire method depends on recognising the same user across sessions and channels, which requires identity and cookies, so it processes personal data and falls squarely inside GDPR and ePrivacy consent requirements. This is the opposite trade from Plausible or Pirsch: you accept the banner because cross-session identity is exactly what you are paying for.

### Which attribution models does it support?

Five models, all on the Pro plan: first touch, last touch, linear, time decay, and position based. Each runs across four configurable modes, including one built for product-led and trial-based businesses where visits after signup should not receive credit. That is more model coverage than GA4 offers, since Google removed first click, linear, time decay, and position based from its reporting models in 2023.

### How honest is Attribution about post-ATT and privacy limits?

The product's positioning is unusually candid about the arithmetic problem it solves, which is platforms each claiming full credit for shared conversions. It is subject to the same structural limits everyone faces after Apple's App Tracking Transparency and the decline of third-party cookies: cross-app and cross-device journeys are harder to stitch than they were, and no vendor has fully solved that. What Attribution offers instead of a modelled guess is a visible audit trail, so you can see exactly which visits produced a number and judge its reliability yourself.

### Does it work for B2B with buying committees?

Partly on Pro and properly on Custom. HubSpot and Salesforce integration on Pro joins attribution to closed pipeline, but account-based attribution, which rolls credit up to the account rather than the individual, is a Custom-tier feature. If multiple people from the same company touch your site before a deal closes, price the Custom conversation rather than assuming $399 covers you.

### Can I get the raw data out?

Yes, and this is one of Attribution's stronger points. Full-fidelity visit-level data exports to Snowflake, BigQuery, Redshift, AWS S3, Azure Blob Storage, and Google Cloud Storage, so an analyst can rebuild or challenge the vendor's model in your own warehouse. There is also a native MCP server so Claude and other assistants can query the data conversationally.

### What does it cost at 100,000 monthly pageviews or $50,000 monthly ad spend?

The meter is tracked visitors, not pageviews, so a 100,000-pageview site might sit anywhere from comfortably inside the 10,000 visitor allowance to several thousand dollars of overages depending on pages per session. At $50,000 a month of ad spend, the $399 base is under one percent of media budget, which is the level at which the tool clearly pays for itself if it stops you misallocating even a small fraction of that spend.

### How is this different from Google Analytics attribution?

GA4 gives you data-driven attribution, which is a modelled allocation you cannot inspect, plus last click, and it removed its other models in 2023. Attribution gives you five models with four modes each and shows the visits and cost allocations behind every figure. GA4 is free and connects to Google Ads; Attribution costs $399 and is defensible in a budget meeting. Most customers run both.

### Who is behind Attribution and is it a stable supplier?

It is a privately held, independent company based in San Francisco, incorporated in 2014 and led by founder and chief executive Ryan Koonce, with no significant disclosed venture funding. It cites more than 1,000 customers including Calendly, Replit, and Stanford University. That means no investor-driven pivot risk and a small team, so expect email support rather than a staffed account organisation below the Custom tier.

## Editorial verdict

Attribution is the most intellectually honest product in this category. It states the arithmetic problem plainly, which is that every ad platform claims full credit for shared conversions, and it fixes it by binding spend to users itself and showing you the visits behind every number. Five models across four modes, a product-led growth configuration almost nobody else models, full-fidelity warehouse exports, and an MCP server for conversational querying make it deeper on modelling than tools costing several times more, and the published $399 price with a real trial is unusual in a market that mostly refuses to quote. The limits are equally clear: it does one job and will not replace your analytics stack, the 10,000 visitor ceiling makes high-traffic sites expensive, account-based attribution needs a Custom quote, and cross-session identity means the consent banner stays. If you spend $50,000 a month on ads and cannot reconcile what the platforms tell you, this is worth well over its price. If you spend a tenth of that, it is not.

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Source: SaaSTracker (https://saastracker.org), an independent editorial project. This profile is compiled from public information, carries no peer reviews or paid placement, and was last reviewed 2026-08-22. Awards are judged on published criteria: https://saastracker.org/methodology