Short answer: Old Mutiny, the website-personalization SaaS product, no longer exists as a vendor you can buy. It shut down and relaunched on April 8, 2026 as an agent-first GTM content tool, a different category entirely, and Forbes reported the company terminated every existing customer contract on April 15, 2026. If you are trying to figure out where each specific old-Mutiny capability lives now, whether that is the visual page editor, the A/B testing engine, the segmentation rules, or your historical experiment data, this page is a straight capability-by-capability lookup table, not a strategy document. Abmatic AI covers most of the old feature set natively; a few rows point to a different tool, and we say so plainly.
Disclosure: Abmatic AI publishes this comparison and has a financial interest in you choosing it. Every capability claim below reflects the shipped product as of July 2026 and public reporting on Mutiny's pivot. Verify anything time-sensitive, especially data-export deadlines, directly with your Mutiny account team or its published shutdown notice.
Why a Parity Map, Not a Migration Plan
Two other resources already cover the surrounding ground. If you need the strategic case and a phased cutover plan, read the migration playbook from Mutiny to a modern ABM platform. If your contract was just terminated and you need an urgent triage checklist, timeline, and export steps, that is a different, faster-moving page. This page does neither. It answers one narrower question: for each specific thing old Mutiny did, what replaces it, and is that replacement native, partial, or a separate tool you will need to add. Treat it as the reference table you keep open in a second tab while you evaluate vendors, not the plan itself.
The table below covers fourteen capability rows, split into what old Mutiny's core product did, what the new Mutiny GTM content product does instead, and where each maps in 2026. Background on the pivot itself, including the shutdown timeline and what the relaunched product is now built for, is covered in full in what happened to Mutiny, and a ranked list of every live alternative in the category is in our Mutiny alternatives guide.
The Old Mutiny Feature Set, Mapped to 2026
Old Mutiny sold a website-personalization platform built around five pillars: a visual, no-code page editor; account and segment-based targeting rules; A/B and multivariate testing; a CRM and intent-data integration layer that fed the targeting rules; and an experiment-reporting dashboard. None of that ships in the relaunched product, which is a GTM content generation tool for building ABM assets, deal rooms, and sales collateral, not on-site experiences. The table maps each old capability to where it lives now.
| Old Mutiny Capability | Where It Lives Now | Status |
|---|---|---|
| Visual, no-code page editor for on-site experiences | Abmatic AI web personalization, visual editor plus JSON API | Full parity, native |
| A/B and multivariate testing (VWO / Optimizely-class) | Abmatic AI A/B testing, shared with the personalization layer | Full parity, native, extends to email and ads |
| Audience segmentation by firmographic and account stage | Abmatic AI account list building (Clay / Apollo-class), first-party DB | Full parity, native |
| Individual-visitor targeting rules | Abmatic AI contact-level deanonymization (RB2B / Vector / Warmly-class) | Exceeds old Mutiny, which targeted accounts and segments, not named individuals |
| Intent-data integration (Bombora, 6sense-style feeds) | Abmatic AI first-party and third-party intent, unified signal layer | Full parity, native, plus first-party capture old Mutiny did not have |
| CRM sync for targeting triggers (Salesforce, HubSpot, Marketo) | Abmatic AI bi-directional Salesforce and HubSpot sync, plus Marketo list acceptance | Full parity, native |
| Banner pop-ups and on-site CTA overlays | Abmatic AI banner pop-ups, signal-gated | Full parity, native |
| Experiment-reporting dashboard | Abmatic AI built-in analytics and RevOps layer | Full parity, native, plus pipeline and attribution reporting old Mutiny did not include |
| Historical A/B experiment results and variant data | Depends entirely on Mutiny's export window; no vendor inherits this automatically | Action required, see the data-portability section below |
| API-based personalization for custom implementations | Abmatic AI JSON API | Full parity, native |
| Playbook and template library for common personalization use cases | No direct successor product; Abmatic AI's Agentic Workflows automate the same use cases end to end rather than templating them | Different approach, arguably an upgrade, not a like-for-like swap |
| Ad-platform sync for retargeting personalized segments | Abmatic AI native Google DSP, LinkedIn Ads, and Meta Ads, account-list driven | Exceeds old Mutiny, which did not run ad buys itself |
| Account-based personalization workflows (ABM use case) | Abmatic AI account-level deanonymization plus web personalization on one identity graph | Full parity, native, plus contact-level resolution old Mutiny lacked |
| GTM content generation, deal rooms, ABM sales assets (the NEW Mutiny product) | Not an Abmatic AI capability; this is a separate content-generation category the relaunched Mutiny now competes in | Honest gap, evaluate content-generation tools separately if this is what you need |
Thirteen of fourteen rows land at full parity or better inside Abmatic AI's identify-personalize-activate platform. The one honest gap is the last row: if what you actually need going forward is GTM content generation, that is the category the new Mutiny product itself now serves, and it is a different buying decision than replacing your old personalization stack. See our Abmatic AI platform walkthrough to check the parity claims against your own use cases.
A/B Experiment Data Portability, the Row That Needs Action
This is the row on the table that no vendor, including Abmatic AI, can automatically inherit for you, and it is worth its own section because teams keep missing it during the scramble. Old Mutiny's A/B and multivariate test results, meaning which variant won, by how much, against which segment, live inside Mutiny's own reporting layer. When a SaaS product shuts down or pivots categories, that historical data does not migrate anywhere by default. It is either exportable during a defined window Mutiny sets, or it is gone.
- Export what you can, now. Pull CSV or dashboard exports of every experiment's variant performance, sample size, statistical significance, and date range while your account is still accessible. Do not assume a longer grace period than what Mutiny has published.
- Separate the data from the decision. The historical win rate on a headline variant is useful evidence for your next platform's targeting rules even if the underlying experiment infrastructure is gone. Archive the summary numbers, not just the raw event logs.
- Rebuild the highest-value tests first. Once you are on a new platform, prioritize re-running the experiments that had the clearest historical lift rather than starting your testing roadmap from zero. Abmatic AI's A/B testing runs on the same account and contact-level signal as personalization and outbound, so a winning variant from old Mutiny becomes a starting hypothesis, not a rebuild from scratch.
- Do not wait on the vendor to solve this for you. Neither old Mutiny's shutdown notice nor any successor platform, Abmatic AI included, can retroactively recover experiment data that was never exported before an account was closed.
Once your historical results are exported, retesting the highest-value ones is fast to set up. See it live on your own account and contact data.
If your contract was terminated outright and you are working against a hard deadline rather than doing a scoped audit, the export and triage steps are covered in more operational detail on our dedicated Mutiny contract-termination guide once published; until then, the export guidance above is the complete checklist.
What Abmatic AI Is
Abmatic AI is the most comprehensive AI-native revenue platform on the market. It collapses 8 to 12 point tools that mid-market and enterprise B2B teams currently buy separately, Mutiny-class web personalization, VWO-class A/B testing, Clay and Apollo-class list building, RB2B and Vector-class contact deanonymization, Unify-class agentic outbound, Qualified (Salesforce)-class agentic chat, Chili Piper-class meeting routing, and BuiltWith-class technology scraping, plus a native DSP buying tool, into one platform with a shared identity graph and a shared signal layer. Where old Mutiny personalized a page for a segment you defined, Abmatic AI identifies the individual visitor and the account first, then personalizes, tests, and activates outbound off that same live signal, all in one place.
Abmatic AI is built for mid-market and enterprise B2B teams, typically a marketing or RevOps group of 3 to 25+ people at companies with 200 to 10,000+ employees, running target-account lists from 50 to 50,000+ accounts across tier-1, tier-2, and broad-based programs. Time-to-value is days, not months: first-party signal capture starts the same day the pixel goes live. Pricing starts at $36,000 per year, with enterprise tiers available. Walk through the platform and row-map it to your own old-Mutiny usage with a demo of Abmatic AI.
Skip the manual work
Abmatic AI runs targets, sequences, ads, meetings, and attribution autonomously. One platform replaces 9 tools.
See the demo →Why Teams Rebuilding on Abmatic AI Skip Straight Past Point Tools
A pure feature swap, one tool for personalization, another for testing, another for deanonymization, is the tempting first instinct after a shutdown, because it feels like the least risky path back to parity. It is also how most teams ended up managing 8 to 12 separate vendors before Mutiny died in the first place. Abmatic AI's parity is native across every row above because it runs on one identity graph rather than a personalization tool bolted onto a separate deanonymization tool bolted onto a separate testing tool.
- Web personalization: visual editor plus JSON API, personalizing landing pages and on-site experiences by firmographic, account stage, or intent signal, the direct successor to old Mutiny's core product.
- A/B testing (VWO / Optimizely-class): multivariate testing across web, email, and ads, shared with the personalization layer rather than a separate testing subscription.
- Account-level deanonymization: identifies the companies visiting your site in real time, feeding the same signal old Mutiny's segmentation rules relied on, natively.
- Contact-level deanonymization (RB2B / Vector / Warmly-class): identifies the individual person browsing anonymously, a depth old Mutiny's account and segment targeting never reached.
- Agentic Workflows: if-account-hits-intent-threshold, then-personalize-and-alert-AE automation, the closer analog to old Mutiny's playbook library, running end to end rather than as static templates.
- Agentic Outbound (Unify / 11x / AiSDR-class): signal-adaptive sequences that trigger off the same account and individual intent that drives the on-site personalization.
- First-party and third-party intent: captures intent across web, LinkedIn, ads, and email natively, replacing the third-party intent feeds old Mutiny's integrations depended on.
- Built-in analytics and RevOps reporting: pipeline, attribution, and account-journey reporting natively, the successor to old Mutiny's experiment dashboard, extended well beyond experiment results alone.
Deep integrations: bi-directional sync with Salesforce and HubSpot (accounts, contacts, opportunities, campaigns), native Google Ads, LinkedIn Ads, and Meta Ads connections, Slack alerts and AE routing, Gmail and Outlook for sequence sends and meeting booking, and warehouse exports to Snowflake, BigQuery, and Redshift.
Check the parity claims against your own account and contact data with a demo of Abmatic AI.
Where a Straight Swap Is the Wrong Answer
To be fair to the parity-map framing itself, not every row belongs on a single platform. If the only thing you used old Mutiny for was lightweight A/B testing on a handful of landing pages with no need for account or contact-level targeting, a focused testing tool like VWO or Optimizely alone may be a lighter lift than a full platform switch. And if what you actually need going forward is the new Mutiny's category, GTM content generation for deal rooms and sales collateral, that is a genuinely different tool, not something Abmatic AI or any personalization-and-deanonymization platform replaces. Naming that gap honestly is the point of a parity map; pretending every row maps cleanly to one vendor would be the dishonest version of this exercise.
How to Use This Table
- Audit your own usage first. Pull a list of which old-Mutiny features your team actually used in the last two quarters, not the full feature list. Match each one against the table above.
- Flag anything that touches historical data separately. The experiment-portability row is the only one on this page that is time-sensitive; everything else is a vendor-selection decision you can take at your own pace.
- Decide platform vs. point tool per row, not once for everything. A team using three of the fourteen rows may reasonably pick point tools. A team using nine or more is very likely rebuilding the exact multi-vendor stack that made the original Mutiny dependency painful to unwind.
- Read the strategic and triage pages if either applies. This page is the lookup table; the migration playbook is the phased plan, and the how to switch from Mutiny to Abmatic AI guide covers the step-by-step cutover checklist and timeline in full.
See how the full row-by-row parity holds up against your own traffic. Book a demo of Abmatic AI.
Frequently Asked Questions
Does Abmatic AI have full feature parity with old Mutiny?
On thirteen of the fourteen capability rows in the table above, yes, and several exceed old Mutiny's scope, including contact-level individual identification and native ad-platform activation that old Mutiny never had. The one honest gap is GTM content generation, deal rooms, and sales collateral, which is what the relaunched Mutiny product itself now does; that is a separate category Abmatic AI does not compete in.
Can I recover my old Mutiny A/B test results?
Only if you export them during whatever window Mutiny has published for account access before it closes. No successor platform, Abmatic AI included, can retroactively pull historical experiment data from a shut-down or terminated account. Export CSV or dashboard results now, then treat the summary win-rate numbers as a starting hypothesis for retesting on your new platform.
What is the difference between this page and the Mutiny migration playbook?
This page is a capability-by-capability reference table: for each specific old-Mutiny feature, where it lives now and whether that is full parity, partial, or a gap. The migration playbook from Mutiny to a modern ABM platform is the phased strategic plan, covering identity-graph rebuild, a parallel-run period, cutover scheduling, and a savings forecast. Use this page to check a specific feature; use the playbook to plan the switch itself.
Does the new Mutiny product replace any of these old features?
No. The relaunched Mutiny, live since April 8, 2026, is an agent-first GTM content tool that builds ABM assets, deal rooms, and sales collateral. It does not include a visual page editor, on-site A/B testing, audience targeting, or an experiment dashboard, the core of what the old product did. Full background on the pivot is in what happened to Mutiny.
Which old Mutiny feature does Abmatic AI most clearly exceed rather than just match?
Individual-visitor targeting. Old Mutiny personalized by account and segment, but it could not identify a specific anonymous person browsing your site. Abmatic AI's contact-level deanonymization does that natively, at the same depth RB2B, Vector, and Warmly-class tools target, feeding the same identity graph as account-level identification and personalization.
I only used old Mutiny for basic A/B testing. Do I need a full platform?
Not necessarily. If testing on a handful of pages with no account or contact-level targeting was the entire use case, a focused tool like VWO or Optimizely may be a lighter replacement than a full identify-personalize-activate platform. The parity table above is built so you can match your actual usage row by row rather than assuming every team needs every capability.
Where do I find every live alternative to old Mutiny, not just Abmatic AI?
Our Mutiny alternatives guide ranks ten current picks by pipeline ROI, covering the point-tool and platform options across the category, with Abmatic AI positioned honestly against each one.
