AI-native GTM startup Reevo is doubling down on leadership as demand accelerates for its Revenue Operating System.

The company announced the appointments of Naman Khan as Chief Marketing Officer and Ali Ghotbi as Chief Revenue Officer, adding enterprise SaaS pedigree to a platform that only launched in November 2025. The hires follow an $80 million fundraise co-led by Khosla Ventures and Kleiner Perkins, and what Reevo describes as a 4x surge in demand since launch.

For a startup positioning itself as the “AI-native” alternative to fragmented go-to-market stacks, the message is clear: product-market fit may be emerging, and now it’s time to operationalize scale.

From Tool Sprawl to Revenue OS

Reevo’s pitch is bold but timely. Rather than layering AI across disconnected CRM, marketing automation, and customer success tools, the company is building what it calls a unified Revenue Operating System.

The goal: collapse fragmented GTM workflows into a single platform powered by first-party data and AI automation.

In practical terms, Reevo claims revenue teams can:

• Build target account lists

• Engage prospects

• Manage pipeline

• Coordinate across sales, marketing, and CS

—without stitching together third-party integrations.

That positioning directly targets a persistent pain point in SaaS: tool sprawl. Even mid-sized companies often run dozens of GTM systems across CRM, sequencing, enrichment, analytics, and support. LLMs have amplified automation potential, but they’ve also highlighted how brittle disconnected stacks can be.

Reevo is betting that AI works best when it’s native, not bolted on.

A CMO With Platform Playbook Experience

Naman Khan joins as CMO with experience at major SaaS platforms, including Salesforce and Dropbox.

At Salesforce, Khan supported $1 billion in revenue growth through customer expansion during the company’s transition into a multi-product platform. At Dropbox, he helped drive the push into commercial B2B, contributing to revenue surpassing $1 billion.

That background is particularly relevant for Reevo. Moving from single-product momentum to multi-product platform credibility requires disciplined positioning, category creation, and narrative control—especially in a crowded AI landscape.

Khan frames the opportunity around LLM disruption. As large language models rapidly reshape SaaS expectations, he argues that Reevo isn’t just adding AI features—it’s architected around AI from day one.

For marketing, that means defining not just a product, but a category: AI-native GTM infrastructure.

A CRO Who’s Scaled Through IPO

On the revenue side, Ali Ghotbi brings more than 25 years of experience, including 14 years at Box, where he most recently served as Senior Vice President of Sales.

Ghotbi helped guide Box from early-stage growth through IPO and beyond, contributing to ARR expansion from tens of millions to over $1 billion. Prior to Box, he held leadership roles at HP and Oracle.

At Reevo, he’ll oversee sales execution, operations, and alignment across customer success—with plans to expand the sales team 10x in 2026.

That scale ambition signals confidence. But it also underscores the stakes. GTM platforms don’t just need product strength—they need disciplined sales motion, especially when competing against entrenched ecosystems like Salesforce, HubSpot, and a growing wave of AI-first point solutions.

Timing the AI Inflection Point

Reevo launched in November 2025, entering a market in flux.

LLMs have reshaped expectations across SaaS. Buyers now expect:

• Real-time account intelligence

• Automated pipeline insights

• AI-driven prospecting

• Cross-functional visibility

But many companies are retrofitting AI into legacy architectures. Reevo’s thesis is that starting fresh—with a unified data model and AI core—delivers cleaner execution and faster time-to-value.

CEO and co-founder David Zhu says the mission is to eliminate fragmentation and manual work that slow down modern revenue teams. The early 4x demand increase suggests resonance, though the durability of that demand will hinge on measurable ROI and adoption depth.

The Bigger Competitive Picture

The GTM tech landscape is increasingly polarized:

• Legacy platforms are embedding AI into existing systems.

• Startups are building AI-native workflows from scratch.

Reevo sits firmly in the latter camp.

Its success will depend on whether revenue teams are willing to consolidate core workflows into a new operating layer—or prefer incremental upgrades within familiar ecosystems.

Hiring senior operators from Salesforce and Box suggests Reevo understands that scaling an AI platform isn’t just a technical challenge. It’s an organizational and sales execution challenge.

If the company can translate early demand into repeatable revenue motion, it may carve out a credible position in the evolving Revenue OS category.

For now, the signal is clear: Reevo is no longer in build-only mode. It’s gearing up to compete at enterprise scale.

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In a digital world overloaded with ads, emails, and social feeds, live and virtual events remain one of the few channels that can meaningfully cut through the noise. Cvent is betting on that principle with its latest resource: Event-Led Growth For Dummies, Cvent Special Edition, a practical guide that reframes events as strategic revenue engines rather than one-off campaigns.

The book is aimed squarely at marketers seeking to link events directly to pipeline, deal velocity, and customer success outcomes—a discipline Cvent calls event-led growth (ELG).

Reframing Events as a Revenue Driver

“Events are one of the most powerful growth levers for marketers,” said Kate Hammit, Vice President of Marketing at Cvent. “By reframing events as a strategic channel rather than a standalone campaign, organizations can create sustainable growth that spans the full customer lifecycle.”

Unlike traditional event marketing—which often evaluates success via attendance or lead counts—ELG treats every interaction as a measurable contribution to revenue. According to Cvent research, 52% of closed-won deals are influenced by events, and attendees tend to close faster than non-attendees.

Event-Led Growth For Dummies walks marketers through actionable strategies, including how to:

• Map event programs to every stage of the buyer journey, from awareness to renewal

• Align event objectives with GTM priorities and revenue KPIs

• Integrate event tech with CRM and marketing automation systems for accurate attribution

• Track influence on pipeline, closed-won deals, and renewals

• Repurpose event content and leverage engagement data for broader campaigns

• Overcome digital fatigue while generating first-party engagement data and real-time insights

The book emphasizes that measurement and integration are what transform events from cost centers into defensible revenue drivers, making them “budget-proof” in a climate of constrained marketing spend.

From Book to Certification

Cvent isn’t stopping at the book. The release coincides with its Event-Led Growth Masterclass and Certification program, which provides hands-on guidance to implement ELG practices in real-world settings.

Since launch, over 600 marketers across SMBs and enterprise organizations have enrolled. Early participants have praised the program for combining strategic depth with practical tactics.

“This course is packed with great insights on how to turn events into real business drivers… Every module was straight to the point and highly actionable.”
— Event marketing leader, global workspace provider

“If you’re in event marketing, field marketing, or just looking to sharpen your GTM strategy, this is seriously worth your time and investment.”
— Director of field marketing, AI-powered marketing technology company

Together, the Cvent Special Edition book and certification program give marketers both a conceptual framework and actionable tools to operationalize event-led growth, helping organizations embed events at the center of their go-to-market strategy.

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GitLab Inc., the AI-native orchestration platform for DevSecOps, has launched an expanded Managed Service Provider (MSP) Partner Program designed to give MSPs a single, comprehensive service across the entire software development lifecycle (SDLC).

The program comes as enterprises increasingly demand agentic AI capabilities that go beyond accelerating coding to streamline planning, security, compliance, and deployment workflows—all within a governed, auditable environment.

From Fragmented Tools to Unified AI Orchestration

While AI tools have accelerated coding, bottlenecks persist in pipeline handoffs, security checks, and compliance reviews. GitLab’s platform addresses these gaps by enabling AI agents to orchestrate work across the SDLC, giving MSPs a differentiated offering to help clients innovate faster while maintaining full control over data.

The enhanced program also responds to strong demand for managed deployment options that meet local data residency and regulatory requirements in regions including EMEA, Latin America, and Asia-Pacific. Partners can deploy GitLab, including AI-native Duo Agent Platform features, across MSP-owned data centers, customer premises, colocation facilities, or hyperscaler environments.

Program Highlights

GitLab’s expanded MSP initiative delivers multiple benefits for partners:

• Revenue opportunities: Standard partner margins plus MSP premiums, with partners retaining 100% of deployment, migration, training, and consulting fees.

• Priority support: Direct engagement with GitLab experts and escalation channels.

• Not-for-resale licenses: Build internal expertise and demonstrate platform capabilities to prospects.

• Training and development: Quarterly technical bootcamps covering platform capabilities, best practices, and troubleshooting.

• Marketing development funds and co-branding: Support for joint case studies, events, and customer acquisition campaigns.

Partner Perspectives

Industry partners praised the program for enabling secure, scalable, and compliant managed services:

• Matthew Hope, Adaptavist: “The MSP program reinforces our commitment to delivering tailored GitLab services, helping customers maximize their investment and leverage features like Duo Agent Platform.”

• Gil Oliveira, Adfinis: “The enhanced MSP program lets us scale 24/7 services while maintaining digital sovereignty and accelerating innovation.”

• Henri Hämäläinen, Eficode: “It enables us to deliver GitLab’s intelligent orchestration platform at scale, helping customers innovate faster while staying compliant.”

Strategic Implications

GitLab’s move highlights a broader trend in DevSecOps: enterprises want managed, AI-driven solutions that unify toolchains without compromising security or compliance. By expanding the MSP program, GitLab positions partners to capture growing demand for intelligent, end-to-end software lifecycle automation while giving clients flexibility in deployment and governance.

Ian Steward, GitLab CRO, emphasized: “By enabling MSPs to deliver our complete platform as a managed service, we're creating a scalable path to market that benefits partners, customers, and GitLab's long-term growth strategy.”

Alex Picker, VP of Global Ecosystems, added: “Our enhanced program addresses the challenge enterprises face in adopting agentic AI while maintaining strict control over their data and compliance posture.”

For MSPs and enterprise customers, GitLab’s expansion represents a step toward a unified, AI-driven approach to DevSecOps—turning fragmented tool stacks into a single, governed revenue and innovation engine.

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Amplitude, Inc. (Nasdaq: AMPL) announced that members of its management team will participate in three upcoming investor conferences in early March 2026, giving stakeholders insight into the company’s strategy and growth trajectory.

Investor Conference Schedule:

• Citizens Technology Conference: Monday, March 2, 6:30 p.m. ET

• KeyBanc Emerging Technology Summit: Tuesday, March 3, 2:00 p.m. ET

• Morgan Stanley Technology, Media, and Telecom Conference: Wednesday, March 4, 6:20 p.m. ET

All presentations will be webcast live via Amplitude’s investor relations portal at investors.amplitude.com  Replays will also be available following each session for those unable to attend live.

These appearances provide Amplitude an opportunity to discuss its AI analytics platform, recent developments, and market positioning with investors and industry analysts, continuing the company’s active engagement with the financial community.

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Thryv Holdings, Inc. (NASDAQ: THRY) reported robust SaaS growth in 2025, highlighting the company’s ongoing transformation from legacy print and marketing services to a leading software provider for small and medium-sized businesses (SMBs).

Key 2025 Financial Highlights:

• Full-Year SaaS Revenue: $461.0M, up 34% YoY; excluding Keap acquisition: $391.4M, up 18.6% YoY

• Fourth Quarter SaaS Revenue: $119.0M, up 14% YoY; excluding Keap: $102.8M, up 13.1% YoY

• Marketing Services Revenue: $324.0M for the year, down 32.6% YoY

• Consolidated Total Revenue: $785.0M, down 4.7% YoY

• Consolidated Net Income: $0.3M for the year vs. net loss of $74.2M in 2024

• Consolidated Adjusted EBITDA: $151.8M, with a 19.3% margin

• SaaS Adjusted EBITDA: $73.8M, 16.0% margin

• SaaS Gross Profit & Margin: $325.8M, 70.7%; Adjusted Gross Profit: $335.0M, 72.7%

Operational Metrics:

• SaaS Clients: 100,000 at year-end 2025

• Quality Customers: 69% of SaaS revenue from clients contributing >$400 MRR in Q4

• Seasoned Net Revenue Retention: 94% as of December 31, 2025

• SaaS ARPU: $373 in Q4, up 15% YoY

• Marketing Center Revenue: Grew 56% in Q4 and over 100% for the full year

CEO Commentary:

Joe Walsh, Chairman and CEO, stated:

“We delivered solid full-year 2025 results, with SaaS revenue growth of 34% YoY and SaaS Adjusted EBITDA margin of 16.0%. We have successfully transitioned into a leading SMB software company, with SaaS revenue now contributing over 62% of total revenue. Looking ahead, we are shifting to a unified growth offering enabled by AI—the Thryv Platform—designed to help small businesses market, sell, and grow.”

Upcoming Earnings Conference Call:

Thryv will host a call on Thursday, February 26, 2026, at 8:30 a.m. ET to discuss Q4 results and outlook. Live webcast and registration details are available at investor.thryv.com.

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Enterprise CRM environments rarely stay tidy. After years of acquisitions, regional expansions, and decentralized IT decisions, many global companies now run multiple instances of Salesforce—often with little coordination between them.

Today, Sweep wants to change that.

The enterprise automation startup announced the launch of its Multi-Org Agent for Salesforce, a new addition to what it calls an “agentic layer” for enterprise systems. The tool is built specifically for companies juggling multiple Salesforce orgs, promising to map dependencies, automations, data models, and rules across fragmented environments in days rather than months.

In practical terms: it gives CIOs and enterprise architects a unified view of systems that, until now, few teams fully understood.

And that visibility matters more than ever.

The Multi-Org Problem No One Owns

Running multiple Salesforce orgs is common—and messy.

Enterprises often accumulate orgs through mergers and acquisitions, geographic expansion, or business unit autonomy. Over time, duplicated workflows, inconsistent field structures, and conflicting automations creep in. One division customizes opportunity stages; another rewires approval logic. A third integrates billing in a slightly different way. Multiply that by years of iterative changes, and you get architectural drift at scale.

The result? A CRM landscape where no single team has full visibility.

That becomes a serious liability when leadership decides to consolidate systems, integrate newly acquired companies, or roll out AI initiatives. Without a clear map of cross-org dependencies, organizations risk:

• Automation conflicts that break workflows

• Outages during migration

• Compliance gaps due to permission inconsistencies

• Customer-facing errors triggered by misaligned logic

According to Sweep CEO and cofounder Ido Gaver, that fragmentation is a root cause of stalled modernization efforts.

“For thousands of companies, running multiple orgs at once is a reality, but there’s often very little intentional strategy behind it,” Gaver said in the announcement. “That disconnect is behind many of the setbacks we see in consolidation and AI programs.”

In other words: enterprises are making high-stakes architectural decisions without a blueprint.

What Sweep’s Multi-Org Agent Actually Does

The Multi-Org Agent is designed to act as an intelligence layer across multiple Salesforce environments. Instead of auditing each org manually—often a months-long effort—Sweep’s agent maps structural differences and cross-org dependencies automatically.

Core capabilities include:

• Comparing configurations, field structures, and automation logic across orgs

• Identifying redundant or conflicting automation before it triggers downstream failures

• Mapping structural inconsistencies that complicate consolidation

• Surfacing technical debt and permission inconsistencies at scale

• Assessing architectural readiness for AI deployments, including Agentforce

The emphasis here is metadata visibility. By reasoning across orgs, Sweep aims to expose architectural fragmentation that would otherwise stay hidden until something breaks—or until a migration project runs over budget.

It’s a shift from reactive troubleshooting to proactive architecture governance.

Why This Matters Now: AI Raises the Stakes

The timing isn’t accidental.

Enterprises are racing to deploy AI agents across sales, service, and operations. But AI systems depend on clean metadata, consistent business logic, and predictable automation. Fragmented org structures degrade performance, introduce hallucination-like behavior in rule-based systems, and amplify edge-case errors.

If AI is layered onto messy CRM architecture, it inherits the mess.

Sweep positions Multi-Org Agent as an AI-readiness tool as much as a consolidation tool. Before enterprises roll out large-scale AI initiatives, the agent surfaces structural inconsistencies that could undermine reliability.

That’s particularly relevant as Salesforce pushes deeper into AI-powered CRM capabilities. Organizations investing in new AI layers need confidence that their underlying systems won’t sabotage those deployments.

From Manual Audits to Incremental Modernization

One of the more pragmatic use cases Sweep highlights is consolidation planning.

Traditionally, enterprises considering org consolidation face two unattractive options: launch a multi-year reimplementation program or attempt risky migrations with incomplete visibility. Both are expensive. Both carry operational risk.

Sweep’s approach aims to enable incremental modernization. By mapping org differences in advance, teams can:

• Evaluate consolidation scenarios based on real architecture

• Identify structural conflicts before migration begins

• Avoid unnecessary reimplementation

• Plan phased integrations grounded in data rather than assumptions

For M&A-heavy organizations, the value proposition is even clearer. Newly acquired Salesforce environments can be assessed immediately, compressing what typically requires months of manual discovery.

In a market where deal velocity often outpaces IT integration, that speed matters.

Governance and Compliance at Scale

Beyond modernization and AI, governance is another pressure point.

Multi-org environments make it difficult to enforce consistent permission models and policy controls. Configuration drift—where orgs gradually diverge—can introduce compliance risk without triggering alarms.

Sweep’s agent continuously scans across orgs to surface:

• Permission inconsistencies

• Policy violations

• Configuration drift

The goal is to provide compliance teams with a single source of truth across distributed CRM architecture—a tall order in organizations where business units operate semi-independently.

Expanding Beyond Salesforce

Sweep isn’t stopping at CRM.

In the coming weeks, the company plans to extend its Multi-Org Agent capabilities to Snowflake and ServiceNow environments.

That expansion hints at a broader ambition: connecting CRM architecture with data infrastructure and service layers to deliver cross-system intelligence.

If successful, that would move enterprises from managing isolated systems to governing integrated architecture—an increasingly critical shift as digital transformation initiatives mature.

In practice, it means visibility not just across multiple Salesforce orgs, but across the systems that feed and depend on them.

The Bigger Picture: The Rise of the Agentic Layer

Sweep’s launch reflects a larger trend in enterprise IT: the rise of agentic systems that reason across complex environments rather than operate within single tools.

As SaaS sprawl continues and enterprises accumulate overlapping platforms, the challenge isn’t just automation—it’s orchestration. Companies need systems that understand architecture, not just execute tasks.

Multi-Org Agent is an attempt to tackle one of the most stubborn examples of enterprise sprawl: multi-instance CRM.

If it works as advertised, CIOs may finally gain the cross-org visibility they’ve lacked for years—and de-risk the next wave of consolidation and AI transformation projects in the process.

For enterprises staring at a tangle of Salesforce orgs and wondering where to begin, that kind of clarity could be overdue.

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High-stakes consumer litigation isn’t where most ad tech platforms flex their efficiency claims. It’s expensive, competitive, and unforgiving. Leads are scarce. Qualification is strict. And the only metric that truly matters is whether someone signs a legal retainer.

That’s precisely the environment where KNOREX Ltd. says it proved its point.

The AI-driven programmatic advertising firm announced a nationwide campaign with a performance-focused legal marketing partner that reduced cost per acquisition (CPA) by 29%—cutting it to $354 from a historical blended benchmark of $500 in comparable litigation cases.

In a vertical where margins hinge on case eligibility and signed retainers, that’s not incremental optimization. It’s structural improvement.

Optimizing for Retainers, Not Clicks

Most digital campaigns still optimize for proxy metrics: impressions, clicks, form fills, maybe marketing-qualified leads. In litigation marketing, those signals can be misleading. A click doesn’t pay legal fees. A signed retainer does.

KNOREX structured the campaign around a single success metric: verified signed legal retainers.

That shift reframed the entire optimization model. Instead of chasing low-cost traffic or inflated conversion rates, the campaign aligned spend with confirmed revenue events.

The engine behind it was KNOREX’s AI-powered XPO platform, which executed across search, social, and display channels while maintaining centralized management. But the real differentiator was how feedback flowed back into the system.

Daily retainer confirmations were fed into a closed-loop optimization model, allowing the platform to refine bidding and targeting based on actual legal outcomes—not surface-level engagement data.

In effect, the algorithm learned from revenue, not activity.

A Tough Vertical Gets Tougher

Consumer litigation advertising is one of digital marketing’s most challenging segments. Audience pools are narrow. Competition for eligible claimants is intense. And compliance considerations add another layer of operational complexity.

The partner’s previous blended CPA of $500 reflected what it considered the economic threshold for sustainable performance. Any higher, and campaign viability becomes questionable given qualification rates and case value variability.

Reducing CPA to $354 materially shifts that equation.

A 29% drop in acquisition cost in a high-CPA vertical doesn’t just improve margins—it expands the number of cases that can be pursued profitably. That can influence media allocation strategy, geographic expansion, and overall campaign scale.

And that’s exactly what followed. After validating performance, the legal marketing partner expanded budgets nationally.

AI With a Revenue Anchor

KNOREX attributes the performance lift to four core elements within its XPO platform:

• Retainer-Based Performance Measurement: Optimization tied exclusively to verified signed retainers

• Closed-Loop Feedback Engine: Daily outcome data used to retrain targeting and bidding logic

• Advanced Audience Segmentation: Behavioral targeting of specific claimant profiles and relevant influencers

• Unified Cross-Channel Execution: Centralized orchestration across search, social, and display

The broader industry shift is hard to miss. Advertisers increasingly want outcome-based models rather than engagement-based reporting. That’s especially true in sectors where each acquisition carries significant financial weight.

Legal marketing is one. Financial services and healthcare are others.

By anchoring optimization to signed retainers, KNOREX aligned media investment directly with measurable legal revenue outcomes—a step beyond typical performance marketing models that stop at lead generation.

The Economics of Predictability

One of the biggest barriers to scaling litigation campaigns is unpredictability. Qualification rates vary. Case values fluctuate. And many campaigns struggle to consistently hit economic thresholds.

The nationwide rollout was structured as a validation test: could AI-driven programmatic advertising sustain predictable economics in a sensitive, high-CPA environment?

The CPA reduction and subsequent budget expansion suggest the answer, at least in this case, is yes.

For KNOREX, the results serve as proof that its unified AI framework can operate effectively in regulated, performance-sensitive sectors where traditional digital approaches often falter.

The Bigger Trend: From Engagement to Unit Economics

The timing aligns with a broader recalibration in digital advertising.

Marketers are under pressure to justify spend with measurable financial outcomes. Vanity metrics are losing currency. Boards and CFOs increasingly demand clarity on unit economics.

In that context, optimizing for signed retainers instead of clicks isn’t just a tactical shift—it reflects where performance marketing is headed.

If platforms can consistently tie ad spend to revenue events in complex verticals like litigation, it could reshape how performance is measured across other high-value industries.

KNOREX’s campaign suggests that AI-driven programmatic isn’t limited to e-commerce conversions or app installs. With the right feedback loop, it can target revenue in sectors where the stakes—and the CPAs—are significantly higher.

For advertisers tired of paying for activity instead of outcomes, that distinction may be the one that matters most.

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Trust is the currency of review platforms. And in 2025, that currency is under pressure from AI-generated content, coordinated review rings, and increasingly sophisticated scams.

Yelp Inc. (NYSE: YELP) says it’s fighting back—at scale.

In its newly released 2025 Trust & Safety Report, Yelp disclosed that it identified and filtered nearly half a million suspected AI-generated reviews, shut down more than 1.3 million user accounts for policy violations, and ramped up enforcement across scams, compensated reviews, and viral-driven review abuse.

The message is clear: as generative AI tools proliferate and moderation budgets tighten elsewhere, Yelp is positioning itself as the industry’s hardliner on authenticity.

Nearly Half a Million AI Reviews Filtered

AI-written reviews violate Yelp’s content guidelines. Reviews must reflect genuine, firsthand experiences—and users are prohibited from using third-party AI tools to draft them.

With AI writing tools now widely accessible, Yelp says it significantly expanded detection efforts in 2025, deploying new AI-powered systems to flag suspicious patterns. The result: nearly 500,000 reviews exhibiting characteristics of AI-generated content were filtered out by automated systems.

That’s a substantial volume, especially considering Yelp received approximately 22 million reviews globally in 2025.

Of those:

• About 70% were recommended by Yelp’s automated recommendation software

• 17% were not recommended

• 11% were removed by the User Operations team

• 2% were self-removed by users

Unlike platforms that lean heavily on community reporting, Yelp emphasizes that its recommendation engine operates independently. It evaluates every review using hundreds of signals related to quality, user behavior, and reliability—and cannot be overridden by employees or business owners.

In 2025, Yelp further tuned that system to demote reviews lacking sufficient detail or showing signs of undisclosed conflicts of interest.

In an era when AI can generate polished, convincing narratives in seconds, detail alone is no longer proof of authenticity. Yelp’s bet is that layered detection—automated plus human moderation—remains defensible at scale.

Account Closures Surge 138%

The fight against deceptive behavior extended beyond reviews.

Yelp closed over 1.3 million user accounts in 2025, a 138% increase from 2024. The surge was largely driven by airline phone support scams—an increasingly common tactic where fake support listings divert consumers seeking help.

Yelp’s systems identified and removed more than 889,800 fake phone support accounts tied to these schemes.

It also rejected more than 50,700 new business page submissions associated with spam-like behaviors—a 29% year-over-year increase. Many were concentrated in high-risk emergency service categories such as locksmiths, plumbing, roadside assistance, and garage door repair, where consumers are especially vulnerable during urgent situations.

Additionally, Yelp removed over 1,340 business pages linked to deceptive lead generators attempting to create fake listings to resell consumer inquiries.

Taken together, the data underscores how review platforms are increasingly battlegrounds for fraud beyond just fake five-star ratings.

Cracking Down on Paid and Coordinated Reviews

Compensated and incentivized reviews remain a persistent challenge across the industry. Yelp says it proactively investigates both its own platform and external sites to infiltrate review-trading groups.

In 2025, the company:

• Placed 128 Compensated Activity Alerts on business pages

• Issued 363 Suspicious Review Activity Alerts tied to coordinated behavior

• Closed nearly 2,000 accounts linked to review exchange rings (a 49% increase)

Yelp also reported making more than 1,020 notifications to platforms including Meta Platforms (Facebook and Instagram), X Corp., LinkedIn, Reddit, TikTok, and Craigslist after identifying groups attempting to trade or purchase reviews.

According to Yelp, 60% of those reports resulted in action by the receiving platforms—a 62% increase from the previous year.

The company identified more than 1,100 suspicious groups, posts, or individuals tied to review trading, marking a 45% year-over-year rise.

In other words, the arms race is escalating.

Viral Moments Trigger Review Surges

Not all moderation challenges stem from scams. Social virality can distort review ecosystems just as quickly.

Yelp reported a 58% year-over-year increase in Media Attention Alerts and Unusual Activity Alerts placed on business pages following spikes in abnormal review behavior.

More than 80,000 reviews were removed in 2025 due to viral-driven activity. Of those cases, 75% stemmed from social media amplification that triggered waves of reviews from users without firsthand experiences.

Yelp placed:

• Over 1,190 Unusual Activity Alerts

• 266 Public Attention Alerts related to accusations or discrimination claims

In some cases, the platform temporarily disabled review posting to prevent review bombing.

As social media outrage cycles accelerate, review platforms increasingly function as secondary battlegrounds. Yelp’s approach—temporary freezes and visible alerts—signals a more interventionist stance compared to platforms that rely solely on reactive moderation.

Pushing Back on Legal Intimidation

The report also highlights Yelp’s resistance to legal demands aimed at unmasking reviewers.

In 2025, the company says it avoided producing personal information related to 99% of user accounts targeted by subpoenas or legal requests from law enforcement, government entities, or private parties.

Yelp also placed six Questionable Legal Threat Alerts on business pages after identifying what it described as potential abuse of the legal system to silence reviews.

Legal pressure as a moderation tactic isn’t new—but Yelp’s data suggests it remains active, particularly when negative reviews threaten reputation.

A Competitive Positioning Play

While the report focuses on enforcement metrics, there’s a strategic layer beneath the numbers.

As generative AI accelerates content production and some platforms recalibrate trust-and-safety budgets, Yelp is leaning into moderation as a differentiator. By publicizing detection volumes and enforcement growth, it positions itself as a platform prioritizing authenticity over frictionless scale.

The challenge going forward won’t just be identifying AI-written content—it will be distinguishing increasingly sophisticated synthetic narratives from genuine human experiences.

Filtering half a million suspected AI reviews in one year is a strong signal. Whether that pace holds as generative models evolve will be the next test.

For now, Yelp is making its stance clear: authenticity isn’t optional—it’s the product.

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