A small business website can attract thousands of visitors and still fail at its most important job: turning the right visitors into potential customers. A new HelloNation article featuring digital marketing expert Sean O’Kelly argues that qualified lead generation starts with fundamentals such as clear messaging, intuitive navigation, mobile performance, trust signals and measurable calls to action—not visual design alone.

For many small businesses, the website is the point where a prospect moves from simply discovering a company to deciding whether it is worth contacting. That makes the website less of a digital brochure and more of a conversion layer connecting search, advertising, social media and other marketing channels to revenue.

The HelloNation article featuring Sean O’Kelly focuses on what prospective customers need to see before taking that next step. Its central argument is straightforward: a small business website should quickly explain what the company does, who it serves and why a visitor should consider it.

That clarity begins above the fold. Visitors should not have to interpret an abstract slogan or scroll through several sections to understand the business. A concise value proposition, supported by relevant evidence and a visible next step, can reduce the friction between arriving on a page and beginning a sales conversation.

Navigation is another deceptively important component. Small businesses do not necessarily need complex website architectures. In many cases, a simpler structure works better, allowing visitors to move from the homepage to services, supporting information and contact options without unnecessary detours.

The approach is broadly compatible with established website platforms, including WordPress, Wix and Squarespace, as well as more sophisticated marketing ecosystems such as HubSpot, Salesforce and Adobe Experience Cloud. The technology stack can influence capabilities, but the underlying conversion principles remain largely the same. A technically advanced website can still underperform if its messaging is unclear or its conversion paths are difficult to follow.

Performance has become equally difficult to separate from marketing strategy. Google recommends that site owners pay attention to Core Web Vitals, which measure loading performance, responsiveness and visual stability. Its current guidance targets an LCP of 2.5 seconds or less, INP below 200 milliseconds and CLS below 0.1 for a good user experience.

For small businesses, that translates into practical decisions. Oversized images, excessive scripts, outdated plugins and weak hosting infrastructure can create unnecessary friction, particularly for mobile users. Speed optimization is therefore not simply a technical SEO exercise; it can affect whether a visitor reaches the point of submitting a form, calling a business or requesting a quote.

Trust is another critical part of the equation. A first-time visitor often has no existing relationship with the company, so the website has to provide evidence that reduces uncertainty. Customer reviews, case studies, certifications, recognizable clients, industry credentials and transparent contact information can all help answer the question behind many conversion decisions: “Can I trust this company to solve my problem?”

That matters even more in local and service-based markets, where reputation is closely connected to discovery. Google Search and Maps display review scores and review information for businesses, making reputation part of the broader digital customer journey.

Calls to action then provide the bridge between interest and action. Rather than relying on generic prompts, businesses can use context-specific actions such as requesting a quote, scheduling a consultation, booking an appointment or speaking with a specialist. The objective is not to force every visitor into the same funnel, but to give qualified prospects an obvious next step.

Content plays a parallel role. A useful website can answer common customer questions before a sales conversation begins, while also creating additional opportunities to rank for relevant search queries. Service pages, comparison content, educational articles, FAQs and case studies can collectively build topical relevance while addressing buyer concerns.

This is increasingly important as digital channels take a larger share of marketing activity. Gartner reported in 2025 that digital channels represented 61.1% of total marketing spend among surveyed organizations, with paid online channels accounting for 69% of digital spending.

That shift raises the stakes for the destination behind those campaigns. Spending more on Google Search, social advertising or other digital channels does little if the landing experience cannot convert the resulting traffic.

The final piece is measurement. Website analytics should reveal which pages attract qualified visitors, where prospects abandon the journey and which forms or calls to action generate responses. For larger organizations, this can extend into marketing automation, CRM integration, attribution and predictive analytics. For a small business, even basic conversion tracking can expose significant gaps that traffic reports alone cannot show.

The broader lesson from O’Kelly's perspective is that lead generation does not begin with an advertising campaign or end with a contact form. It is the product of a connected digital experience in which search visibility, website performance, credibility, content and conversion paths work together.

Market Landscape

The small-business website market is increasingly shaped by a divide between website creation and marketing infrastructure. Platforms such as WordPress, Wix and Squarespace make it easier to launch professional-looking websites, while ecosystems such as HubSpot, Salesforce and Adobe provide deeper CRM, automation, analytics and personalization capabilities.

For smaller companies, however, buying more technology does not automatically solve the conversion problem. The competitive advantage often comes from using a simpler stack effectively: strong positioning, fast pages, useful content, credible proof and reliable measurement.

That is also where AI is beginning to influence the website experience. AI-powered chatbots and conversational interfaces can help answer questions and qualify prospects, while marketing automation platforms can route leads into sales workflows. Gartner has specifically identified website AI chatbots as a potential way to improve buyer experience and accelerate lead qualification.

The emerging model is therefore less about choosing the “best” website builder and more about connecting the website to the broader marketing technology stack.

Strategic Outlook

Small business websites are becoming part of a wider customer-data and demand-generation system. Search engines, AI assistants, paid advertising platforms, CRM systems, analytics tools and marketing automation increasingly influence the same buyer journey.

That means businesses should evaluate their websites against business outcomes rather than aesthetics alone. A high-performing site should be discoverable, understandable, credible, fast and measurable.

As AI-generated search and conversational discovery become more prominent, structured information and answer-focused content will also become increasingly important. Businesses that clearly explain their services, expertise, customer outcomes and areas of specialization will have a stronger foundation for both traditional search and emerging AI-driven discovery.

Top Insights

• Small business websites are becoming conversion infrastructure, requiring clear messaging, trust signals and measurable journeys rather than functioning as static digital brochures.
• Google’s Core Web Vitals make performance a strategic concern, particularly for mobile-first businesses where slow pages can undermine both user experience and search visibility.
• Customer reviews, case studies and credentials reduce buyer uncertainty, making reputation an increasingly important component of local search and website conversion.
• Website builders simplify publishing, but platforms such as HubSpot, Salesforce and Adobe compete at a deeper level through automation, CRM and analytics.
• AI-powered chatbots and marketing automation could help smaller teams qualify prospects faster while connecting website interactions to broader demand-generation workflows.

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Webtoon platforms are increasingly turning digital fandom into physical experiences, and Tappytoon is bringing that strategy to Anime NYC 2026. The global webtoon platform will expand its presence at this year's event with a Club JEM merchandise booth, exclusive collectibles and an industry panel focused on the rapid growth of Boys' Love (BL) and romantasy fandoms.

Tappytoon is expanding its presence at Anime NYC 2026 as the webtoon publisher looks to deepen the connection between digital storytelling, physical merchandise and fan communities.

The company, operated by Contents First, will return to Anime NYC from August 20–23 at New York's Javits Center. Its presence will include Booth #1131 for Club JEM, Tappytoon's official merchandise shop, alongside an industry panel exploring how BL and romantasy have evolved into increasingly influential entertainment categories.

The move reflects a broader change in how digital entertainment companies approach fandom. Rather than treating reading as the endpoint of a content experience, publishers and platforms are increasingly building ecosystems around intellectual property (IP), allowing audiences to interact with characters and stories through merchandise, print editions, events and community experiences.

For Tappytoon, Anime NYC provides a physical extension of an audience that primarily encounters its content digitally.

From Webtoon Reading to Physical Fandom

At the Club JEM booth, fans will be able to purchase merchandise connected to five Tappytoon webtoon properties: He Might Bite!, DEAR. DOOR, Don't Mind Me, Daddy, and Kill Me Now.

The merchandise lineup includes character goods, diorama stands, art cards, photocards, stickers and keychains.

The company is also marking its 10th anniversary with a custom keycap clicker experience featuring Jem, Tappytoon's feline mascot. The activation allows visitors to personalize a collectible, adding an interactive element to what could otherwise be a conventional merchandise display.

That distinction matters in an increasingly crowded convention environment.

Physical events give digital-first entertainment brands an opportunity to transform audience engagement into something tangible. Merchandise can extend the commercial life of an IP while live activations give fans opportunities to interact with properties outside the original content format.

The strategy is familiar across larger entertainment ecosystems, from anime and gaming to streaming and comics. Companies increasingly treat successful stories as expandable IP rather than standalone products.

BL and Romantasy Move Into the Mainstream

Tappytoon's Anime NYC panel will focus on another important development: the growing commercial and cultural influence of BL and romantasy.

The August 23 session, titled "BL & Romantasy: Genre Fandoms Rise with Tappytoon," will bring together representatives from Penguin Random House imprint Inklore, Seven Seas Entertainment and Yen Press imprint Ize Press.

The discussion will examine how genres that were once viewed as niche have developed highly engaged global audiences.

The panel will also explore the relationship between digital readership and traditional publishing. Several Tappytoon titles have expanded into print editions, illustrating how successful webtoon IP can move between formats.

That transition is becoming increasingly important to publishers.

Digital platforms can provide publishers with early signals about reader engagement, including which stories attract sustained attention and which characters or themes generate strong fan communities. Successful digital properties can then become candidates for physical editions, merchandise and other adaptations.

For publishers, that creates a potentially valuable feedback loop between audience behavior and publishing decisions.

Tappytoon's Digital-to-Physical Strategy

Tappytoon's approach sits within a larger transformation in the global comics and manga market.

Webtoon companies such as WEBTOON Entertainment have helped normalize mobile-first serialized storytelling, while publishers continue to explore how digital properties can translate into print and other formats.

The opportunity is particularly relevant for genres with highly engaged communities.

BL and romantasy readers often participate in fandom through social platforms, fan discussions, collecting and recommendations. That creates opportunities for publishers to develop relationships that extend beyond individual chapters or books.

Tappytoon's Club JEM merchandise operation is therefore more than an event activation. It represents an attempt to connect content discovery, commerce and community around the same IP portfolio.

The challenge will be maintaining that engagement beyond major conventions.

A successful fan ecosystem requires a steady pipeline of new stories, merchandise and experiences without making the audience feel that every interaction is primarily a sales opportunity.

Why Anime NYC Matters for Digital Publishers

Anime conventions have become important discovery and engagement channels for entertainment companies seeking direct access to highly active fan communities.

For Tappytoon, Anime NYC provides a particularly relevant environment because its audience overlaps with the readers and collectors driving demand for webtoons, manga and anime-related properties.

The company's decision to combine a retail-style booth with an industry discussion also broadens the purpose of its presence.

Fans get an opportunity to interact directly with characters and merchandise, while publishers and industry professionals can discuss how reader behavior is influencing the future of publishing.

That combination reflects the increasingly blurred boundaries between digital publishing, entertainment commerce and fan culture.

Market Landscape

The global webtoon ecosystem is increasingly evolving from a digital publishing model into a broader IP economy.

Successful webtoons can generate opportunities across print publishing, merchandise, animation, licensing and live fan experiences. The growth of mobile-first storytelling has also created new pathways for discovering properties before they reach traditional publishing channels.

For marketing and entertainment technology teams, the trend highlights the importance of connecting audience data with content strategy and commerce. Reader engagement can increasingly influence which properties receive physical editions, adaptations and merchandising investment.

Tappytoon's Anime NYC strategy is a smaller but visible example of this broader digital-to-physical transition.

Strategic Outlook

The next stage of webtoon growth may depend less on simply acquiring readers and more on building durable IP ecosystems around them.

Platforms that can identify highly engaged fandoms and then connect those communities to print, merchandise, events and adaptations have more opportunities to extend the commercial lifecycle of their content.

Tappytoon's 10th-anniversary activation illustrates that strategy in practice.

The company is using Anime NYC not simply as a promotional venue but as a bridge between its digital platform and the physical communities surrounding its stories. As webtoon IP continues moving across formats, that connection between content, commerce and fandom could become increasingly important to digital publishers.

Top Insights

• Tappytoon's Anime NYC expansion connects webtoon content with merchandise and live experiences, giving digital IP additional opportunities for fan engagement and monetization.
• BL and romantasy's growing mainstream presence demonstrates how highly engaged niche audiences can influence publishing strategies, print adaptations and broader entertainment trends.
• Club JEM gives Tappytoon a physical commerce channel around its webtoon properties, extending character and story engagement beyond the digital reading experience.
• The Anime NYC panel highlights growing collaboration between webtoon platforms and traditional publishers as digital stories increasingly move into print formats.
• Tappytoon's strategy reflects a wider entertainment shift toward building IP ecosystems spanning digital content, merchandise, publishing, events and fan communities.

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Campaign teams often have the data they need but still struggle to find it quickly. NGP VAN is addressing that problem with Navigator, a natural-language AI search assistant built into its Create a List (CAL) segmentation tool. The feature lets fundraisers, organizers and digital teams describe the audience they want in plain language, then converts that request into editable CRM search criteria.

For organizations managing large supporter databases, finding the right people can be as important as collecting the data itself. NGP VAN's new Navigator is designed to reduce the technical friction between those two tasks.

The company has launched Navigator as a natural-language search assistant within Create a List, the core segmentation functionality of its CRM platform. Instead of manually combining filters and search criteria, users can describe the audience they need in everyday language.

Navigator uses AI to interpret the request and translate it into the corresponding search configuration.

A fundraiser, for example, can describe a group of supporters based on giving activity, contact information or engagement history. Navigator then presents the criteria it believes are relevant. Users can inspect those selections, modify them and approve the search before it runs.

That approval step is important. Rather than allowing an AI system to silently determine who appears in a campaign database, NGP VAN keeps the generated logic visible and editable.

Turning CRM Search Into a Natural-Language Interface

The technology reflects a broader shift taking place across enterprise software.

For years, CRM and marketing platforms have required users to understand the application's own vocabulary. Building an audience often means navigating multiple menus, selecting fields, defining operators and combining conditions.

That model can be powerful, but it also creates a learning curve.

Natural-language interfaces are increasingly being positioned as an alternative. Salesforce, Microsoft and other enterprise software vendors have been developing AI assistants that allow users to interact with business systems using conversational instructions.

NGP VAN is applying the same basic interface concept to supporter segmentation.

Navigator does not replace Create a List. Instead, it acts as an AI layer on top of the existing search functionality.

That distinction could make adoption easier because organizations do not need to abandon their established workflows. Experienced users can continue building searches manually, while newer users get a conversational starting point.

AI With Human Review Built In

One of the more notable aspects of the launch is the level of user control.

Navigator is optional. Users can ignore it and continue using manual search. Previously saved searches remain unchanged, and generated criteria are displayed before execution.

That creates a relatively straightforward human-in-the-loop model: AI translates intent into system logic, while the user remains responsible for reviewing and approving the result.

For CRM applications containing sensitive supporter information, that model is particularly relevant.

AI-generated searches can potentially misunderstand ambiguous language or select criteria that do not precisely match a campaign's intent. Making the underlying filters visible gives users an opportunity to catch those errors before a list is used for outreach.

It also makes the feature more explainable than a system that simply returns an opaque audience.

Eight Data Categories at Launch

At launch, Navigator can work across eight Create a List search options: Activist Codes, Addresses, Email, Online Forms, Recurring Commitments, Contributions, Contribution Summaries and My Saved Lists.

Those categories cover several of the data points campaigns commonly use when segmenting supporters.

The immediate value is less about creating a new database capability than making existing data easier to access.

A campaign's CRM may already contain years of contribution records, forms, contact information and engagement signals. The challenge is often turning a human objective—such as identifying a particular group of supporters—into the correct database query.

Navigator attempts to automate that translation.

NGP VAN's Broader AI Roadmap

NGP VAN says Navigator is the beginning of a broader effort to incorporate AI into campaign workflows.

Future capabilities under development include bulk data uploading, analysis of canvassing notes and additional ways to create lists.

If those capabilities reach production, Navigator could evolve from a search assistant into a broader natural-language interface for campaign operations.

That would place NGP VAN within a larger enterprise software trend in which AI agents increasingly sit between users and complex business applications.

The important question will be whether these tools improve productivity without reducing the control and accuracy required for data-driven campaign operations.

For organizations using NGP VAN, the initial approach is deliberately incremental: introduce AI inside an established workflow rather than asking users to adopt an entirely new system.

The Competitive CRM Context

NGP VAN operates in a market where CRM platforms are rapidly adding conversational AI and automation.

Salesforce's Einstein and Agentforce initiatives, Microsoft's Copilot ecosystem and other enterprise AI platforms are moving toward natural-language interaction with customer and business data.

NGP VAN's differentiation is its focus on the political campaign and progressive organizing ecosystem.

That specialization matters because campaign databases contain domain-specific concepts and workflows that generic CRM assistants may not understand as naturally. A purpose-built search layer can potentially reduce the amount of configuration required by organizers and fundraising teams.

At the same time, AI-assisted CRM search is becoming less unusual across enterprise software. NGP VAN's long-term advantage will depend on how well Navigator understands campaign-specific data, how reliably it generates search criteria and how deeply it can extend into other campaign workflows.

Market Landscape

AI-powered natural-language search is becoming an important interface layer for CRM, marketing automation and enterprise data platforms.

The underlying technology is not simply about replacing search boxes with chat. Its larger purpose is to allow business users to translate operational intent into structured actions without mastering complex software interfaces.

For marketing and CRM teams, that trend could reduce training requirements and make sophisticated segmentation available to a broader group of users.

The approach also aligns with the growth of AI agents, which are increasingly being designed to interpret instructions, interact with enterprise systems and execute multi-step workflows.

NGP VAN's Navigator is an early example of that model being applied to campaign CRM segmentation, with user approval remaining part of the workflow.

Strategic Outlook

The next phase of AI-powered CRM will likely move beyond answering questions about customer data toward actually translating business intent into executable workflows.

NGP VAN's initial implementation is relatively focused, but the roadmap points toward a broader model in which organizers could use natural language to upload information, analyze field notes and build targeted audiences.

For enterprise marketing teams, the broader lesson is significant: the value of AI may increasingly come from making existing data infrastructure easier to operate, rather than simply generating new content.

That shift could make natural-language interfaces a standard component of CRM and marketing platforms, particularly as companies try to put sophisticated data capabilities into the hands of nontechnical teams.

Top Insights

• NGP VAN Navigator converts natural-language audience requests into editable CRM filters, reducing the technical learning curve for campaign fundraising and organizing teams.
• Human approval remains central, with Navigator exposing every generated criterion before execution to reduce errors and preserve user control over supporter segmentation.
• The launch demonstrates how AI assistants are becoming interface layers for complex CRM systems, following a broader enterprise trend led by Salesforce and Microsoft.
• Future Navigator capabilities could extend AI beyond search into data uploads and canvassing analysis, potentially creating a broader campaign workflow assistant.
• NGP VAN's domain-specific approach gives it an opportunity to tailor conversational AI to political organizing workflows rather than generic CRM use cases.

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As enterprises move AI agents from experimentation into production, the cost of choosing the wrong model for routine tasks can quickly become significant. Snowflake is addressing that problem with dynamic model routing in Cortex AI Gateway, allowing workloads to be matched automatically with models based on task complexity, quality requirements and cost. The company is also expanding access to open models, giving enterprises more options as AI workloads scale.

Snowflake is expanding its enterprise AI infrastructure with dynamic model routing designed to help businesses control inference costs without forcing developers to manually select a model for every AI task.

The capability is being introduced within Snowflake Cortex AI Gateway and integrated into Snowflake's AI products, including Snowflake CoCo and Snowflake CoWork. It is also available to third-party AI agents connected through Cortex AI Gateway.

The underlying idea is straightforward: not every AI request needs a frontier model.

A repetitive classification task, simple data transformation or routine workflow may be handled effectively by a less expensive model. A complex reasoning problem, coding task or sophisticated agent workflow may justify a more capable—and potentially more expensive—model.

Snowflake's dynamic routing system is designed to make that decision automatically.

The move comes as enterprise AI deployments become increasingly multi-model. Organizations can now choose from proprietary systems offered by companies such as OpenAI, Anthropic and Google, alongside rapidly evolving open models from providers such as DeepSeek, Meta and Mistral.

That choice creates flexibility, but it also creates operational complexity.

Model Choice Becomes an Infrastructure Problem

When organizations run a handful of AI experiments, model selection is relatively straightforward. Developers can test several models and choose one based on quality and price.

Production AI is different.

An enterprise may have hundreds or thousands of agents making requests across customer service, analytics, software development, marketing and internal operations. Model pricing and capabilities can also change quickly.

Using the most capable model for every request can increase costs unnecessarily. But optimizing manually creates another problem: engineering teams must continually monitor model performance, pricing, availability and compliance requirements.

Snowflake is positioning Cortex AI Gateway as an abstraction layer that handles some of that complexity.

Its dynamic routing capability can direct lower-complexity work toward more efficient models while sending tasks requiring deeper reasoning to frontier systems.

The approach effectively turns model selection into an infrastructure function rather than a decision developers must repeatedly build into individual applications.

Snowflake's "Intelligence Efficiency" Strategy

Snowflake describes this approach as intelligence efficiency—a measure of how effectively organizations convert compute, models, data and context into business value.

That framing is significant because enterprise AI economics are becoming more complicated than simply measuring the number of tokens consumed.

A less expensive model may be the better choice if it produces an acceptable result with significantly lower inference costs. Conversely, a more powerful model can make economic sense if better reasoning reduces errors, rework or downstream human intervention.

Snowflake says internal testing demonstrated the potential impact.

In one evaluation, agents using dynamic routing to build a dbt pipeline achieved up to three times greater token efficiency than a frontier-model-only approach while maintaining comparable quality.

In another test, engineering teams completed the same number of pull requests with 25% greater token efficiency.

Those are Snowflake's internal results rather than independently verified industry benchmarks, so they should be viewed as directional rather than universal performance expectations.

Still, they illustrate the central economic argument: model quality and model cost do not necessarily need to move together.

Open Models Expand the Enterprise AI Mix

Snowflake is also adding more open models to its Cortex AI environment, including DeepSeek-V4-Flash 0731 and GLM-5.3.

The company already provides access to models from several major providers, including Anthropic, OpenAI, Google, xAI, Meta and Mistral.

For enterprises, the importance of that growing model catalog extends beyond having more choices.

Open and proprietary models can have different cost structures, capabilities, licensing conditions, deployment characteristics and regional availability.

A multinational enterprise, for example, may need to consider where a model is available and whether its use complies with internal data policies or regional requirements.

Snowflake says Cortex AI Gateway allows customers to control which models and providers are available to users.

That governance layer could become increasingly important as enterprises introduce AI agents into sensitive workflows.

Governance Meets Multi-Model AI

The development also illustrates why model routing is becoming closely connected with enterprise AI governance.

A company may want employees to have access to multiple models, but that does not mean every employee or application should have unrestricted access to every provider.

Centralized controls can help organizations define approved models, manage access and account for regional requirements.

Snowflake's approach is particularly relevant to enterprises that already keep data and AI workflows inside its platform.

Rather than requiring developers to integrate every new model independently, Snowflake is attempting to create a governed environment in which models can be added and substituted behind the application layer.

That could reduce the infrastructure burden associated with the rapid pace of model releases.

Competition Is Moving Up the AI Stack

Snowflake is entering a competitive enterprise AI infrastructure market that includes Microsoft Azure, Amazon Web Services, Google Cloud and Databricks, among others.

Cloud providers increasingly offer model catalogs, routing mechanisms, agent infrastructure and governance tools. Data platforms are also moving toward becoming orchestration layers for enterprise AI.

Snowflake's advantage is its existing position around enterprise data.

The company is betting that customers want model flexibility without moving governed data between multiple environments or rebuilding applications whenever a better model becomes available.

That strategy also aligns with the broader shift from single-model AI applications toward multi-model architectures.

The winning platform may not necessarily be the one with the single strongest model. It could be the one that helps enterprises choose, govern and operate multiple models efficiently.

Market Landscape

Enterprise AI is entering a multi-model era.

Organizations increasingly use different models for different workloads rather than standardizing on a single provider. That creates opportunities for model gateways and orchestration platforms that can manage routing, access, security and cost.

Snowflake's Cortex AI Gateway competes indirectly with capabilities emerging across Microsoft Azure AI, Amazon Bedrock, Google Cloud Vertex AI and Databricks Mosaic AI.

The competitive differentiator is therefore shifting from model access alone to model optimization and governance.

For enterprise marketing teams, the implications extend beyond IT. AI-powered content generation, customer analytics, campaign optimization and marketing agents can generate large volumes of model requests. Automatically routing those requests to appropriate models could help organizations control costs while maintaining acceptable output quality.

Strategic Outlook

The economics of enterprise AI will increasingly depend on orchestration rather than simply model performance.

As models become more numerous and specialized, organizations will need infrastructure that can evaluate quality, cost, latency, availability and governance requirements simultaneously.

Dynamic routing is one response to that problem.

Snowflake's strategy suggests the future enterprise AI stack may look less like a collection of applications tied to individual models and more like a governed intelligence layer capable of switching models underneath those applications.

For enterprise marketing teams, that could eventually mean AI agents that use inexpensive models for routine segmentation or content tasks and more sophisticated reasoning models only when a campaign or customer decision warrants the additional cost.

The broader lesson is that AI efficiency may increasingly come from using the right model at the right moment, rather than simply finding the most powerful model available.

Top Insights

• Snowflake's dynamic model routing automatically matches AI workloads with appropriate models, helping enterprises reduce inference costs without manually managing model selection.
• Cortex AI Gateway gives enterprises greater control over multi-model environments, including provider access, regional availability and governance requirements across AI applications.
• Snowflake's internal tests reported up to three-times greater token efficiency for certain agent workflows, though independent benchmarking is needed to validate broader results.
• New DeepSeek and GLM models expand Snowflake's open-model options, giving enterprises more flexibility to balance performance, cost and governance.
• Model routing positions Snowflake against cloud and data-platform competitors as enterprise AI shifts toward multi-model architectures and centralized orchestration.

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Small businesses are becoming more satisfied with their commercial insurers as insurance rate increases moderate and digital policy-management tools improve. The J.D. Power 2026 U.S. Small Commercial Insurance Study found overall satisfaction increased 15 points year over year, with the strongest gains tied to digital channels, pricing perceptions, problem resolution and coverage offerings.

For small businesses, insurance has traditionally been a relationship-driven service. But as insurers invest in digital policy management, online support and self-service tools, the customer experience is increasingly becoming a technology story.

The latest J.D. Power research suggests those investments are starting to translate into higher satisfaction.

Overall satisfaction among small commercial insurance customers reached 713 points on a 1,000-point scale in 2026, up 15 points from the previous year. J.D. Power attributes the improvement partly to slower rate increases and significant gains in digital channels.

The study surveyed 2,900 small commercial insurance customers with businesses employing 50 or fewer people. Research was conducted from January through April 2026.

Digital channels recorded the largest year-over-year improvement, rising 29 points. Satisfaction with price for coverage increased 16 points, while problem resolution and product and coverage offerings each gained 16 points.

For insurers, the results point to an increasingly important connection between digital insurance platforms and customer loyalty.

Digital Tools Are Closing a Service Gap

The biggest impact appears to be among the smallest companies.

Micro businesses, defined in the study as companies with fewer than five employees, recorded the sharpest improvement in satisfaction. J.D. Power says digital capabilities are a major factor, giving small business owners access to policy information and allowing them to make changes without contacting an agent.

That may seem like a straightforward convenience, but for a business owner managing payroll, customers, suppliers and day-to-day operations, reducing the number of interactions required to handle an insurance policy can have meaningful value.

The shift also reflects a broader transformation across financial services.

Banks, insurers and fintech companies have spent years moving routine services online. Small commercial insurance is following the same trajectory, with customers increasingly expecting the ability to obtain information, manage policies and resolve straightforward issues through digital channels.

The implication for insurers is clear: digital self-service is no longer simply an efficiency initiative. It is becoming part of the customer experience itself.

Rate Stability Is Helping Satisfaction

Technology is not the only explanation for the improvement.

The percentage of small commercial insurance customers experiencing a rate increase declined slightly to 33%, compared with 34% the previous year.

More importantly, among businesses that experienced a rate increase, 52% said it resulted from an insurer-initiated rate increase rather than changes in coverage or exposure. That figure fell four percentage points year over year.

The distinction matters because insurer-initiated rate increases are strongly associated with lower satisfaction.

When customers perceive that premiums are rising because their insurer has changed pricing rather than because the business itself has changed, dissatisfaction can increase quickly.

The stabilization of rates therefore gives insurers a more favorable environment in which improvements to digital experiences can have a greater effect.

Understanding the Business Still Matters

Despite the growing importance of technology, the study shows that digital tools cannot entirely replace industry and customer knowledge.

J.D. Power found a substantial satisfaction difference based on how well insurers and agents understand the customer's business.

Satisfaction reaches 750 points when both the insurer and agent completely understand the customer's business. When neither understands the business, satisfaction falls to 547.

That 203-point gap illustrates an important limitation of digital transformation.

A small business does not simply need an insurance portal. It needs coverage that reflects its operations, risks and growth plans.

A technology platform can make policy administration easier, but it cannot necessarily substitute for expertise when a company is evaluating coverage requirements or dealing with a complex claim.

The strongest insurance experiences may therefore combine digital convenience with knowledgeable human support.

Erie Leads Small Commercial Insurance Satisfaction

The study also provides a competitive snapshot of the small commercial insurance market.

Erie Insurance ranked first in overall customer satisfaction with a score of 760. Chubb followed with 746, while Allstate ranked third with 732.

The rankings highlight the challenge facing insurers as customer expectations evolve.

Large insurers are competing not only on premiums and coverage but also on the quality of their digital interfaces, responsiveness, claims resolution and ability to understand the businesses they serve.

Companies such as Microsoft, Salesforce and Adobe have helped establish expectations for intuitive enterprise software experiences across other industries. Insurance providers are increasingly expected to deliver comparable levels of digital convenience, even though the underlying products and regulatory requirements are considerably more complex.

Insurance Technology Becomes a Competitive Differentiator

The J.D. Power findings reinforce a broader trend in InsurTech: digital transformation is shifting from back-office modernization toward customer-facing differentiation.

Policy portals, mobile experiences, automated communications, AI-powered service tools and digital claims processes can reduce friction throughout the insurance lifecycle.

For small businesses, that matters because they often lack dedicated insurance or risk-management teams. The ability to quickly access documents, make policy changes and understand coverage can directly affect how efficiently they operate.

The next phase will likely involve more AI.

Insurers are already exploring AI for underwriting, claims processing, customer service, fraud detection and personalized recommendations. The challenge will be deploying those capabilities without making insurance interactions less transparent or harder for customers to navigate.

The strongest insurers may ultimately be those that use AI and automation behind the scenes while keeping the customer experience simple.

Market Landscape

The small commercial insurance market sits at the intersection of insurance technology, digital transformation and financial services modernization.

The latest J.D. Power results suggest that pricing remains a fundamental driver of satisfaction, but digital experience is becoming a more significant differentiator.

For micro and small businesses, self-service capabilities can reduce dependence on agents for routine policy administration. At the same time, the large satisfaction gap associated with business understanding shows that digital transformation cannot eliminate the need for knowledgeable human support.

This creates a hybrid opportunity for insurers: automate routine processes while using agents and intelligent systems for more complex customer needs.

Strategic Outlook

The next competitive battleground in small commercial insurance is likely to involve the combination of digital convenience, AI-enabled service and personalized insurance expertise.

Insurers that can provide easy policy management while accurately understanding a customer's business could have an advantage over providers that optimize only one side of the experience.

The findings also suggest that technology investments are most effective when they solve concrete customer problems. A better portal matters because it saves time. Digital policy changes matter because small-business owners can avoid unnecessary calls. Better data integration matters because it can help insurers understand risk more accurately.

As AI adoption accelerates across financial services, the question will increasingly shift from whether insurers use AI to whether customers experience tangible improvements because of it.

Top Insights

• Small commercial insurance satisfaction reached 713 points, with digital channels delivering the strongest improvement as insurers modernize policy-management experiences.
• Micro businesses benefited most from digital improvements, gaining easier access to policy information and self-service capabilities without agent assistance.
• Slower insurer-initiated rate increases are also improving sentiment, demonstrating that pricing remains a major factor in commercial insurance satisfaction.
• Business expertise remains critical, with satisfaction 203 points higher when both insurers and agents completely understand the customer's business.
• Erie Insurance led the 2026 rankings, followed by Chubb and Allstate, highlighting competition around digital service, pricing and customer experience.

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As enterprises move AI from experimentation into customer-facing operations, the challenge is shifting from what AI can automate to how safely it can make decisions at scale. Pegasystems (Pega) is addressing that problem with new responsible AI capabilities for customer engagement, alongside a partnership with contact-governance company Gryphon aimed at helping regulated businesses manage compliance while deploying AI-driven marketing.

Pegasystems has introduced new responsible AI capabilities for customer engagement, giving enterprise marketing teams more ways to use agentic AI while maintaining governance, approval controls and compliance oversight.

The company announced the general availability of Pega Customer Engagement Studio, a set of agentic and automation capabilities within Pega Customer Decision Hub. The technology is designed to let marketers create and modify customer engagement strategies using natural-language instructions while applying predefined best practices and governance controls.

Pega also announced a strategic partnership with Gryphon, a contact governance platform focused on omnichannel compliance and auditability.

The combination reflects a growing concern across enterprise MarTech: AI can accelerate campaign development and personalization, but automated decisions also introduce new risks around targeting, consent, contact rules and regulatory compliance.

For financial services, insurance, healthcare, telecommunications and other regulated industries, those risks can make the difference between an AI system that is merely impressive in a demonstration and one that can actually operate in production.

Turning Natural Language Into Marketing Strategy

Pega Customer Engagement Studio is designed to shorten the distance between a marketer's objective and an executable engagement strategy.

Users can describe what they want in natural language. An embedded AI assistant interprets the request, asks clarifying questions and translates the intended strategy into executable rules.

The system also checks the resulting strategy against embedded best practices and can enforce approval workflows.

That is significant because enterprise marketing automation traditionally requires specialized knowledge of campaign rules, data models, eligibility conditions and contact policies.

Instead of asking marketers to manually configure every component, Pega is attempting to make the interaction more conversational while retaining controls behind the interface.

The approach resembles the broader evolution of enterprise software toward agentic AI, where AI systems do more than generate recommendations and begin performing multistep operational tasks.

The difference is that Pega is positioning governance as part of that workflow rather than as a separate compliance layer.

Governance Becomes Part of the AI Workflow

Pega's new capabilities include approval histories, escalation and re-approval controls, as well as validation of targeting rules.

The company says its AI assistant can reuse approved logic when helping users create engagement policies. Policies can cover areas such as eligibility, suitability, applicability and contact rules.

This is particularly relevant to enterprises where marketing decisions cannot be treated as simple optimization problems.

A campaign might identify a highly responsive customer segment, for example, but still be prohibited from contacting certain individuals because of an opt-out, regulatory requirement or internal policy.

Pega says its compliance monitoring can detect changes in connected systems, including customer opt-outs, and flag issues before an action is executed.

That makes the platform less about AI-generated campaign ideas and more about controlled AI execution.

Pega Partners With Gryphon on Contact Governance

The Gryphon partnership extends that strategy beyond Pega's own engagement environment.

Gryphon provides contact governance, continual auditing and reach-recovery capabilities designed for highly regulated sectors. Its compliance coverage includes requirements associated with the Telephone Consumer Protection Act (TCPA), Telephone Relay Service (TRS), Do Not Call (DNC) rules and Fair Debt Collection Practices Act (FDCPA).

The partnership is aimed at helping enterprises maintain contact governance across channels while using AI-driven customer engagement.

This matters because AI can increase the speed and volume of customer interactions. Without centralized controls, that same scalability can amplify mistakes.

An incorrectly configured automated campaign can potentially reach thousands or millions of customers before a marketing team realizes there is a problem.

For enterprises, the ability to audit decisions and demonstrate why a customer was or was not contacted can therefore become as important as campaign performance itself.

Responsible AI Is Becoming an Enterprise Requirement

Pega's announcement arrives as organizations face growing pressure to establish formal AI governance.

The company cites EY research showing that only about one-third of companies have responsible controls for current AI models, despite nearly three-quarters having AI integrated into organizational initiatives.

The disparity illustrates a broader enterprise challenge.

AI adoption is moving faster than governance infrastructure.

Companies are deploying AI across marketing, customer service, sales and operations, but many still have to determine how to monitor automated decisions, maintain audit trails and ensure that AI systems follow changing policies.

For marketing organizations, the issue becomes particularly complicated because customer engagement combines personal data, behavioral signals, predictive models and automated decision-making.

Platforms such as Salesforce, Adobe and Microsoft are also incorporating AI into enterprise marketing and customer workflows, making governance increasingly important across the broader MarTech ecosystem.

The Competitive Shift Toward Governed AI

Pega's competitive positioning is not simply about adding a conversational AI layer to marketing automation.

The company is betting that enterprises will increasingly value AI platforms that can execute decisions while preserving control over how those decisions are made.

That could become a meaningful differentiator as AI agents move deeper into campaign planning, audience selection, personalization and optimization.

The technology also reflects an emerging principle in enterprise AI: autonomy needs boundaries.

Organizations may want AI agents to build campaigns, identify audiences and optimize interactions, but they also need mechanisms to constrain those agents, validate their actions and prove compliance.

For highly regulated businesses, that combination could be more valuable than raw AI productivity.

Market Landscape

Enterprise customer engagement is moving from rule-based marketing automation toward AI-assisted and agentic decisioning.

Platforms such as Pega Customer Decision Hub, Salesforce Marketing Cloud and Adobe Experience Cloud are increasingly incorporating AI into campaign planning, personalization and customer journey management.

The competitive question is shifting accordingly. It is no longer simply whether a platform can use AI to recommend the next-best action. Enterprises also need to know whether that recommendation can be explained, audited and governed.

Pega's emphasis on embedded validation, approval workflows and contact governance places it within this emerging category of responsible AI for marketing automation.

The Gryphon partnership is particularly relevant for regulated industries, where customer-contact rules can vary across channels, jurisdictions and business processes.

Strategic Outlook

The next stage of enterprise AI adoption will likely depend less on model availability and more on operational controls.

Marketing teams can already access generative AI for campaign copy, audience analysis and content creation. The harder problem is integrating autonomous systems with enterprise data, policies and customer-contact requirements.

Pega's approach suggests that governance will increasingly become a native capability of marketing platforms rather than an external review process.

That could benefit large organizations that need to scale personalization without creating parallel compliance workflows.

The bigger test will be whether these systems can maintain accuracy as policies, customer preferences, regulatory requirements and connected data sources change. If AI agents are going to operate continuously, governance will need to operate continuously as well.

Top Insights

• Pega Customer Engagement Studio brings agentic AI into campaign strategy while embedding validation and approvals, targeting enterprises that need automation without sacrificing governance.
• The Gryphon partnership extends contact governance across regulated industries, addressing compliance risks that can increase as AI automates customer communications.
• Pega's natural-language campaign design reduces technical configuration requirements, potentially allowing marketers to build sophisticated engagement strategies without extensive platform expertise.
• Opt-out monitoring and targeting validation are becoming critical as AI systems gain greater autonomy over customer segmentation, personalization and campaign execution.
• Pega's strategy reflects a broader MarTech shift toward governed AI, where auditability and policy enforcement become as important as automation and optimization.

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Independent grocers have traditionally relied on weekly circulars to drive store traffic, but print offers provide limited insight into which households see an offer and what ultimately influences a purchase. AppCard is bringing purchase data into that process with a new Digital Circular that combines AI-generated shopping content, onsite engagement and offsite advertising targeted using real shopper behavior.

AppCard has launched a Digital Circular designed to give independent grocery retailers a more measurable alternative to traditional weekly advertising, combining digital circulars with onsite and offsite advertising capabilities.

The platform is aimed at smaller grocers competing with national and regional chains that typically have greater access to customer data, advertising technology and sophisticated audience targeting.

At the center of the offering is AppCard's Circular Management dashboard, part of the company's AppCard Management Suite (AMS). Grocers can upload an existing static weekly advertisement, after which AppCard's AI system, Pinky, converts it into an interactive digital circular.

The technology changes the circular from a static promotional document into a shopping-oriented experience.

When a customer selects a sale item, Pinky can recommend a recipe built around that product. AppCard says its recipe library contains more than 6,500 recipes. Shoppers can then add the recipe's ingredients to a shopping list.

That creates a potentially important shift in grocery marketing: an individual promotion can become the starting point for a broader shopping basket.

Turning Purchase Data Into Advertising Audiences

The more significant technology story is what happens beyond the circular itself.

AppCard allows the same digital circular to become an offsite advertisement. The company says audience targeting can use purchase behavior, ZIP code and point-of-sale data, allowing grocers to identify households based on what shoppers actually purchase.

That moves the offering closer to retail media than traditional circular management.

Retail media networks have become increasingly sophisticated because large retailers can combine first-party transaction data with advertising inventory. Walmart, Amazon and Kroger, for example, have built advertising businesses around their customer and commerce ecosystems.

Independent grocers generally have fewer resources to develop comparable systems.

AppCard is attempting to narrow that gap by connecting a grocer's existing point-of-sale information with digital advertising.

The ads can appear across Google, YouTube, Gmail and millions of news, sports and lifestyle websites, according to the company. Budget allocation and campaign performance are managed through AMS rather than requiring grocers to operate a separate advertising platform.

AI Turns the Circular Into a Shopping Tool

The AI component is not limited to advertising.

Pinky transforms the uploaded weekly ad into clickable content and connects individual sale products with recipes and shopping lists.

That functionality is strategically relevant because grocery purchases are rarely isolated decisions. A shopper buying pasta may also need sauce, cheese and vegetables. A discounted chicken product can lead to purchases of seasonings, vegetables or side dishes.

By connecting promotional products to recipes, AppCard is trying to influence the broader basket rather than simply drive a click on a single discounted item.

It also gives the grocer another source of behavioral information.

Interactions with the circular can show which products attract attention, which recipes generate engagement and whether shoppers explore beyond the initial promotion.

Early Results Point to Higher Engagement

AppCard cites early performance from Crops Fresh Marketplace, a single-store independent grocer in Pennsylvania.

Following the launch of its offsite advertising, the retailer reported daily page views increasing from approximately 204 to 1,180, or about 5.8 times higher. Daily sessions rose from roughly 127 to 330, representing a 2.6-fold increase.

Pages per session also approximately doubled, suggesting that visitors were exploring more content rather than immediately leaving.

AppCard says the ads generated click-through rates between 2% and 3%, which the company describes as above common display benchmarks.

These figures are early customer results and should not be treated as independently verified benchmarks for the broader platform. Performance can vary significantly depending on audience size, creative, geography, promotions and campaign duration.

Still, the results illustrate the potential value of connecting advertising with an existing customer relationship.

Retail Media Moves Beyond the Biggest Chains

The launch comes as retail media expands beyond Amazon and large national retailers.

The fundamental asset behind retail media is first-party commerce data. Retailers know what customers purchase, how frequently they shop and, in many cases, which categories or products matter to particular households.

That information can make advertising more relevant than generic demographic targeting.

Independent grocers have access to similar transaction data, but historically have lacked the technology and scale required to turn it into an advertising product.

AppCard's approach attempts to package that capability into a more accessible system.

The company is effectively connecting three components: point-of-sale data, digital merchandising and media activation.

That creates a feedback loop. Purchase behavior can inform audience selection; promotions can drive engagement; digital interactions can generate additional signals; and campaign results can feed back into future marketing decisions.

What It Means for Grocery Marketing Teams

For independent grocers, the practical appeal may be less about replacing the weekly circular and more about extending its usefulness.

A retailer can continue producing familiar promotional content while turning it into an interactive digital experience and targeted advertising campaign.

That could help smaller chains compete for consumer attention in an environment where national retailers increasingly use personalized promotions, loyalty data and retail media.

The bigger question will be whether independent grocers can generate enough transaction data and advertising scale to produce consistent returns.

AppCard's model suggests that they may not need the enormous customer bases of Walmart or Amazon to participate in data-driven retail media. They may instead need better ways to activate the customer information they already possess.

If that model scales, the humble grocery circular could evolve from a weekly promotional document into a data-driven marketing and commerce platform.

Market Landscape

Retail media is increasingly built around first-party purchase data, but most of the industry's largest advertising businesses belong to major retailers with enormous customer bases.

Independent grocers face a different challenge. They often possess valuable point-of-sale and loyalty information but have fewer resources to build audience segmentation, advertising infrastructure and measurement systems.

AppCard is positioning its Digital Circular at that gap.

The competitive landscape includes retail media platforms, grocery loyalty technology, digital circular providers, DSPs and advertising networks. AppCard's differentiation is the attempt to connect the retailer's existing POS data directly to circular content and media activation.

This is part of a broader movement toward commerce media, where transaction data becomes a foundation for both marketing and measurement.

Strategic Outlook

The grocery advertising market is likely to become increasingly data-driven as retailers look for alternatives to broad demographic targeting and seek more measurable ways to influence purchases.

For independent grocers, the opportunity is particularly interesting because their customer data is often highly local. Purchase behavior combined with ZIP-code information can potentially create highly relevant household-level audiences without requiring the scale of a national retailer.

Privacy and data governance will remain critical. Retailers and their technology partners must ensure that customer information is collected, processed and activated according to applicable privacy requirements and consent frameworks.

The longer-term opportunity is broader than digital circulars. If purchase data can consistently connect promotions, advertising exposure and basket behavior, independent grocers could develop their own localized retail media ecosystems.

Top Insights

• AppCard's Digital Circular combines POS data, AI-generated recipes and advertising activation, giving independent grocers a more connected approach to digital customer engagement.
• Pinky converts static weekly advertisements into interactive circulars, linking sale products with recipes and shopping lists designed to encourage broader basket purchases.
• Purchase behavior and ZIP-code data allow AppCard to target households based on actual buying patterns rather than relying solely on generic audience characteristics.
• The offering gives smaller grocers access to capabilities increasingly associated with major retail media networks, including audience targeting, campaign management and performance measurement.
• Early Crops Fresh Marketplace results suggest stronger digital engagement after offsite advertising, although the reported performance remains limited to an early customer example.

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For small businesses, being visible in local search is no longer limited to Google rankings or a well-managed Business Profile. Customers are increasingly using AI assistants such as ChatGPT, Gemini and Claude to discover, compare and evaluate local companies. Matter is responding to that shift by relaunching its small business marketing offering, combining local SEO, digital advertising, content and AI search visibility into packaged programs for Main Street businesses.

Matter, a PR, marketing and creative agency, has relaunched its local marketing services as small businesses face a more complicated digital discovery environment shaped by traditional search, social media and generative AI.

The refreshed offering is designed to give local companies access to agency-level marketing capabilities without requiring them to manage multiple specialists, platforms and campaigns themselves.

The timing reflects a broader problem in small-business marketing. According to Constant Contact, only 18% of small business owners were very confident that their marketing was working, down from 27% a year earlier.

That measurement and confidence gap is becoming more significant as the way consumers discover businesses changes.

Search engines remain important, but generative AI tools are becoming another layer in the customer journey. A potential customer might ask ChatGPT for a local recommendation, use Gemini to compare providers or turn to traditional search before contacting a business.

For small companies that depend heavily on local demand, appearing consistently across these discovery environments is becoming a strategic concern.

Matter Combines Local SEO With AI Discovery

Matter's updated offering combines several established digital marketing services, including local search engine optimization and search engine marketing, geo-targeted content, Google Business Profile management, review management, organic social media, website optimization and digital advertising.

The company has also incorporated AI search discovery into the offering.

That is an important distinction from traditional local SEO.

Optimizing a website and Google Business Profile remains necessary, but visibility in generative AI can depend on a broader collection of signals, including structured business information, authoritative content, reviews, local relevance and the consistency of information across the web.

AI systems do not simply reproduce Google's local rankings. Their responses can synthesize information from multiple sources to produce recommendations or comparisons.

For a local business, that means digital visibility increasingly extends beyond the familiar blue links of a search results page.

The Local Marketing Stack Is Becoming More Integrated

Matter's offering also reflects a broader consolidation taking place in small-business marketing.

A local company may need SEO, paid search, social media, website updates, photography, video, reputation management and advertising creative. Historically, those activities could be handled by different vendors or by an owner trying to manage them independently.

The result can be fragmented campaigns and limited visibility into what is actually driving customers.

Matter is packaging these capabilities into three tiers intended to accommodate different budgets and growth objectives.

The agency says its approach is designed to combine visibility and consideration with customer acquisition rather than treating individual marketing channels as separate activities.

That model mirrors a wider shift in MarTech toward integrated customer journeys, where search, content, social, advertising and analytics increasingly work together.

AI Search Creates a New Challenge for Main Street Businesses

The most consequential part of the relaunch may be the focus on AI-generated discovery.

For large enterprises, optimizing for AI search can involve dedicated SEO, content and analytics teams. A small business typically does not have those resources.

That creates an opportunity for agencies to turn emerging Generative Engine Optimization (GEO) practices into more accessible services.

The challenge is that AI search visibility is still evolving. There is no single equivalent of Google's traditional ranking position that guarantees visibility across ChatGPT, Gemini, Claude and other AI systems.

Instead, businesses need to establish strong digital signals across their broader online presence.

That includes accurate business information, useful local content, customer reviews, authoritative mentions and a website that clearly explains what the company offers and where it operates.

Matter's strategy effectively brings these activities under one local marketing program.

Reviews and Local Content Still Matter

Despite the emphasis on AI, the fundamentals of local marketing have not disappeared.

Google Business Profiles, customer reviews, localized content and website performance remain important touchpoints for consumers. Those same assets can also provide useful information to AI systems attempting to understand a business.

Review management is particularly significant because reputation influences both human purchasing decisions and the information ecosystem surrounding local companies.

Matter's inclusion of review strategy and response management therefore places a traditional local marketing discipline alongside newer AI visibility efforts.

The combination is likely to become increasingly common as businesses realize that optimizing for AI does not necessarily require abandoning established SEO practices.

Competing With DIY Marketing Platforms

Matter is entering a market where small businesses already have access to relatively inexpensive tools from companies such as HubSpot, Wix, Squarespace, Google and Canva, alongside specialized SEO and advertising platforms.

The difference is that those products largely provide the tools. Matter is selling managed expertise and execution.

That distinction could appeal to business owners who understand the importance of digital marketing but lack the time or internal resources to operate a complete marketing stack.

The economics will ultimately determine how compelling the model becomes. Small businesses remain highly sensitive to marketing costs, and agencies must demonstrate that managed services generate enough incremental visibility, leads and customers to justify the investment.

What It Means for Local Marketing

Matter's relaunch reflects a larger transformation in local customer acquisition.

The local marketing funnel is no longer simply Google search → website → phone call. It can now include social platforms, reviews, maps, paid media and AI-generated recommendations.

For small businesses, that fragmentation creates complexity but also makes integrated marketing more valuable.

The winners will likely be businesses that maintain consistent information across channels, produce credible local content, build strong customer reviews and measure which discovery sources actually produce customers.

Matter is betting that small businesses will increasingly prefer an agency to manage that complexity rather than assemble the pieces themselves.

Market Landscape

Local marketing is moving from traditional local SEO and search advertising toward a broader discovery ecosystem that includes Google Maps, social platforms, review sites and generative AI.

Google remains a critical source of local intent, but AI assistants introduce a new layer where consumers can ask questions instead of entering conventional keyword queries.

For marketing agencies, this creates a new service opportunity around AI search optimization, local content, reputation management and digital presence management.

The competitive landscape includes DIY platforms, local SEO specialists, digital agencies and larger MarTech ecosystems. Matter's differentiation is its attempt to combine these capabilities with PR, creative and integrated marketing expertise.

Strategic Outlook

AI search will not eliminate traditional local SEO. Instead, it is likely to make a strong digital foundation more important.

Local businesses need accurate information, authoritative content, strong reviews and consistent brand signals before they can expect meaningful visibility across emerging discovery platforms.

The bigger opportunity is measurement.

As AI referrals become part of the customer journey, agencies will need to demonstrate not just that a business appears in AI-generated answers, but whether that visibility produces website visits, calls, inquiries and ultimately revenue.

For small businesses, that connection between AI visibility and measurable customer acquisition could determine whether AI search becomes another marketing expense or a meaningful growth channel.

Top Insights

• Matter is combining local SEO, advertising, reputation management and AI search discovery to give small businesses a more integrated customer-acquisition strategy.
• AI assistants are creating another local discovery channel, requiring businesses to maintain authoritative content and consistent information beyond traditional Google search optimization.
• Matter's managed-service model targets owners who lack the time or expertise to coordinate SEO, social media, websites, advertising and content independently.
• Review management and Google Business Profile optimization remain important as customer reputation and accurate business information influence modern digital discovery.
• The next challenge for local marketing agencies will be proving that AI search visibility generates measurable calls, leads, customers and revenue for small businesses.

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