As enterprise marketing teams face increasing pressure to prove return on investment (ROI), NEWMEDIA.COM is urging organizations to rethink how they evaluate paid media performance. In a newly released industry analysis, the digital marketing agency argues that traditional click-based metrics are no longer sufficient for complex B2B buying journeys, where success is determined by qualified pipeline, revenue impact, and the integration of paid media with SEO and AI-driven discovery.

The rapid evolution of B2B buying behavior is forcing marketers to reconsider how they measure advertising success. As buyers conduct more independent research across search engines, AI assistants, industry publications, and social platforms before engaging with sales teams, traditional paid media metrics such as clicks and impressions are becoming less meaningful indicators of business performance.

Against this backdrop, NEWMEDIA.COM has published a new analysis advocating for a pipeline-first approach to B2B performance marketing. The report argues that enterprise organizations should evaluate paid marketing investments based on qualified pipeline generation and return on investment rather than engagement metrics that often fail to correlate with revenue outcomes.

The analysis reflects a broader transformation occurring across enterprise marketing. In consumer advertising, campaign performance is frequently measured by cost per click (CPC), cost per acquisition (CPA), or other short-term engagement metrics. However, B2B purchasing cycles typically involve multiple stakeholders, longer sales processes, and significantly higher contract values, making click-based optimization less representative of actual business performance.

According to NEWMEDIA.COM, optimizing campaigns solely around low-cost clicks or form submissions can result in substantial advertising spend without generating qualified sales opportunities. Instead, the company argues that marketing teams should prioritize metrics such as cost per qualified lead, influenced pipeline, sales-qualified opportunities, and overall ROI.

The report identifies several common challenges affecting enterprise paid media strategies. These include broad keyword targeting that attracts low-intent audiences, campaign optimization focused on inexpensive conversions rather than qualified buyers, limited tracking beyond the initial click, and disconnected execution between paid advertising and long-term organic marketing initiatives.

These observations align with broader industry trends. As organizations deploy increasingly sophisticated marketing technology stacks, visibility across the entire customer journey has become a strategic requirement rather than a competitive advantage.

One of the report's central themes is that paid media delivers greater value when integrated with search engine optimization (SEO), content marketing, and AI visibility strategies instead of operating independently.

The company argues that paid advertising accelerates demand capture, while organic search and educational content establish long-term authority. Together, these channels reinforce one another by attracting high-intent audiences, improving content visibility, and generating first-party customer insights that support campaign optimization.

NEWMEDIA.COM also places significant emphasis on Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO), positioning AI visibility as an increasingly important component of enterprise marketing strategies.

As AI-powered search experiences become more common, buyers are increasingly obtaining product recommendations and vendor comparisons directly from conversational AI platforms before visiting company websites. The report suggests brands must optimize content not only for traditional search engines but also for AI-generated answers where purchase decisions are increasingly influenced.

This perspective reflects wider developments across the marketing technology industry. Forrester has identified generative AI as an increasingly important research channel for B2B buyers, while Gartner continues to report that modern enterprise buyers increasingly prefer self-directed purchasing journeys before interacting with sales representatives.

Similarly, Google has stated that creating helpful, authoritative, and well-structured content remains fundamental to both traditional search visibility and inclusion in AI-powered search experiences.

To support this strategy, NEWMEDIA.COM highlights its proprietary RankOS™ framework, which combines paid media, SEO, and AI visibility into a unified operating model. Rather than treating performance marketing as an isolated advertising function, the framework is designed to coordinate multiple acquisition channels around shared business objectives and pipeline measurement.

The company also cites examples from its client portfolio to demonstrate this integrated approach. According to NEWMEDIA.COM, extending conversion tracking beyond click-level metrics, refining keyword strategies, and aligning paid campaigns with organic content can improve qualified pipeline generation without requiring higher advertising budgets.

Beyond methodology, the company references its broader market experience, reporting more than 4,500 client engagements, work across 50-plus industries, and more than $3.5 billion in client revenue and enterprise value influenced. It also highlights third-party recognition from organizations including Clutch and UpCity.

For enterprise marketing leaders, the report reinforces an increasingly accepted principle across the MarTech industry: marketing performance can no longer be evaluated solely through platform-generated engagement metrics.

As customer journeys become more fragmented across search engines, AI assistants, publisher content, and digital communities, organizations are shifting toward measurement models that connect advertising investments directly to business outcomes. Increasingly, success depends on integrating paid media, first-party data, SEO, marketing analytics, and AI visibility into a unified growth strategy that supports measurable pipeline generation and sustainable revenue growth.

Market Landscape

Enterprise B2B marketing is moving away from channel-specific optimization toward integrated revenue operations. Paid media, SEO, AI search visibility, customer data platforms, and marketing analytics are increasingly managed as interconnected components of a single demand generation strategy. As AI-powered search reshapes buyer research, marketers are adopting pipeline-based attribution models that better reflect long buying cycles, multi-touch engagement, and revenue contribution rather than isolated campaign metrics.

Top Insights

• NEWMEDIA.COM argues that B2B marketing performance should be measured by qualified pipeline and ROI rather than clicks, impressions, or low-value conversions.
• The analysis recommends integrating paid media with SEO, content marketing, and AI visibility to improve long-term demand generation and marketing efficiency.
• The report highlights AEO and GEO as emerging disciplines that help brands appear within AI-generated answers as buyers increasingly research independently.
• The company advocates extending attribution beyond click tracking to connect advertising investments with qualified leads, pipeline, and business revenue.
• The findings reflect broader enterprise marketing trends emphasizing first-party data, revenue attribution, and AI-assisted customer discovery across complex buying journeys.

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As AI-powered search experiences continue to reshape how consumers discover products and brands, Awin has introduced new discovery intelligence capabilities designed to help marketers measure brand visibility beyond traditional clicks. The affiliate marketing technology platform announced a partnership with ScalePost alongside new platform features, including AI Visibility and Smart Search, aimed at giving advertisers and publishers greater insight into AI-driven customer journeys.

The rapid adoption of generative AI is transforming one of digital marketing's foundational metrics: the click.

As consumers increasingly receive answers directly from AI assistants and AI-powered search experiences, marketers are confronting a new reality where brand discovery often occurs without website visits or measurable click-throughs. To help advertisers navigate this evolving landscape, Awin has announced an expanded AI discovery intelligence strategy that combines new measurement capabilities with platform enhancements designed to improve visibility into AI-influenced customer journeys.

The company revealed a new partnership with ScalePost, together with new features including AI Visibility and Smart Search, as part of a broader effort to help brands understand how AI-generated experiences contribute to customer discovery, publisher influence, and business performance.

The announcement reflects one of the most significant shifts currently affecting digital marketing. AI-powered platforms, conversational search engines, and generative assistants are increasingly answering consumer questions directly, reducing the need for users to click through to publisher websites or brand-owned properties.

According to Awin, approximately two-thirds of Google searches now end without a click, highlighting the growing importance of zero-click search experiences. As a result, traditional performance metrics no longer capture the full customer journey, creating new challenges for marketing attribution and budget optimization.

For enterprise marketing teams, understanding where brands appear within AI-generated responses has become increasingly valuable as search behavior evolves.

To address this, Awin's partnership with ScalePost introduces an additional measurement layer focused on AI-generated discovery. Unlike many existing AI visibility tools that rely on simulated prompts or modeled datasets, the partnership uses first-party citation data to identify where brands are actually referenced within AI experiences.

This approach allows marketers to evaluate how publisher content contributes to AI-generated recommendations while providing greater transparency into the content influencing customer decisions.

The initiative is further supported through collaborations with Peec.ai and Profound, expanding Awin's ability to analyze AI-driven discovery across multiple stages of the customer journey. Together, the partnerships are intended to provide brands with a more comprehensive understanding of how AI, publishers, and content ecosystems interact before a purchase occurs.

Alongside these partnerships, Awin introduced two platform enhancements aimed at improving campaign optimization and partner discovery.

AI Visibility enables advertisers to monitor when brands appear within AI-powered experiences while identifying publisher content contributing to that exposure. For publishers, the capability offers greater recognition of how editorial content supports discovery and customer engagement, even when interactions occur without traditional referral clicks.

The company also launched Smart Search, a natural language-powered discovery tool that helps advertisers identify relevant publisher partners more efficiently. According to Awin, advertisers using Smart Search are twice as likely to invite publisher partners compared with traditional directory-based searches, suggesting AI-assisted partner discovery may reduce manual program management while accelerating affiliate growth.

The announcements reflect broader changes occurring across the affiliate marketing ecosystem. Historically, affiliate performance has been measured primarily through clicks, conversions, and last-click attribution. However, AI-generated search results, conversational commerce, and recommendation engines increasingly influence purchasing decisions before measurable interactions occur.

For brands, this shift is driving demand for new attribution models capable of recognizing influence across increasingly fragmented customer journeys.

Industry analysts have highlighted similar trends. According to Gartner, marketing organizations are rapidly reassessing performance measurement frameworks as AI reshapes customer engagement across search, commerce, and content platforms. Meanwhile, Forrester has emphasized that future marketing success will depend on connecting customer intent, content influence, and business outcomes across multiple digital touchpoints rather than relying solely on click-based attribution.

The evolution also reflects the growing importance of first-party data. As privacy regulations continue tightening and third-party cookies disappear from major browsers, marketers are increasingly prioritizing measurement approaches built around owned customer data, verified engagement, and transparent attribution.

Companies including Google, Microsoft, Adobe, and Salesforce are similarly expanding AI-powered search, customer intelligence, and marketing analytics capabilities as enterprise organizations seek greater visibility into AI-influenced customer behavior.

For affiliate marketers, publishers, and enterprise brands, measuring AI-driven discovery represents an emerging frontier in performance marketing. Understanding where brands appear within AI-generated recommendations—and which publishers influence those recommendations—may become as strategically important as traditional search rankings over the coming years.

As AI continues reshaping digital discovery, marketing success will increasingly depend on connecting visibility, influence, and conversion across a customer journey that extends well beyond the click.

Market Landscape

AI-powered search is redefining digital discovery by shifting customer engagement from traditional search engine results toward conversational interfaces, zero-click experiences, and AI-generated recommendations. This evolution is creating demand for new measurement frameworks that combine first-party data, attribution intelligence, publisher analytics, and AI visibility. Marketing technology vendors are increasingly investing in AI-powered analytics and discovery tools to help brands understand customer influence beyond conventional performance metrics.

Top Insights

• Awin has expanded its AI discovery strategy through a partnership with ScalePost and new platform capabilities that measure brand visibility across AI-powered customer experiences.
• The company introduced AI Visibility and Smart Search to help advertisers better understand publisher influence, AI citations, and partner discovery within evolving digital journeys.
• The new measurement approach relies on first-party citation data rather than modeled prompts, offering marketers greater transparency into AI-generated brand discovery.
• Collaborations with Peec.ai and Profound broaden Awin's visibility into AI-driven customer behavior and publisher contribution across fragmented marketing channels.
• The announcement reflects a wider industry transition toward zero-click search measurement, AI attribution, and first-party data strategies for enterprise marketing.

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Fast-casual restaurant chain Pollo Campero has appointed Karla Patino as Vice President of U.S. Marketing and Sales, strengthening its leadership team as the company accelerates its nationwide expansion strategy. The appointment comes as the brand surpasses 150 U.S. restaurants and advances its goal of reaching 250 locations by 2030, with a continued focus on engaging Hispanic consumers through culturally relevant marketing and localized growth initiatives.

As restaurant brands compete for consumer attention in an increasingly digital and culturally diverse marketplace, marketing leadership has become a critical driver of long-term growth. Pollo Campero, the Guatemalan-born fast-casual restaurant chain, has named Karla Patino as Vice President of U.S. Marketing and Sales, reinforcing its investment in brand expansion and customer engagement across the United States.

In her new role, Patino will oversee marketing and sales strategy for Campero USA, leading initiatives designed to deepen customer relationships, expand brand awareness, and strengthen the company's connection with U.S. Hispanic consumers. Her appointment aligns with Pollo Campero's broader expansion strategy as the company plans to increase its U.S. footprint from more than 150 restaurants today to approximately 250 locations by 2030.

The leadership change reflects a growing trend across the restaurant industry, where quick-service and fast-casual brands are increasingly investing in experienced marketing executives to support digital transformation, customer loyalty, and omnichannel engagement.

Patino brings nearly two decades of brand-building experience across several of the restaurant industry's largest global chains. Throughout her career, she has held senior marketing positions with Taco Bell, KFC, Burger King, Chipotle, and Subway, developing expertise in brand strategy, international market expansion, customer acquisition, and category growth.

Most recently, Patino served as Chief Marketing Officer for Taco Bell Latin America, where she led the brand's first international artist partnership through a Taco Tuesday campaign featuring Latin music artist Myke Towers. During her tenure within the Yum! Brands portfolio, she also helped lead business turnarounds for KFC operations across Colombia, Costa Rica, and Brazil while supporting new market expansion initiatives, including Taco Bell's entry into Ecuador.

Her appointment signals Pollo Campero's intention to strengthen its marketing capabilities during a period of accelerated growth. As restaurant competition intensifies, brands are increasingly differentiating themselves through customer experience, digital engagement, loyalty programs, and culturally relevant storytelling rather than menu innovation alone.

For Pollo Campero, cultural authenticity remains central to its positioning. Founded in Guatemala and widely recognized across Latin America, the company has steadily expanded its presence in the United States by serving both Hispanic communities seeking familiar flavors and broader consumer audiences exploring international cuisine.

The company's emphasis on Hispanic consumer engagement also reflects broader demographic and economic trends. According to McKinsey & Company, multicultural consumers continue to represent one of the fastest-growing drivers of consumer spending in the United States, making culturally informed marketing an increasingly important competitive advantage. Meanwhile, Statista projects continued growth across the U.S. quick-service restaurant market as brands invest in digital ordering, personalized marketing, and customer loyalty technologies.

For marketing organizations, leadership appointments such as Patino's increasingly extend beyond traditional advertising responsibilities. Modern restaurant marketing executives oversee omnichannel customer engagement strategies spanning mobile applications, loyalty programs, customer relationship management (CRM), digital advertising, social media, influencer partnerships, and localized community outreach.

Technology platforms from companies including Google, Adobe, Salesforce, and Microsoft continue to expand AI-powered marketing, customer analytics, and personalization capabilities that help restaurant brands better understand customer behavior and deliver more relevant experiences across digital and physical channels.

For growing restaurant chains like Pollo Campero, combining operational expansion with data-driven marketing will likely be essential to sustaining customer acquisition while strengthening long-term brand loyalty.

The company's ambitious expansion plan also underscores the continued growth opportunities within the U.S. fast-casual restaurant sector. As consumer preferences evolve toward convenience, digital ordering, and authentic culinary experiences, brands that successfully combine cultural heritage with modern marketing strategies are increasingly well positioned to compete against established national restaurant chains.

Patino's experience leading regional and international marketing initiatives across multiple global restaurant brands provides Pollo Campero with leadership expertise that supports both operational expansion and customer-centric brand development. As the company works toward its 2030 growth targets, marketing strategy will play an increasingly important role in differentiating the brand within the highly competitive quick-service restaurant landscape.

Market Landscape

Restaurant marketing is increasingly driven by digital customer engagement, loyalty ecosystems, AI-powered personalization, and first-party customer data. Quick-service and fast-casual brands are investing heavily in CRM platforms, mobile ordering, omnichannel marketing automation, and localized campaigns to improve customer retention and increase lifetime value. As multicultural audiences become a larger share of U.S. consumer spending, culturally relevant marketing strategies are becoming a key competitive differentiator for expanding restaurant brands.

Top Insights

• Pollo Campero has appointed Karla Patino as Vice President of U.S. Marketing and Sales to support brand expansion and strengthen engagement with Hispanic consumers.
• Patino brings nearly 20 years of marketing leadership experience across Taco Bell, KFC, Burger King, Chipotle, and Subway, including international market expansion expertise.
• The appointment supports Pollo Campero's objective of expanding from more than 150 U.S. restaurants to 250 locations by 2030.
• The company continues investing in culturally relevant marketing as Hispanic consumers become an increasingly influential segment within the U.S. restaurant industry.
• The leadership move reflects broader restaurant industry investments in digital marketing, customer experience, loyalty programs, and AI-powered personalization technologies.

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Scorpion has introduced the Franchise Marketing Playbook, a new resource developed for members of the International Franchise Association (IFA) to help franchise organizations improve marketing performance and align national strategies with local execution. Drawing on research from franchise executives, homeowners, and business owners, the playbook outlines data-driven frameworks for marketing governance, performance measurement, and franchise growth at a time when brands are increasingly investing in digital marketing and AI-powered customer engagement.

Franchise organizations have long faced a unique marketing challenge: balancing centralized brand consistency with the flexibility local operators need to compete in their individual markets. As customer acquisition becomes increasingly digital and marketing technology grows more sophisticated, aligning national strategy with local execution has become a strategic priority for franchise systems.

Against this backdrop, Scorpion, a provider of digital marketing and technology solutions for franchise businesses, has released its Franchise Marketing Playbook, a strategic guide created for members of the International Franchise Association (IFA). The playbook is designed to help franchise brands establish measurable marketing standards, improve operational alignment, and strengthen local growth through data-driven decision-making.

The resource follows Scorpion's designation as the IFA's preferred vendor in the National and Local Digital Marketing Lead Generation category, reflecting the growing role technology providers are playing in modern franchise marketing ecosystems.

Rather than focusing solely on campaign tactics, the playbook examines how franchise organizations can build scalable marketing operations that connect corporate leadership with franchise owners through shared objectives, performance metrics, and reporting frameworks.

The research underpinning the guide combines insights from more than 100 franchise brand leaders with consumer surveys involving over 2,000 homeowners and 1,000 business owners. Together, the findings offer a snapshot of the operational challenges many franchise systems continue to face as digital marketing becomes increasingly performance-driven.

One of the report's most notable findings is that half of franchise brands rated their own marketing performance as a C grade or lower, suggesting many organizations recognize significant room for improvement. One-third of respondents reported ongoing challenges in aligning marketing with other internal business functions, while 25% acknowledged lacking the key performance indicators (KPIs), reporting capabilities, or operational infrastructure needed to make confident marketing decisions.

The study also identifies several characteristics shared by higher-performing franchise organizations.

Brands responding to prospective customers within 30 minutes or less reported same-store sales improvements at a rate 66% higher than slower-response organizations among businesses experiencing growth exceeding 5%. The findings reinforce a growing body of research demonstrating the importance of speed-to-lead in digital customer acquisition, particularly for service-based businesses where response time often influences conversion rates.

Marketing governance also emerged as a differentiator. Nearly nine in ten franchise brands that evaluated their marketing performance positively reported reviewing marketing strategies at least once each month. Regular performance reviews enable organizations to adapt campaigns, monitor customer behavior, and optimize investments more effectively in rapidly changing digital markets.

Investment levels likewise appeared to influence business outcomes. According to the research, 70% of brands reinvesting more than 5% of monthly revenue into marketing experienced improvements in same-store sales, suggesting sustained marketing investment continues to play an important role in long-term franchise growth.

Perhaps the most significant operational insight concerns collaboration between corporate leadership and local franchise operators. Franchise systems that develop marketing strategies jointly with franchisees reported same-store sales growth exceeding 5% at three times the rate of organizations where headquarters independently determines marketing direction.

The findings reflect a broader shift within franchise marketing, where centralized brand governance increasingly coexists with localized personalization supported by marketing technology platforms.

The playbook also highlights changing consumer expectations. According to Scorpion's consumer research, 83% of consumers begin searching for service providers online, reinforcing the importance of digital visibility across search engines, local listings, and online review platforms. Meanwhile, 65% indicated openness to AI-assisted customer intake experiences, suggesting growing consumer acceptance of conversational AI, automated scheduling, and virtual customer service technologies.

These trends mirror wider developments across the MarTech industry. According to Gartner, organizations continue increasing investments in customer experience technologies, marketing automation, and AI-powered engagement platforms to improve acquisition efficiency and customer retention. McKinsey & Company has similarly reported that companies delivering personalized customer experiences consistently outperform peers in revenue growth and customer satisfaction.

For franchise organizations, these developments are accelerating demand for integrated marketing platforms capable of connecting national campaigns, local execution, customer relationship management, analytics, and AI-driven customer engagement.

Technology providers including Google, Microsoft, Salesforce, and Adobe continue expanding AI-powered marketing capabilities that help multi-location businesses personalize customer interactions while maintaining centralized governance. Franchise systems increasingly require similar capabilities to ensure local operators can execute campaigns efficiently without compromising brand consistency.

The release of the Franchise Marketing Playbook reflects this evolution. Rather than treating franchise marketing as a collection of independent campaigns, the guide positions marketing as a coordinated operational function built around shared KPIs, transparent reporting, first-party customer data, and collaborative decision-making.

As digital channels continue to dominate customer acquisition, franchise brands that successfully combine centralized strategy with localized execution may be better positioned to improve customer engagement, strengthen franchisee performance, and support sustainable long-term growth.

Market Landscape

Franchise marketing is evolving from decentralized advertising toward integrated digital marketing ecosystems that combine local SEO, customer relationship management, AI-powered marketing automation, analytics, and first-party data. Multi-location businesses increasingly seek unified MarTech platforms that balance national brand governance with localized customer engagement. As AI becomes more prevalent across marketing operations, franchise organizations are prioritizing measurable KPIs, standardized reporting, and collaborative marketing strategies to improve customer acquisition and franchise profitability.

Top Insights

• Scorpion's Franchise Marketing Playbook provides IFA members with data-driven strategies for aligning national marketing initiatives with local franchise execution and measurable business growth.
• The research found half of franchise brands rated their marketing performance as average or below, highlighting opportunities to improve KPIs, reporting, and organizational alignment.
• Brands responding to customer inquiries within 30 minutes reported substantially stronger same-store sales growth, reinforcing the business value of speed-to-lead strategies.
• Organizations collaborating closely with franchisees on marketing strategy achieved significantly higher sales growth than brands relying solely on corporate-led decision-making.
• Consumer research indicates online search and AI-assisted customer interactions are becoming increasingly influential in franchise customer acquisition and engagement strategies.

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As enterprise marketers increase investment in digital advertising, a new executive brief from Anura argues that artificial intelligence is reshaping one of the industry's most persistent challenges: ad fraud. The report warns that AI-assisted fraudulent traffic is rapidly contaminating marketing data, reducing campaign effectiveness, and making it harder for chief marketing officers (CMOs) to accurately measure return on advertising spend (ROAS) and business growth.

Digital advertising has become one of the largest areas of enterprise marketing investment, with global spending exceeding $750 billion in 2025. Yet a growing share of that investment may never reach legitimate audiences. According to a new executive brief from Anura, AI-powered ad fraud is evolving at a pace that traditional fraud detection methods are struggling to match, creating significant financial and operational risks for marketers.

The report, Stop Blaming Your Marketing Strategy. The Problem Is Your Data., argues that the industry's biggest challenge is no longer simply fraudulent clicks or fake impressions. Instead, AI-assisted fraud is increasingly corrupting the marketing data organizations depend on to evaluate campaign performance, optimize spending, and make strategic business decisions.

Anura estimates advertisers lost approximately $165 billion to ad fraud during 2025, positioning invalid traffic as one of the largest hidden costs in digital marketing. According to the company's traffic analysis across millions of webpages and major advertising channels, fraud rates remained between 25% and 28% throughout much of 2025. By June 2026, however, invalid traffic had risen to 40%, representing nearly a 50% increase in just six months.

The findings point to a rapidly changing threat landscape driven by generative AI technologies. Tasks that previously required highly specialized development expertise can now be automated using widely accessible AI tools, lowering the barrier for fraudsters to launch increasingly sophisticated attacks against advertising platforms.

For marketing leaders, the consequences extend well beyond wasted media budgets.

Modern digital marketing strategies rely heavily on performance data generated by platforms such as Google Ads, Meta Ads, Microsoft Advertising, and programmatic advertising ecosystems. These platforms continuously optimize campaigns using engagement signals including impressions, clicks, conversions, session duration, and attribution data.

When fraudulent traffic enters those systems, optimization algorithms may begin making decisions based on invalid user behavior rather than genuine customer intent. As a result, marketers can experience declining return on ad spend (ROAS), lower lead quality, inflated conversion metrics, and customer acquisition strategies that appear successful in dashboards but fail to translate into revenue growth.

The report argues that this creates a dangerous feedback loop. AI-powered optimization systems become increasingly effective only when trained on accurate data. If that underlying data is compromised, campaign automation may amplify poor decisions rather than improve performance.

Anura also highlights how AI has accelerated the sophistication of fraud operations. The company says it identified a new Sophisticated Invalid Traffic (SIVT) attack during late 2025 that successfully bypassed many traditional JavaScript-based fraud detection techniques commonly used across the advertising ecosystem.

Following its discovery, Anura developed updated detection capabilities designed to identify and mitigate the attack. The incident illustrates how fraud prevention vendors are increasingly engaged in an ongoing technological arms race as attackers leverage AI to develop faster and more adaptive fraud methods.

The report arrives as enterprise organizations continue expanding investments in AI-driven marketing technologies. According to Gartner, CMOs are increasingly prioritizing AI-enabled analytics, marketing automation, and customer intelligence platforms to improve efficiency and campaign performance. Meanwhile, Statista projects continued growth in worldwide digital advertising investment as brands allocate larger portions of marketing budgets toward digital channels.

That combination of increased spending and greater automation raises the stakes for data integrity. Fraudulent traffic no longer represents only a media buying issue—it also threatens attribution models, predictive analytics, audience segmentation, customer journey analysis, and machine learning systems that rely on high-quality behavioral data.

The findings reinforce an emerging priority across enterprise MarTech: independent data validation. Rather than relying solely on platform-generated metrics, organizations are increasingly evaluating third-party fraud detection, traffic verification, and measurement solutions capable of identifying invalid traffic before it influences optimization decisions.

The report also reflects broader industry concerns surrounding first-party data quality. As privacy regulations evolve and third-party cookies continue to decline, marketers are placing greater emphasis on trusted customer data. AI-generated fraudulent interactions undermine those efforts by introducing inaccurate behavioral signals into customer data platforms, analytics systems, and attribution models.

For enterprise marketing teams, the message is increasingly clear: protecting advertising budgets now requires protecting the integrity of the underlying data powering marketing decisions.

As AI becomes more deeply embedded across advertising technology, campaign optimization, and customer analytics, organizations may need to treat fraud prevention not simply as a cybersecurity function but as a core component of marketing performance management.

The report concludes that without stronger fraud detection strategies and independent traffic validation, financial losses from ad fraud could exceed the company's estimated $165 billion annual impact, while organizations risk making increasingly expensive business decisions based on compromised marketing intelligence.

Market Landscape

AI is reshaping both digital marketing and digital advertising fraud. As advertising platforms automate bidding, targeting, attribution, and optimization using machine learning, the quality of marketing data has become a strategic competitive asset. Enterprise advertisers are increasingly investing in fraud prevention, traffic validation, first-party data strategies, and independent measurement platforms to protect campaign performance. Vendors that combine AI-powered fraud detection with transparent analytics are expected to play a growing role as organizations seek trustworthy marketing intelligence across increasingly automated MarTech and AdTech ecosystems.

Top Insights

• Anura estimates advertisers lost approximately $165 billion to ad fraud in 2025, highlighting the growing financial impact of AI-assisted fraudulent traffic on enterprise marketing investments.
• The report found invalid traffic increased from roughly 25–28% during 2025 to 40% by June 2026, signaling rapidly accelerating AI-powered fraud activity.
• Fraudulent traffic increasingly contaminates campaign metrics, causing AI-driven optimization systems to make inaccurate decisions that reduce ROAS and lead quality.
• Anura identified a Sophisticated Invalid Traffic (SIVT) attack capable of bypassing conventional JavaScript-based detection methods, underscoring the evolving nature of advertising fraud.
• The research emphasizes independent traffic validation and advanced fraud prevention as essential components of modern enterprise marketing and advertising strategies.

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Lightspeed Commerce has expanded its partnership with Klaviyo by launching a new integration that embeds automated email, SMS, and omnichannel marketing capabilities into the Lightspeed Retail platform. The integration enables retailers to synchronize customer, sales, and product data in real time, allowing marketing campaigns to be triggered automatically based on customer behavior across both physical and online stores.

As retailers increasingly prioritize customer retention and personalized engagement, marketing automation is becoming a core capability rather than an optional add-on. Lightspeed Commerce has announced an expanded partnership with Klaviyo designed to simplify how merchants deliver personalized marketing by integrating customer relationship management and automation directly into the Lightspeed Retail platform.

The new integration enables retailers to connect operational commerce data with automated marketing workflows, eliminating the need to manually export customer information or manage multiple disconnected systems. By synchronizing customer profiles, purchase history, product catalogs, and promotional offers in real time, businesses can create personalized campaigns that respond automatically to customer activity.

The announcement reflects a broader shift across the retail technology market, where commerce platforms are evolving into unified ecosystems that combine point-of-sale, inventory management, customer data, and marketing automation. Rather than relying on separate applications for commerce and customer engagement, retailers are increasingly seeking integrated platforms that streamline operations while improving customer lifetime value.

With the integration, merchants using Lightspeed Retail can deploy automated lifecycle marketing campaigns including welcome emails, post-purchase follow-ups, abandoned customer re-engagement programs, and targeted promotional messages delivered through email, SMS, and other supported communication channels. Because the platform continuously synchronizes store and ecommerce activity, campaigns can respond to real-time customer behavior without requiring manual intervention.

Marketing automation has become increasingly important as retailers seek to improve customer retention while managing rising acquisition costs. According to Gartner, acquiring new customers typically costs significantly more than retaining existing ones, prompting many retailers to increase investment in customer lifecycle marketing and personalization strategies. Meanwhile, McKinsey & Company reports that companies excelling at personalization can generate 40% more revenue from those activities compared with slower-moving competitors.

The partnership positions Lightspeed to strengthen its omnichannel commerce offering by extending beyond retail operations into customer engagement. Instead of functioning solely as a commerce management platform, Lightspeed now enables merchants to activate first-party customer data directly within marketing campaigns.

For enterprise retailers and growing brands, the integration also addresses a common challenge within modern MarTech environments: fragmented customer data. Many organizations operate separate systems for ecommerce, point-of-sale, email marketing, loyalty programs, and customer relationship management. These disconnected environments often create data silos that delay campaign execution and limit personalization.

By connecting operational and marketing data through a single workflow, merchants can automatically segment audiences based on purchasing behavior, shopping frequency, product preferences, and historical transactions. This enables more relevant communications while reducing the manual effort traditionally associated with campaign management.

The integration may prove particularly valuable for retailers operating in high-frequency purchasing categories such as apparel, footwear, beauty, and specialty retail, where repeat purchases play a significant role in long-term profitability. Automated replenishment reminders, loyalty promotions, personalized recommendations, and post-purchase engagement can all contribute to stronger customer retention and higher lifetime value.

The announcement also reflects broader competitive trends within the retail technology landscape. Major enterprise platforms from companies including Salesforce, Adobe, Shopify, and Microsoft continue expanding AI-powered marketing capabilities alongside unified customer data platforms. As retailers demand more connected digital infrastructure, software vendors are increasingly building deeper integrations rather than offering isolated point solutions.

From a technology perspective, the integration leverages first-party commerce data—customer profiles, transaction history, product information, and promotional offers—to automate marketing decisions in real time. This approach aligns with the industry's continued transition toward first-party data strategies as businesses adapt to evolving privacy regulations and the gradual decline of third-party tracking technologies.

For marketing teams, the integration reduces reliance on manual data transfers while improving campaign speed and consistency. Marketing automation platforms are increasingly expected to support personalized customer journeys across multiple channels without requiring technical expertise or complex workflow configuration.

The collaboration also underscores the growing convergence between commerce technology and customer relationship management. As AI-powered marketing, predictive analytics, and customer data platforms become more interconnected, retailers are seeking unified solutions capable of supporting both operational efficiency and long-term customer engagement.

With customer experience continuing to influence purchasing decisions, integrated commerce and marketing platforms are becoming a strategic investment for retailers looking to build stronger relationships while improving marketing performance through automation and real-time customer intelligence.

Market Landscape

Retail technology is moving toward unified commerce platforms that combine point-of-sale systems, ecommerce, customer data, CRM, marketing automation, and analytics within a connected ecosystem. As first-party data becomes increasingly valuable, retailers are prioritizing platforms capable of activating customer insights across every touchpoint. Integrations between commerce platforms and marketing automation vendors are becoming a key differentiator as businesses seek to improve personalization, reduce operational complexity, and increase customer lifetime value through AI-assisted engagement.

Top Insights

• Lightspeed and Klaviyo have expanded their partnership to integrate marketing automation directly into Lightspeed Retail, enabling retailers to automate personalized customer engagement using real-time commerce data.
• The integration synchronizes customer profiles, order history, product catalogs, and promotions automatically, reducing manual data management while improving omnichannel marketing execution.
• Retailers can launch lifecycle campaigns including welcome journeys, post-purchase communications, and customer re-engagement workflows across email and SMS from a unified platform.
• The partnership supports first-party data activation, helping retailers strengthen customer retention strategies while simplifying marketing operations and improving customer lifetime value.
• The announcement reflects growing demand for unified commerce and MarTech ecosystems that connect operational data with AI-powered marketing automation and customer relationship management.

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Artificial intelligence has become deeply embedded in enterprise marketing workflows, but new research from Optimizely suggests the technology is introducing an unexpected productivity challenge. According to a global survey of more than 2,000 marketing leaders, the time saved by AI-generated content is increasingly being offset by the effort required to review, fact-check, edit, and align outputs with brand standards. The findings highlight a growing disconnect between executive expectations of AI efficiency and the operational realities experienced by marketing teams.

Artificial intelligence has rapidly evolved from an experimental capability into a core component of modern marketing technology stacks. Organizations now rely on AI to accelerate content production, campaign planning, personalization, analytics, and workflow automation. Yet despite widespread adoption, a new global study from Optimizely indicates that many enterprise marketing teams are encountering an operational bottleneck that could limit AI's long-term productivity gains.

The company's latest research, based on responses from more than 2,000 marketing leaders across seven international markets, introduces the concept of a growing "revision tax"—the additional time marketers spend reviewing, correcting, and refining AI-generated content before it becomes suitable for publication.

The research suggests that AI adoption is no longer the primary challenge for enterprise marketing organizations. Instead, the focus is shifting toward governance, workflow integration, and maintaining brand quality as AI-generated content becomes increasingly common.

According to the study, 76% of marketers spend at least three hours each week editing, fact-checking, or correcting AI-generated outputs. Nearly half of respondents (48%) identified hallucination reviews and factual verification as the largest source of additional work, while 40% cited the inefficiencies created by moving content across disconnected marketing platforms.

These findings reflect a broader challenge facing enterprise marketing operations. While generative AI can accelerate content creation, fragmented technology ecosystems often introduce manual review processes that reduce overall efficiency. Organizations using multiple AI applications alongside customer relationship management, content management, and digital asset management platforms may inadvertently create additional operational complexity instead of eliminating it.

The research also reveals how increasing pressure to publish content quickly is influencing editorial standards. One-quarter of respondents acknowledged they frequently publish AI-generated content that they know does not fully align with brand guidelines when deadlines become difficult to meet. Meanwhile, 30% admitted they regularly present AI-generated work as entirely human-created.

Perhaps more notably, only 4% of marketers reported that AI saves time throughout every stage of the content lifecycle. Just 19% said their organization operates from a single integrated AI platform, highlighting the fragmented nature of today's enterprise marketing technology environment.

The study also exposes a widening perception gap between executive leadership and operational marketing teams.

While 69% of C-suite executives believe AI adoption is fully aligned across their organizations, only 27% of marketing analysts share that assessment. Similarly, senior leadership expressed significantly greater confidence in organizational AI transparency than employees responsible for daily campaign execution.

This discrepancy suggests many executives continue to measure AI success primarily through deployment metrics or content volume, whereas frontline marketers remain focused on the additional effort required to validate AI-generated work before publication.

The findings further indicate differing attitudes toward AI usage itself. Among C-suite respondents, 44% said they frequently present AI-generated work as their own, compared with just 23% of marketing managers. The data illustrates how AI adoption is influencing workplace norms and raises broader questions around transparency, governance, and editorial accountability.

The research also suggests organizations remain cautious about accelerating AI deployment without stronger operational controls. Nearly two-thirds (65%) of respondents said they would pause or adjust their company's AI rollout if given the opportunity to strengthen governance frameworks, improve oversight, or redesign existing workflows.

Beyond operational efficiency, the report raises concerns about AI's long-term impact on creativity and strategic marketing.

Almost four in ten marketers (39%) reported spending so much time managing AI workflows and production processes that they have less opportunity to focus on strategic planning or campaign innovation. Meanwhile, 46% believe heavy reliance on AI could hinder creative skill development among junior marketing professionals.

Brand differentiation also emerged as a significant concern. Only 30% of respondents believe their organization's brand voice is genuinely distinctive, while 53% said current AI systems successfully reproduce factual brand information but struggle to communicate emotional nuance or authentic storytelling. More than half of respondents also expressed concerns that widespread AI adoption may contribute to increasing similarity across marketing content.

These findings align with broader industry discussions surrounding generative AI maturity. According to McKinsey & Company, generative AI has the potential to contribute $4.4 trillion annually to the global economy across industries, provided organizations successfully redesign workflows rather than simply automate existing tasks. Meanwhile, Gartner has consistently emphasized that enterprise AI success depends as much on governance, process redesign, and organizational change as on model performance itself.

For enterprise marketing leaders, the Optimizely research reinforces an important shift in AI strategy. Competitive advantage is likely to depend less on producing higher volumes of AI-generated content and more on integrating AI into connected marketing ecosystems that preserve human oversight, brand consistency, and creative differentiation.

As enterprise MarTech stacks continue to evolve alongside platforms from companies such as Google, Microsoft, Adobe, and Salesforce, organizations are increasingly prioritizing AI orchestration, unified workflows, and governance capabilities over standalone content generation tools.

Rather than replacing marketers, the next phase of enterprise AI adoption appears increasingly focused on enabling marketing teams to spend less time managing technology and more time developing strategy, customer insight, and differentiated brand experiences.

Market Landscape

The findings arrive as enterprise organizations accelerate investments in AI-powered marketing platforms while simultaneously confronting growing governance challenges. Modern marketing departments increasingly operate across customer data platforms, content management systems, marketing automation platforms, analytics solutions, and generative AI applications. Without unified workflows, these disconnected environments can introduce significant operational friction.

The study highlights an emerging industry trend: enterprise AI maturity is shifting beyond content generation toward AI governance, workflow orchestration, brand safety, and integrated MarTech infrastructure. Vendors capable of combining AI generation with enterprise-grade governance and cross-platform integration are likely to gain a competitive advantage as organizations seek to reduce manual review cycles while maintaining compliance and brand consistency.

Top Insights

• Optimizely's global survey found that 76% of marketers spend several hours weekly editing AI-generated content, highlighting a growing productivity challenge despite widespread AI adoption.
• Executive leadership views AI implementation more positively than operational marketing teams, revealing significant organizational alignment and governance gaps affecting enterprise AI strategies.
• Fragmented AI ecosystems continue to increase manual review work, with only 19% of organizations operating from a unified AI platform that streamlines enterprise marketing workflows.
• Marketers increasingly worry AI may reduce opportunities for strategic thinking, creative development, and authentic brand differentiation despite improving content production speed.
• The research suggests future AI success will depend more on governance, integration, and workflow optimization than simply expanding content generation capabilities.

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Enterprise customer experience platforms are increasingly evolving into unified AI-powered ecosystems that connect customer data, engagement, and analytics across business functions. Reflecting this shift, Sprinklr has been recognized as an Exemplary Provider in the 2026 ISG Buyers Guide™ for Customer Experience Management (CXM), highlighting the growing importance of AI-native platforms that enable organizations to manage the entire customer lifecycle from a single system.

Customer experience has become one of the primary competitive differentiators for enterprise organizations. As customer interactions span websites, contact centers, social media, messaging platforms, mobile applications, and digital commerce channels, businesses are increasingly replacing disconnected customer engagement tools with unified customer experience management platforms.

Sprinklr announced that it has been named an Exemplary Provider in the 2026 ISG Buyers Guide™ for Customer Experience Management and recognized as a Leader in Capability, placing it among only three vendors to receive that distinction in the latest evaluation.

The recognition comes as enterprise organizations continue modernizing customer engagement through AI-powered platforms capable of orchestrating customer journeys, automating workflows, and delivering consistent experiences across multiple channels.

According to ISG Research, this year's evaluation assessed customer experience management providers based on their ability to satisfy enterprise requirements across two primary dimensions: product experience—including platform capabilities—and customer experience. Sprinklr scored above the median in both categories, resulting in its placement within the Buyers Guide's highest "Exemplary" classification.

The recognition reflects broader changes taking place across the customer experience technology market.

Organizations have traditionally relied on separate applications for customer service, social media management, marketing, contact centers, conversational AI, employee collaboration, and analytics. These fragmented technology environments often create inconsistent customer experiences while making it difficult for organizations to maintain a unified view of customer interactions.

Enterprise software providers are increasingly responding by consolidating these functions into unified customer experience platforms built around artificial intelligence, centralized customer data, and workflow automation.

Sprinklr positions its Unified Customer Experience Management (Unified-CXM) platform as an AI-native environment designed to connect customer engagement, analytics, workflow orchestration, and decision-making across front-office operations.

Rather than managing customer interactions within isolated business units, organizations can coordinate marketing, customer service, digital engagement, and contact center operations through a common platform supported by shared data and AI-powered insights.

ISG Research notes that the customer experience management market is transitioning from department-centric software toward integrated platforms capable of supporting journey orchestration, lifecycle analytics, and AI-driven decision-making.

That transition aligns with broader enterprise technology trends.

Companies including Google, Microsoft, Salesforce, Adobe, and Amazon continue expanding AI-powered customer engagement capabilities across their cloud platforms, integrating generative AI, conversational assistants, predictive analytics, and workflow automation to improve enterprise customer experiences.

Sprinklr's platform addresses similar objectives by providing organizations with unified visibility into customer interactions while enabling AI-powered recommendations, automation, and operational coordination across customer-facing teams.

Industry analysts increasingly view this level of integration as essential for organizations seeking to improve customer satisfaction while reducing operational complexity.

According to Gartner, enterprises are prioritizing AI-enabled customer experience technologies capable of delivering personalized, contextual interactions across every stage of the customer journey. Meanwhile, Forrester continues to identify unified customer data and cross-functional customer engagement as foundational capabilities for modern customer experience strategies.

The latest ISG Buyers Guide also emphasizes governance, reliability, and integrated application architecture as key evaluation criteria for enterprise buyers. Rather than assembling customer engagement solutions from numerous independent products, organizations increasingly seek platforms that simplify deployment, reduce administrative overhead, and maintain consistent governance across customer interactions.

For marketing organizations, these developments reinforce the growing convergence of marketing technology, customer service, digital experience, and artificial intelligence.

Modern customer experience platforms now extend beyond traditional CRM capabilities by combining customer data, omnichannel communications, AI-powered analytics, workflow automation, and decision intelligence into unified operational environments capable of supporting the complete customer lifecycle.

As organizations continue investing in AI-native customer engagement strategies, independent industry evaluations such as the ISG Buyers Guide provide insight into how enterprise software providers are adapting to changing customer expectations and increasingly complex digital ecosystems.

Sprinklr's recognition illustrates the broader evolution of customer experience management from collections of disconnected engagement tools toward unified AI-powered platforms designed to help enterprises coordinate customer interactions, improve operational efficiency, and deliver more consistent experiences across every digital touchpoint.

Market Landscape

The Customer Experience Management (CXM) market is rapidly shifting toward AI-native, unified platforms that integrate marketing, customer service, contact centers, analytics, and workflow automation. Gartner identifies customer experience and AI-driven decision intelligence as strategic priorities for enterprise digital transformation, while Forrester highlights unified customer engagement platforms as essential for delivering consistent omnichannel experiences. As organizations reduce reliance on fragmented technology stacks, integrated CXM platforms are becoming central to enterprise customer engagement strategies.

Top Insights

• Sprinklr has been recognized as an Exemplary Provider in the 2026 ISG Customer Experience Management Buyers Guide and named a Capability Leader among enterprise CXM vendors.
• The recognition reflects increasing enterprise demand for unified AI-native platforms that integrate customer engagement, analytics, workflow automation, and journey orchestration.
• ISG Research highlights a market transition from fragmented customer experience tools toward centralized platforms built on governed customer data and artificial intelligence.
• Sprinklr's Unified-CXM platform is designed to connect front-office operations through shared customer intelligence, enabling more consistent omnichannel customer experiences.
• Independent analyst evaluations continue to emphasize AI, unified data, governance, and integrated application architecture as key differentiators in enterprise customer experience platforms.

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