G2 is making one of the most consequential moves in the history of B2B software discovery. The company announced it has formally agreed to acquire Capterra, Software Advice, and GetApp from Gartner, uniting four of the most influential software review and recommendation platforms under one roof.

The deal reshapes the software buying landscape at a moment when AI-driven search, buyer intent data, and trust signals are rapidly redefining how businesses evaluate technology. Once finalized, the acquisition will give G2 unmatched scale, data depth, and reach—positioning it as the default infrastructure layer for software discovery in the AI era.

For buyers, vendors, investors, and partners alike, the implications are substantial.

A Power Shift in B2B Software Discovery

Individually, G2, Capterra, Software Advice, and GetApp have long been go-to destinations for researching business software. Together, they form what may be the most comprehensive dataset ever assembled on how companies discover, evaluate, and purchase technology.

The combined platform will offer:

• 6 million verified customer reviews

• More than 200 million annual software buyers globally

• 10,000+ software vendors served

• Coverage across 2,000+ software and service categories

• An expanded foundation of first- and second-party buyer intent data

That scale fundamentally changes the competitive dynamics of the software marketplace industry, particularly as AI-powered recommendations begin to replace traditional listicles, rankings, and keyword-based search.

“This acquisition represents a transformational moment for G2 and, more importantly, the global B2B software industry,” said Godard Abel, CEO and co-founder of G2. “By integrating the verified reviews, insights, and audiences from Capterra, Software Advice, and GetApp, we’re building the trusted data foundation for buyers and sellers of software for the age of AI.”

Why This Deal Matters Now

Software buying has reached an inflection point.

Traditional discovery models—search engines, analyst reports, and static comparison pages—are struggling to keep pace with exploding category complexity and accelerating AI adoption. At the same time, buyers increasingly expect personalized, context-aware recommendations rather than generic rankings.

This is where G2’s timing becomes critical.

By consolidating trusted review platforms and layering AI-driven intelligence on top, G2 is positioning itself not just as a marketplace, but as the decision engine behind modern software purchasing.

The acquisition also reflects a broader trend: as AI reshapes search behavior, companies with proprietary, high-quality data gain outsized power. Verified reviews, buyer intent signals, and real behavioral data are becoming more valuable than traffic alone.

What Changes for Software Buyers

For buyers, the most immediate impact will be smarter, faster, and more personalized discovery.

G2 plans to integrate the newly acquired platforms’ datasets directly into G2.ai, its AI-driven recommendation engine. With a much larger pool of verified feedback and behavioral data, G2.ai aims to move beyond surface-level comparisons toward genuinely contextual guidance.

That means:

• More accurate recommendations based on role, industry, company size, and intent

• Faster shortlists with fewer irrelevant options

• Greater confidence that insights are based on real, verified user experiences

In practice, G2 wants to become the AI-powered “guide” that buyers consult before, during, and after evaluating software—reducing friction in a process that has become notoriously time-consuming.

A Bigger Opportunity for Software Vendors

For vendors, the acquisition dramatically expands both reach and revenue potential.

By absorbing Capterra, Software Advice, and GetApp, G2 gains access to massive inbound buyer traffic—much of it coming from high-intent searches near the moment of purchase. That creates new leverage for demand capture, advertising, and intent-based sales activation.

According to G2, vendors can expect:

• Expanded global visibility across traditional search and AI-driven discovery

• Up to 3x more Buyer Intent signals through unified datasets

• Stronger performance across SEO and answer engine optimization (AEO)

• A more advanced digital advertising infrastructure

• A forthcoming pay-per-lead model designed to convert intent into sales-ready opportunities

This is a notable evolution from review platforms as passive awareness channels to active revenue drivers—especially for B2B SaaS companies under pressure to improve pipeline efficiency.

The SEO and AI Search Angle

One of the most strategic aspects of the acquisition is its impact on search—both traditional and AI-powered.

Capterra, Software Advice, and GetApp are already dominant players in organic search across thousands of high-intent software keywords. Combining that footprint with G2’s review depth and buyer intent intelligence gives the company a commanding position as search behavior shifts toward AI-generated answers.

G2 has explicitly framed this as an AEO and SEO play, preparing for a future where:

• Buyers ask AI tools for software recommendations instead of clicking through multiple websites

• Search engines prioritize trusted, structured datasets over generic content

• Discovery happens inside conversational interfaces rather than static web pages

In that context, owning the underlying data becomes more important than owning the front-end experience—and G2 now controls more of that data than any competitor.

What Gartner Gets Out of the Deal

While G2’s upside is clear, the deal also signals a strategic recalibration for Gartner.

By divesting Capterra, Software Advice, and GetApp, Gartner appears to be sharpening its focus on its core strengths: research, advisory services, and enterprise decision support. The move allows Gartner to step back from operating high-scale, consumer-style marketplaces while still benefiting from its broader position in the enterprise ecosystem.

For G2, acquiring assets previously backed by Gartner also adds credibility and reinforces trust—particularly among enterprise buyers who already rely on Gartner insights.

Implications for the Broader Software Ecosystem

Beyond buyers and vendors, the acquisition has ripple effects across the industry.

Partners and integrators gain access to richer datasets that can improve targeting, personalization, and workflow automation.
Consultants and investors can leverage deeper, verified insights to assess market trends, competitive positioning, and category growth.
Product teams gain clearer visibility into customer sentiment and unmet needs across thousands of categories.

In short, the combined platform becomes not just a marketplace, but a system of record for software adoption and sentiment.

Competitive Landscape: Who Can Keep Up?

This deal raises uncomfortable questions for competitors.

Smaller review sites and comparison platforms may struggle to compete with G2’s combined scale, especially as AI systems increasingly favor authoritative data sources. Even large digital publishers face challenges as AI-driven discovery reduces reliance on traditional content models.

Meanwhile, adjacent players in intent data, ABM, and B2B advertising will need to rethink integrations as G2 consolidates more of the buyer journey inside its ecosystem.

The message is clear: in the AI era, fragmented data loses value. Unified, trusted datasets win.

The Bottom Line

G2’s acquisition of Capterra, Software Advice, and GetApp marks a defining moment for B2B software discovery.

By uniting the industry’s most trusted review platforms, G2 is building what it describes as the trusted data foundation for software buying in the age of AI—one that serves buyers seeking clarity, vendors chasing demand, and partners navigating an increasingly complex market.

As AI reshapes how decisions are made, this deal positions G2 not just as a marketplace, but as the intelligence layer behind the global software economy.

G2 is making one of the most consequential moves in the history of B2B software discovery. The company announced it has formally agreed to acquire Capterra, Software Advice, and GetApp from Gartner, uniting four of the most influential software review and recommendation platforms under one roof.

The deal reshapes the software buying landscape at a moment when AI-driven search, buyer intent data, and trust signals are rapidly redefining how businesses evaluate technology. Once finalized, the acquisition will give G2 unmatched scale, data depth, and reach—positioning it as the default infrastructure layer for software discovery in the AI era.

For buyers, vendors, investors, and partners alike, the implications are substantial.

A Power Shift in B2B Software Discovery

Individually, G2, Capterra, Software Advice, and GetApp have long been go-to destinations for researching business software. Together, they form what may be the most comprehensive dataset ever assembled on how companies discover, evaluate, and purchase technology.

The combined platform will offer:

• 6 million verified customer reviews

• More than 200 million annual software buyers globally

• 10,000+ software vendors served

• Coverage across 2,000+ software and service categories

• An expanded foundation of first- and second-party buyer intent data

That scale fundamentally changes the competitive dynamics of the software marketplace industry, particularly as AI-powered recommendations begin to replace traditional listicles, rankings, and keyword-based search.

“This acquisition represents a transformational moment for G2 and, more importantly, the global B2B software industry,” said Godard Abel, CEO and co-founder of G2. “By integrating the verified reviews, insights, and audiences from Capterra, Software Advice, and GetApp, we’re building the trusted data foundation for buyers and sellers of software for the age of AI.”

Why This Deal Matters Now

Software buying has reached an inflection point.

Traditional discovery models—search engines, analyst reports, and static comparison pages—are struggling to keep pace with exploding category complexity and accelerating AI adoption. At the same time, buyers increasingly expect personalized, context-aware recommendations rather than generic rankings.

This is where G2’s timing becomes critical.

By consolidating trusted review platforms and layering AI-driven intelligence on top, G2 is positioning itself not just as a marketplace, but as the decision engine behind modern software purchasing.

The acquisition also reflects a broader trend: as AI reshapes search behavior, companies with proprietary, high-quality data gain outsized power. Verified reviews, buyer intent signals, and real behavioral data are becoming more valuable than traffic alone.

What Changes for Software Buyers

For buyers, the most immediate impact will be smarter, faster, and more personalized discovery.

G2 plans to integrate the newly acquired platforms’ datasets directly into G2.ai, its AI-driven recommendation engine. With a much larger pool of verified feedback and behavioral data, G2.ai aims to move beyond surface-level comparisons toward genuinely contextual guidance.

That means:

• More accurate recommendations based on role, industry, company size, and intent

• Faster shortlists with fewer irrelevant options

• Greater confidence that insights are based on real, verified user experiences

In practice, G2 wants to become the AI-powered “guide” that buyers consult before, during, and after evaluating software—reducing friction in a process that has become notoriously time-consuming.

A Bigger Opportunity for Software Vendors

For vendors, the acquisition dramatically expands both reach and revenue potential.

By absorbing Capterra, Software Advice, and GetApp, G2 gains access to massive inbound buyer traffic—much of it coming from high-intent searches near the moment of purchase. That creates new leverage for demand capture, advertising, and intent-based sales activation.

According to G2, vendors can expect:

• Expanded global visibility across traditional search and AI-driven discovery

• Up to 3x more Buyer Intent signals through unified datasets

• Stronger performance across SEO and answer engine optimization (AEO)

• A more advanced digital advertising infrastructure

• A forthcoming pay-per-lead model designed to convert intent into sales-ready opportunities

This is a notable evolution from review platforms as passive awareness channels to active revenue drivers—especially for B2B SaaS companies under pressure to improve pipeline efficiency.

The SEO and AI Search Angle

One of the most strategic aspects of the acquisition is its impact on search—both traditional and AI-powered.

Capterra, Software Advice, and GetApp are already dominant players in organic search across thousands of high-intent software keywords. Combining that footprint with G2’s review depth and buyer intent intelligence gives the company a commanding position as search behavior shifts toward AI-generated answers.

G2 has explicitly framed this as an AEO and SEO play, preparing for a future where:

• Buyers ask AI tools for software recommendations instead of clicking through multiple websites

• Search engines prioritize trusted, structured datasets over generic content

• Discovery happens inside conversational interfaces rather than static web pages

In that context, owning the underlying data becomes more important than owning the front-end experience—and G2 now controls more of that data than any competitor.

What Gartner Gets Out of the Deal

While G2’s upside is clear, the deal also signals a strategic recalibration for Gartner.

By divesting Capterra, Software Advice, and GetApp, Gartner appears to be sharpening its focus on its core strengths: research, advisory services, and enterprise decision support. The move allows Gartner to step back from operating high-scale, consumer-style marketplaces while still benefiting from its broader position in the enterprise ecosystem.

For G2, acquiring assets previously backed by Gartner also adds credibility and reinforces trust—particularly among enterprise buyers who already rely on Gartner insights.

Implications for the Broader Software Ecosystem

Beyond buyers and vendors, the acquisition has ripple effects across the industry.

Partners and integrators gain access to richer datasets that can improve targeting, personalization, and workflow automation.
Consultants and investors can leverage deeper, verified insights to assess market trends, competitive positioning, and category growth.
Product teams gain clearer visibility into customer sentiment and unmet needs across thousands of categories.

In short, the combined platform becomes not just a marketplace, but a system of record for software adoption and sentiment.

Competitive Landscape: Who Can Keep Up?

This deal raises uncomfortable questions for competitors.

Smaller review sites and comparison platforms may struggle to compete with G2’s combined scale, especially as AI systems increasingly favor authoritative data sources. Even large digital publishers face challenges as AI-driven discovery reduces reliance on traditional content models.

Meanwhile, adjacent players in intent data, ABM, and B2B advertising will need to rethink integrations as G2 consolidates more of the buyer journey inside its ecosystem.

The message is clear: in the AI era, fragmented data loses value. Unified, trusted datasets win.

The Bottom Line

G2’s acquisition of Capterra, Software Advice, and GetApp marks a defining moment for B2B software discovery.

By uniting the industry’s most trusted review platforms, G2 is building what it describes as the trusted data foundation for software buying in the age of AI—one that serves buyers seeking clarity, vendors chasing demand, and partners navigating an increasingly complex market.

As AI reshapes how decisions are made, this deal positions G2 not just as a marketplace, but as the intelligence layer behind the global software economy.

G2 is making one of the most consequential moves in the history of B2B software discovery. The company announced it has formally agreed to acquire Capterra, Software Advice, and GetApp from Gartner, uniting four of the most influential software review and recommendation platforms under one roof.

The deal reshapes the software buying landscape at a moment when AI-driven search, buyer intent data, and trust signals are rapidly redefining how businesses evaluate technology. Once finalized, the acquisition will give G2 unmatched scale, data depth, and reach—positioning it as the default infrastructure layer for software discovery in the AI era.

For buyers, vendors, investors, and partners alike, the implications are substantial.

A Power Shift in B2B Software Discovery

Individually, G2, Capterra, Software Advice, and GetApp have long been go-to destinations for researching business software. Together, they form what may be the most comprehensive dataset ever assembled on how companies discover, evaluate, and purchase technology.

The combined platform will offer:

• 6 million verified customer reviews

• More than 200 million annual software buyers globally

• 10,000+ software vendors served

• Coverage across 2,000+ software and service categories

• An expanded foundation of first- and second-party buyer intent data

That scale fundamentally changes the competitive dynamics of the software marketplace industry, particularly as AI-powered recommendations begin to replace traditional listicles, rankings, and keyword-based search.

“This acquisition represents a transformational moment for G2 and, more importantly, the global B2B software industry,” said Godard Abel, CEO and co-founder of G2. “By integrating the verified reviews, insights, and audiences from Capterra, Software Advice, and GetApp, we’re building the trusted data foundation for buyers and sellers of software for the age of AI.”

Why This Deal Matters Now

Software buying has reached an inflection point.

Traditional discovery models—search engines, analyst reports, and static comparison pages—are struggling to keep pace with exploding category complexity and accelerating AI adoption. At the same time, buyers increasingly expect personalized, context-aware recommendations rather than generic rankings.

This is where G2’s timing becomes critical.

By consolidating trusted review platforms and layering AI-driven intelligence on top, G2 is positioning itself not just as a marketplace, but as the decision engine behind modern software purchasing.

The acquisition also reflects a broader trend: as AI reshapes search behavior, companies with proprietary, high-quality data gain outsized power. Verified reviews, buyer intent signals, and real behavioral data are becoming more valuable than traffic alone.

What Changes for Software Buyers

For buyers, the most immediate impact will be smarter, faster, and more personalized discovery.

G2 plans to integrate the newly acquired platforms’ datasets directly into G2.ai, its AI-driven recommendation engine. With a much larger pool of verified feedback and behavioral data, G2.ai aims to move beyond surface-level comparisons toward genuinely contextual guidance.

That means:

• More accurate recommendations based on role, industry, company size, and intent

• Faster shortlists with fewer irrelevant options

• Greater confidence that insights are based on real, verified user experiences

In practice, G2 wants to become the AI-powered “guide” that buyers consult before, during, and after evaluating software—reducing friction in a process that has become notoriously time-consuming.

A Bigger Opportunity for Software Vendors

For vendors, the acquisition dramatically expands both reach and revenue potential.

By absorbing Capterra, Software Advice, and GetApp, G2 gains access to massive inbound buyer traffic—much of it coming from high-intent searches near the moment of purchase. That creates new leverage for demand capture, advertising, and intent-based sales activation.

According to G2, vendors can expect:

• Expanded global visibility across traditional search and AI-driven discovery

• Up to 3x more Buyer Intent signals through unified datasets

• Stronger performance across SEO and answer engine optimization (AEO)

• A more advanced digital advertising infrastructure

• A forthcoming pay-per-lead model designed to convert intent into sales-ready opportunities

This is a notable evolution from review platforms as passive awareness channels to active revenue drivers—especially for B2B SaaS companies under pressure to improve pipeline efficiency.

The SEO and AI Search Angle

One of the most strategic aspects of the acquisition is its impact on search—both traditional and AI-powered.

Capterra, Software Advice, and GetApp are already dominant players in organic search across thousands of high-intent software keywords. Combining that footprint with G2’s review depth and buyer intent intelligence gives the company a commanding position as search behavior shifts toward AI-generated answers.

G2 has explicitly framed this as an AEO and SEO play, preparing for a future where:

• Buyers ask AI tools for software recommendations instead of clicking through multiple websites

• Search engines prioritize trusted, structured datasets over generic content

• Discovery happens inside conversational interfaces rather than static web pages

In that context, owning the underlying data becomes more important than owning the front-end experience—and G2 now controls more of that data than any competitor.

What Gartner Gets Out of the Deal

While G2’s upside is clear, the deal also signals a strategic recalibration for Gartner.

By divesting Capterra, Software Advice, and GetApp, Gartner appears to be sharpening its focus on its core strengths: research, advisory services, and enterprise decision support. The move allows Gartner to step back from operating high-scale, consumer-style marketplaces while still benefiting from its broader position in the enterprise ecosystem.

For G2, acquiring assets previously backed by Gartner also adds credibility and reinforces trust—particularly among enterprise buyers who already rely on Gartner insights.

Implications for the Broader Software Ecosystem

Beyond buyers and vendors, the acquisition has ripple effects across the industry.

Partners and integrators gain access to richer datasets that can improve targeting, personalization, and workflow automation.
Consultants and investors can leverage deeper, verified insights to assess market trends, competitive positioning, and category growth.
Product teams gain clearer visibility into customer sentiment and unmet needs across thousands of categories.

In short, the combined platform becomes not just a marketplace, but a system of record for software adoption and sentiment.

Competitive Landscape: Who Can Keep Up?

This deal raises uncomfortable questions for competitors.

Smaller review sites and comparison platforms may struggle to compete with G2’s combined scale, especially as AI systems increasingly favor authoritative data sources. Even large digital publishers face challenges as AI-driven discovery reduces reliance on traditional content models.

Meanwhile, adjacent players in intent data, ABM, and B2B advertising will need to rethink integrations as G2 consolidates more of the buyer journey inside its ecosystem.

The message is clear: in the AI era, fragmented data loses value. Unified, trusted datasets win.

The Bottom Line

G2’s acquisition of Capterra, Software Advice, and GetApp marks a defining moment for B2B software discovery.

By uniting the industry’s most trusted review platforms, G2 is building what it describes as the trusted data foundation for software buying in the age of AI—one that serves buyers seeking clarity, vendors chasing demand, and partners navigating an increasingly complex market.

As AI reshapes how decisions are made, this deal positions G2 not just as a marketplace, but as the intelligence layer behind the global software economy.

Get in touch with our MarTech Experts.

MiningLamp Technology has added a major credential to its fast-growing reputation in enterprise AI. The Hong Kong–listed company (2718.HK) took home the Grand Prize at the national finals of the 3rd China’s Innovation Challenge on Artificial Intelligence Application Scene (CICAS)—one of the country’s most competitive and influential AI events—cementing its status as a serious force in Agentic AI and multimodal large models.

The winning project, developed in collaboration with Peking University, is called “Intelligent Platform for Brand Globalization Creative Generation and Emotional Connection Based on Multimodal Large Models.” Beyond the long name, the idea is straightforward and timely: help companies expand globally by using AI to localize creative content, predict emotional response, and generate marketing assets faster—without losing cultural nuance.

The project was also named a “2025 National Artificial Intelligence Application Scenario Exemplary Case,” a designation reserved for AI systems with strong real-world commercial and societal impact.

A Fierce Competition With National Significance

CICAS is not a typical startup pitch contest. Jointly organized by the Chinese Association for Artificial Intelligence, the Suzhou Municipal People’s Government, and Soochow University, the competition is designed to surface AI technologies that can scale across industries.

This year’s challenge drew more than 3,250 registered teams, with 113 elite teams advancing to the national finals. Over 350 participants—from China and abroad—competed in Suzhou, Jiangsu Province, placing MiningLamp’s win firmly in “best-of-the-best” territory.

For MiningLamp, this marks a symbolic moment. While the company has been active in enterprise AI since 2006, the CICAS Grand Prize represents its first major national AI competition win since its Hong Kong Stock Exchange listing in November 2025.

Why Brand Globalization Is an AI Problem Now

Global expansion has become harder, not easier, for brands. Cultural missteps go viral instantly, consumer sentiment shifts faster than traditional research can track, and content localization remains expensive and slow.

MiningLamp’s platform is built around a clear thesis: global brand marketing is no longer a creative-only problem—it’s a data, emotion, and automation problem.

According to Wu Minghui, Founder, CEO, and CTO of MiningLamp, brands going global face three persistent barriers:

• Cultural and emotional differences across markets

• High costs and long timelines for content localization

• Limited data-driven insight into how creative will actually land

The platform addresses these challenges by combining multimodal AI, Agentic workflows, and proprietary data intelligence into a single system designed for marketing teams—not just data scientists.

Four Technologies Powering the Platform

At the core of MiningLamp’s winning solution are four tightly integrated capabilities. Together, they form an end-to-end workflow that spans insight generation, emotional evaluation, and content creation.

1. A Global Multimodal Content Asset Library

The platform includes a multimodal content library covering major global markets, incorporating video, image, and text assets. Rather than starting from scratch for every campaign, brands can draw from culturally relevant creative materials aligned with regional norms and preferences.

The practical upside is speed and cost efficiency. Localization cycles that once took weeks can now be compressed into days—or even hours—while maintaining cultural relevance.

In a market where brands are expected to “think global but act local,” this library becomes a strategic advantage rather than a simple repository.

2. Trustworthy Data Collection via the “Dexterous Hand” Mano Model

MiningLamp’s Mano model—described internally as an AI “dexterous hand”—is one of the platform’s most distinctive features.

Mano can operate across browser environments, visually identifying interface elements and interacting with them much like a human would. Users simply provide a URL and a description of their data needs; Mano handles the rest, collecting multi-source web data with minimal manual intervention.

This capability matters because global market analysis often fails due to fragmented, unreliable data. Mano’s human-like perception allows it to gather cleaner, more contextual datasets—critical for downstream decision-making.

Technical benchmarks underscore Mano’s maturity:

• Ranked first in the specialized model category of the OSWorld benchmark

• Ranked second overall, just behind Anthropic’s Claude-Sonnet-4.5

• Achieved SOTA performance on the Mind2Web benchmark

• A 7B-parameter version supports private deployment for enterprise security needs

For enterprises wary of black-box AI, this emphasis on transparency and controllability is notable.

3. Subjective Emotional Perception Analysis With HMLLM

Perhaps the most ambitious element of the platform is its Hypergraph Multimodal Large Language Model (HMLLM), designed to simulate how different audiences feel about content—not just how they engage with it.

Unlike traditional sentiment analysis, HMLLM models subjective emotional response across dimensions like attention, emotion, and cognition. It can estimate how viewers from different cultures, age groups, and genders are likely to react to advertising content before it goes live.

The model is trained on uniquely rich datasets:

• Video-SME and SPA-ADV, built from EEG and eye-tracking data

• Data collected from over 10,000 real human subjects

• Emotional response modeling with R² consistency exceeding 89%

The research behind HMLLM earned a Best Paper Nomination at ACM MM 2024, lending academic credibility to what is often treated as a fuzzy marketing problem.

For global brands, the implication is clear: fewer cultural misfires, less guesswork, and more confidence in creative decisions.

4. AI-Driven Video Generation at Scale

Once insights and emotional assessments are complete, the platform can automatically generate and optimize video content. This closes the loop—from market understanding to creative output—inside a single AI-driven workflow.

MiningLamp claims the system can compress traditional video production timelines from weeks to hours, a meaningful advantage as short-form video and rapid campaign iteration become standard across platforms like TikTok, YouTube, and connected TV.

This positions the platform not just as an analytics tool, but as a full-stack AI marketing engine.

Enterprise-Grade AI, Not Just a Demo

MiningLamp’s broader technical credentials reinforce the seriousness of the platform. The company has published 20+ papers in top-tier international journals and conferences, including:

• ACM MM 2024 (CCF-A): Best Paper Nomination for HMLLM

• TPAMI (SCI Q1): Few-shot video instance segmentation

• IJCV (SCI Q1): Image generation methods

• AAAI 2026 (CCF-A): Mano model compression, accepted as an oral presentation

These aren’t marketing whitepapers—they’re peer-reviewed contributions that help explain why MiningLamp is increasingly described as China’s first “Agentic AI” public company.

Strategic Implications for MarTech and Global Brands

MiningLamp’s win highlights a broader industry trend: AI is moving from content optimization to content decision-making.

While many Western MarTech platforms focus on performance metrics after launch, MiningLamp is betting on AI that evaluates cultural fit and emotional resonance before content reaches consumers. That shift could reshape how global campaigns are planned, especially in regulated or reputation-sensitive industries.

The platform also aligns with the growing enterprise demand for trustworthy AI—systems that are explainable, auditable, and deployable in private environments.

What Comes Next

At the CICAS closing ceremony, MiningLamp signed a cooperation intent with Gusu District, signaling plans to expand AI R&D and real-world deployment scenarios locally.

The company says it will continue applying its “data-driven trustworthy productivity” philosophy beyond brand globalization, targeting additional vertical industries where Agentic AI can deliver measurable impact.

As global competition intensifies and AI-driven differentiation becomes table stakes, MiningLamp’s platform could emerge as a critical infrastructure layer for companies trying to scale internationally without losing cultural intelligence along the way.

Get in touch with our MarTech Experts.

Campaign Monitor is making a clear bet on practical AI—not flashy automation for its own sake, but tools designed to help small and mid-sized businesses actually make better email marketing decisions.

The company has announced three new AI-powered features—Marketing Monitor, Segment Mapper, and AI Email Booster—aimed at giving marketers always-on guidance directly inside the platform. The goal: reduce guesswork, shorten optimization cycles, and help lean teams improve results without changing how they work.

Marketing Monitor is already live for customers, while Segment Mapper and AI Email Booster roll out on January 28.

AI as an In-App Marketing Partner, Not a Black Box

Campaign Monitor’s new features are positioned less as autonomous AI and more as a built-in marketing advisor—surfacing insights, recommendations, and next steps without forcing users to hand over control.

That distinction matters. Many SMB marketers are surrounded by dashboards and metrics but lack clarity on what to act on next. Campaign Monitor’s approach focuses on turning data into direction.

Together, the three features cover the core email marketing loop: performance analysis, audience targeting, and campaign optimization.

Marketing Monitor: Performance With Context

Marketing Monitor tackles one of email marketing’s biggest blind spots: knowing whether your results are actually good.

The feature benchmarks campaign performance against relevant industry standards, adding context to metrics like opens, clicks, and engagement. Instead of just showing numbers, it highlights where marketers should focus next—helping teams prioritize fixes that will have the most impact.

For SMBs without analysts or dedicated optimization teams, this kind of guidance can dramatically speed up decision-making.

Segment Mapper: Audience Building Without the Technical Headaches

Segment Mapper lowers the barrier to advanced targeting by letting marketers describe their audience goals in plain language. The AI then translates that intent into usable audience segments inside Campaign Monitor.

This removes a common friction point for non-technical users who know who they want to reach but struggle with filters, logic rules, and segmentation syntax. It’s a notable step toward making personalization more accessible—especially as inbox competition continues to intensify.

AI Email Booster: Optimization Inside the Builder

AI Email Booster works directly inside the email builder, analyzing content as it’s created and surfacing clear, actionable recommendations. Marketers can apply suggestions with a single click, rather than switching tools or interpreting abstract scores.

The focus here is speed and clarity. Instead of overwhelming users with AI-generated rewrites or opaque predictions, Campaign Monitor is aiming for small, confident improvements that compound over time.

Why This Matters for SMB Marketers

Email remains one of the highest-ROI channels, but expectations for personalization and relevance keep rising. At the same time, most SMBs don’t have the time, staff, or budget to experiment endlessly or interpret complex analytics.

Campaign Monitor’s AI strategy is designed to close that gap by:

• Reducing time-to-value for campaign improvements

• Making advanced tactics accessible to non-experts

• Preserving human control over creative and strategy

“AI should make email marketing easier, not more complicated,” said Elizabeth Smalley, Chief Product Officer at Campaign Monitor. “We built these new AI features to provide always-on guidance directly inside the platform, helping marketers better see what’s working to optimize faster, without losing control of their strategy.”

That emphasis on collaboration—AI assisting rather than replacing human judgment—sets Campaign Monitor apart from more aggressive automation-first approaches in the email marketing space.

Launch Events and Availability

To showcase the new capabilities, Campaign Monitor will host two live launch webinars:

• Tuesday, February 3 at 1:00 PM EST

• Wednesday, February 4 at 10:30 AM AEST

The sessions will walk marketers through real-world use cases and demonstrate how the tools can simplify decision-making and boost performance.

The Bigger Picture

Campaign Monitor’s update reflects a broader MarTech shift: AI is moving from experimental features to embedded decision support. Rather than asking marketers to trust AI blindly, platforms are increasingly focused on delivering contextual guidance that fits naturally into existing workflows.

For SMBs, that balance—between intelligence and control—may be exactly what’s needed to stay competitive as inboxes grow more crowded and customer expectations continue to rise.

Get in touch with our MarTech Experts.

In the multifamily housing business, speed is money. Miss a prospect inquiry—especially after hours—and there’s a good chance that lead is already touring a competing property by morning. H2L Marketing is betting that problem is big enough, and expensive enough, to warrant a dedicated solution.

The company has officially launched Ellipse, a leasing-automation platform designed to ensure multifamily properties respond to every prospect inquiry, all the time. Emails, texts, and voice calls are handled in real time, day or night, while human leasing teams focus on higher-value work—like tours, relationship-building, and closing leases.

At a time when property operators are under pressure from rising costs, tighter margins, and increasingly digital-first renters, Ellipse positions itself as a productivity engine rather than just another chatbot. The promise is straightforward: fewer missed leads, faster response times, and better use of leasing staff.

Why Ellipse Exists: The Cost of Silence in Leasing

Industry data consistently shows that more than half of leasing inquiries go unanswered, particularly outside traditional business hours. For properties juggling lean staffing models and high inquiry volumes, responding instantly to every prospect simply isn’t realistic.

Ellipse aims to close that gap with intelligent automation that handles initial engagement, scheduling, and follow-ups without burning out on-site teams.

“With Ellipse, our mission is clear,” said Femi Lakeru, Chief Operating Officer at H2L Marketing. “We enable properties to respond to 100% of prospect inquiries and improve property staff utilization through intelligent automation.”

Unlike generic marketing automation tools, Ellipse is purpose-built for multifamily leasing. H2L Marketing says the platform was developed in consultation with leasing teams and property owners—people who understand firsthand how easily opportunities slip through the cracks.

That owner-operator perspective is notable. Ellipse isn’t framed as a replacement for leasing agents, but as infrastructure that handles repetitive front-line interactions so humans can focus on what actually closes deals.

What Ellipse Does—and How It’s Different

At its core, Ellipse functions as a 24/7 digital leasing assistant. When a prospect reaches out—via email, text, or phone—the platform responds instantly, answering questions, capturing lead details, and moving conversations toward the next step.

Key capabilities include:

• Always-on lead handling: All initial contacts are managed around the clock, including evenings, weekends, and holidays.

• Real-time responses across channels: Ellipse engages prospects through email, SMS, and voice, meeting renters where they already are.

• Automated tour scheduling: Prospects can move from inquiry to scheduled tour without waiting for staff availability.

• Seamless integration: The platform is designed to work with existing property management and CRM systems, minimizing disruption.

• Transparent pricing: No opaque usage tiers or hidden fees—pricing is straightforward and predictable.

This focus on operational fit matters. Multifamily operators are often wary of new tech that promises transformation but requires complex integrations or retraining. H2L’s pitch is that Ellipse fits into current workflows rather than forcing teams to rebuild them.

Early Results: Faster Tours, Higher Conversions

During pilot deployments, properties using Ellipse reported measurable gains across the leasing funnel. According to H2L Marketing, participating properties saw:

• 54% faster tour scheduling from the initial prospect contact

• 35% more leases attributed to Ellipse’s after-hours interactions

• 16% increase in lead-to-lease conversion rates

• 15% increase in overall occupancy

Those numbers highlight an often-overlooked reality in multifamily marketing: a significant portion of leasing activity happens when offices are closed. Prospects browse listings at night, send inquiries on weekends, and expect responses that feel immediate—even if they’re automated.

Ellipse’s strongest impact appears to come from capturing and nurturing those off-hours interactions, which are traditionally the most neglected.

Automation Meets Human Leasing Teams

One of the persistent fears around automation—especially in sales and leasing—is that it degrades the customer experience. H2L Marketing is careful to position Ellipse as an assistant, not a replacement.

By handling repetitive first-touch interactions, Ellipse frees leasing agents to focus on:

• Delivering high-quality, personalized property tours

• Building rapport with qualified prospects

• Supporting resident satisfaction and retention

That division of labor reflects a broader trend in B2B and B2C tech: automation handles scale, humans handle nuance. In leasing, that nuance often determines whether a prospect signs—or keeps shopping.

Ellipse also addresses staff utilization, a growing concern as properties operate with smaller teams. Rather than forcing agents to juggle phones, inboxes, and walk-ins simultaneously, Ellipse absorbs the constant background noise of inbound inquiries.

The Competitive Landscape: Not Just Another Chatbot

Ellipse enters a crowded ecosystem of proptech tools, many of which promise AI-driven engagement. What sets Ellipse apart is its narrow focus on leasing outcomes rather than generalized marketing automation.

Compared with basic chatbots or generic CRM automations, Ellipse emphasizes:

• Multi-channel engagement (not just web chat)

• Leasing-specific workflows, including tour scheduling

• Metrics tied directly to occupancy and lease conversion

Rival solutions often require extensive customization or rely heavily on scripted interactions. Ellipse, by contrast, is marketed as an operational layer that works continuously in the background.

This specialization aligns with a larger industry shift. As proptech matures, platforms are becoming more vertical-specific, solving discrete operational problems rather than offering all-in-one dashboards that do a little of everything.

Pricing and Accessibility

Ellipse’s pricing model reflects its operational positioning. Complete packages for properties with 100 or more units start at $499 per month, with options available for properties of all sizes.

That price point places Ellipse within reach of mid-sized operators—not just large institutional owners. Transparent pricing also reduces friction in procurement, a pain point for property managers burned by unpredictable SaaS costs.

In an environment where every expense is scrutinized, Ellipse’s value proposition hinges on ROI: fewer missed leads, faster leasing cycles, and higher occupancy rates.

Why This Matters Now

The timing of Ellipse’s launch is notable. Multifamily operators are navigating a complex market shaped by:

• Increased competition for renters

• Rising operational costs

• Higher expectations for digital responsiveness

Renters accustomed to instant replies in e-commerce and travel bring those same expectations to housing. Properties that fail to respond quickly risk appearing outdated—or worse, uninterested.

Ellipse addresses that expectation gap directly. By ensuring no inquiry goes unanswered, it turns responsiveness into a competitive advantage rather than a staffing challenge.

From a MarTech perspective, Ellipse also underscores how marketing automation is moving closer to revenue operations. This isn’t about brand awareness or campaign performance—it’s about signed leases and filled units.

The Bigger Picture: Automation as a Revenue Safeguard

H2L Marketing frames Ellipse as a tool to “protect investment,” and that language is telling. In multifamily real estate, vacancy is one of the most expensive problems an owner can face.

Automation that prevents even a small percentage of missed opportunities can have outsized financial impact. A single additional lease per month can easily justify Ellipse’s subscription cost.

That calculus explains why leasing automation is gaining traction while other categories of proptech struggle for adoption. The value is concrete, measurable, and immediate.

Final Take

Ellipse isn’t flashy, and that may be its strength. It targets a mundane but costly problem—missed leasing inquiries—and solves it with always-on automation designed around real-world workflows.

For multifamily operators looking to improve responsiveness without expanding headcount, Ellipse offers a pragmatic answer. And for the MarTech ecosystem, it’s another sign that automation’s future lies not in novelty, but in quietly making money where it’s already being lost.

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Artificial intelligence has officially crossed the point of no return in marketing. According to Jasper’s newly released 2026 State of AI in Marketing Report, AI is no longer an experimental productivity boost or a “nice-to-have” add-on. It’s now foundational infrastructure—embedded in how marketing teams operate, measure success, and are held accountable.

Just two years ago, most marketing organizations were still testing the waters. In early 2025, many teams were debating whether AI belonged in their workflows at all. That debate is over. In 2026, the question isn’t if marketers use AI, but how well they run it.

Jasper’s report captures this inflection point clearly—and not always comfortably. While adoption has gone nearly universal, the pressure to scale AI responsibly, govern it effectively, and prove business impact has intensified. AI has moved from experimentation to expectation, and with that shift comes scrutiny.

AI Adoption Is Now Table Stakes

The headline number is hard to ignore: 91% of marketing teams now use AI, up sharply from 63% in 2025. What’s more telling is how mature that usage has become. Nearly two-thirds of marketers—63%—now describe their AI maturity as intermediate or advanced, signaling a broad move beyond pilots and isolated use cases.

This maturation reflects a wider industry trend. AI tools are no longer limited to copy drafts or brainstorming sessions. They’re increasingly embedded in content operations, campaign execution, and performance workflows. For many teams, AI access is as assumed as a CMS or analytics platform.

“Our findings capture just how quickly AI in marketing has evolved from experimentation toward measurable business impact,” said Loreal Lynch, CMO at Jasper. “With adoption now table stakes, the advantage is shifting to organizations that run AI with clear ownership, disciplined governance, and meaningful measurement.”

In other words, simply using AI no longer differentiates leaders from laggards. Execution does.

Scale Becomes the New Battleground

As AI use becomes widespread, the competitive edge is shifting to scale—and not just more output, but consistent, high-quality execution.

Jasper’s data shows that scaling high-quality content is now the top AI objective for marketers, and the fastest-growing priority year over year. Compared to 2025, this goal has increased 2.4x, reflecting a shift from experimentation to repeatable production.

This evolution mirrors what many marketing leaders are experiencing firsthand. Early AI wins were often tactical—faster drafts, lower costs, quicker turnaround. Now, organizations want AI systems that can reliably support always-on content engines without degrading brand voice, accuracy, or trust.

That’s a much harder problem to solve. It requires not just better prompts or models, but governance, workflows, and ownership structures that treat AI like core infrastructure rather than a side tool.

ROI: Harder to Prove, More Valuable Than Ever

One of the report’s more counterintuitive findings is that fewer marketers can confidently prove AI ROI than last year. In 2026, just 41% say they can demonstrate clear returns, down from 49% in 2025.

This doesn’t necessarily mean AI is performing worse. Instead, expectations have risen. As AI becomes operational—and often mandatory—leaders are demanding harder evidence of impact, not anecdotal wins.

Among teams that do measure ROI, the results are compelling. Most report returns of 2x or greater on their AI investments, reinforcing the idea that disciplined measurement unlocks confidence and continued investment.

The gap between perceived value and provable value is becoming a fault line. Organizations that fail to connect AI usage to revenue, pipeline, or growth metrics risk seeing their initiatives stall—even as adoption remains high.

Governance Emerges as the Primary Bottleneck

In 2025, AI challenges were scattered: budget limitations, lack of expertise, leadership skepticism. In 2026, the constraints have consolidated—and intensified.

Jasper’s report shows that friction from cross-functional review processes has increased 3.4x year over year, making governance the single biggest blocker to scaling AI. Legal, compliance, and brand teams are now deeply involved in AI oversight, slowing execution but raising accountability.

This shift reflects AI’s new status. When AI-generated content is experimental, risks are tolerated. When it becomes core infrastructure, scrutiny follows.

The implication is clear: organizations that don’t build scalable governance frameworks will struggle to grow AI usage beyond small teams. Manual reviews and ad hoc approvals don’t scale—and marketers are feeling the drag.

The CMO–IC Divide Widens

Another striking insight from the report is the growing disconnect between leadership and frontline marketers.

CMOs report the highest levels of AI maturity, job satisfaction, and ROI confidence, with 61% saying they can prove AI ROI. Among individual contributors, that number drops to just 12%—even as pressure increases for AI usage to be mandatory.

This gap suggests that while AI is delivering strategic value at the top, the operational burden is falling disproportionately on individual marketers. For ICs, AI isn’t optional experimentation anymore—it’s part of the job description, often without clear ownership or support.

The risk here isn’t burnout, but misalignment. Without structure and transparency, AI can feel like surveillance or enforcement rather than empowerment.

AI Disruption Correlates With Satisfaction—With Conditions

Contrary to common fears, AI isn’t broadly burning marketers out. In fact, teams most impacted by AI report the highest job satisfaction, but only when AI is supported by clear structure, governance, and ownership.

Overall, 75% of marketers say AI increased their job satisfaction in 2026, down slightly from 78% in 2025. That modest dip reflects rising accountability rather than declining enthusiasm.

The takeaway is nuanced: AI can be energizing or exhausting depending on how it’s implemented. Structure turns disruption into momentum. Chaos turns it into stress.

Marketing Roles Are Being Redefined

Perhaps the most lasting impact of AI’s rise is how it’s reshaping marketing roles themselves.

According to Jasper, one in three marketers now has AI responsibilities formally built into their role, spanning prompt design, workflow development, and governance. AI fluency is no longer a bonus skill—it’s becoming baseline competence.

The talent implications are significant. 97% of marketers say access to AI factors into their job decisions, and 75% say it’s critical when considering a role. For employers, AI maturity is now part of the employer brand.

This aligns with broader workforce trends across tech and knowledge work, where AI access and enablement increasingly influence retention, recruitment, and satisfaction.

From Efficiency Tool to Competitive Advantage

Jasper positions this moment as a strategic fork in the road. AI can remain a collection of efficiency hacks—or it can become a durable competitive advantage.

“At Jasper, we are focused on helping marketers turn AI into a durable competitive advantage, not just a short-term efficiency gain,” said Timothy Young, CEO of Jasper. “This research reinforces that success with AI now depends on how well teams operationalize it.”

That distinction matters. Efficiency gains are easily replicated. Operational excellence is not.

Organizations that treat AI like infrastructure—complete with governance, ownership, and measurement—are pulling ahead. Those that rely on informal adoption risk stagnation, even as usage remains high.

The Bottom Line

Jasper’s 2026 State of AI in Marketing Report makes one thing unmistakably clear: AI has grown up. It’s embedded, expected, and increasingly evaluated with the same rigor as any other core system.

The winners in this next phase won’t be the teams with the most tools, but those with the clearest operating models. AI leadership now looks less like experimentation and more like execution discipline.

For marketers, the era of “trying AI” is over. The era of running it well has begun.

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European medical device company ViCentra has appointed Reman McDonagh, PhD, as its new Vice President of Global Marketing, marking a key move as the company scales commercialization for its Kaleido insulin patch pump system. McDonagh’s hiring comes at a pivotal stage for ViCentra, as it strengthens its European presence and prepares for the next-generation Kaleido system launch in both the EU and the U.S.

The move coincides with ViCentra’s recent $98 million Series D financing extension, providing the financial backing to support ambitious growth plans.

A Proven Diabetes and MedTech Marketing Leader

McDonagh brings over 20 years of experience in diabetes and medical device commercialization, covering the full spectrum from early-stage innovation to large-scale international expansion. Her career includes senior leadership roles at Roche, Medtronic, Cellnovo, and Insulet, with deep experience in brand strategy, go-to-market planning, market development, and high-profile product launches across both mature and emerging markets.

Most recently, she spearheaded Insulet’s Omnipod DASH launch across 12 European countries and contributed to the European strategy for Omnipod 5. Her appointment signals ViCentra’s intent to combine operational rigor with marketing sophistication as it expands its footprint.

“Reman joins ViCentra at a pivotal stage as we transition from strong early traction to disciplined, scalable growth,” said Tom Arnold, CEO of ViCentra. “She brings a rare combination of deep diabetes expertise, end-to-end marketing leadership, and operational rigor, as we strengthen our presence in key European markets and prepare for U.S. market entry.”

Driving Global Marketing Strategy for Kaleido

In her new role, McDonagh will oversee ViCentra’s global marketing strategy, including:

• Strengthening Kaleido’s value proposition

• Accelerating demand generation in priority European markets

• Ensuring cross-functional readiness for upcoming product launches

“Kaleido is a truly differentiated insulin delivery system, and ViCentra has built meaningful momentum through a clear focus on the user experience,” said McDonagh. “I’m excited to join the team as we scale in key markets and prepare for the next generation of Kaleido, bringing greater choice, flexibility, and freedom to more people living with diabetes.”

Bolstering a World-Class Commercial Team

McDonagh’s hiring follows a series of senior commercial leadership additions at ViCentra, reflecting the company’s commitment to building a high-performing, global marketing organization capable of executing its long-term growth strategy. With a PhD in Chemistry and leadership experience managing business units exceeding $400 million in annual revenue, McDonagh brings both technical expertise and commercial acumen.

As ViCentra looks ahead to the EU and U.S. launches of its next-generation Kaleido system, the company is betting that combining innovation with strong marketing leadership will position it as a major player in insulin delivery solutions.

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As AI increasingly powers product discovery and recommendations, the people who generate the content behind those answers—journalists, reviewers, and creators—are often left out of the value chain. impact.com aims to change that with Geodesix, a new data marketplace that provides AI systems with licensed commerce content and ensures creators are fairly compensated.

Developed through Impact Labs, impact.com’s innovation and venture arm, Geodesix addresses a structural imbalance in the AI economy. Large language models often rely on the work of publishers and creators to answer consumer questions, yet those original content producers typically see little or no revenue when their work informs AI outputs.

Industry data underscores the urgency. AI-generated answer features can reduce user clicks on publisher links by nearly 50%, and some publishers report search referral losses exceeding 30% as AI engines deliver answers directly, bypassing the original site entirely. Geodesix offers a transparent solution: a licensed content layer that gives publishers and creators a stake in the AI economy.

How Geodesix Works

Hanan Maayan, head of Impact Labs and general manager of Geodesix, explained the marketplace’s approach: “AI is built on content, but the people who create that content haven’t had a fair way to participate in the value it generates. Geodesix creates a simple, transparent way for AI companies to access high-quality publisher content, and for publishers to finally get paid when their work is used.”

Geodesix provides AI systems with approved access to trusted commerce content, including:

• Product reviews and buying guides

• Listicles and tutorials

• Comparisons and recommendation content

When an AI-generated answer draws from that content, Geodesix identifies the contributing sources and distributes revenue to publishers via a share-value model. The system ensures both compliance and transparency, giving AI developers a reliable content layer while rewarding the creators whose work fuels the recommendations.

Independent Yet Integrated

Although incubated within impact.com, Geodesix operates independently with its own platform and team. This structure allows the marketplace to move quickly, work with a broad range of AI companies, brands, and publishers, and contribute to impact.com’s long-term growth in commerce partnerships.

Currently, Geodesix is available to select customers, with early applications focused on AI-powered shopping assistants and product recommendation tools. Looking ahead, the company plans to expand into additional verticals, including travel, finance, and B2B software, where AI-driven recommendations increasingly influence buying decisions.

Why It Matters

Geodesix is part of a broader industry conversation about AI ethics, creator compensation, and sustainable content ecosystems. As large language models become dominant channels for discovery, publishers face declining referral traffic and mounting pressure to find alternative monetization strategies. Geodesix establishes a model where creators’ contributions are recognized and rewarded, helping preserve content quality while supporting the AI economy.

In short, the platform represents a convergence of commerce, AI, and creator economy best practices: content drives AI answers, AI drives commerce, and creators finally share in the value they generate.

For brands, publishers, and AI companies alike, Geodesix signals a potential blueprint for responsible, economically fair AI content integration.

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Global digital marketing leader Incubeta has unveiled two new agentic AI tools—Creative Performance Index (CPI) and OutperformBI—designed to help brands move beyond static dashboards and subjective decision-making. The goal: give marketers clearer insight into what actually drives performance across channels and campaigns.

“Marketing teams don’t lack data, they lack clarity,” said Max Flajsner, Global Director of Data and AI at Incubeta. “With CPI and OutperformBI, we use agentic AI to move beyond dashboards and deliver faster, more accurate insight into what’s actually driving performance and incremental impact.”

The launch comes at a time when generative AI is accelerating content production and consumer attention is increasingly fragmented. Marketing leaders are under growing pressure to prove ROI and prioritize spend effectively, making tools that diagnose performance drivers critical.

Creative Performance Index (CPI): Measuring Creative Impact

CPI uses AI to analyze creative assets at a granular level—looking at branding placement, calls to action, imagery, music, and emotional cues—and maps those elements to live performance data from advertising platforms. By continuously monitoring which creative components correlate with success, CPI helps brands:

• Reduce guesswork and creative fatigue

• Optimize testing and development roadmaps

• Connect creative quality directly to revenue outcomes

The platform integrates with major ad platforms to ingest creative assets and performance metrics, and its data can feed advanced measurement approaches such as marketing mix modeling and causal impact analysis.

Beta tests have already shown striking results. One brand saw a +102% click-through rate and a 37% reduction in cost per lead, while another achieved +87% conversion rate and a 38% increase in return on ad spend (ROAS).

OutperformBI: From Reporting to Root Cause Analysis

While CPI focuses on creative, OutperformBI provides a broader view of marketing performance. It connects multiple data streams—including marketing mix models, customer data platforms, product feeds, experimentation plans, promotional calendars, and external signals like search trends and weather—to help marketers diagnose why campaigns perform the way they do.

The platform uses a natural-language interface and AI-driven workflows to automate analysis, letting users move from answering “what happened” to understanding why outcomes occurred. This capability supports smarter media planning, budget allocation, executive reporting, and demand analysis.

“CPI and OutperformBI were built to address client requests for faster, better insights across larger, more complex data sets,” said Alex Langshur, CEO Americas at Incubeta. “Our roadmap is built from the ground up, shaped by the real challenges our clients ask us to solve daily, ultimately driving business growth.”

Why This Matters

Incubeta’s new tools reflect a growing trend in marketing: agentic AI that not only surfaces insights but diagnoses them across multiple data dimensions. As brands face increasingly fragmented channels and massive volumes of content, tools like CPI and OutperformBI promise to shift decision-making from intuition and spreadsheets to data-driven strategy and measurable business impact.

For marketers, this could mean faster optimization cycles, higher ROI, and more confident allocation of budgets, all while connecting creative performance directly to revenue.

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