Parloa has made its Agent Management Platform available as an SAP Solution Extension under the name SAP Conversational Agent Management by Parloa, bringing its agentic AI technology into SAP's customer experience ecosystem. The integration is designed to help enterprises deploy and manage AI agents across customer service channels while connecting conversations to SAP data and business processes. The announcement reflects a broader shift in enterprise customer experience management: moving beyond chatbots that answer questions toward AI agents that can resolve customer issues, personalize interactions, and hand complex cases to human employees with relevant context intact.

SAP integration puts business context behind AI conversations

The key proposition is the connection between conversational AI and the enterprise systems that manage customer accounts, cases, orders, and service processes. Instead of operating as a standalone chatbot, Parloa's platform is designed to let AI agents use relevant SAP data and business context during customer interactions.

The integration supports voice and other customer channels, with the aim of enabling agents to resolve routine requests and transfer more complex cases to human employees with a summary of the conversation. That handoff is important in service environments where customers expect continuity rather than having to repeat information.

The announcement also gives the product a route into SAP's existing customer base. As an SAP Solution Extension, the platform has undergone the company's qualification process and is supported through available SAP support services. This can simplify vendor evaluation for organizations already invested in SAP Customer Experience, although buyers should still verify integration scope, licensing, deployment requirements, and support responsibilities.

Customer service AI faces a trust test

The move comes as enterprises rethink the role of conversational AI. Gartner reported in July 2026 that customers were approximately three times more likely to use third-party generative AI tools than company-provided chatbots when resolving customer service issues. Its research suggests that customers increasingly expect AI to help complete tasks, not just answer questions.

That creates an opening for agentic systems that connect natural-language conversations to business processes. A customer asking about an order, for example, needs more than a fluent response: the system may need to retrieve the order status, check relevant policies, initiate an action, or escalate the issue.

But more autonomy raises the stakes around permissions, data access, accuracy, and accountability. Gartner also found that 87% of surveyed customers considered access to a human agent essential when companies use generative AI in customer service.

Parloa's customer Fressnapf, a European pet retail business, says its voice agent resolves customer questions and issues and provides employees with a short summary when a handoff is needed. The example illustrates how AI can support human service teams rather than simply attempt to replace them. The company has not disclosed quantified outcomes from this deployment in the announcement.

Market Landscape

Parloa competes in a growing enterprise conversational AI market alongside platforms such as Google Cloud's Contact Center AI, Microsoft Dynamics 365 Contact Center, and specialist providers including NICE and Genesys. Their capabilities differ, spanning voice automation, contact center infrastructure, agent assistance, analytics, and customer engagement.

Parloa's positioning is its focus on managing AI agents across customer interactions, combined with its expanding relationship with SAP. That could appeal to enterprises seeking to connect customer-facing automation with SAP-based business data and processes rather than build multiple integrations independently.

The SAP Solution Extension designation adds distribution and support advantages within the SAP ecosystem, but does not establish that Parloa outperforms alternatives. Buyers should compare supported workflows, integration depth, language coverage, operational controls, pricing, and the quality of human handoffs against their own requirements.

Strategic Outlook

The next phase of enterprise customer experience AI will depend on whether agents can complete useful tasks reliably within governed business workflows. Connecting conversation systems to enterprise data is a necessary step, but it does not guarantee accurate resolutions or a better customer experience.

For SAP customers, Parloa's availability provides another option for bringing voice and conversational automation into customer engagement operations. Its long-term value will depend on measurable improvements in resolution rates, customer satisfaction, service costs, and employee productivity—while preserving customers' ability to reach a person when needed.

Top Insights

• SAP integration: Parloa's Agent Management Platform is now an SAP Solution Extension, giving SAP Customer Experience customers another route to deploy conversational AI agents.

• Agentic AI: The platform aims to move beyond scripted chatbots by connecting customer conversations with enterprise data, context, and operational workflows.

• Human handoffs: Fressnapf's use case highlights AI-assisted voice support that resolves routine issues and passes conversation summaries to employees when escalation is needed.

• Market demand: Gartner found customers were three times more likely to use third-party GenAI than company-provided chatbots for service issues, underscoring the need for more useful customer-facing AI.

   

• Enterprise governance: Buyers must assess permissions, data security, auditability, escalation policies, and resolution quality before expanding autonomous customer service.

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Australian-founded advertising technology company Cuttable is expanding its AI-powered creative platform in the United States, aiming to address a persistent problem in performance marketing: determining which advertisement to create next. The platform connects AI-generated ad production with campaign performance data from Meta, allowing marketers to use historical results to inform future creative decisions. The announcement comes as the company reports that the U.S. now accounts for 40% of its revenue, just one year after entering the market, and as brands seek ways to increase advertising output without losing sight of campaign performance.

From ad generation to a continuous feedback loop

Cuttable's platform combines several stages of the advertising workflow that are often handled by separate tools. It analyzes a brand's website, social channels, and guidelines to create an editable brand strategy and brand kit. Marketers can then write briefs in plain language and generate editable advertisements using existing product assets or Shoots, the company's AI tool for creating and extending photo and video content.

The platform also connects directly to Meta Ads Manager, publishing finished ads and retrieving performance indicators such as click-through rate, thumbstop rate, and return on ad spend (ROAS). These results inform subsequent creative briefs, allowing marketers to develop new variations based on previous campaign performance.

The distinction matters because generating more ads does not necessarily produce better advertising. Performance teams still need to identify which messages, formats, and creative approaches resonate with their audiences. Cuttable's approach attempts to connect that analysis directly to production, reducing the manual work between campaign reporting and the next round of testing.

The company says its platform has processed more than 280,000 ads and over $320 million in Meta advertising spend. Its analysis found that roughly one in 11 ads generated returns of at least 10 times their spend, suggesting that performance can be concentrated among a relatively small number of creative assets. These figures are company-reported findings, rather than independently audited industry benchmarks.

Funding supports a larger U.S. push

The platform announcement coincides with Cuttable's latest funding round, an A$20 million Series A led by Australian venture capital firm Airtree Ventures. Existing investor Square Peg also participated, according to a separate company announcement.

Cuttable says it now serves more than 420 brands across the United States, Australia, New Zealand, Asia, and Europe, including lululemon, Rodan & Fields, and Brick. The company reports that the U.S. contributes 40% of its revenue and says it is expanding its San Francisco team.

The business was founded by Sam Kroonenburg, who previously co-founded online technology education company A Cloud Guru, acquired in 2021. The experience gives Cuttable's leadership a background in scaling a software business, although success in a different category does not guarantee adoption in the crowded marketing technology market.

Competition is moving beyond creative generation

Cuttable operates in a market that includes creative generation tools such as AdCreative.ai, creative analytics platforms such as Motion, and broader advertising automation products such as Smartly. Meta also offers its own AI-assisted creative capabilities within its advertising ecosystem.

Cuttable's pitch is to connect creative production with campaign learning in a single workflow. That positioning could appeal to ecommerce teams that run frequent paid-social campaigns and have enough historical data to identify meaningful performance patterns.

There are limits to what performance feedback alone can establish. ROAS can be affected by attribution settings, audience selection, budgets, seasonality, product margins, and changes in platform delivery. An ad that performs well in one campaign may not produce the same results with another audience or offer.

For enterprise marketing teams, the value of the platform will depend on whether its recommendations improve outcomes beyond what existing creative and analytics tools already deliver. Integration depth, approval controls, brand consistency, and the ability to connect advertising results with actual business profitability will be important evaluation criteria.

Market Landscape

The advertising technology market is moving toward tighter integration between AI-generated content, creative testing, campaign measurement, and optimization. Meta and Google are investing in AI across their advertising ecosystems, while third-party vendors compete by connecting data and workflows across multiple marketing activities.

Cuttable's immediate focus is narrower: ecommerce performance marketers who need a steady pipeline of paid-social creative. Its feedback-loop approach could reduce the distance between discovering a winning ad and producing the next iteration.

However, platform-generated recommendations are only as useful as the data and measurement practices behind them. Advertisers should validate whether reported gains reflect incremental business results, not just changes in platform-attributed ROAS.

Strategic Outlook

Cuttable's U.S. expansion and Series A funding give it room to develop a more integrated creative workflow. The broader opportunity is to make advertising production a learning system, where each campaign informs subsequent briefs rather than leaving performance insights in a separate reporting dashboard.

If the company can demonstrate consistent improvements across different brands, products, and campaign conditions, its approach could appeal to marketing teams seeking to scale creative output without proportionally increasing manual analysis. The test will be whether its recommendations generate measurable, repeatable gains in business performance.

Top Insights

• Creative intelligence: Cuttable connects AI ad generation with campaign performance data, helping performance marketers turn historical results into actionable creative briefs.

• Advertising automation: Direct Meta Ads Manager integration connects creative production and reporting, potentially reducing manual handoffs between advertising, analytics, and creative teams.

• U.S. expansion: The United States accounts for 40% of Cuttable's revenue, making North American growth a central priority for its advertising technology business.

• Funding and growth: An A$20 million Series A led by Airtree Ventures will support platform development and expansion, increasing Cuttable's capacity to compete in AI advertising.

• Measurement challenges: Reported ROAS improvements require independent validation, as attribution models, budgets, audience mix, and profit margins can affect campaign performance.

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Korean bakery café chain TOUS les JOURS has appointed Max Gallegos as chief marketing officer for North America, placing a former McDonald’s executive in charge of its marketing strategy across the United States and Canada. The appointment comes as the brand pursues an ambitious target of 1,000 U.S. locations by 2030. Gallegos will oversee brand strategy, creative, digital marketing, loyalty, category development, and field marketing as the company looks to build customer awareness and support franchise expansion in an increasingly competitive bakery café market.

From McDonald’s to a Korean Bakery Café Brand

Gallegos brings more than 25 years of experience at McDonald’s Corporation, where he held leadership positions spanning communications, strategy, marketing, and field operations. Most recently, he led U.S. Cultural Strategy and Field Marketing Engagement. Earlier, he managed a regional business unit valued at $5 billion in the Southwest.

His background in a large franchise network is relevant to TOUS les JOURS’ expansion strategy. Marketing a growing bakery café chain requires more than national advertising. Brand positioning, local store promotions, customer loyalty, and franchisee coordination must work together across markets with different consumer preferences.

Gallegos will oversee these functions across North America, although the company has not disclosed specific campaign plans, marketing investment levels, or targets for customer acquisition and loyalty.

A 1,000-Store Ambition Raises the Marketing Stakes

TOUS les JOURS is targeting 1,000 U.S. locations by 2030. The company operates within CJ Foodville, part of South Korea's CJ Group, and combines Korean bakery traditions with French-inspired baking.

The chain's recent openings in Albuquerque, Toronto, and New York reflect its geographic expansion across North American markets. In September 2026, CJ's newsroom reported that the brand had reached 205 U.S. stores as of June 2026, providing a useful baseline for measuring progress toward its target.

Reaching 1,000 locations would require the company to add hundreds of stores in less than four years. That makes consistent brand execution and effective franchise marketing important operational priorities, not simply communications objectives.

Gallegos' remit spans brand, category, creative, digital, loyalty, and field marketing. Coordinating these functions could help the company build a recognizable customer experience while adapting promotions to local markets. Loyalty programs and digital engagement may also help turn occasional bakery purchases into repeat visits.

The challenge will be maintaining consistency as the franchise network grows. New locations need local awareness and repeat customers, while the broader brand must preserve the Korean bakery identity that differentiates it from conventional coffee shops and neighborhood bakeries.

Competition Extends Beyond Bakery Cafés

TOUS les JOURS competes for consumer spending with bakery café chains, independent bakeries, coffee retailers, and quick-service restaurants. Its combination of breads, pastries, cakes, and beverages gives it several consumption occasions, from everyday breakfast purchases to celebration orders.

The appointment also comes amid a demanding restaurant operating environment. The National Restaurant Association projected U.S. restaurant and foodservice sales of $1.55 trillion in 2026, while highlighting persistent cost pressures and uneven customer traffic.

In that environment, marketing leaders need to connect brand awareness with store-level performance. Digital campaigns can generate interest, but location accessibility, product availability, service quality, and franchise execution determine whether that interest translates into sustainable sales.

Gallegos' experience across marketing and field leadership could prove useful in connecting national strategy with local operations. The appointment, however, does not itself establish that TOUS les JOURS will achieve its expansion target. Store openings, franchisee economics, customer retention, and competitive conditions will ultimately determine the pace of growth.

Market Landscape

TOUS les JOURS is positioning itself at the intersection of Korean food culture, French-inspired baking, and the North American café market. Its competitive set includes Panera Bread, Paris Baguette, Starbucks, and independent bakery cafés, although their formats and product mixes differ.

Paris Baguette is a particularly relevant comparison because it also uses a bakery café model rooted in Korean heritage and is expanding in North America. Starbucks competes for breakfast and beverage occasions, while Panera offers a broader café and food menu.

TOUS les JOURS' opportunity is to differentiate through its bakery assortment and celebration-focused products while building everyday customer habits. Its 2030 target will depend on whether the brand can reproduce that experience consistently across a much larger franchise network.

Strategic Outlook

The appointment signals that TOUS les JOURS is strengthening marketing leadership to support its next stage of expansion. Gallegos' experience at McDonald's may help the company coordinate national branding, digital engagement, and franchise-level execution.

The key measure of success will be whether those capabilities translate into stronger customer retention, productive new-store openings, and sustainable franchise growth. As the network expands, marketing effectiveness will need to be assessed alongside store economics and operational consistency.

Top Insights

• Leadership: Max Gallegos brings more than 25 years of McDonald's experience, potentially strengthening TOUS les JOURS' brand strategy and franchise marketing execution.

• Expansion: The 1,000-store U.S. target by 2030 increases pressure on marketing teams to support local awareness, customer acquisition, and repeat visits.

• Digital marketing: Gallegos' remit includes digital and loyalty, creating opportunities to connect customer engagement with measurable store-level performance.

• Competitive positioning: TOUS les JOURS combines Korean bakery heritage with French-inspired baking, distinguishing its offering from coffee-led and conventional quick-service restaurant competitors.

• Execution risk: National brand consistency, franchisee economics, and local customer demand will influence whether marketing initiatives translate into sustainable expansion.

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Certinia has been named a Visionary in the 2026 Gartner Magic Quadrant for Customer Success Management Platforms, marking its first appearance in the analyst firm's evaluation. The recognition puts the Salesforce-native CS Cloud platform in focus as enterprise software providers increasingly compete to connect customer success operations with artificial intelligence, revenue forecasting, and retention management. The announcement also highlights a broader industry challenge: helping customer success teams move beyond fragmented account data to make decisions that improve renewals, expansion, and net revenue retention (NRR).

Certinia’s recognition comes as customer success management (CSM) platforms evolve from account-monitoring tools into operational systems that connect customer health, service delivery, renewal planning, and revenue growth. The Gartner report, published on October 19, 2026, evaluates vendors on their ability to execute and completeness of vision.

Salesforce-native architecture is Certinia’s main differentiator

At the center of Certinia’s offering is Customer Success Cloud, which runs natively on Salesforce. Rather than maintaining a separate customer success database and synchronizing it with a CRM, the platform uses Salesforce records to connect sales, services, support, and customer success activities.

The approach is designed to reduce data duplication and integration overhead. It also gives customer success teams access to professional services information, account interactions, project activity, and customer communications within a shared operational context.

Certinia combines this architecture with Veda, its suite of agentic AI capabilities. The Customer Success Agent can prepare meeting briefings, prioritize tasks, generate board and pipeline reports, and flag potential cost-to-serve or team-capacity issues. According to the company, its AI-generated actions remain subject to organizational permissions, approval thresholds, and audit controls.

The practical goal is to help customer success managers spend less time assembling reports and more time addressing customer needs. However, the extent of those benefits will depend on data quality, workflow configuration, and how well the system fits an organization's existing Salesforce environment.

Connecting customer success to net revenue retention

The financial case for the platform centers on net revenue retention, a key metric for subscription and services businesses. NRR measures how recurring revenue from existing customers changes over time after accounting for expansions, contractions, and churn, typically excluding revenue from new customers.

In many enterprises, the information required to calculate and explain NRR sits across CRM, customer success, and services systems. Different records and reporting schedules can create discrepancies between finance, sales, and customer success teams.

Certinia aims to address that problem by connecting renewal activity, service delivery, and expansion opportunities to a common Salesforce-based record. That could make quarterly business reviews and revenue forecasts easier to reconcile, although a unified record alone does not guarantee accurate forecasts or consistent metric definitions.

Agentic AI moves into customer success operations

Certinia is also developing predictive capabilities intended to identify retention risks and expansion opportunities before they become visible in conventional pipeline reviews. Its longer-term direction is to extend AI agents across onboarding, account management, renewals, and expansion while keeping customer success leaders involved in decisions.

The shift reflects broader enterprise interest in AI that can act within established workflows rather than simply generate summaries or recommendations. Gartner reported in August 2026 that AI spending among surveyed customer service leaders had increased by 38%, while overall service and support budgets rose by just 2%. The findings point to growing investment in AI, alongside pressure to demonstrate measurable returns.

For enterprise buyers, the central question is whether agentic AI can improve retention and expansion outcomes without introducing new governance risks. Human approval, permission controls, traceable actions, and reliable customer data will remain essential as automation takes on more operational responsibility.

Certinia’s Visionary placement is a useful market signal, but it is not proof of product superiority or customer outcomes. The company’s next challenge is to demonstrate that its Salesforce-native architecture and Veda capabilities can deliver measurable value against established customer success platforms.

Market Landscape

The 2026 Gartner Magic Quadrant includes vendors such as Gainsight, ChurnZero, HubSpot, Planhat, Vitally, Custify, and Velaris alongside Certinia.

Certinia's competitive argument rests on its close connection between customer success and professional services operations. That may appeal particularly to services-led businesses already using Salesforce, where delivery performance, utilization, customer health, and account expansion are tightly linked.

By contrast, established specialists such as Gainsight and ChurnZero compete around dedicated customer success workflows, customer health management, and retention-focused analytics. HubSpot brings customer success capabilities into a broader CRM ecosystem, while Planhat and Vitally offer alternative approaches to customer data, account management, and customer lifecycle operations.

The choice is therefore not simply about which vendor has AI features. Buyers need to weigh integration requirements, existing CRM investments, services-management complexity, reporting needs, and the maturity of each vendor's automation and governance controls. Certinia's first-time evaluation adds visibility to its position, but enterprises should assess the full Gartner report and conduct their own product evaluations before making a decision.

Strategic Outlook

The next competitive phase in customer success software will likely center on how effectively platforms translate customer data into measurable business action. AI-generated account summaries are becoming less distinctive; reliable risk detection, explainable recommendations, controlled execution, and demonstrable improvements in NRR are harder tests.

For marketing, sales, and customer experience leaders, better alignment between customer success and revenue operations could also improve expansion planning and customer lifecycle engagement. Yet these gains require shared definitions, trusted data, and coordination across teams—not just a new AI layer.

Top Insights

• Certinia's first Gartner Magic Quadrant evaluation recognizes its entry into a competitive customer success market, giving enterprise buyers another platform to consider.

• CS Cloud uses Salesforce-native records to connect sales, services, and customer success, potentially reducing data duplication and reconciliation work for operations and finance teams.

• Veda's agentic AI automates customer success administration, including account briefings, task prioritization, pipeline reporting, and capacity-risk identification for customer success leaders.

• Certinia's NRR strategy links customer retention and expansion signals to shared account data, helping finance and customer success teams build more consistent revenue reporting.

• Enterprise buyers should evaluate AI governance, integration costs, forecast accuracy, and measurable retention outcomes rather than treating Gartner recognition as a substitute for product testing.

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Referral marketing technology provider NaXum has launched a redesigned website positioning artificial intelligence as a way to help businesses coordinate personal recommendations, member engagement and commission management. The platform combines AI-generated marketing assistance and suggested next actions with tools for referral tracking, commerce and payouts. The announcement reflects a broader MarTech challenge: using automation to scale relationship-led marketing without losing the trust and personal connection that make referrals valuable.

NaXum targets referral marketing workflows with AI-powered tools

NaXum’s October 22 announcement introduces a new website and a clearer presentation of its AI-enabled referral marketing platform. The company says it has supported more than 180 brands over more than 25 years and facilitated tens of millions in commission payouts. These are company-reported figures; the announcement does not include independently audited performance data.

The platform serves four main markets: influencer and creator brands, brands and manufacturers, affiliate and referral programs, and direct selling and network marketing. Its product portfolio is designed to support different parts of the referral business, from member-facing marketing activity to commission calculations and e-commerce.

NaXum Builder provides marketing tools and a mobile app for members. Tracker focuses on referral and commission tracking and payments. UNIFY combines marketing, commerce and commissions in one platform, while BuilderPRO is designed for field leaders within established organizations. The products are delivered through the NaXum Virtual Office and app, with capabilities varying by product and plan.

AI focuses on the work around a recommendation

The announcement highlights three AI-enabled capabilities intended to support daily referral marketing operations.

Predictive Actions recommends a next step for each member, aiming to turn activity and performance signals into a practical daily task. AI Marketing Assistant helps users draft social posts, campaigns and follow-up messages using a brand’s approved language. AI Support provides round-the-clock answers based on a company’s policies and reward plan, according to NaXum.

Together, these features target common operational challenges in referral programs: helping members decide what to do next, maintain consistent communications and find answers without always relying on a central support team.

NaXum founder and chief visionary officer Rodd Kirby argues that AI should handle repetitive work surrounding a referral rather than replace the human recommendation itself. That positioning distinguishes the company’s stated approach from fully automated outreach strategies: AI supports content, timing, follow-up and tracking, while the member remains the personal connection between a brand and a prospective customer.

However, the release does not provide comparative data showing whether the AI features improve conversion rates, member retention, response times or commission efficiency. Their business impact will depend on adoption, recommendation quality, governance and how effectively the tools fit into existing workflows.

Connecting referrals, commerce and commission management

Referral programs often involve several connected processes: identifying prospective customers, sharing content, following up, recording purchases, attributing referrals and calculating rewards. When these processes are split across separate systems, businesses may face reconciliation work and limited visibility into the relationship between marketing activity and payouts.

NaXum’s integrated product options are designed to address that operational fragmentation. UNIFY brings marketing, online shopping and commission management together, while Builder and Tracker can serve businesses that want to add particular capabilities to existing systems. NaXum also describes integrations with external commerce platforms, including Shopify and WooCommerce.

For marketing and commerce leaders, the proposition is less about generating content alone and more about coordinating the entire referral workflow. AI-generated messages have limited value if referral attribution is unreliable or rewards are delayed; likewise, accurate commission tracking does not automatically produce effective customer engagement.

The website launch itself should not be confused with evidence of a new platform release or independently verified product-performance gains. It provides a new showcase for NaXum’s existing product structure and AI positioning.

As referral, affiliate and creator-led commerce continue to converge, the key question for platforms such as NaXum is whether they can make participation easier for members while giving brands reliable control over messaging, attribution and rewards. AI can help scale the work around personal recommendations, but trust, transparency and measurable business outcomes remain essential.

Market Landscape

• Referral marketing automation: Platforms are expanding beyond referral links to include content creation, follow-up, tracking and reward management.

• AI-assisted engagement: Suggested next actions and brand-aligned content generation aim to help members carry out marketing tasks more consistently.

• Creator and affiliate commerce: Brands increasingly need ways to connect recommendations with commerce activity and commission attribution.

• Integrated marketing operations: Combining marketing, storefront and payout workflows can reduce the need to manage disconnected tools, although integration quality matters.

• Trust and governance: AI-generated messages and automated support need to remain consistent with approved brand language, program rules and customer expectations.

Strategic Outlook

NaXum is positioning AI as an operational layer within referral marketing rather than as a replacement for personal recommendations. The strategy targets businesses that need to support large networks of members, creators, affiliates or direct-selling representatives.

The next measure of progress will be tangible outcomes: member adoption, time saved on routine tasks, response quality, referral conversion, attribution accuracy and payout reliability. Brands evaluating the platform should also examine integration requirements, access controls, content approval processes and how AI recommendations are generated.

The broader MarTech implication is that AI value increasingly depends on the workflows it improves. In referral marketing, that means connecting content and follow-up with the systems that record sales and reward the people responsible for generating them.

Top Insights

• AI supports the referral workflow: NaXum highlights suggested actions, brand-aligned marketing content and automated support to help members manage routine activities.

• The platform combines several operational layers: Builder, Tracker, UNIFY and BuilderPRO address different marketing, commerce and commission-management requirements.

• Personal recommendations remain central to the pitch: NaXum’s stated strategy is to automate supporting tasks while preserving the human relationship behind a referral.

• Integration is part of the proposition: Connecting marketing, commerce and commissions can help businesses coordinate activity and reward attribution.

• Performance evidence remains limited: The announcement provides company-reported scale figures but no independent benchmarks demonstrating the impact of its AI features.

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The Coca-Cola Company has completed its global marketing operating system review, retaining WPP Open X as its media partner across most international markets while selecting Omnicom for North America. Dentsu will continue handling media in Japan and South Korea, while WPP Open X retains Coca-Cola’s global creative remit. The decision signals a focus on connecting media, data, customer relationship management (CRM), loyalty, creator marketing and AI-enabled capabilities within a more integrated marketing ecosystem.

Coca-Cola reshapes its global marketing operating model around data and AI

Coca-Cola’s agency review was not simply a media buying decision. It was an assessment of how the company organizes marketing capabilities across markets, with an emphasis on consumer understanding, operational agility and technology-enabled execution.

Under the revised arrangement, WPP Open X will remain Coca-Cola’s media partner globally, excluding North America, Japan and South Korea. Omnicom has been selected to manage media in North America and will work closely with WPP StudioX. Dentsu retains its existing media responsibilities in Japan and South Korea, which were outside the current review. WPP Open X will also continue as Coca-Cola’s global creative partner, a role not included in the review.

The new structure builds on a relationship that began with the creation of Open X in 2021. Coca-Cola says WPP has helped modernize its marketing operations across more than 200 countries and territories, citing capabilities in media, data, technology, creators and commerce.

Coca-Cola executive Manolo Arroyo, executive vice president and chief marketing and customer commercial officer, also highlighted WPP’s Open Intelligence data solution and its application during the company’s FIFA World Cup 2026 activation. These capabilities reflect the growing importance of connecting marketing investment with audience insights and campaign performance.

Omnicom’s North American remit extends beyond media

The North American appointment is particularly significant because Coca-Cola intends to bring several capabilities together rather than manage them as separate marketing functions.

According to the company, Omnicom’s remit will connect media, data, CRM, loyalty and creator marketing within a more integrated ecosystem. The goal is to move beyond channel-by-channel execution toward consumer experiences that are coordinated across interactions.

That approach aligns with a broader shift in enterprise marketing: brands increasingly need to understand how paid media, customer relationships, loyalty initiatives and creator-led activity work together. When those functions operate in silos, teams can struggle to maintain consistent audience insights, coordinate campaigns and evaluate business outcomes across touchpoints.

Coca-Cola’s announcement describes the operating model it wants to build, but it does not disclose specific performance targets, implementation costs or quantified returns expected from the new arrangement.

Why the decision matters for marketing technology

The review places data infrastructure and AI alongside agency expertise as components of Coca-Cola’s marketing strategy. WPP’s connected technology ecosystem, including WPP Open and Open Intelligence, is part of the retained global relationship. In North America, the collaboration between Omnicom and WPP StudioX introduces an additional coordination requirement across agency teams and technology capabilities.

For large advertisers, an integrated marketing model can support more consistent audience understanding, campaign planning and measurement. However, the benefits depend on how well data is shared, how responsibilities are defined and whether teams use consistent performance measures.

The arrangement also illustrates that global consistency does not necessarily require a single agency to manage every market. Coca-Cola is retaining a global partner while selecting a different media partner for North America and maintaining Dentsu in two Asian markets.

The revised operating model is expected to be introduced in phases beginning December 1, 2026, according to industry reporting.

The key test will be execution: whether the agency structure can combine global scale with local market expertise while improving the speed, relevance and measurable impact of marketing. For the wider MarTech sector, Coca-Cola’s decision reinforces a central priority for enterprise brands: integrating people, data, platforms and AI into a coordinated marketing system rather than treating technology as a collection of disconnected tools.

Market Landscape

• Integrated agency models: Large advertisers are organizing creative, media, data and technology capabilities around connected operating structures.

• Data-led marketing: Audience intelligence and measurement are becoming central to campaign planning and optimization.

• AI-enabled marketing operations: Brands and agency networks are investing in technology intended to improve workflows, insights and execution at scale.

• Local-market specialization: Coca-Cola’s arrangement shows how a global marketing model can retain central coordination while assigning specific markets to different agency partners.

• Ecosystem governance: Multiple agency groups working together will need clear accountability, data-sharing rules and consistent measurement standards.

Strategic Outlook

Coca-Cola’s decision gives WPP continuity across much of its global media business and preserves its global creative role, while expanding Omnicom’s responsibilities in North America. For Coca-Cola, the strategic objective is to coordinate capabilities that have often been managed separately.

The outcome will depend on implementation. Key indicators to watch include campaign effectiveness, speed of execution, audience and customer insights, media efficiency, creator and retail media performance, and the ability to connect marketing activity to business results.

For marketing leaders, the broader lesson is that agency selection increasingly involves evaluating not only creative quality or media buying scale, but also the technology, data practices and collaboration model behind delivery.

Top Insights

• WPP retains a central role: WPP Open X remains Coca-Cola’s global media partner outside North America, Japan and South Korea, and continues as its global creative partner.

• Omnicom takes North America: The new remit is designed to connect media, data, CRM, loyalty and creator marketing in a more integrated operating model.

• Dentsu remains in two markets: Japan and South Korea were excluded from the current review, so Dentsu continues its existing media responsibilities.

• Technology is part of the agency proposition: Coca-Cola highlighted WPP’s data and technology capabilities, including Open Intelligence and WPP Open.

• Execution will determine the impact: The announcement sets out an operating direction, but does not quantify expected savings, ROI improvements or campaign performance gains.

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Most marketers say they are confident in their ability to measure return on investment (ROI), but far fewer connect performance across traditional and digital media. Nielsen’s The Marketing ROI Blueprint, published in October 2025, found that 85% of marketers were confident in their ROI measurement capabilities, while only 32% measured ROI holistically across traditional and digital channels. For e-commerce brands managing paid search, social media, affiliate marketing, email and other touchpoints, the gap highlights a critical distinction: measuring campaign results is not the same as understanding what drives them.

E-commerce marketers face a gap between ROI confidence and measurement

Marketing teams have no shortage of performance data. Paid search platforms report clicks and conversions, social networks provide engagement metrics, affiliate networks track referrals, and email tools measure opens and purchases. The difficulty is combining these signals to understand how different channels contribute to a sale.

Nielsen’s The Marketing ROI Blueprint identifies this challenge in its research on marketing measurement. While 85% of marketers reported confidence in their ability to measure ROI, just 32% said they measure traditional and digital media spending holistically. The report also found that 38% of marketers prioritize sales or ROI as their top metrics for success.

The findings point to a distinction between measuring individual campaigns and evaluating the combined impact of a marketing strategy.

Why channel-level ROI can give an incomplete picture

A customer might discover a product through a paid social campaign, research it through organic search, receive a promotional email and finally purchase using an affiliate link. Each platform could claim credit for some part of the journey, depending on its measurement rules.

If a retailer evaluates every channel in isolation, it may overvalue the last interaction and undervalue the earlier activity that introduced the product or encouraged consideration. The reverse can also happen: a channel may generate substantial engagement without contributing meaningfully to sales.

Neither clicks nor conversions are inherently misleading. The problem arises when metrics are interpreted without enough context about the customer journey, overlapping exposure and the role each channel plays.

This is where marketing attribution becomes important. First-touch attribution credits the initial recorded interaction, while last-touch attribution assigns credit to the final interaction before conversion. Both offer useful perspectives, but neither independently explains the full path to purchase.

Moving toward cross-channel measurement

For e-commerce marketers, a more complete approach combines channel-level reporting with broader measurement methods. These may include multi-touch attribution, marketing mix modelling, incrementality testing and brand- or sales-lift studies. Each answers different questions, and no single method is suitable for every business or campaign.

Multi-touch attribution can help teams understand interactions across trackable digital journeys. Marketing mix modelling can assess how different marketing investments relate to business outcomes over time, including channels that are harder to track at an individual level. Incrementality tests help determine whether a campaign generated additional conversions rather than simply receiving credit for purchases that would have happened anyway.

Nielsen’s report also highlights the use of both reach and frequency measures alongside ROI: 60% of marketers incorporate both into their cross-media measurement strategies. It further points to creative evaluation, including brand lift and sales lift, as a way to connect advertising execution with outcomes.

What e-commerce teams should measure next

The practical priority is to establish a consistent measurement framework that connects media investment with business outcomes. Teams should align on definitions of conversion, revenue, acquisition cost and return, while accounting for differences in attribution windows and platform reporting.

They should also compare reported conversions with incremental sales, customer lifetime value and profitability where suitable data is available. A campaign that produces a high volume of first purchases may not be as valuable as one that attracts customers who return and spend more over time.

Privacy restrictions, incomplete tracking and data silos can still limit visibility. Cross-channel measurement should therefore be treated as an ongoing process of combining evidence, testing assumptions and improving decision-making—not as a promise that every customer interaction can be perfectly identified.

For e-commerce brands, the objective is not simply to report ROI with greater confidence. It is to understand the limits of that measurement, determine which investments are genuinely driving results and allocate budgets accordingly.

Market Landscape

• Fragmented reporting: Marketing platforms use different attribution rules, metrics and reporting windows, making direct comparisons difficult.

• Pressure to prove business impact: Marketers increasingly need to demonstrate sales and ROI rather than relying exclusively on reach, clicks or engagement.

• Multiple measurement methods: Attribution, marketing mix modelling and incrementality testing offer complementary views rather than interchangeable answers.

• Creative accountability: Brand-lift and sales-lift studies can help teams evaluate whether creative activity contributes to measurable outcomes.

   

   

Strategic Outlook

E-commerce marketing teams should move from isolated channel dashboards toward a shared measurement framework connecting media investment, customer acquisition and revenue outcomes. That requires consistent definitions, clear attribution assumptions and regular validation against business results.

The most useful measurement strategy will depend on a brand’s channel mix, data quality, sales cycle and available resources. Teams should combine methods where appropriate and avoid treating platform-reported conversions as proof of incremental impact.

Top Insights

• Confidence is not completeness: Nielsen found that 85% of marketers were confident in ROI measurement, but only 32% measured traditional and digital media holistically.

• Sales and ROI matter: 38% of marketers identified sales or ROI as their top success metrics, reflecting a focus on business outcomes.

• Customer journeys cross channels: Single-touch attribution can overlook the contribution of earlier interactions that influence a final purchase.

• Measurement methods serve different purposes: Attribution, marketing mix modelling and incrementality testing provide complementary evidence about performance.

• Better measurement supports budget decisions: A connected view of marketing outcomes can help teams compare investments and challenge misleading channel-level conclusions.

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Lightspeed Commerce is expanding its retail, restaurant and golf platforms with new AI-powered workflows, advertising measurement integrations, payment options and demand-capture features. The product updates aim to connect more of the merchant journey—from digital ad exposure and product availability to checkout, reservations and business intelligence—positioning Lightspeed as more than a point-of-sale provider. The broader MarTech significance is the convergence of commerce operations, customer data and marketing performance within a connected platform.

Lightspeed connects marketing attribution, operations and customer conversion

The October 22, 2026, announcement spans nine updates across Lightspeed Retail, Restaurant and Golf. Rather than introducing one flagship AI product, the company is connecting existing commerce workflows with new capabilities designed to reduce manual work and help businesses convert more demand.

Retail: Connecting ad spend to store sales

One of the most significant marketing technology updates is Lightspeed’s integration with Meta Conversions API. Retailers can synchronize their in-store product catalog and send point-of-sale transaction data to Meta, helping them measure how advertising relates to purchases made in physical stores.

This matters for merchants that run digital campaigns but complete many sales offline. By connecting advertising exposure and transaction signals, retailers can improve campaign measurement and optimize toward revenue-related outcomes without necessarily operating an ecommerce store.

The integration could help close a longstanding gap in omnichannel attribution. However, measurement quality will still depend on data matching, consent, signal quality and the retailer’s broader attribution approach. Lightspeed has not published independent performance results showing how much the integration improves return on ad spend.

Lightspeed is also introducing Omni Customer Accounts, allowing brick-and-mortar shoppers to view purchase history and loyalty information online without requiring the retailer to run a separate ecommerce store. This creates another digital touchpoint for customer relationships after an in-store transaction.

AI targets operational bottlenecks

Lightspeed’s AI Doc Import is designed to turn supplier invoices, packing slips and order confirmations into purchase orders. Staff can review and approve extracted product and quantity details, with product matching and bulk product creation available through the web dashboard or Scanner mobile app.

The practical objective is to reduce repetitive data entry and move stock through receiving workflows faster. Because employees can review imported information, the process retains a human approval step rather than treating document extraction as an entirely autonomous operation.

For hospitality businesses, Lightspeed AI adds Custom Charts and Saved Charts. Operators can turn AI-generated charts into dashboard tiles or reports that update as new transactions arrive. This could make recurring business questions—such as sales trends or changes in performance—easier to monitor without repeatedly rebuilding reports.

Lightspeed is also connecting its POS and ecommerce platforms with ShipStation. Retailers can use the integration to fulfill special orders or ship products directly to customers when items are unavailable at the local store. The goal is to reduce the chance that an inventory gap becomes a lost sale.

Restaurants and golf courses gain new conversion paths

The hospitality updates focus on reducing friction at checkout and during booking. Reserve with Google lets diners discover availability and book through Google Search and Maps, reducing the steps between finding a restaurant and making a reservation.

Lightspeed’s new 8-inch Customer Display combines customer-facing checkout information with integrated payments. It is currently available to select customers. The enhanced Pay at Table app is in beta, while Scan to Pay lets guests view a bill, split payments, add a tip and pay using their phones.

In golf, the On Deck feature addresses a different inventory challenge: canceled tee times. Golfers can register interest in a preferred time or window and receive an email when a matching opening becomes available, giving courses another way to fill inventory that might otherwise remain unsold.

The broader connected commerce strategy

Taken together, these updates position Lightspeed around a more connected merchant operating model. Marketing signals can be tied to store transactions; customer profiles can extend beyond the physical shop; AI can assist with operational reporting and document processing; and booking and fulfillment tools can help convert demand into completed transactions.

The competitive challenge is making these connections work reliably across different business types. Retailers, restaurants and golf operators have distinct workflows, so the value will depend on how well the features fit existing operations, integrate with other systems and deliver measurable results.

For merchants evaluating the updates, the most useful indicators will be reduced administrative time, improved attribution coverage, higher booking conversion, more recovered sales and better use of available inventory. Those outcomes—not the number of AI features alone—will determine whether connected commerce delivers tangible business value.

Market Landscape

Lightspeed’s release reflects three broader developments in commerce technology:

• Retail media and offline attribution: Retailers want to connect digital advertising activity with physical-store revenue.

• Operational AI: AI is being applied to tasks such as document processing, reporting and business analysis, where it can reduce repetitive work.

• Frictionless conversion: Booking integrations, digital payments and flexible fulfillment help businesses reduce barriers between customer interest and purchase.

The strategic distinction is the connection between these capabilities. Individual tools can solve narrow problems, but a unified commerce platform aims to link acquisition, transactions, inventory, customer data and operational decisions.

Strategic Outlook

Lightspeed is expanding from its POS foundation toward a broader commerce operating platform. The latest features are intended to help merchants not only process transactions but also understand demand, attribute marketing performance and respond more quickly to operational changes.

For marketers, the Meta Conversions API integration and Omni Customer Accounts are particularly relevant because they link physical retail activity with digital measurement and customer relationships. For operators, AI Doc Import and AI-powered reporting target routine work that can consume staff time.

The next step is evidence of adoption and impact. Merchants should evaluate how easily the features fit their workflows and whether they improve sales recovery, booking rates, attribution quality or staff productivity.

Top Insights

1. Lightspeed’s nine updates connect retail, hospitality and golf workflows, extending the platform beyond point-of-sale transactions into marketing measurement and demand conversion.

2. Meta Conversions API integration helps retailers link in-store transactions with digital advertising signals, supporting stronger measurement of offline sales.

3. AI Doc Import and AI-generated charts target operational efficiency by reducing manual document entry and making business insights easier to monitor.

4. Reserve with Google and golf’s On Deck feature aim to convert customer intent into bookings by reducing friction and matching demand to available inventory.

5. The business impact will depend on integration quality and measurable results, including recovered sales, improved attribution and reduced administrative work.

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