MarketAnywhere is expanding its nationwide direct marketing operations, giving businesses a centralized platform for coordinating flyer distribution, door-hanger campaigns and brand ambassador programs across markets in all 50 U.S. states.

The expansion targets a persistent operational challenge in offline marketing: coordinating physical campaigns across multiple cities, neighborhoods and service territories while maintaining visibility into when and where field activity takes place.

MarketAnywhere's broader offering includes direct mail, printing and mobile billboard advertising alongside physical distribution services. Businesses can use its platform to select campaign dates, times and locations, communicate with field teams, track activity and review service verification.

The approach reflects an evolution in how offline marketing is being managed. Flyers, door hangers and hand-to-hand promotions are established channels, but companies operating across multiple locations increasingly need centralized campaign management rather than separate local arrangements.

For hand-to-hand distribution, MarketAnywhere targets events, high-traffic areas and other selected locations. Residential campaigns can use door-to-door distribution or door hangers to reach defined neighborhoods.

The company also supports QR codes on physical marketing materials, creating a direct connection between offline exposure and digital destinations such as websites, promotional pages or lead-generation experiences.

Market Landscape

Physical marketing remains relevant for businesses that depend on geographic reach, including home-service providers, local retailers, franchises, events and multi-location companies.

Its challenge is measurement and operational control. Digital advertising platforms provide dashboards for impressions, clicks and conversions, while physical campaigns can be harder to monitor once promotional materials enter the field.

MarketAnywhere is addressing that gap with campaign-management capabilities centered on four functions: schedule, track, communicate and verify.

Real-time tracking and photo verification are intended to give businesses additional evidence that distribution activity has occurred. QR codes can provide another measurement layer by allowing recipients to move directly from a physical advertisement to an online experience.

The model does not make offline advertising equivalent to digital advertising. Instead, it adds operational data and digital response mechanisms to traditional physical outreach.

Strategic Outlook

The expansion could be particularly relevant to businesses managing multiple geographic territories. A centralized provider allows campaign standards to be established nationally while distribution locations, dates and formats can be adjusted for individual markets.

That flexibility is important because physical marketing is inherently local. Neighborhood density, foot traffic, audience composition and business objectives can differ significantly between markets.

For marketers, the opportunity is to treat physical campaigns as part of a broader omnichannel strategy rather than as isolated promotional activity. A flyer can create local awareness, a QR code can generate a digital interaction and campaign tracking can provide operational feedback.

The larger opportunity for platforms such as MarketAnywhere is to make offline marketing more repeatable and accountable without removing the local characteristics that make physical outreach useful.

Top Insights

• MarketAnywhere is expanding direct marketing operations across all 50 states, giving multi-location businesses a centralized approach to physical campaign execution.
• Its platform combines scheduling, field-team communication, tracking and verification to address operational challenges associated with distributed offline campaigns.
• Flyers, door hangers and hand-to-hand distribution can be tailored to residential neighborhoods, events, high-traffic locations and defined service territories.
• QR-code integration creates a bridge between physical advertising and digital destinations, giving marketers another way to connect offline exposure with online engagement.
• Centralized campaign management could help multi-market businesses standardize operations while adapting distribution methods to local audiences and conditions.

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Yattayo AI has launched an AI-powered marketing platform that uses a company's website URL as the starting point for developing, executing and continuously optimizing a marketing strategy.

The platform targets a familiar problem for small businesses, founders, marketing teams and agencies: creating a marketing plan is relatively easy compared with maintaining the continuous cycle of content production, publishing, performance analysis and optimization required to execute it.

Yattayo's approach is to connect those activities within a single AI-driven workflow. After a business provides its website URL, the platform analyzes information from the site alongside market and competitor data to develop a structured strategy covering positioning, target audiences, communications, content pillars and publishing guidelines.

That strategy then becomes the operating framework for connected social media profiles. Yattayo can generate content, organize posts in a publishing calendar, automatically publish them and analyze performance.

The resulting workflow is designed as a continuous loop: analyze, strategize, create, publish, measure and optimize.

That distinction is important as marketing platforms increasingly move beyond generative AI that produces individual assets. Yattayo is positioning AI as an operational layer that can continue managing a workflow after the initial strategy and content have been created.

From AI Content Generation to Autonomous Marketing

Much of the current AI marketing market remains focused on specific tasks, such as generating social posts, writing advertising copy, summarizing analytics or producing campaign ideas.

Yattayo instead connects those tasks. Performance data from managed social profiles can feed into subsequent marketing decisions, allowing the system to identify which content approaches are producing results and use those observations to influence future publishing.

The model resembles an increasingly important direction in marketing automation: closed-loop systems in which AI does not simply generate an output but uses the outcome of that output to determine what happens next.

For businesses managing multiple brands or clients, Yattayo also supports independent social profiles. Each profile can maintain its own business context, strategy, content and publishing workflow.

That capability is particularly relevant to agencies and consultants, which often manage multiple businesses with different audiences, positioning and content requirements.

Market Landscape

Marketing automation has traditionally depended on teams connecting multiple specialized platforms for strategy, content creation, social scheduling, publishing and analytics.

AI is beginning to compress those workflows. Platforms from companies such as HubSpot, Salesforce and Adobe increasingly incorporate generative and agentic capabilities into broader marketing ecosystems, while specialized AI products compete around individual parts of the marketing lifecycle.

Yattayo's differentiator is the simplicity of its initial input: a business URL. The platform is designed to transform information already available on a company's website into a broader marketing operating model.

The challenge for platforms pursuing this approach is maintaining accuracy and strategic consistency. Website information can be incomplete or outdated, while competitor and market signals can change quickly. Autonomous publishing therefore requires effective monitoring and controls rather than content generation alone.

Strategic Outlook

Yattayo's launch points toward a potential evolution in small-business marketing software, where the value proposition shifts from helping marketers perform tasks faster to allowing AI to coordinate those tasks continuously.

For agencies, the multi-profile model could also make AI-managed marketing more scalable. Instead of applying one centralized workflow to multiple clients, each account can operate according to its own context and strategy.

The larger competitive question will be whether autonomous platforms can demonstrate sustained performance improvements without sacrificing brand consistency, editorial quality or human oversight.

As AI agents become more capable of connecting strategy, execution and measurement, marketing teams may increasingly focus on setting objectives, reviewing performance and establishing boundaries while AI handles more of the recurring operational workload.

Top Insights

• Yattayo uses a business website URL as the starting point for generating positioning, audience, content and publishing strategies.
• The platform connects strategy, content creation, social publishing and performance analysis into a continuous AI-managed marketing workflow.
• Performance data feeds subsequent content decisions, creating a closed-loop model rather than treating AI-generated content as a one-time deliverable.
• Independent social profiles allow agencies and consultants to operate separate AI marketing workflows for different businesses and brands.
• The platform reflects a broader shift from AI-assisted marketing tasks toward autonomous execution across recurring marketing operations.

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Force Marketing has expanded its automotive marketing technology footprint with four new OEM-certified partnerships covering Acura, Honda, Hyundai and Nissan, bringing its total number of OEM-certified programs to 16.

The expansion gives Tier 3 automotive retailers access to Force Marketing's data-driven advertising, customer data and retention technologies through programs designed to connect manufacturer requirements with local dealership marketing operations.

For dealerships, OEM certification can influence how quickly campaigns are deployed and how effectively retailers use cooperative marketing funds. Force Marketing says its certified relationships are intended to simplify that process while connecting marketing activity across the customer journey, from initial vehicle discovery through purchase, service and eventual trade-in.

The company's technology stack is built around Audience iQ, its customer data platform (CDP), which is designed to unify dealership customer information and support first-party data activation. The platform is positioned as the foundation for targeting, personalization, advertising optimization and customer retention.

The newly added brands join Force Marketing's existing OEM-certified relationships, which include Porsche, Audi, BMW MINI, INFINITI, Jaguar Land Rover, Kia, Mazda, Stellantis, Subaru and GM Canada.

Automotive Marketing Moves Toward Unified Data Activation

Automotive retailers increasingly operate across fragmented marketing channels, including paid search, social media, display, retargeting, SEO, streaming media, dealership websites and customer relationship systems.

Force Marketing's approach is to consolidate those activities within a connected marketing infrastructure. Its digital advertising services use dealership and customer data to coordinate campaigns across multiple stages of the buying journey.

Its DRIVE streaming media product creates dynamic video using current dealership inventory and incorporates actual vehicle identification numbers (VINs) from dealership websites. Force says its publisher relationships include Amazon, The Trade Desk, TikTok, YouTube TV and Spotify, allowing inventory-based campaigns to extend across streaming and digital environments.

Other components address different points in the customer lifecycle. Recapture targets consumers who have shown interest but have not converted, while Conquest Connect uses a cookieless activation approach to adjust messaging across channels based on shopper behavior.

The company's ATOM service-retention platform extends communications across a dealership's dealer management system (DMS), supporting campaigns designed to encourage repeat service and sales activity.

Market Landscape

The dealership marketing market is becoming increasingly dependent on first-party data as third-party identifiers become less reliable and consumers interact with retailers across more digital touchpoints.

That makes the CDP increasingly relevant to automotive marketing. Rather than treating advertising, lead management, sales and service communications as separate functions, retailers can use unified customer data to coordinate experiences across departments.

The competitive advantage, however, depends on data quality and integration. A connected platform cannot deliver meaningful personalization if customer records remain fragmented or if inventory, CRM, DMS and advertising data cannot be synchronized.

Force Marketing says its solutions are used by more than 1,400 dealerships across North America. The company is now positioning its expanded OEM certification network as another layer of infrastructure for connecting manufacturer programs with dealership-level execution.

Strategic Outlook

The addition of Acura, Honda, Hyundai and Nissan strengthens Force Marketing's position as a technology and marketing partner operating between OEMs and local retailers.

For dealerships, the bigger development is less about adding four logos to a partner list and more about reducing the number of disconnected systems required to execute omnichannel marketing.

As automotive retailers compete for both vehicle sales and recurring service revenue, the ability to connect first-party customer data, inventory signals, advertising activation and retention communications could become increasingly important.

The OEM-certified model also gives Force Marketing a route to standardize its technology across more dealership networks while adapting execution to individual OEM requirements.

Top Insights

• Force Marketing now has 16 OEM-certified partnerships, expanding its dealership marketing reach across Acura, Honda, Hyundai and Nissan.
• Audience iQ serves as the company's customer data platform, connecting first-party customer information with advertising, personalization and marketing activation.
• DRIVE connects real-time dealership inventory with streaming and digital advertising, using VIN-level information to create more relevant vehicle campaigns.
• Conquest Connect and Recapture address shopper activation and remarketing while reducing reliance on traditional third-party cookie-based targeting.
• ATOM extends marketing into dealership service retention, linking customer communications with DMS data to support repeat revenue opportunities.

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Zendesk is moving its AI strategy beyond general-purpose assistants with the launch of Specialized AI Agents designed to handle business-specific workflows using industry expertise, company knowledge, connected systems and defined policies.

The customer service technology company says its new agents can automate up to 80% of workflows. The offering consists of Industry Agents, which are preconfigured for common tasks within specific sectors, and Custom Agents, which businesses can create around their own processes and requirements.

The launch represents a broader shift in enterprise AI from answering questions to completing multi-step work. Rather than simply generating a response, Specialized AI Agents can access business systems, retrieve information, follow policies and take actions while maintaining human approval requirements where organizations want them.

Zendesk is initially introducing Industry Agents for commerce. The agents can support shopping, order management, returns and exchanges, delivery issues and refunds. The company plans to expand the model into financial services, media and technology.

For commerce organizations, the agents can connect with platforms including Shopify, Narvar, Stripe and Riskified. This allows an AI agent to work across multiple systems instead of requiring customers or service representatives to manually switch between applications.

Zendesk is also integrating Riskified's risk intelligence into commerce workflows to support decisions involving returns, refunds and exchanges and help retailers address fraud and policy abuse.

Market Landscape

Enterprise AI agents are increasingly shifting from standalone conversational interfaces toward workflow automation. Companies such as Salesforce and ServiceNow are developing agentic capabilities that allow AI systems to interact with enterprise data and applications rather than simply provide information.

The competitive question is therefore moving beyond whether a company has an AI agent. It is becoming whether that agent has enough context, permissions and system connectivity to complete a business process reliably.

Zendesk's industry-specific approach addresses one of the biggest challenges with generalized AI: business workflows often depend on specialized terminology, policies, integrations and approval structures. A retail returns workflow, for example, requires different logic from a financial-services service request.

The company says customers have already completed more than 1 million Custom Agent executions within seven weeks of launch, while some customers have seen automated resolution rates increase by 10% after deployment. Those figures are company-reported and should be viewed in that context.

Strategic Outlook

Custom Agents extend the strategy to processes that cannot easily be standardized. Through Zendesk's no-code Agent Builder, organizations can define what an agent is responsible for, which systems it can access, what actions it can perform and when human approval is required.

Agents can also operate proactively based on business events or schedules, potentially changing customer service from a reactive function into a continuously automated operation.

Zendesk says Industry and Custom Agents can run within Zendesk as well as service environments such as Salesforce and ServiceNow. That interoperability could become important for enterprises that want to introduce agentic automation without replacing their existing service infrastructure.

The longer-term objective is Zendesk's Autonomous Service Workforce, where AI handles an expanding portion of service operations while organizations retain control over policies, permissions and escalation.

Top Insights

• Zendesk is positioning specialized agents as workflow operators, combining AI with industry knowledge, business policies and enterprise system access.
• Commerce is the first Industry Agent category, covering shopping, orders, returns, refunds and delivery issues across connected retail systems.
• Custom Agents let enterprises automate proprietary processes while controlling agent permissions, actions, integrations and human approval requirements.
• Salesforce and ServiceNow compatibility gives businesses a path to deploy specialized AI without replacing established service platforms.
• Proactive and scheduled agent execution could move customer service automation beyond customer-initiated requests toward continuous business-process automation.

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The Estée Lauder Companies is expanding its generative AI search strategy through a global partnership with Profound, aiming to understand and improve how its prestige beauty brands appear across AI assistants and emerging discovery channels.

The partnership gives Estée Lauder Companies a unified view of brand representation across major generative AI platforms, including how products are recommended, what information AI systems surface and where brand visibility or accuracy can be improved.

The move reflects a broader change in product discovery. Consumers increasingly use AI assistants such as ChatGPT and Google Gemini to research products, compare options and obtain personalized recommendations before visiting a brand or retailer website. For a global portfolio containing multiple beauty brands, managing that representation creates a different challenge from optimizing individual websites for conventional search.

Estée Lauder Companies will use Profound's AI marketing and agentic optimization capabilities to analyze and improve content across product description pages, blogs, YouTube channels and other content-production workflows. Areas including product information, ingredients, claims and benefits are expected to be optimized so that large language models can more easily interpret and surface relevant information.

The company describes the deployment as a global, portfolio-wide implementation of Generative Engine Optimization (GEO), rather than an initiative limited to a single brand or market.

Market Landscape

AI-generated recommendations are creating another layer between consumers and the brands competing for their attention. Traditional SEO largely focuses on ranking pages for queries, while GEO also considers whether a brand is represented accurately and consistently when AI systems generate an answer.

That distinction is particularly important in beauty, where product attributes can include ingredients, skin concerns, benefits, formulations and usage recommendations. AI-generated answers may combine information from brand-owned properties with retailer pages, editorial publications, reviews and other third-party sources.

Enterprise marketers therefore face two connected challenges: determining what AI systems currently say about their brands and identifying which content or authority gaps could influence future answers.

Estée Lauder Companies' portfolio approach also highlights an emerging enterprise requirement. Managing AI visibility across many brands requires centralized measurement while preserving the positioning and product distinctions of individual brands.

Strategic Outlook

The partnership could signal a broader shift toward AI visibility becoming an operational marketing function rather than an experimental SEO initiative.

For enterprise beauty companies, the strategic value is not simply appearing more frequently in AI answers. Accurate representation matters because recommendations can shape consideration before a consumer reaches a traditional search result, retailer or brand site.

The next competitive stage will likely involve connecting AI visibility data with existing content management, digital commerce and marketing operations. Companies that can identify inaccurate representations, understand the sources behind AI answers and systematically improve their digital content will have greater control over how their brands participate in AI-mediated discovery.

Top Insights

• Estée Lauder Companies is applying GEO across its global portfolio, moving AI visibility from individual experiments toward centralized enterprise marketing operations.
• Profound will provide visibility into AI brand representation, helping marketers identify recommendation, accuracy and content opportunities across generative search platforms.
• Product pages, blogs and YouTube content become strategic AI-search assets as brands optimize product information for large language model interpretation.
• Beauty's ingredient- and claim-heavy product discovery makes accurate AI representation particularly important as consumers seek personalized recommendations.
• Portfolio-wide AI monitoring could become an emerging enterprise capability as marketers manage brand visibility across multiple generative AI platforms.

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AI search is creating a new competitive battlefield for health and wellness brands, where traditional brand recognition does not necessarily translate into visibility. New research from Avenue Z shows that the sources influencing AI-generated answers can vary substantially depending on the product category.

Avenue Z, a digital marketing, PR and Answer Engine Optimization (AEO) agency, has released its 2026 AI Visibility Index (AIVx) findings across five health and wellness segments: multivitamins, greens and gut supplements, hydration supplements, protein and performance, and GLP-1 and peptides.

The reports identify leading brands and examine the sources that AI systems cite when answering questions in each category. The findings suggest that health brands cannot rely on a single GEO or content strategy. Institutional websites, editorial media, review platforms, manufacturer content and trade publications can carry very different levels of influence depending on the market.

That matters as AI increasingly becomes part of consumer research. McKinsey reported in 2025 that half of consumers surveyed were already using AI-powered search, while 44% of AI-search users said it was their primary or preferred source of insight for purchase decisions.

AI Visibility Varies Sharply by Health Category

Avenue Z's multivitamin analysis places Nature Made at the top, followed by Thorne, Ritual, Pure Encapsulations, Garden of Life and FEEL. The six brands collectively account for 68% of AI share of voice, with Nature Made and Thorne representing 43%.

Institutional domains dominate citations in this segment, accounting for 52% of cited sources. Trade publications and editorial media each represent much smaller portions of the citation landscape.

The pattern changes in greens and gut supplements, where AG1 leads and the top three brands—AG1, Amazing Grass and Bloom—collectively capture 66% of AI share of voice. Avenue Z found a more distributed citation ecosystem in this category, with institutional domains, editorial outlets, competitor content and trade publications all contributing meaningfully.

In hydration supplements, Liquid I.V. leads a concentrated market in which Liquid I.V., LMNT, DripDrop, Ultima Replenisher and Pedialyte account for 74% of AI share of voice. Institutional, editorial and trade sources exert more influence than user-generated content, retailer pages and review platforms.

The protein and performance category is less concentrated. Optimum Nutrition leads, while Transparent Labs and Dymatize bring the top-three share to 43%. Isopure, Levels and NOW Sports reportedly recorded notable year-over-year ranking gains. Institutional sources account for 40% of citations, while review platforms and reference media play a comparatively larger role.

The most regulated segment, GLP-1 and peptides, shows another distinct pattern. Teladoc leads the category, followed by Ro, Hims, Hers, WeightWatchers Clinic and PlushCare. Institutional domains account for 67% of citations, reinforcing the importance of authoritative sources around safety, eligibility, approval, coverage and access.

Market Landscape

The findings reinforce a broader change in search optimization: brands are no longer competing only for rankings on their own websites. AI systems increasingly assemble answers from a wider source ecosystem.

McKinsey's research found that brand websites can represent only 5% to 10% of sources referenced by AI-powered search, with systems also drawing on affiliates and user-generated content.

For health and wellness marketers, that makes reputation and third-party authority strategically important. A brand may have strong first-party content yet remain underrepresented if the external sources AI systems rely upon do not reinforce its expertise.

Avenue Z recommends category-specific approaches that include concise answer-oriented content, technical optimization, relevant PR and publication strategies, and continuous monitoring of defined AI prompts.

That approach also reflects the higher stakes of health-related search. McKinsey's 2026 healthcare research notes that AI-generated health information can improve consumer experiences while raising concerns around privacy, misinformation and trust.

Strategic Outlook

The AIVx findings suggest that GEO for health and wellness is moving toward a category-level discipline rather than a generic extension of SEO.

For marketers, the objective is increasingly to understand which sources AI systems trust for a particular category, then build the content, authority and technical infrastructure needed to participate in that ecosystem.

The winners may not simply be brands producing the most content. They are likely to be companies that understand how AI systems construct answers and deliberately build credibility across the sources those systems already consult.

Top Insights

• Nature Made dominates multivitamin AI visibility, where institutional sources account for 52% of citations and create a distinct authority model for marketers.
• AG1 leads greens and gut supplements, but its category has a more diverse citation ecosystem spanning institutions, editorial media and trade publications.
• Liquid I.V. leads hydration supplements as five major brands capture 74% of AI share, highlighting concentrated competition for generative visibility.
• Optimum Nutrition leads protein and performance, while emerging brands such as Isopure and Levels show that AI visibility remains contestable.
• Teladoc leads GLP-1 and peptide visibility, where institutional sources represent 67% of citations and regulatory credibility becomes particularly important.

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Fashion brands have long used runway shows and lookbooks to create desire around new collections. At New York Fashion Week, ALICE + OLIVIA and Glance are testing a more personalized approach: letting attendees see themselves wearing the clothes as the collection is unveiled.

The fashion brand and Glance launched an AI-powered “See Yourself in the Show” experience during ALICE + OLIVIA's Spring 2027 New York Fashion Week presentation. The activation used Glance's AI virtual try-on technology to generate images of attendees wearing selected pieces from the new collection.

Rather than simply viewing models wearing the clothes, guests could place themselves inside the collection through AI-generated imagery. The experience reflects a broader shift in fashion discovery from static editorial content toward interactive, personalized commerce.

“Fashion has always been about imagination and possibility,” said Stacey Bendet, founder, CEO and creative director of ALICE + OLIVIA. She described the partnership as a way to combine fashion and technology around a more immersive experience.

For Glance, the activation also provides a high-profile example of how generative AI and virtual try-on technology can become part of the shopping journey rather than remaining separate experimentation.

From Lookbooks to Personalized Fashion Discovery

The traditional fashion marketing funnel largely separates inspiration from product interaction. Consumers see a runway presentation, browse campaign imagery or explore an online product grid before eventually considering an item.

AI-powered virtual try-on changes that sequence by putting the consumer into the visual experience.

At the ALICE + OLIVIA presentation, attendees used the Glance experience to generate images of themselves wearing selected Spring 2027 pieces. The technology effectively transformed the collection from something being observed into something participants could visualize on themselves.

That distinction matters for fashion marketers because apparel purchasing is inherently visual. Consumers often need to imagine how a particular garment might look on their own appearance, style and context before moving toward a purchase.

The activation does not eliminate the traditional fashion experience, but adds an interactive layer to it. For brands, that creates potential applications across launches, digital campaigns, social commerce, retail experiences and personalized product discovery.

Market Landscape

The partnership arrives as AI becomes increasingly embedded in digital commerce. Platforms and technology companies including Google, Amazon, Microsoft and Adobe are investing in AI-assisted discovery, personalization and commerce experiences, while retailers are exploring ways to shorten the distance between inspiration and purchase.

Virtual try-on is particularly relevant because it addresses a longstanding limitation of online apparel shopping: consumers cannot physically test how products will look before buying.

Glance's approach places that capability within a fashion-event environment rather than limiting it to an ecommerce product page. That makes the activation notable from a marketing perspective. The technology becomes part of the brand experience itself.

There are still practical challenges. AI-generated fashion imagery needs to represent garments accurately, preserve important design details and avoid creating misleading expectations about fit, color or appearance. Brands also need to consider image permissions, privacy and how generated experiences connect to actual commerce.

For enterprise fashion marketers, the larger opportunity lies in combining generative AI, visual commerce and personalization. A successful implementation could allow a collection launch to simultaneously generate awareness, personalized content and shopping intent.

Strategic Outlook

The ALICE + OLIVIA and Glance activation points toward a fashion marketing model in which consumers increasingly participate in collection storytelling.

The significance is less about replacing traditional runway presentations than about adding an interactive commerce layer around them. If virtual try-on can move from novelty to measurable product discovery and conversion, fashion brands may increasingly use AI to personalize major launches in real time.

That could make the next generation of digital fashion campaigns less about showing consumers what a collection looks like—and more about helping them imagine themselves in it.

Top Insights

• ALICE + OLIVIA and Glance brought AI virtual try-on to Fashion Week, turning collection viewing into a personalized consumer experience.
• The activation moves fashion discovery beyond static lookbooks by allowing attendees to visualize themselves wearing selected Spring 2027 pieces.
• AI-powered visual commerce could help apparel brands shorten the journey between inspiration, product consideration and purchase intent.
• Fashion marketers may increasingly combine generative AI, personalization and virtual try-on across launches, ecommerce and social commerce.
• Accuracy, privacy and clear representation of garments remain important challenges as AI-generated fashion experiences move toward mainstream commerce.

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Freshpet's experience with generative engine optimization (GEO) offers a glimpse into a new challenge for brands: being recognized by traditional search engines is no longer enough when consumers increasingly receive answers directly from AI systems.

Intero Digital shared new results from its work with Freshpet during a recent Search Engine Journal webinar focused on improving brand visibility in AI-generated search results. The digital marketing agency reported that Freshpet increased its appearances in Google AI Overviews by 645% over six months, while traffic from major AI search platforms increased 46%. Key events generated from AI referrals rose 44%.

The Aug. 20 webinar, titled From Invisible to Cited: The 3-Part GEO Strategy That Put Freshpet in AI Overviews, brought together Intero Digital executives Brittni Ratliff and Cosima Compton with Freshpet Senior Director of Digital Marketing Steven Elwell.

The results illustrate how GEO is developing beyond conventional SEO. Instead of optimizing solely for rankings and clicks, brands increasingly need content that AI systems can discover, interpret and cite when generating answers.

From Search Rankings to AI Citations

Intero Digital said Freshpet's earlier AI visibility problems were not primarily related to a lack of brand recognition or content volume. Some content was written in a magazine-style format that made it harder for AI systems to extract concise answers, while review material rendered through JavaScript was reportedly inaccessible to AI crawlers.

The agency used its RASE framework, evaluating AI search visibility through four dimensions: relevance, authority, structure and engagement.

The approach reflects an important difference between traditional SEO and GEO. A page can perform well in conventional search while still failing to provide the machine-readable, directly answerable information that generative search systems need.

Intero Digital said it now tracks 475 individual prompts for Freshpet every day across major large language models, organizing those prompts into more than a dozen categories. The objective is to identify where Freshpet is being cited, where competitors appear instead and which visibility gaps are closest to commercial outcomes.

That level of prompt monitoring points toward a more granular form of search measurement. Rather than tracking a fixed set of keywords, marketers can examine the questions consumers ask AI systems and measure whether their brands become part of the resulting answers.

Market Landscape

The rise of AI Overviews and conversational search from companies such as Google, Microsoft and other AI providers is changing how brands think about search visibility. Traditional SEO remains important, but generative interfaces introduce an additional layer in which content can influence an answer without necessarily producing a conventional organic click.

Intero Digital's Freshpet findings suggest that technical accessibility and content structure can directly affect this new visibility layer. Short, self-contained passages, expanded schema markup and accessible content can make information easier for AI systems to retrieve and interpret.

The recommendations also extend beyond technical SEO. Intero Digital advocates pursuing relevant niche and trade publications because third-party credibility can contribute to the signals AI systems use when determining which sources and brands to surface.

For enterprise marketing teams, the implication is significant: GEO cannot be treated solely as a content-writing exercise. Technical SEO, digital PR, structured data, reputation management and conversion analytics increasingly intersect in AI search optimization.

Strategic Outlook

The Freshpet case suggests that GEO is moving toward an operational discipline built around continuous measurement. Tracking a defined prompt set can show marketers where competitors are winning AI citations and where optimization could have the greatest commercial impact.

The broader shift is from optimizing pages for search engines to optimizing information ecosystems for AI interpretation. Brands that can combine authoritative sources, technically accessible content and clear answers may have a stronger chance of appearing in AI-generated responses.

As AI search becomes more prominent, marketers will likely need to monitor not just where their pages rank, but whether their brand is present in the answers consumers receive.

Top Insights

• Freshpet's 645% increase in Google AI Overviews illustrates how GEO can materially change brand visibility within emerging generative search experiences.
• Intero Digital's RASE framework connects relevance, authority, structure and engagement to the practical challenge of earning AI citations.
• JavaScript-rendered reviews and narrative content created accessibility and extraction barriers that conventional SEO performance may not reveal.
• Tracking 475 daily prompts gives Freshpet a granular view of AI visibility gaps and helps prioritize opportunities closer to conversion.
• Enterprise GEO increasingly combines technical SEO, structured content, digital reputation and third-party authority rather than relying on content volume alone.

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