Airship has been recognized in the 2026 Gartner Magic Quadrant for Multichannel Marketing Hubs for the second consecutive year, placing its mobile-first customer experience platform within a market increasingly shaped by AI decisioning, real-time personalization and automated journey orchestration. The recognition follows Airship's continued expansion into AI-powered customer experience technology, including its recently launched Decisioning AI.

Airship has announced its second consecutive appearance in Gartner's Magic Quadrant for Multichannel Marketing Hubs, following its initial recognition in the 2025 report. Gartner's 2026 research identifies Airship alongside vendors including Adobe, Bloomreach, Braze, CleverTap, Insider One, Iterable, Klaviyo, MoEngage, Optimove, Salesforce and SAP.

The recognition comes as multichannel marketing hubs evolve from campaign-management systems toward platforms capable of making real-time decisions about customer interactions.

Gartner's 2026 research says AI assistants and agents are now commonplace across multichannel marketing hubs, with differentiation increasingly centered on decision-making capabilities, including the ability to optimize journeys, offers and consent states at the moment of customer interaction.

That shift aligns with Airship's current product strategy. The company recently launched Airship Decisioning AI, designed to allow digital experience teams to make in-the-moment decisions using customer context and natural-language input. Airship says the technology can execute decisions on-device, reducing dependence on server-side processing and enabling experiences to respond to immediate customer intent.

The company is positioning that capability as part of a broader move toward outcome-led AI. Airship also highlights agent-to-agent standards, real-time performance monitoring and interoperability with enterprise data warehouses as elements of its product strategy.

The emphasis on decisioning is significant because multichannel marketing increasingly involves more than determining which message should be sent. Marketing systems must decide when, where and under what circumstances an interaction should occur, while accounting for customer context, consent and previous engagement.

Gartner's accompanying Critical Capabilities for Multichannel Marketing Hubs report evaluates areas including AI agent orchestration, decisioning and prescriptive intelligence, real-time personalization, journey management, two-way messaging and conversational or agent-augmented marketing.

Airship's mobile-first approach gives it a particular position within this market. Its platform supports customer experiences across mobile and other channels, while its architecture is designed around mobile applications, real-time events and personalized interactions. Gartner's Peer Insights page currently lists Airship's Customer Experience Platform at 4.6 out of 5 based on 87 ratings, although customer ratings are separate from Gartner's Magic Quadrant evaluation.

The company was also recognized six times in Gartner's Market Guide for Mobile Marketing Platforms, according to Airship. Its 2025 Gartner recognition marked the company's first appearance in the Multichannel Marketing Hubs Magic Quadrant.

For enterprise marketing teams, the development illustrates how the category is broadening from multichannel campaign execution toward AI-assisted customer experience orchestration. Airship's challenge will be translating its mobile expertise and real-time decisioning capabilities into measurable outcomes across increasingly complex enterprise marketing stacks.

Market Landscape

Multichannel marketing hubs are becoming a central layer between customer data and marketing execution. Gartner defines the category around SaaS applications that orchestrate personalized campaigns and event-driven customer journeys using customer data, predictive models, real-time insights and AI.

The 2026 market includes both large enterprise marketing-cloud providers and specialized customer-engagement platforms. Adobe, Salesforce and SAP compete alongside vendors such as Braze, CleverTap, Iterable, Klaviyo, MoEngage and Airship.

The competitive focus is increasingly shifting toward real-time decisioning, AI agents, personalization and data interoperability rather than simply supporting more communication channels.

Strategic Outlook

Airship's latest recognition comes at a point when AI decisioning is becoming a core capability of customer experience platforms.

Its Decisioning AI strategy reflects an industry transition from analyzing customer behavior after an interaction to making contextual decisions during the interaction itself. Airship says its on-device approach can make decisions without server round trips, potentially reducing latency for mobile experiences.

For enterprise marketers, the larger issue is how these decisioning systems integrate with existing data warehouses, consent frameworks, analytics infrastructure and marketing automation. The ability to coordinate those components will increasingly determine how effectively AI can move from recommendation to real-time customer experience execution.

Top Insights

• Airship has appeared in Gartner's Multichannel Marketing Hubs Magic Quadrant for a second consecutive year as AI reshapes customer journey orchestration.
• Gartner's 2026 research highlights decisioning, context, AI agents and real-time personalization as increasingly important areas of multichannel marketing technology.
• Airship Decisioning AI brings natural-language input and customer context into real-time experience decisions, including on-device processing for mobile experiences.
• The competitive market includes Adobe, Salesforce, SAP, Braze, CleverTap, Iterable, Klaviyo, MoEngage and other enterprise customer-engagement platforms.
• Airship's strategy increasingly connects mobile expertise with AI decisioning, data interoperability and real-time customer experience orchestration.

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As brands increasingly track visibility across ChatGPT, Google AI Overviews, Gemini, Claude and Perplexity, simple mention and citation counts are becoming less informative. Somantra has launched an AEO and GEO metrics suite designed to measure not only whether AI systems surface a brand, but how they position and discuss it during search conversations.

Somantra has announced general availability of its AEO Metrics Suite, introducing three proprietary measurements: Brand Mindshare Score, Brand Consideration Score and Brand Engagement Score.

The company positions the metrics as a new measurement layer for Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO), where marketers increasingly need to understand how brands appear inside AI-generated answers rather than relying exclusively on traditional search rankings.

Most AI visibility monitoring systems focus on whether a brand is mentioned or whether a website is cited. Somantra argues that these measurements can obscure important differences between a brand that is merely referenced and one that is actively recommended.

Its Brand Mindshare Score is designed to measure share of voice and citation across a broader query landscape, including variations of queries that can change how AI systems respond. Brand Consideration Score evaluates how favorably a brand is positioned against named competitors within an answer. Brand Engagement Score examines how extensively an AI system engages with a brand's claims throughout a multi-turn conversation.

The distinction becomes particularly relevant as AI search moves toward conversational buying journeys. A user may begin with a broad category question, ask for alternatives, introduce a budget constraint and then request a recommendation. A brand appearing in the first answer does not necessarily mean it remains part of the consideration set later in the conversation.

Somantra says its own perturbation testing illustrates this volatility. The company analyzed 4,445 ChatGPT responses across 135 matched query pairs in the Australian insurance category and found that changing a single word in a query could alter which brand an AI assistant recommended for attributes such as safety or value.

Because the research is Somantra's own testing rather than an independent industry study, the finding should be viewed as a company-reported indication of query sensitivity rather than a universal benchmark across all AI search systems.

The new metrics are built on Somantra's existing conversation-mapping infrastructure, which the company says tracks millions of AI search conversations across brand categories. Its system builds query sets based on product and service information, customer personas and statistically significant competitors, then evaluates responses across platforms including ChatGPT and Google AI.

The resulting data can be viewed at brand and product-line level. Somantra says marketers can refresh the scores daily, weekly or monthly and examine movement over time, competitor comparisons and individual queries.

Rentomojo, an Indian furniture and appliance rental company, is using the metrics as part of its AEO/GEO strategy. According to Dhruv Wahal, AVP – Marketing & Growth at Rentomojo, the company uses the scores to identify buyer-intent conversations where its brand is recommended or absent across different product categories.

Wahal also said the Engagement Score helps Rentomojo understand which pages and content AI assistants draw from during conversations.

The competitive landscape around AI visibility measurement is developing quickly. Platforms including Semrush, Ahrefs, BrightEdge and Profound have expanded into AI-search visibility, brand monitoring or generative-search analytics. The market is consequently shifting from a basic question—“Does AI mention us?”—toward more nuanced measurements around recommendation, competitive positioning, citation sources and conversational persistence.

Somantra's launch reflects that transition. If AI assistants become a meaningful discovery layer for commercial research, marketers will need metrics that distinguish exposure from actual consideration.

Market Landscape

Traditional SEO measurement revolves around rankings, impressions, clicks and organic traffic. AEO and GEO introduce a different measurement problem because AI-generated answers can synthesize information from multiple sources and may not provide a conventional ranking position.

This has created demand for visibility platforms that monitor mentions, citations, source pages, sentiment and competitive presence across AI systems.

Somantra's three-score framework attempts to add another layer by separating brand exposure from recommendation strength and multi-turn engagement. The broader industry is still developing common measurement standards, making methodology and repeatability important considerations for enterprise marketers.

Strategic Outlook

AI-search measurement is moving toward quality of visibility rather than visibility alone.

For marketing teams, the practical question is increasingly whether AI systems associate a brand with the attributes that matter during purchase research—and whether those associations persist as a conversation becomes more specific.

Somantra's approach also highlights the importance of query variation. A brand's AI-search presence may change based on wording, intent, comparison criteria or conversation context, meaning periodic snapshots can provide only part of the picture.

The next phase of AEO and GEO measurement is likely to focus increasingly on connecting AI visibility data with content strategy, competitive positioning and measurable customer journeys.

Top Insights

• Somantra's AEO Metrics Suite introduces Mindshare, Consideration and Engagement scores designed to measure different dimensions of brand visibility across AI search.
• Brand Consideration Score distinguishes recommendations from passing mentions by examining how a brand is positioned relative to named competitors.
• Brand Engagement Score evaluates multi-turn AI conversations, providing visibility into whether an assistant continues engaging with a brand's claims.
• Rentomojo uses the metrics to identify buyer-intent conversations where its brand is recommended or absent across furniture and appliance categories.
• The launch reflects a broader shift from counting AI citations toward measuring competitive positioning and the quality of brand visibility.

Get in touch with our MarTech Experts.

Small and midsized service businesses often manage websites, paid advertising, search visibility, content and lead tracking across separate tools. TruLata is attempting to consolidate those functions into a single AI marketing platform, combining website management, advertising, content, outbound campaigns and lead attribution in one system.

TruLata has launched its AI marketing platform on Product Hunt, targeting service businesses that need to run recurring marketing activities without managing multiple disconnected systems.

The platform is designed to operate a business's website, search presence, Google and Meta advertising, content and outbound marketing on scheduled workflows, depending on the subscription plan. Its central dashboard is intended to show each lead, its acquisition source and the associated marketing cost.

The company is also introducing a website builder that can be used without an upfront payment or credit card. Businesses can build and edit a website for free, while publishing it on their own domain costs $49 per month, according to TruLata.

The product emerged from TruLata's experience as a marketing agency serving service businesses since 2017. Founder Trace Gordon says the agency identified two recurring problems: business owners spending time on repetitive marketing operations and struggling to connect marketing expenditure with actual leads.

That problem is particularly relevant for service companies, where a phone call, consultation request or web form can represent a much more valuable conversion than a conventional engagement metric.

TruLata attempts to address that attribution gap by turning website forms into tracked lead events. The platform also monitors forms for failures and can flag a form that stops sending leads, according to the company.

Another component focuses on visibility in AI-powered search. TruLata says its platform can show where a business appears in Google as well as in responses generated by ChatGPT, Gemini, Claude and Grok.

This reflects a growing shift in local and service-business marketing from traditional search rankings toward visibility across generative AI interfaces. For businesses whose customers increasingly use conversational systems to research providers, tracking whether a company is mentioned or surfaced by AI platforms is becoming an emerging component of search strategy.

The platform also provides daily monitoring of changes made within a Google Ads account. Combined with lead-source and cost information, this gives business owners a consolidated view of paid acquisition activity rather than requiring them to interpret advertising dashboards separately.

TruLata's approach places it within a broader MarTech market that includes platforms such as HubSpot, GoHighLevel, Semrush and Vendasta, which combine different elements of marketing automation, customer acquisition, reporting and business growth. TruLata's positioning is narrower, focusing specifically on service businesses and simplifying the operational layer around their marketing.

Pricing starts at $400 per month for Starter, followed by Launch at $650 and Growth at $1,200. A Command plan is available through sales. Plans are offered monthly or at a 20% discount when billed annually, with no setup fee.

The website builder remains a separate entry point: businesses can create and edit their website for free, then pay $49 per month to publish it on their own domain, or $39 per month when billed annually.

The larger question for service businesses is whether consolidating marketing operations can make attribution and execution easier without sacrificing control. TruLata's product reflects a broader movement toward AI-enabled marketing systems that automate recurring tasks while giving business owners a single operational view of acquisition.

Market Landscape

The service-business MarTech market is increasingly moving toward all-in-one marketing platforms that combine websites, CRM, advertising, automation and analytics. Platforms such as HubSpot and GoHighLevel provide broader marketing infrastructure, while tools such as Semrush focus more heavily on search intelligence.

TruLata differentiates itself by combining marketing execution with lead-level attribution and AI-search visibility in a product specifically positioned for service businesses.

The emerging AI-search component is particularly notable. Traditional SEO reporting generally focuses on rankings, traffic and clicks, while generative search introduces new questions around brand mentions, citations and whether AI systems recommend a business for relevant queries.

Strategic Outlook

TruLata's launch illustrates how AI marketing platforms are increasingly moving beyond content generation toward continuous marketing operations.

For service businesses, the potential value lies less in having another AI writing assistant and more in connecting website activity, advertising changes, lead generation and acquisition costs in one workflow.

The key test will be whether automated execution and consolidated reporting can produce enough operational simplicity to justify an all-in-one platform compared with assembling specialized tools.

Top Insights

• TruLata combines website management, advertising, content, outbound marketing and lead attribution for service businesses in a single AI-powered platform.
• Its lead dashboard connects individual leads with acquisition sources and costs, addressing attribution challenges common among businesses dependent on calls and inquiries.
• The platform tracks visibility across Google and major generative AI systems, including ChatGPT, Gemini, Claude and Grok.
• A free website builder lowers the entry barrier, while publishing on a business's own domain costs $49 monthly or $39 with annual billing.
• TruLata's launch reflects the broader shift from standalone AI content tools toward systems capable of running recurring marketing operations.

Get in touch with our MarTech Experts.

Influencer marketing platforms are moving beyond creator discovery and campaign management toward autonomous workflow automation. partnrUP.ai has rebuilt its platform around persistent brand intelligence, reusable creator personas and AI agents, claiming the new architecture can cut campaign development time by more than 99% for some workflows while making campaign setup several times faster.

The rebuild targets a familiar bottleneck in enterprise influencer marketing: much of the work happens before a campaign is actually configured inside a platform.

According to partnrUP, teams can spend around 20 hours on creator discovery, vetting, shortlisting and recommendations before moving into campaign strategy and creative briefing. Its redesigned platform attempts to automate much of that preparation, moving from creator identification toward campaign activation.

The core technology is an agentic AI architecture. Rather than using AI only to generate individual pieces of content, partnrUP says its AI agents can work from persistent brand intelligence and reusable creator personas to perform multiple connected tasks.

Those tasks include developing creator recruitment and application strategies, generating personalized outreach, suggesting qualification questions, recommending campaign hooks and preparing initial creative briefs.

That distinction matters as influencer marketing becomes more operationally complex. A brand running a small campaign may be able to manage creator selection manually, but always-on programs spanning multiple products, audiences and markets create a much larger workload. Automating repetitive coordination can therefore become as important as improving creator discovery itself.

partnrUP also reports significant improvements within its campaign builder. Across paid UGC and influencer-posting campaigns, average setup time declined from a historical benchmark of approximately 28.4 minutes to 8.3 minutes, according to the company. That represents a roughly 3.4-fold increase in setup speed.

Paid influencer-posting campaigns reportedly fell from approximately 33.3 minutes to 9.1 minutes, while UGC campaign setup declined from about 24.5 minutes to 7.7 minutes.

Product gifting and PR-seeding campaigns saw setup times fall by approximately 83%, according to partnrUP. The company estimates this saves about 20 minutes per campaign compared with its historical benchmarks.

The larger strategic shift is from campaign-centric influencer marketing toward always-on creator programs. Instead of treating creators as a list of temporary campaign participants, brands can build reusable creator communities and maintain relationships across multiple activations.

This puts partnrUP into an increasingly competitive creator technology market. Platforms such as CreatorIQ, GRIN, Aspire and Later offer combinations of creator discovery, relationship management, campaign execution, content management and measurement. The differentiation is increasingly moving toward how much of the workflow can be automated without removing marketers from strategic decision-making.

PartnrUP says marketers remain responsible for strategy, creative judgment and creator relationships while its AI handles more operational work. That human-in-the-loop model is important because creator campaigns involve brand suitability, tone, audience fit and relationship considerations that cannot always be reduced to automated recommendations.

The company cites Dole, JUNK Brands and Red’s All Natural among existing customers using its platform. However, the reported time savings are company-provided benchmarks rather than independently verified performance measurements.

The development reflects a broader movement across MarTech toward agentic systems that can execute multi-step workflows instead of simply assisting with individual tasks. In influencer marketing, that could mean AI increasingly handling the operational layer connecting creator discovery, recruitment, briefing and campaign configuration.

Market Landscape

Influencer marketing is becoming more integrated with broader creator commerce, social commerce and performance marketing strategies. As brands expand creator programs, manual processes around recruitment, communication and campaign setup can become significant operational costs.

The competitive market includes CreatorIQ, GRIN, Aspire and other platforms that combine creator databases with campaign management and analytics. Meanwhile, broader marketing platforms are adding AI capabilities that can automate content creation, audience analysis and campaign workflows.

Agentic AI introduces another competitive dimension: the ability to coordinate several related tasks from a single campaign objective rather than requiring marketers to execute each step separately.

Strategic Outlook

The most important development is not simply faster campaign configuration. It is the potential shift from influencer campaign software to AI-assisted creator program infrastructure.

If agentic systems can reliably manage repetitive discovery, recruitment and preparation tasks, marketing teams could operate larger creator communities without increasing administrative workloads at the same rate.

The remaining challenge is control. Brands will need visibility into why AI agents recommend particular creators, how outreach is personalized and how automated decisions align with brand-safety and creator-relationship requirements.

Top Insights

• partnrUP’s agentic platform automates creator discovery, recruitment and campaign preparation, targeting operational bottlenecks that limit the scalability of influencer programs.
• Campaign setup times fell substantially in partnrUP’s reported benchmarks, with paid influencer and UGC workflows becoming several times faster.
• Persistent brand intelligence and reusable creator personas allow AI agents to work from established context rather than starting each campaign from scratch.
• The platform targets always-on creator programs, reflecting a broader shift from isolated influencer campaigns toward continuous creator relationships and commerce.
• Human marketers remain responsible for strategy and creative judgment, creating a human-in-the-loop model as agentic AI takes over repetitive campaign operations.

Get in touch with our MarTech Experts.

Market America Worldwide has completed the sale of the SHOP.COM domain name to Shopify, ending a 15-year chapter for the digital commerce property as the company consolidates its shopping, product and entrepreneurship ecosystem under MarketAmerica.com. The move comes alongside the launch of a redesigned MarketAmerica.com platform built on Shopify and incorporating an AI-powered shopping assistant.

The transaction marks a significant change in Market America's digital identity, but the company says it is not abandoning the commerce capabilities developed through SHOP.COM. Instead, it is bringing its retail and entrepreneurship operations back under the Market America brand.

Market America acquired SHOP.COM in 2011 and subsequently developed the domain into an international shopping destination. The company used it as part of its expansion into e-commerce and social shopping while serving customers and its UnFranchise Owners.

On September 22, Market America launched a redesigned MarketAmerica.com, built on Shopify, as the company's primary global digital destination. The platform brings its exclusive brands, products, shopping experience and UnFranchise business together under one domain.

The timing is notable because brand consolidation is becoming increasingly important in digital commerce. Businesses operating multiple web properties can create fragmented customer journeys, complicate analytics and require consumers to navigate between different digital identities. Consolidating those experiences can provide a more direct relationship between brand, commerce platform and customer data.

Market America says the new site is designed around a mobile-first experience, with simplified checkout, improved navigation and search capabilities. It also introduces Atlas, an AI-powered shopping assistant intended to help customers discover products across the company's portfolio.

AI shopping assistants are becoming a significant area of competition in e-commerce. Amazon has integrated generative AI into product discovery and shopping experiences, while Google is developing AI-powered commerce and product discovery through its search ecosystem. Shopify, meanwhile, has expanded AI capabilities across merchant operations and commerce workflows.

Market America's approach is focused more narrowly on using AI as a discovery layer within its own commerce ecosystem. Atlas could potentially reduce the friction involved in navigating a large product catalog by allowing customers to find products through conversational interactions rather than conventional category browsing.

The redesigned platform retains existing customer programs including Subscribe & Save, Cashback and the 60-Second Health Quiz, according to the company.

For UnFranchise Owners, the consolidation also changes how the company's digital ecosystem is presented. Market America says the unified platform is intended to connect its products, customers and entrepreneurship model more directly.

The strategic shift reflects the evolution of Market America itself. Founded in 1992, the company has moved through relationship marketing, direct-to-consumer commerce, e-commerce and social shopping before adding AI-enabled commerce to its technology strategy.

The SHOP.COM domain sale also has a broader industry dimension because the buyer is Shopify. The transaction gives Shopify control of a highly recognizable commerce-related domain while Market America focuses its digital identity around its corporate brand.

The value of the transaction was not disclosed in the announcement, so its financial significance cannot be assessed from the available information.

For Market America, the more consequential development may be the platform consolidation rather than the domain transaction itself. Bringing commerce, AI-assisted product discovery and its entrepreneurship ecosystem under one digital identity gives the company a simpler foundation from which to develop its next generation of e-commerce services.

Market Landscape

E-commerce platforms are increasingly becoming experience layers rather than simple transaction engines. Search, recommendations, customer data, payments, loyalty programs and AI assistants are converging within the digital storefront.

Shopify, Amazon and other major commerce ecosystems are investing heavily in AI-assisted discovery and merchant technology. At the same time, brands are reconsidering how many separate digital properties they need as consumers increasingly expect seamless mobile and conversational shopping experiences.

Market America's move reflects that consolidation trend. By transitioning its primary destination to MarketAmerica.com and building the experience on Shopify, the company is combining its brand identity with a modern commerce infrastructure.

Strategic Outlook

The next phase of Market America's digital strategy will depend on how effectively it uses the new platform beyond a domain and storefront transition.

Atlas gives the company an opportunity to test AI-assisted product discovery, while the unified platform could provide a more coherent foundation for customer engagement, commerce analytics and its UnFranchise ecosystem.

The larger trend is clear: e-commerce brands are increasingly treating AI as part of the shopping interface itself. Product discovery that once depended on navigation menus and keyword searches is gradually moving toward recommendation engines and conversational assistance.

Top Insights

• Market America sold SHOP.COM to Shopify while consolidating its commerce ecosystem under MarketAmerica.com, simplifying its digital brand architecture.
• The redesigned MarketAmerica.com uses Shopify infrastructure and introduces Atlas, an AI-powered shopping assistant for product discovery and navigation.
• The platform retains programs including Cashback and Subscribe & Save, linking the company's legacy commerce services with its redesigned digital experience.
• The transaction illustrates how e-commerce companies are consolidating digital identities while investing in AI-powered product discovery and mobile-first shopping experiences.
• Shopify's acquisition of the SHOP.COM domain adds a recognizable commerce-focused digital asset to an increasingly competitive e-commerce technology ecosystem.

Get in touch with our MarTech Experts.

As AI-generated answers and zero-click search change how consumers discover brands, Spinutech is using the 2026 North American Marketing Leadership Summit to argue that traditional SEO metrics no longer tell the full story of brand visibility. The digital agency will present a framework that expands measurement beyond rankings, clicks and website traffic to include citations, AI recommendations, sentiment and visibility across a fragmented discovery ecosystem.

Spinutech is sponsoring the 2026 North American Marketing Leadership Summit (NAMLS), taking place September 28–30 at the Arizona Biltmore in Phoenix, where two of the agency’s executives will examine how artificial intelligence is changing the way brands are discovered and evaluated.

Kip Russell, Senior Director of Business Insights, and Taylor Fisher, Associate Director of Content Delivery, will present “Built to Be Found: The New Rules of Brand Visibility in an AI-Driven World.” The session focuses on a shift that is becoming increasingly important for marketing organizations: consumers are no longer relying on a single search engine or website to research potential purchases.

Instead, discovery is spreading across conventional search, AI assistants, social networks, video platforms and third-party publications. That fragmentation creates a measurement problem for marketing teams that have historically relied heavily on rankings, organic traffic and clicks to assess search performance.

Spinutech argues that those metrics remain relevant but provide an incomplete view of visibility in an AI-mediated search environment.

The distinction is particularly important as Google AI Overviews, Google AI Mode, ChatGPT, Microsoft Copilot and other generative AI interfaces increasingly provide synthesized answers rather than simply presenting lists of links. A consumer may therefore encounter a brand recommendation without visiting the company's website at all.

This is driving greater interest in Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO). Traditional SEO focuses heavily on helping websites become discoverable and rank for relevant queries. AEO and GEO broaden that objective to include whether information about a brand can be retrieved, cited and accurately represented by AI systems.

Russell describes the change as a redistribution rather than disappearance of the customer journey. That distinction is significant for enterprise marketing teams because the same prospect can encounter a company through several independent information sources before reaching a branded website.

The implications extend beyond search optimization. AI systems can draw information from news coverage, reviews, directories, social media, videos and other third-party sources. Brand authority therefore increasingly depends on the consistency and quality of information available across the wider web.

Spinutech's proposed measurement framework reflects that change by adding visibility, citations and sentiment to traditional search metrics. Instead of asking only whether a page ranks or receives a click, marketers can also ask whether an AI system mentions the brand, what sources influence that answer and how the company is represented.

That approach places SEO closer to broader digital PR, content marketing, social media, paid media and brand reputation management. For large organizations, it also raises the importance of entity consistency and authoritative third-party references.

The competitive landscape is evolving accordingly. SEO platforms such as Semrush, Ahrefs and BrightEdge have expanded their capabilities around AI search visibility, while major marketing platforms from Adobe, Salesforce and HubSpot increasingly incorporate AI into content, analytics and customer engagement workflows.

Spinutech's summit presentation does not suggest abandoning conventional SEO. Instead, its argument is that marketers need a wider scoreboard as search becomes more distributed.

For marketing leaders, that could ultimately change how teams define search success. A ranking may still matter, but visibility increasingly includes whether a brand becomes part of the answer itself—and whether the information presented about it helps influence a purchasing decision.

Market Landscape

The rise of generative AI is turning search visibility into a broader brand discovery problem. Search engines remain important, but AI assistants, social platforms, video and third-party content increasingly participate in the research process.

That creates new responsibilities for SEO, content, PR and marketing analytics teams. Rather than optimizing only owned web properties, organizations need to understand how their brand is represented throughout the information ecosystem that AI systems can access.

The development also increases the importance of measurement. Traditional SEO tools can report rankings, impressions and clicks, while emerging AI visibility platforms are beginning to monitor brand mentions, citations and responses generated by AI systems.

Strategic Outlook

The next phase of search marketing is likely to be less about choosing between SEO and AI optimization and more about connecting them.

Traditional technical SEO, authoritative content and structured information remain foundational. AEO and GEO add another layer by asking whether that information can be retrieved and used accurately in AI-generated responses.

For enterprise marketing teams, this means search strategy may increasingly overlap with digital PR, reputation management, content operations and brand intelligence. The organizations that can connect these signals will have a clearer picture of how customers encounter their brands before a website visit ever occurs.

Top Insights

• Spinutech is expanding brand visibility measurement beyond rankings and clicks as AI-generated answers redistribute discovery across multiple digital channels.
• AEO and GEO extend traditional SEO by focusing on whether brands are retrieved, cited and accurately represented within AI-generated answers.
• AI search makes third-party sources more important, increasing the strategic role of digital PR, reviews, social media and authoritative content.
• Marketing teams increasingly need visibility, citation and sentiment data alongside conventional organic search metrics to understand modern brand discovery.
• The shift connects SEO with content, paid media, social strategy and reputation management as customer journeys become increasingly distributed.

Get in touch with our MarTech Experts.

Omnicom has received recognition in two newly published 2026 Gartner reports on global digital marketing agencies, including a Leader position in Gartner’s Magic Quadrant and the highest evaluated scores across the use cases covered in its Critical Capabilities research. The assessments arrive as agencies increasingly compete on AI, data, martech implementation and integrated customer experience capabilities. Gartner published the Magic Quadrant on August 25 and the Critical Capabilities report on August 26, 2026.

Omnicom’s latest Gartner recognition puts the advertising holding company squarely in a market that is changing as artificial intelligence blurs the boundaries between traditional agencies, technology integrators and marketing platforms.

In Gartner’s Critical Capabilities for Global Digital Marketing Agencies, Omnicom was evaluated across seven use cases: global brand and marketing campaign execution, omnichannel content generation, AI-driven marketing innovation, data-driven performance marketing, B2B marketing, digital commerce and customer-experience overhaul, and website and digital product design. Gartner’s research says the report is intended to help organizations assess agency capabilities against specific requirements rather than simply relying on overall market positioning.

The accompanying Magic Quadrant for Global Digital Marketing Agencies, published August 25, placed Omnicom Precision Marketing among the evaluated providers and identified the market as one where CMOs are increasingly scrutinizing agency spending, particularly amid AI disruption and constrained budgets.

Omnicom says its Critical Capabilities evaluation considered areas including AI vision, creative execution, martech strategy and implementation, content supply chain optimization, first-party data enrichment and digital marketing performance.

The company's response to that market is increasingly centered on Omni, its AI-enabled intelligence platform. The system is designed to connect enterprise teams, AI agents, data, identity, activation and measurement. Omnicom says Omni incorporates capabilities from Acxiom, Flywheel, its media operations and proprietary content and cultural signals.

That architecture reflects a broader shift in enterprise marketing technology. Instead of operating customer data, media activation, creative production and measurement through separate systems, large agencies are attempting to connect those functions into integrated operating environments.

For enterprise marketing teams, that distinction matters because AI adoption is increasingly moving beyond content generation. AI is being incorporated into audience analysis, campaign planning, optimization, personalization and measurement. Gartner's Critical Capabilities research specifically identifies proprietary AI platforms, AI initiatives and rollout, martech strategy and implementation, digital commerce and personalization among the capabilities relevant to this market.

Omnicom's ecosystem also includes Credera, its digital transformation consultancy, which the company says adds capabilities in marketing technology strategy, organizational design and change management.

The competitive landscape includes agencies such as Accenture Song, Deloitte Digital, dentsu, DEPT, Digitas, GUT Network, Havas CX, Monks and VML, all of which appear among the providers evaluated in Gartner's 2026 research.

That competitive set illustrates how the definition of a digital marketing agency is expanding. Providers are no longer competing solely through creative services or media scale. Data infrastructure, AI capabilities, customer experience transformation and technology implementation are becoming part of the agency value proposition.

Omnicom's Gartner recognition therefore provides more than an award headline. It illustrates how the agency market is being reshaped around integrated technology capabilities. The longer-term test for Omnicom and its competitors will be whether these AI and data investments translate into measurable improvements in marketing performance and customer experience for enterprise clients.

Market Landscape

The global digital marketing agency market is increasingly converging with consulting and technology services. Gartner describes the market as one where AI is blurring the boundaries between creative agencies and technology integrators.

That convergence is also visible elsewhere in the MarTech ecosystem. Adobe, Salesforce, Microsoft and Google increasingly combine AI, data, customer experience and marketing execution within broader technology platforms, while agencies are building their own proprietary layers to orchestrate these capabilities.

Gartner's 2026 research includes ten major global providers, highlighting a market where scale alone is no longer the only differentiator. AI strategy, content operations, martech implementation, digital commerce and customer experience capabilities are increasingly part of agency evaluation.

Strategic Outlook

The agency industry's next phase is likely to be defined by how effectively human expertise, proprietary data and AI systems work together.

For enterprise marketers, the practical issue is less about adopting AI in isolation and more about connecting AI to existing customer data, identity systems, media activation and measurement infrastructure.

Omnicom's Omni strategy represents one response to that challenge. Its combination of AI agents, identity, data and activation reflects the industry's movement toward integrated marketing operating systems rather than collections of individual campaign tools.

The Gartner evaluations also suggest that agency selection is becoming more use-case driven. Organizations may increasingly assess providers according to their ability to support specific business transformations rather than simply choosing a large global agency based on reputation or geographic reach.

Top Insights

• Omnicom’s Gartner recognition reflects the agency market’s shift toward AI, data, martech implementation and integrated customer experience capabilities.
• Omni connects AI agents, identity, data, activation and measurement, positioning Omnicom around an integrated enterprise marketing operating model.
• Gartner’s Critical Capabilities research evaluates agencies across seven use cases, giving enterprise marketers more detailed capability context than broad market positioning alone.
• Competition now includes agencies with consulting, technology and AI capabilities, increasing pressure on traditional advertising groups to demonstrate measurable technology value.
• Enterprise marketing teams increasingly need partners capable of connecting creative, customer data, AI, media activation and measurement within unified workflows.

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Adobe and the National Hockey League are expanding their partnership around AI, content production and customer experience technology as sports organizations increasingly compete for attention across mobile apps, social platforms, streaming and live events. The agreement makes Adobe an Official Creative, Marketing and AI Partner of the NHL, with Adobe’s enterprise technology set to support personalized fan experiences across the League and its 32 Clubs.

The partnership brings together Adobe’s marketing, creative and artificial intelligence portfolio with the NHL’s global fan ecosystem. The League says it has more than 200 million fans across 147 countries, creating a large-scale test case for using AI to produce localized content while maintaining consistent branding.

At the center of the initiative is Adobe GenStudio, the company’s AI-powered content supply chain platform. The NHL plans to use the technology to accelerate content production for NHL.com, its mobile application, social media and digital advertising. AI-generated workflows can also help adapt content for different markets and languages while maintaining predefined brand standards.

For sports marketers, the challenge is increasingly one of content volume. A single game can generate statistics, highlights, player stories, social posts, promotional material and advertising assets across multiple markets. Producing variations manually can slow campaigns and make personalization difficult to scale.

Adobe is addressing that problem through what it calls a broader content supply chain approach: connecting content creation, management, customization and distribution rather than treating creative production as an isolated function.

The second component involves Adobe Experience Platform and Adobe Journey Optimizer. Experience Platform provides a real-time customer data foundation, while Journey Optimizer is designed to use those signals to coordinate interactions across channels.

For the NHL, that could mean tailoring experiences based on how individual fans interact with the League. Someone browsing player statistics on NHL.com, for example, could receive different content from a fan attending a game or interacting with the NHL app. The technology is intended to connect those interactions into a more centralized personalization strategy.

This approach reflects the broader movement toward customer experience orchestration (CXO), where customer data, AI, content and journey management are increasingly connected. Adobe says more than 20,000 brands use its solutions for customer experience orchestration, although the company’s figure is not an independent measure of adoption across the wider market.

The partnership also extends AI beyond the League's internal marketing operations. Adobe says Adobe Express, supported by its Firefly generative AI technology, could give NHL fans tools for creating hockey-themed content. Potential use cases include customized social graphics and other fan-created media using NHL templates.

That consumer-facing layer could become particularly relevant as sports leagues compete with creator platforms for fan engagement. Rather than limiting audiences to consuming official League content, organizations are increasingly exploring ways to make supporters participants in the content ecosystem.

Adobe competes in this broader enterprise marketing technology market with platforms including Salesforce, Microsoft, Google and Oracle, which combine customer data, AI and marketing automation in different ways. Adobe’s differentiation here is the integration of creative tooling with its customer experience stack.

For the NHL, the strategic objective is to connect those capabilities across a global organization and 32 Club markets. The partnership will span major events including the Stanley Cup Playoffs, NHL Global Series and North American and international broadcasts.

The result will depend less on AI content generation alone than on how effectively the League connects data, creative operations and fan interactions. As sports consumption becomes increasingly distributed across apps, social media, streaming and physical venues, the ability to maintain a consistent yet personalized experience may become a significant part of sports marketing infrastructure.

Market Landscape

Sports organizations are becoming sophisticated customer experience operators. They manage large databases of fans while producing high volumes of time-sensitive content across web, mobile, social, email, advertising and live-event environments.

Adobe's NHL partnership illustrates the convergence of MarTech, generative AI, customer data platforms and digital experience technology. GenStudio addresses content production, Experience Platform provides the data layer, and Journey Optimizer connects that information to customer interactions.

The model resembles the broader enterprise MarTech shift toward integrated systems rather than disconnected marketing tools. Competitors such as Salesforce and Microsoft are pursuing similar convergence between AI, data and customer engagement, while Adobe retains a strong connection between creative production and experience management.

Strategic Outlook

The partnership points toward a future in which sports marketing becomes increasingly automated and individualized without abandoning centralized brand control.

For enterprise marketing teams, the more significant development is the combination of AI-generated content, real-time customer data and journey orchestration. That combination can potentially reduce production bottlenecks while enabling organizations to create market-specific experiences at greater scale.

For Adobe, the NHL provides a high-profile environment to demonstrate how its creative and customer experience technologies can operate as a connected enterprise stack. For the League, the opportunity is to turn a global fan base into a more continuously personalized digital audience.

Top Insights

• Adobe and the NHL are combining generative AI, customer data and journey orchestration to personalize fan experiences across global digital channels.
• Adobe GenStudio could help the NHL scale localized content production while maintaining consistent branding across 32 Clubs and international markets.
• Experience Platform and Journey Optimizer connect fan data with personalized interactions, bringing customer experience orchestration deeper into sports marketing.
• Adobe Express and Firefly could shift fans from content consumers into creators by enabling personalized NHL-themed social content and imagery.
• The partnership illustrates how enterprise MarTech stacks are converging creative production, AI, customer data and marketing automation into integrated workflows.

Get in touch with our MarTech Experts.