Two Private Equity Roll-ups. One Clear Signal for Product & Design Teams.

What’s happening in Jan 2026

Two major private-equity firms are quietly reshaping the UX / experimentation / insights landscape:

• Thoma Bravo → UserTesting (founded 2007, $1.3B val) + UserInterviews (founded 2015, $x00M val)
• Everstone Capital → Wingify (VWO) (founded 2010, ~$250M val) + AB Tasty (founded 2014, est. $400M val)

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Why these mergers happened

1. A/B testing alone is no longer defensible

Experimentation engines are becoming table stakes:

• Analytics platforms embed testing
• CMSs ship personalization
• AI can auto-generate variants cheaply

Standalone CRO tools are getting commoditized.

So both roll-ups are doing the same thing:
→ Expanding upstream and downstream of testing.

2. The real bottleneck is no longer variants — it’s insight

What teams actually struggle with today:

• Who should we test with?
• Why did something work?
• What should we build before testing?

Both roll-ups converge on the same answer:

High-quality human insight + AI interpretation beats raw experimentation volume.

Roll-up #1: User Research Roll up by Thoma Bravo→ “Human truth at scale”

What they combined

• UserTesting: moderated/unmoderated feedback, enterprise workflows
• UserZoom: research ops, surveys, journey mapping
• UserInterviews: hard-to-reach participant recruitment (B2B, specialists)

Product logic

This creates an end-to-end insight engine:
Recruit → Observe → Synthesize → Feed into product, design, AI systems

Subtext for product teams

• Research is being productized as infrastructure
• “Human data” is being positioned as a strategic input to AI, not a UX checkbox
• Expect tighter coupling between research tools and AI-assisted decision systems

Source: Thoma Bravo PR

Roll-up #2: Everstone → “Automated optimization at scale”

What they combined

• Wingify (VWO): experimentation + CRO mechanics
• AB Tasty: personalization + AI-driven qualitative layers

What VWO specifically gains

With AB Tasty, VWO adds:

1. EmotionsAI

• Infers visitors’ emotional / motivational states
• Enables personalization beyond clicks and funnels
• Moves optimization toward psychographic intent, not just behavior

2. Evi (agentic AI for experimentation)

• Auto-generates hypotheses
• Sets up tests
• Analyzes outcomes
• Reduces human labor in experimentation loops

Compared to VWO’s Copilot:

• Copilot = assistive
• Evi = agentic (does the work)

Sources: TechCrunch, Convert.com

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The "So What" for PMs and Designers

If you’re a PM, designer, or researcher already using CRO + user testing tools, consolidation won’t break your workflow and won't even break the bank in the short term

What likely improves

• Vendor management gets easier Fewer tools. Fewer security reviews. Easier procurement conversations.
• Enterprise support becomes more predictable Dedicated CSMs, clearer SLAs, global rollout support.
• Global reach expands Larger panels, better coverage across regions, languages, and compliance needs. .  
• Large platforms will be conservative: Less raw data access. More abstraction. More compliance layers

What likely gets worse

• Pricing flexibility disappears Example: UserTesting already doesn’t offer true à-la-carte pricing. UserInterview historically did. After consolidation, don’t expect more modularity.
• Panels get bigger, not necessarily better Global reach improves. Niche or hard-to-reach personas don't
• Innovation shifts toward “safe AI” Think summaries, prioritization, automation but not deep behavioral breakthroughs.

Net effect: easier to run programs. Harder to do unconventional research.

The uncomfortable question for teams

If these platforms will soon be able to: 

• Generate variants
• Run tests autonomously
• Summarize results and insights

Then the real leverage shifts to:

Framing the right problems and defining the right signals

That’s where product and design leadership still matter.

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So where does CarbonCopies fit into this?

These companies optimize after teams already decided what to test.

Interviews explain after the fact.

A/B tests validate after shipping.

The expensive part still happens earlier:

– which persona hesitates

– where confidence drops

– why a flow feels wrong before metrics move

That’s where CarbonCopies operates.

Before proof.

Before traffic.

Before weeks of testing.

Simulate decisions upstream.

Reduce how many experiments you need downstream.

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See comparisons: 

CarbonCopies AI vs. A/B Testing

CarbonCopies AI vs. User Research vs. User Testing