Artificial intelligence is becoming an increasingly visible part of local business discovery, creating a new consideration for marketers alongside conventional search rankings, local listings and website traffic. Cybertegic, a Pasadena-based digital marketing and web development agency, has published new guidance focused on helping businesses make their information easier for AI-powered search systems to understand and reference.

The shift is reflected in consumer research cited by Cybertegic. According to the 2026 research referenced in the announcement, 45% of U.S. consumers used AI tools for local business recommendations during the previous 12 months, compared with 6% in 2025. Among those users, 63% said they trusted AI-generated recommendations, while 88% said they checked the source or legitimacy of information provided by AI.

The figures point to a developing consumer behavior pattern: AI can increasingly influence initial discovery, but established digital sources remain important for verification.

Market Landscape

Traditional local SEO has largely centered on helping businesses appear in search results and local listings when consumers look for products or services. AI-generated answers introduce another layer because systems can interpret information from multiple sources and present recommendations or summaries directly to users.

That means businesses may need to consider more than where their website ranks. They also need to ensure that information about their services, locations and areas of expertise is sufficiently clear and consistent for AI systems to interpret.

Cybertegic's guidance frames this as an extension of existing SEO rather than a replacement for it. Strong websites, local search signals and established sources continue to provide important foundations, while AI-powered search creates another environment in which those signals may be interpreted.

The distinction is particularly relevant for local businesses. Geographic context can determine which businesses are surfaced for a particular query, while service descriptions, reviews and other online information can influence how a business is understood.

Cybertegic cited two examples from its own work. A probate mortgage financing business appeared in a Google AI Overview for a Pasadena, California, search, while a family law firm appeared in ChatGPT-generated recommendations for a Monterey Park, California, query.

The agency also acknowledges that AI-generated visibility can vary based on factors including platform, query, location and timing. Consequently, appearing in one AI-generated result does not necessarily establish consistent visibility across all AI systems.

Strategic Outlook

The development creates a new measurement challenge for marketers. Traditional SEO provides familiar indicators such as rankings, organic traffic and local visibility, whereas AI discovery can involve whether a business is mentioned, recommended or used as a source within an AI-generated response.

This does not make conventional SEO obsolete. Instead, businesses may increasingly need to combine established search optimization with clearer digital information structures and stronger supporting signals across the web.

Cybertegic's AI Search Survival Guide outlines eight strategies intended to improve how business information is structured and supported across AI-powered search environments.

For local marketers, the strategic priority is therefore shifting from simply asking whether a business ranks to considering whether its digital presence provides enough consistent, authoritative information for emerging AI systems to identify the business accurately.

As AI becomes another interface between consumers and local businesses, visibility may increasingly depend on how effectively brands can establish their relevance across both traditional search and AI-mediated discovery.

Top Insights

• Cybertegic has published guidance focused on AI-powered local business discovery.
• The company cites a rise in U.S. consumers using AI for local recommendations.
• Consumers continue to verify AI-generated business information through established sources.
• AI visibility adds another consideration alongside traditional local SEO.
• AI-generated recommendations can vary by platform, query, location and timing.

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Qualtrics has unveiled XM Data & AI, a new approach to Experience Management designed to help organizations use customer, employee, product and brand data to simulate outcomes, predict behavior and deliver actions during critical experience moments.

The company says its new Qualtrics XM Data & AI Platform will be available in 2027, expanding its existing experience-management technology toward AI-driven decision-making. Qualtrics is positioning the platform around what it calls the “Experience Gap” — the difference between what people expect from a company and what they ultimately experience.

According to Qualtrics, nearly $3 trillion in sales is at risk from poor customer experiences. The company argues that organizations have historically lacked technology capable of translating experience signals into timely action at scale.

Market Landscape

Customer experience management has traditionally centered on collecting feedback through surveys, analyzing sentiment and measuring satisfaction. While these systems can provide valuable insight, much of the process remains retrospective: organizations learn what happened after an interaction has already occurred.

Qualtrics is attempting to shift that model toward predictive and prescriptive experience management. Its proposed platform combines experience data with AI capabilities intended to help organizations assess potential decisions before deployment, anticipate individual behavior and embed actions directly into customer or employee interactions.

The company’s May 2026 acquisition of Press Ganey Forsta is also central to the expanded data strategy. Qualtrics says the $6.75 billion acquisition adds decades of healthcare experience data and established governance capabilities to its broader XM dataset. Press Ganey brings healthcare experience data spanning more than 41,000 facilities, according to Qualtrics.

Strategic Outlook

A central component of XM Data & AI is the concept of continuous “Experience Loops,” or X-loops. Instead of treating a customer journey as a linear process with a defined endpoint, Qualtrics describes these loops as continuously connecting acquisition, retention and growth.

The platform is designed around three capabilities: simulation, prediction and trusted outcomes. Simulation can be used to test potential customer reactions before a pricing, product or policy decision is implemented. Prediction is intended to identify what an individual may do while there is still time to intervene. Trusted outcomes focus on embedding AI-driven actions directly into business processes.

Qualtrics also emphasizes its experience ontology, which provides context around experience data, including who a signal relates to, where it occurs in the lifecycle and what outcome may be appropriate.

The strategic implication is significant for marketers. If experience data can move from retrospective reporting to predictive decision support, customer experience could become more tightly connected to customer lifetime value, personalization and operational execution.

Top Insights

• Experience data is moving toward prediction: Qualtrics wants organizations to act before experience problems become outcomes.
• Simulation becomes a decision tool: Digital representations of customers could allow organizations to test pricing, products and policies before deployment.
• Context remains critical: Qualtrics argues that AI needs structured experience context to produce more reliable outcomes.
• Healthcare expands the data foundation: The Press Ganey Forsta acquisition adds healthcare experience data and governance capabilities to the platform.

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TechDigital Labs has announced an expanded approach to e-commerce search optimization, focusing on product and category page performance, technical SEO and search-oriented content to help online retailers improve visibility in organic search.

The move comes as e-commerce businesses compete for consumer attention across increasingly crowded search results. Product discovery often begins with searches that allow shoppers to identify, compare and research products before deciding where to buy. For retailers, that makes organic visibility an important part of the customer acquisition journey.

Rather than concentrating exclusively on individual product pages, TechDigital Labs says its expanded strategy evaluates the broader structure of an online store, including how product and category pages are organized, connected and presented to search engines.

Market Landscape

E-commerce SEO presents different challenges from conventional website optimization because online stores can contain thousands of product pages, overlapping categories and frequently changing inventories. Poor site architecture, duplicate content or indexing problems can make it more difficult for search engines to discover and interpret relevant pages.

Product pages remain a central component of that environment because they provide detailed information about individual products. TechDigital Labs' approach includes optimizing product titles, descriptions, headings, images, alternative text, URLs, metadata and structured data.

These elements serve both search engines and shoppers. Clear product information can help establish what a page is about, while structured navigation and relevant content can make it easier for visitors to move from discovery toward purchase.

Category pages play a complementary role. They organize related products and can provide broader entry points for users searching for product types rather than individual items. TechDigital Labs says its optimization process examines category structures, navigation, content, keyword targeting and internal linking between categories, subcategories and products.

This relationship between pages is particularly important for larger e-commerce sites. A coherent internal-linking structure can help establish connections between different levels of the product catalog while making navigation easier for shoppers.

Strategic Outlook

Technical SEO is another major component of the strategy. TechDigital Labs says its audits examine crawl errors, indexing issues, duplicate content, page performance, Core Web Vitals, schema markup and mobile usability.

For retailers, technical performance can influence how efficiently search engines crawl and index large inventories. It can also affect the experience users have after arriving from organic search, particularly on mobile devices.

The company's broader approach reflects the increasing complexity of e-commerce search optimization. Keyword research remains important, but effective organic visibility also depends on site architecture, content quality, technical accessibility and the relationship between different pages.

As retailers expand product catalogs and compete across increasingly specific search queries, SEO strategies that consider the entire commerce site may become more useful than isolated optimization of individual product pages.

The key challenge for businesses will be maintaining these foundations as inventory, categories, URLs and customer search behavior change. For e-commerce marketers, sustainable organic visibility therefore increasingly requires SEO to operate as an ongoing part of digital commerce management rather than a one-time optimization exercise.

Top Insights

• TechDigital Labs is expanding its e-commerce SEO strategy.
• The approach covers product pages, category pages and technical SEO.
• Product optimization includes metadata, images, URLs and structured data.
• Category optimization focuses on navigation, content and internal linking.
• Technical reviews include crawling, indexing, Core Web Vitals and mobile usability.

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Liferay has announced the general availability of Liferay Digital Sales Room (DSR), a new capability within its digital experience platform that gives B2B sales teams a self-service environment for managing buyer interactions, sharing content and monitoring engagement throughout a deal.

The offering addresses a common challenge in complex B2B buying journeys: information is frequently distributed across email conversations, shared drives and separate sales tools. As additional decision-makers become involved, buyers can encounter different versions of proposals, case studies, presentations and pricing information.

Liferay DSR brings those materials into a branded microsite that sales teams can create and manage without waiting for IT or marketing support. Because the sales room operates on Liferay DXP, Liferay says it can inherit existing content, customer data, permissions and governance capabilities from the broader platform.

Market Landscape

B2B buying increasingly involves larger groups of stakeholders, making the organization and delivery of digital content an important part of the customer experience. While traditional sales collateral can support individual conversations, fragmented content environments can make it difficult for buying groups to maintain a consistent view of a vendor's offering.

Digital sales rooms have emerged as a way to centralize these interactions. Instead of sending individual documents through multiple channels, sales teams can provide buyers with a dedicated digital environment containing approved materials and resources relevant to a specific opportunity.

Liferay's approach connects this model with its existing digital experience infrastructure. Salespeople can use templates to create rooms and add presentations, case studies, demonstrations and pricing information as a deal progresses. Buyer-side champions can also share the room with other stakeholders, creating a common information environment for the wider purchasing group.

The platform's governance component is particularly relevant for organizations operating in complex or regulated industries. Centralized permissions and approved content can help organizations maintain greater control over what buyers receive while allowing sales teams to move more independently.

Strategic Outlook

The most significant aspect of Liferay DSR is its attempt to connect sales enablement with broader digital experience management. Rather than introducing a standalone sales tool, Liferay is using its DXP as the underlying infrastructure for content, customer data and access controls.

Buyer engagement data is another important component. DSR tracks interactions with shared content, including what buyers view and download and which individuals engage with materials. Sales teams can use those signals to identify active stakeholders, prioritize follow-up and assess activity around an opportunity.

This creates a closer connection between content consumption and sales engagement. However, the value of such visibility will depend on how effectively organizations integrate engagement signals into their existing sales processes and interpret buyer activity without treating every interaction as an indication of purchase intent.

Liferay's move also places digital experience technology closer to the revenue function. For B2B organizations with complex buying groups, the competitive opportunity may increasingly lie in connecting content governance, personalization, collaboration and engagement analytics within the same digital infrastructure.

Top Insights

• Liferay DSR is now generally available within Liferay's digital experience ecosystem.
• Sales teams can independently create branded, governed microsites for individual deals.
• The rooms can centralize presentations, case studies, demos and pricing information.
• Buyer engagement data includes content views and downloads.
• Liferay is linking sales enablement with its existing DXP content, data and governance capabilities.

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Campaign Monitor has launched Marketing Studio, a new campaign creation experience designed to consolidate email creation, visual design, translation, brand management and social publishing within a single marketing workflow.

The product comes from Marigold, which operates Campaign Monitor as part of its marketing technology portfolio. Marketing Studio combines five capabilities—Email Workspace, Creative Lab, Translation, Brand Hub and Social Suite—into one environment aimed primarily at small marketing teams and solo marketers managing multiple campaign functions themselves.

The launch reflects a broader shift in marketing technology toward reducing the number of disconnected tools required to move a campaign from planning to publication. For smaller teams, campaign production can involve separate applications for copywriting, design, translation, brand management, email deployment and social publishing. Campaign Monitor is positioning Marketing Studio as an alternative to that fragmented workflow.

Market Landscape

Marketing teams are increasingly adopting AI-assisted tools to accelerate content production, but adding individual AI features to existing workflows can also create another layer of complexity. The challenge is no longer simply generating content; marketers must maintain brand consistency, adapt assets across channels and move efficiently from creation to distribution.

Marketing Studio addresses that workflow problem by connecting several campaign-production tasks inside Campaign Monitor. Brand Hub serves as the central source for a customer's logo, colors, imagery and brand voice. Those assets can then be applied across Email Workspace and Creative Lab.

Email Workspace can generate an email campaign from a website URL and a selected campaign objective, including a generated image. Creative Lab provides image and banner generation within the email builder, while allowing users to refine the resulting creative.

Translation extends campaigns into seven languages without replacing the original version. Social Suite then repurposes a completed email campaign into an Instagram post with copy, hashtags and an adjustable image.

Strategic Outlook

The launch illustrates how marketing platforms are moving toward broader campaign orchestration rather than specializing in a single channel. Email remains the core environment, but campaign assets increasingly need to move between email, social and localized versions without requiring marketers to rebuild them manually.

That approach could be particularly relevant for small businesses and lean marketing departments where one person may handle strategy, content, design and distribution. Centralizing those activities also gives platforms greater control over brand information and campaign workflows.

Campaign Monitor said Email Workspace, Creative Lab and Social Suite are available to customers on Essentials and Premier plans, with limited trial access on Free Trial and Lite plans. Translation and Brand Hub are available across plans except pay-as-you-go. Marketing Studio is currently available to direct Campaign Monitor customers, while agency access is planned for a future release.

The larger competitive question will be whether integrated marketing workspaces can deliver enough automation to save time without reducing the creative control marketers still require. As AI becomes embedded across campaign production, workflow integration may become as important as individual content-generation capabilities.

Top Insights

• Campaign Monitor has launched Marketing Studio as a unified campaign-production workspace.
• The platform combines five capabilities covering email, creative, translation, branding and social publishing.
• Brand Hub provides centralized brand information for other Marketing Studio features.
• AI-assisted creation is integrated into email and visual content workflows.
• Agency access is planned for a future release.

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3 Enrollment Marketing has launched 3E AI Feed the Beast, a visibility and reputation platform designed to help colleges and universities improve how they appear across AI-powered search and discovery platforms.

The offering targets a growing challenge for higher education marketers: prospective students can increasingly use conversational AI to research institutions, compare academic programs and explore enrollment options. That shifts part of the discovery process away from traditional search results and toward AI-generated answers, creating new questions around institutional visibility, positioning and accuracy.

According to 3E, the platform is designed to help institutions influence how AI systems understand and represent their programs, strengths and differentiators. The company specifically identifies Google AI Mode, ChatGPT, Gemini and AI Overviews as environments where institutions need to establish a credible digital presence.

Market Landscape

Traditional higher education marketing has relied heavily on search engine optimization, paid advertising, content marketing and institution-owned websites. AI-powered discovery introduces another layer in which information can be synthesized from multiple sources before being presented to a prospective student.

That makes institutional authority and third-party validation increasingly relevant to digital strategy. Rather than focusing solely on ranking individual web pages, marketers must consider whether an institution's broader digital footprint provides enough consistent and authoritative information for AI systems to understand its positioning.

For colleges competing for students beyond their traditional geographic markets, this can create an additional visibility consideration. Accurate representation is equally important: appearing in an AI-generated response has limited value if the institution's programs or strengths are incorrectly described.

Strategic Outlook

3E AI Feed the Beast combines AI visibility analysis with enrollment-focused marketing activities. Its capabilities include competitive analysis, institutional positioning, AI-oriented content development, technical optimization, third-party authority building, visibility monitoring and quarterly strategic optimization.

The approach signals a shift from treating AI search as a standalone SEO problem toward integrating it with broader enrollment strategy. The company positions the platform around measurable enrollment objectives rather than optimization for AI systems as an end in itself.

The more significant strategic challenge for higher education marketers will be maintaining consistency across owned content, third-party sources and institutional data. As AI discovery evolves, colleges will need to evaluate not only how frequently they appear but also whether the information used to describe them is accurate, differentiated and aligned with their enrollment priorities.

Top Insights

• AI discovery is creating a new visibility layer: Colleges must consider how they are represented beyond conventional search rankings.
• Positioning matters alongside visibility: Being surfaced is less useful if AI systems misunderstand an institution's programs or strengths.
• Authority signals remain important: Third-party references and credible institutional information can support broader digital discoverability.
• Enrollment strategy is moving closer to AI strategy: AI visibility can become part of the wider student acquisition and consideration journey.

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Walden Media Group (WMG) has been named an approved marketing vendor for CycleBar, the indoor cycling brand with more than 200 locations within the Extraordinary Brands portfolio. The partnership will give CycleBar franchisees access to WMG's localized performance marketing approach, with the agency focused on rider acquisition and membership growth at individual studio locations.

The arrangement reflects a broader challenge for multi-location and franchise businesses: balancing a consistent national brand with marketing strategies that respond to local audiences. WMG will work directly with individual CycleBar studio owners on acquisition funnels, digital media and hyperlocal campaigns intended to convert prospective customers into riders.

CycleBar's customer experience includes its CycleBeats curated music platform and CycleStats performance tracking system, which provides riders with six post-ride fitness metrics. WMG's role is to translate that existing brand experience into local customer acquisition activity.

Market Landscape

Franchise marketing has increasingly shifted toward localized digital campaigns as individual locations compete for customers within defined geographic markets. National brand recognition can provide awareness, but studio-level growth depends on reaching prospective customers close enough to become regular customers.

WMG's approach combines paid media, acquisition funnels and location-specific targeting rather than relying exclusively on centralized brand campaigns. For a business operating across hundreds of locations, this model can allow marketing activity to reflect differences in local demand while maintaining broader brand consistency.

The partnership also highlights the growing importance of measurement in franchise marketing. Individual operators need visibility into whether marketing activity is generating bookings and memberships, while franchisors have an interest in improving performance across their wider location network.

Strategic Outlook

WMG is simultaneously investing in its own advertising technology infrastructure as it expands its franchise client base. The agency said it is developing AI booking integrations, real-time attribution capabilities and automated campaign infrastructure for multi-location operators.

That technology investment could become strategically important as franchise marketers seek faster campaign optimization and clearer connections between advertising expenditure and local business outcomes.

The combination of centralized technology and studio-level execution is intended to address a recurring problem in franchise marketing: providing individual operators with sophisticated digital capabilities without requiring every location to build its own marketing infrastructure.

For CycleBar, the partnership expands the resources available to individual franchisees while giving WMG another national franchise brand on which to deploy its localized performance marketing model. The longer-term measure will be whether those systems can consistently translate digital advertising and customer acquisition activity into sustainable membership growth at the studio level.

Top Insights

• Walden Media Group has become an approved marketing vendor for CycleBar.
• CycleBar has more than 200 indoor cycling locations.
• WMG will provide localized performance marketing to franchisees nationwide.
• The strategy includes acquisition funnels, digital media and hyperlocal campaigns.
• WMG is investing in AI booking, attribution and automated advertising technology.

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Drivvr AI LLC, an Anshar Labs company, has appointed automotive marketing executive Brian Voss as National Sales Director, adding industry-specific sales leadership as the company expands its AI software and marketing solutions for dealerships across the United States.

Voss will oversee dealer-facing sales efforts and work with Drivvr AI's leadership, product teams and dealership partners. His appointment follows Anshar Labs' acquisition of Dealer World earlier this year, bringing 18 years of dealer relationships and automotive marketing experience into the Drivvr AI business.

Dealer World remains the marketing product within Drivvr AI, while the broader company is developing AI-driven software spanning dealership marketing, customer engagement and operational workflows.

Voss brings more than two decades of marketing experience, including automotive digital marketing, technology and sales leadership. His career has involved working directly with dealerships as the industry moved through successive changes from traditional media to digital, mobile, social and data-driven marketing.

Market Landscape

Automotive retailers are increasingly evaluating artificial intelligence not simply as an emerging technology but as a potential operational tool. Dealerships can apply AI across customer engagement, marketing workflows and other processes where teams need to manage large volumes of interactions and information.

That transition creates a challenge for automotive technology providers. Dealerships already use numerous digital systems, making the ability to demonstrate measurable business value increasingly important when introducing another technology layer.

Drivvr AI is positioning its offering around this practical adoption challenge. Voss said dealers need solutions that improve team effectiveness and customer experiences rather than technology added for its own sake.

The emphasis reflects a wider shift in enterprise AI marketing, where vendors are increasingly expected to connect AI capabilities with specific business outcomes rather than relying on the novelty of the technology itself.

Strategic Outlook

Voss's appointment gives Drivvr AI an executive with established automotive marketing and dealer experience as the company attempts to expand nationally. That industry background could be particularly relevant as dealerships assess how AI can fit into existing marketing and customer-engagement operations.

The acquisition of Dealer World also provides Drivvr AI with an established dealer network alongside its technology development. Combining those relationships with AI software could allow the company to test and refine products against dealership-specific requirements rather than treating automotive retail as a generic enterprise market.

For the broader automotive MarTech sector, the development highlights an ongoing transition from standalone digital marketing tools toward platforms that connect marketing, customer engagement and operational activities.

The key measure for providers such as Drivvr AI will be whether these systems produce tangible improvements for dealerships, including more effective customer interactions and greater operational efficiency.

Top Insights

• Brian Voss has joined Drivvr AI as National Sales Director.
• He brings more than 20 years of marketing experience and extensive automotive-sector expertise.
• The appointment follows Anshar Labs' acquisition of Dealer World.
• Dealer World remains Drivvr AI's marketing product.
• Drivvr AI is developing AI software for dealership marketing, customer engagement and operations.

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