Printing Limitless is expanding its custom banner printing portfolio as businesses increasingly look for flexible, lower-complexity ways to build visibility across storefronts, events, trade shows and outdoor advertising environments.

Outdoor advertising does not always require a large media budget or a complex campaign infrastructure. For small businesses, retailers, event organizers and local marketers, physical signage can provide a direct way to put a brand or promotion in front of people where they already gather.

Printing Limitless is positioning custom banners as one such option, offering a broad range of printed products designed for indoor and outdoor marketing applications.

The company's portfolio includes custom vinyl banners, promotional banners, outdoor banners, indoor banners and step-and-repeat backdrops, alongside more specialized formats for businesses, schools, restaurants, real estate companies, sports organizations and events.

The approach reflects a straightforward marketing principle: visibility still matters, particularly in physical environments where digital advertising cannot provide the same form of presence.

Custom vinyl banners are at the center of the offering. Printed on PVC flex materials, they can incorporate logos, promotional messaging, product information and other brand assets. The format can be used across storefronts, promotional events, roadside locations and other high-traffic environments.

For businesses running time-sensitive campaigns, promotional banners provide a physical complement to digital marketing. Sales, product launches, grand openings and seasonal campaigns can all use temporary signage to communicate an offer to nearby audiences.

Outdoor banners are designed specifically for exterior applications, including fences, buildings, storefronts and community events. Indoor banners, meanwhile, are positioned for retail locations, offices, schools and trade shows.

That distinction matters because banner performance is closely tied to the environment in which the material is displayed. Wind, weather exposure, viewing distance and installation method can affect material and format decisions.

Printing Limitless also offers step-and-repeat banners, which serve a different marketing function. Rather than communicating a short promotional message, these backdrops are typically designed to maintain brand visibility throughout corporate events, award ceremonies, trade shows, red-carpet events and photo opportunities.

Repeated logos and branded graphics can turn photographs taken at an event into additional exposure when attendees share them through social media or other digital channels.

The broader portfolio includes fabric banners, mesh banners, street banners, fence banners, real estate banners, restaurant banners, school banners and sports banners. Customers can select different sizes, materials, hanging configurations and single- or double-sided formats depending on the application.

That variety reflects a fragmented physical advertising market in which there is no universal signage format.

A retailer may need a durable storefront banner, while a construction site could require a fence-mounted mesh banner. An event organizer may prioritize a branded backdrop, whereas a real estate business could need property-specific signage.

Printing Limitless says its objective is to make those choices easier by bringing different banner formats and related promotional products into one platform.

The company is also extending beyond banners into complementary visual marketing products, including custom signs and decals, table covers, flags and freestanding display systems.

That broader approach is increasingly relevant for businesses trying to maintain visual consistency across multiple physical touchpoints.

For marketing teams, the relationship between physical and digital branding is also changing. A banner can carry a QR code, campaign URL, social media handle or promotional offer, allowing offline exposure to connect with measurable digital activity.

This makes physical signage less isolated from the broader MarTech ecosystem. While a printed banner cannot provide the targeting and attribution capabilities of a digital ad platform, it can become an entry point into a measurable digital journey.

The challenge remains proving return on investment. Outdoor banners generally lack the granular attribution available through platforms such as Google Ads or Meta Ads. Businesses therefore need to consider location, foot traffic, campaign objectives and complementary measurement methods when evaluating performance.

Still, the relatively simple deployment model can make banners attractive for organizations that need immediate local visibility.

Ron David, Operations Manager at Printing Limitless, said the company is focused on helping customers select banner products according to their specific applications, including storefront promotions, events and ongoing brand marketing.

The company's strategy places customization and application flexibility at the center of its offering rather than treating banners as a single standardized advertising product.

For marketers, that positioning reflects a broader shift toward integrated brand experiences. Digital campaigns may dominate performance marketing budgets, but physical environments remain important for retailers, local businesses, events and organizations that depend on geographic visibility.

Custom printing can also play a supporting role in experiential marketing, trade shows and field marketing, where consistent visual branding helps reinforce the identity of a campaign across physical spaces.

Market Landscape

Physical advertising remains relevant alongside digital marketing, particularly for local businesses, retail brands, events, trade shows and community organizations.

Digital advertising platforms offer sophisticated targeting and measurement, but they cannot replace every physical brand interaction. Banners, signs, flags and event displays can provide continuous visibility in specific locations without requiring recurring digital media auctions.

The market is also becoming more integrated. QR codes, campaign-specific landing pages and social media calls to action can connect physical advertising with digital experiences, giving marketers ways to measure engagement beyond simple impressions.

Strategic Outlook

Custom printing is likely to remain a practical component of local marketing and experiential campaigns as businesses seek ways to connect digital and physical brand experiences.

The biggest opportunity is not necessarily replacing digital advertising but complementing it. A well-placed banner can establish awareness, while a QR code, promotional URL or event activation can move audiences into a measurable digital funnel.

For small and midsize businesses, that combination can provide a relatively accessible way to extend marketing campaigns into high-traffic physical environments.

Top Insights

• Printing Limitless is expanding custom banner options for businesses seeking flexible physical advertising across storefronts, events, trade shows and outdoor environments.

• Custom vinyl, outdoor and promotional banners provide marketers with adaptable formats for communicating campaigns, branding and offers in high-traffic physical locations.

• Step-and-repeat banners extend branding into corporate events and photo opportunities, potentially increasing exposure when attendees share event content across digital channels.

• The company's broader signs, flags, decals and display portfolio allows businesses to create more consistent visual branding across physical marketing environments and events.

• Physical signage can complement digital campaigns by incorporating QR codes, promotional URLs and social handles that connect offline audiences with measurable online experiences.

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Americaneagle.com has reached the highest tier in Sitecore's global partner program, becoming a Sitecore Diamond Partner as the digital experience platform expands its focus on AI, personalization and enterprise content operations.

Americaneagle.com has been named a Sitecore Diamond Partner, earning the highest designation available in Sitecore's global partner program and strengthening its position as an enterprise digital experience implementation and services provider.

The recognition places Americaneagle.com among an exclusive group of Sitecore partners that meet the platform vendor's highest standards for performance, customer success, innovation and business growth. For enterprise technology buyers, the designation is less about a marketing badge than the depth of expertise and access it can provide when implementing and operating a complex digital experience stack.

Americaneagle.com has worked with Sitecore for more than 15 years, supporting organizations across digital experience management, ecommerce, personalization, content strategy, marketing technology and platform modernization.

The company's elevation comes as enterprise organizations increasingly reassess their digital experience infrastructure around AI. Sitecore has been expanding its platform with AI capabilities, including SitecoreAI, while continuing to develop tools intended to improve content creation, personalization and digital experience management.

For organizations operating large websites and ecommerce ecosystems, that transition is significant. Modernizing a digital experience platform is rarely limited to replacing software. It can involve migrating years of content, integrating customer data, connecting marketing automation systems and redesigning workflows used by marketers, developers and content teams.

Americaneagle.com's Diamond Partner status recognizes its ability to operate across those areas, according to Sitecore.

The agency also has a deeper operational relationship with the platform. Earlier this year, Sitecore selected Americaneagle.com to provide operational support for the infrastructure layer of Sitecore Managed Cloud. The arrangement involves maintaining platform availability and supporting Sitecore customers operating within the managed cloud environment.

That relationship gives Americaneagle.com exposure to both sides of the enterprise Sitecore ecosystem: implementation and digital transformation on one side, and infrastructure operations on the other.

"This recognition is a testament to the talent, dedication, and expertise of our team," said Mike Svanascini, President of Americaneagle.com. He also pointed to customer satisfaction as a central factor in the relationship between the two companies.

The broader market context helps explain why partner expertise matters. Enterprise marketers increasingly need digital experience platforms that can support omnichannel content, personalization, ecommerce and AI-assisted workflows without creating additional technology silos.

Sitecore competes in a crowded digital experience market that includes Adobe Experience Cloud, Salesforce Experience Cloud, Optimizely, Contentful and other enterprise content and experience platforms. These vendors are increasingly incorporating generative AI and automation into content management and customer experience workflows.

The competitive distinction is therefore shifting. A platform's feature set remains important, but implementation expertise can determine whether an enterprise actually realizes those capabilities.

A sophisticated DXP can support personalization and AI-driven content operations, but organizations still need teams that understand migration, integrations, governance, accessibility, security and ongoing optimization.

Americaneagle.com says its Sitecore practice is built around that multidisciplinary model, combining strategists, designers, developers, marketers, accessibility specialists and support professionals.

The agency is also positioning SitecoreAI as an opportunity to improve content operations and team productivity. As organizations produce more content for increasingly fragmented customer journeys, AI-assisted workflows could help reduce the operational burden on marketing teams.

However, AI adoption in enterprise content environments introduces its own challenges. Organizations need governance around generated content, brand consistency, data access, approval workflows and customer privacy. Simply adding generative AI to an existing DXP does not automatically produce better customer experiences.

That makes the partner ecosystem increasingly important. Enterprise buyers often require support well beyond the initial software deployment, particularly when digital experience platforms become interconnected with CRM, ecommerce, customer data and marketing automation infrastructure.

Sitecore Chief Operating Officer Dave Tilbury described Americaneagle.com as a long-standing partner capable of supporting customers across strategy, implementation, managed services and AI readiness.

The company has also referenced Sitecore's acquisition of Scrunch as another development influencing its digital experience strategy. Americaneagle.com says it is focused on helping customers evaluate how new Sitecore capabilities can improve content operations, personalization and customer engagement.

The Diamond designation could therefore become particularly relevant as enterprises move from experimentation with AI toward operational deployment.

For marketing leaders, the objective is increasingly not just to acquire an AI-enabled platform, but to integrate AI into existing content and customer experience processes without disrupting the systems that already support revenue.

Americaneagle.com's expanded relationship with Sitecore positions the agency to participate in that transition. Whether the partnership translates into measurable improvements for customers will ultimately depend on implementation quality, adoption and business outcomes rather than partner status alone.

Market Landscape

Enterprise digital experience platforms are evolving from traditional content management systems into broader experience infrastructure connecting content, commerce, personalization, analytics and AI.

Sitecore competes with Adobe, Salesforce, Optimizely, Contentful and other vendors serving organizations with complex digital experience requirements. AI is becoming a major differentiator as vendors introduce tools for content generation, personalization and marketing productivity.

For enterprises, implementation partners remain critical because large-scale DXP deployments frequently involve migrations, integrations, governance and ongoing managed services.

Americaneagle.com's Diamond designation reflects this broader shift toward partners that can support the entire digital experience lifecycle rather than simply implement a software platform.

Strategic Outlook

The next stage of enterprise DXP adoption will likely center on how effectively organizations integrate AI into existing content and customer experience operations.

SitecoreAI and related capabilities could reduce manual work around content and personalization, but successful adoption will require governance, workflow redesign and strong platform expertise.

For enterprise marketing teams, the partner relationship may therefore become as important as the technology itself. Agencies capable of combining implementation, managed services, marketing expertise and AI readiness could have an advantage as digital experience stacks become more interconnected.

Top Insights

• Americaneagle.com has reached Sitecore's highest partner tier, strengthening its position in enterprise digital experience implementation, managed services and AI-enabled transformation.

• The Diamond designation recognizes Americaneagle.com's long-standing Sitecore expertise as enterprises modernize content platforms, personalization systems, ecommerce infrastructure and marketing technology.

• SitecoreAI is expanding the platform's AI capabilities, creating new opportunities for content operations, productivity and personalized digital experiences across enterprise organizations.

• Americaneagle.com's Sitecore Managed Cloud infrastructure role extends its relationship beyond implementation into operational support for complex enterprise digital experience environments.

• The partnership highlights the growing importance of implementation expertise as enterprises integrate AI, content management, personalization and customer data into unified experience platforms.

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Marketing Architects and Media Consulting Group (MCG) are partnering to combine AI-driven media buying with upstream Connected TV supply optimization, creating a more automated approach to evaluating, shaping and purchasing streaming inventory for performance-focused advertisers.

Connected TV advertising has moved from a primarily brand-oriented channel into an increasingly measurable part of the performance marketing stack. As advertisers shift more budgets toward streaming, the challenge is no longer simply finding available inventory. It is determining which supply can deliver the right audiences, economics and measurable outcomes before a campaign begins.

Media Consulting Group and TV agency Marketing Architects are targeting that problem through a new partnership that combines supply-side intelligence with AI-powered media buying.

MCG optimizes streaming inventory across the United States and Canada, while Marketing Architects uses Annika, its proprietary AI media-buying system, to purchase against the resulting supply. The two companies say the combined approach is designed to improve how premium CTV and OTT inventory is evaluated and activated.

The key difference is where optimization occurs.

Traditional media buying typically begins with available inventory and then applies targeting, bidding and optimization strategies during the buying process. MCG is attempting to move part of that intelligence upstream, evaluating available supply before the bid and organizing it around an advertiser's performance objectives.

The result is intended to give an AI buying system a more relevant supply environment to operate within.

MCG says its AI engineers analyze the broader streaming supply landscape and organize inventory around each buyer's proprietary marketing objectives in near real time. Once that supply has been optimized, Marketing Architects' Annika AI can buy against it.

That creates a two-layer model: MCG focuses on the quality and structure of the supply, while Marketing Architects' AI focuses on buying and optimization.

The distinction is increasingly relevant as CTV becomes more programmatic. Streaming television combines characteristics of traditional television with digital advertising infrastructure, creating a complex environment involving publishers, streaming platforms, ad exchanges, supply-side platforms, demand-side platforms and measurement providers.

Advertisers therefore face a growing supply-path challenge. The same audience can potentially be reached through multiple intermediaries, with differences in fees, inventory quality, transparency and performance.

Supply-path optimization, or SPO, has become a major focus across programmatic advertising because advertisers want greater control over how their media dollars move through the ecosystem. The MCG-Marketing Architects partnership extends that concept into performance-oriented CTV by applying optimization before the media is purchased.

Daniel Elad, Co-Founder and CRO at MCG, said the partnership combines MCG's supply intelligence with Marketing Architects' buying intelligence.

Marketing Architects brings a different piece of the equation. Its Annika platform is designed to continuously learn from campaigns and identify more efficient media opportunities. The company positions the technology as an AI-driven buying system rather than a conventional optimization layer.

By feeding Annika with supply that has already been evaluated against performance objectives, the partnership aims to reduce the amount of inefficient inventory that reaches the buying process in the first place.

That is potentially important for performance TV because advertisers increasingly expect CTV campaigns to demonstrate measurable business outcomes rather than simply reach or completed views.

Full-funnel measurement is therefore another component of the partnership. Marketing Architects says it applies measurement across the customer journey, allowing campaign performance to be evaluated beyond basic delivery metrics.

The competitive landscape includes major programmatic platforms and CTV specialists that already use machine learning for audience targeting, bidding, optimization and measurement. Google, Amazon and other large advertising ecosystems have invested heavily in automated CTV and streaming advertising capabilities, while independent DSPs and supply-side platforms compete around transparency, inventory access and optimization.

The MCG and Marketing Architects approach differs by separating upstream supply intelligence from downstream buying intelligence.

Whether that produces a material performance advantage will depend on how accurately MCG can evaluate supply and how effectively Annika can translate those signals into buying decisions. The partnership also raises a broader question for the CTV market: whether AI optimization should begin before an impression enters an auction rather than only after it becomes available to a buyer.

That could become an important direction as CTV inventory becomes more fragmented.

Streaming platforms continue to add advertising-supported tiers, while traditional broadcasters are expanding digital distribution. More inventory creates more choice, but it also increases complexity for marketers attempting to identify efficient paths to audiences.

AI can help manage that complexity, but automation alone does not guarantee better media economics. The data and inventory available to the algorithms remain critical.

The MCG-Marketing Architects model effectively treats supply quality as an input to AI performance. Instead of giving an automated buying system access to as much inventory as possible, the objective is to improve the quality of the environment in which the AI makes decisions.

For advertisers, that could translate into greater attention to supply-path quality, inventory transparency and pre-bid intelligence as CTV evolves from a reach-focused channel into a performance medium.

Market Landscape

CTV and OTT advertising are becoming increasingly automated as advertisers demand the targeting, measurement and optimization capabilities associated with digital advertising.

The expansion of streaming services has created more inventory, but fragmentation has also made it harder for advertisers to evaluate supply quality. Programmatic CTV can involve multiple intermediaries between the advertiser and publisher, increasing the importance of supply-path optimization and inventory transparency.

Major technology ecosystems including Google and Amazon are competing alongside independent advertising platforms to control CTV buying and measurement infrastructure.

The MCG-Marketing Architects partnership represents another approach: optimize the supply before the AI buying engine makes its decision.

Strategic Outlook

The next phase of CTV advertising may involve increasingly agentic systems that make decisions across the media supply chain rather than simply automating individual bidding or targeting tasks.

If AI can evaluate supply, select efficient paths, execute buying and continuously learn from full-funnel outcomes, media buying could become substantially more autonomous.

But the quality of those decisions will depend on the quality of the underlying supply intelligence. For performance advertisers, that makes upstream optimization an increasingly important part of the CTV technology stack.

Top Insights

• MCG and Marketing Architects are combining upstream CTV supply optimization with AI-powered buying to create a more performance-focused media activation model.

• MCG evaluates streaming inventory before bidding, giving Marketing Architects' Annika AI a supply environment structured around each advertiser's performance objectives.

• The partnership reflects growing advertiser interest in supply-path optimization as fragmented CTV ecosystems make inventory quality and transparency increasingly important.

• Marketing Architects applies full-funnel measurement to AI-driven TV buying, shifting performance TV evaluation beyond reach, impressions and traditional television metrics.

• The combined model points toward more agentic CTV advertising, where AI systems could increasingly evaluate supply, buy media and optimize outcomes with less manual intervention.

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Guideline is partnering with independent media agency Tinuiti to bring verified advertising market data into agency performance benchmarking, challenging the assumption that independent agencies must sacrifice media buying power because they lack the scale of holding-company networks.

For years, media buying power has been closely associated with agency size. Large holding companies have traditionally positioned their scale, aggregated spending and relationships with media platforms as advantages when negotiating advertising costs.

A new partnership between Guideline and Tinuiti is challenging that assumption by putting greater emphasis on verified market data rather than agency size alone.

Guideline, an advertising intelligence provider, has added Tinuiti to its partner ecosystem as a strategic data contributor to its Guideline Ad Intelligence product. In return, Tinuiti gains access to Guideline's advertising intelligence data, giving the independent agency additional visibility into market-level media costs and competitive benchmarks.

The partnership is significant because it addresses a persistent problem in media buying: advertisers often have limited independent visibility into whether the prices and performance reported by their agencies are competitive with broader market conditions.

Agency-reported metrics can show whether a campaign met its internal objectives, but they do not necessarily answer a different question: did the advertiser receive a competitive media price compared with other buyers operating in the same market?

Guideline's approach is designed to provide that external reference point.

According to the companies, third-party validation has shown Tinuiti delivering double-digit media cost advantages across several key channels. The companies did not disclose the specific channels, benchmark methodology or underlying cost figures in the announcement, making the claim difficult to independently assess from the available information.

Still, the underlying concept has broader implications for agency selection.

Independent agencies have traditionally competed against global holding companies by emphasizing agility, specialist expertise and closer client relationships. Buying power, however, has often been perceived as one area where larger networks hold an inherent advantage.

Verified market intelligence could change that equation if it demonstrates that actual media costs are determined by factors beyond aggregate agency spending.

Media pricing can vary based on audience quality, inventory availability, campaign objectives, geographic targeting, seasonality, format, platform relationships and buying strategy. An agency with less overall spending could potentially achieve competitive pricing through specialization, optimization and efficient allocation.

That makes benchmarking particularly relevant as advertisers become more focused on transparency.

The advertising industry has spent years moving toward more measurable media investment. Programmatic buying has increased the amount of available campaign data, while platforms such as Google, Amazon and Meta provide advertisers with extensive reporting environments. Yet platform-level reporting primarily describes performance within an individual ecosystem.

Independent market intelligence addresses a different problem: comparing performance and costs across the market.

That distinction is becoming more important as advertisers diversify budgets across search, social, retail media, connected TV, programmatic advertising and other channels. Each environment has different pricing structures and measurement standards, making apples-to-apples comparisons difficult.

Guideline's Ad Intelligence product is positioned around this benchmarking challenge.

Reuben Tozman, Guideline's Chief Data Strategy and Strategic Alliances Officer, said the value of advertising intelligence depends on the quality and scale of the underlying data. The company argues that agency partnerships can expand the market information available to advertisers while providing agencies with a broader reference point for decision-making.

For Tinuiti, the partnership also provides a way to incorporate external market intelligence into client strategy.

Jeremy Cornfeldt, President of Tinuiti, said access to independent market intelligence provides greater visibility into advertising trends and competitive benchmarks. That can help an agency connect brand and performance investments while evaluating whether media strategies remain competitive.

The development comes as independent agencies continue to compete for increasingly sophisticated enterprise and growth-stage advertisers. Agencies such as Tinuiti increasingly position themselves around integrated performance marketing, media, commerce and customer acquisition rather than traditional media buying alone.

The competitive landscape includes large agency holding companies, independent media agencies, specialist performance agencies and technology-enabled media buying platforms. Companies such as WPP, Omnicom, Publicis Groupe and Dentsu still command substantial global spending, while independent firms compete by emphasizing specialization and flexibility.

The real test for Guideline's proposition will be whether independent benchmarking becomes a standard part of agency evaluation.

For marketers, that could mean moving beyond questions such as "How much does our agency spend?" toward more useful questions about effective media costs, channel-level competitiveness and the value generated from each advertising dollar.

It could also change procurement conversations. Instead of treating agency scale as a proxy for negotiating leverage, brands could use verified market benchmarks to assess whether the actual rates and outcomes delivered by an agency are competitive.

That would be a meaningful shift in how media buying performance is evaluated.

Market Landscape

Media buying is becoming increasingly data-driven, but transparency remains uneven across advertising channels. Advertisers can access detailed reporting from individual platforms, yet determining whether their media costs are competitive against the broader market is considerably harder.

The rise of retail media, connected TV, programmatic advertising and commerce media has further fragmented the buying landscape. Each channel has different auction dynamics, inventory structures and measurement practices.

In this environment, independent benchmarking can provide a reference point that platform dashboards and agency-reported results cannot necessarily provide on their own.

The Guideline-Tinuiti partnership therefore reflects a broader movement toward independent advertising intelligence, where brands evaluate media investment using external market evidence rather than relying solely on agency scale or self-reported performance.

Strategic Outlook

If verified media benchmarks become more widely adopted, agency selection could become less dependent on perceived buying power and more focused on demonstrable performance.

That would benefit independent agencies that can prove they achieve competitive media economics while retaining the strategic flexibility that often distinguishes them from larger holding-company networks.

For advertisers, the bigger opportunity is greater accountability. Independent market data could help marketing leaders, procurement teams and agency executives identify inefficient spending, negotiate from stronger evidence and make more informed allocation decisions across increasingly complex media environments.

Top Insights

• Guideline and Tinuiti are using independent advertising intelligence to challenge the assumption that agency scale automatically determines media buying power and pricing advantages.

• Third-party benchmarking reportedly found double-digit media cost advantages for Tinuiti across several channels, although methodology and channel-level results remain undisclosed.

• Guideline Ad Intelligence gives marketers an external reference point for evaluating media costs instead of relying exclusively on agency or platform-reported performance metrics.

• The partnership could strengthen independent agencies' competitive position by demonstrating buying efficiency through verified market data rather than global spending volume.

• As advertising becomes fragmented across programmatic, retail media and connected TV, independent benchmarks could become increasingly important for enterprise media investment decisions.

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Epoch is expanding its AI-native events platform into B2B marketing with EpochX, a new offering designed to connect event registration, attendance and engagement with Salesforce and HubSpot. The goal is to give field marketing, event marketing and demand generation teams a clearer way to measure how events contribute to pipeline and revenue.

For years, B2B marketing teams have invested heavily in conferences, field events, executive gatherings and customer experiences while struggling to answer a basic question: which opportunities did those events actually influence?

Epoch is attempting to close that measurement gap with EpochX, a new extension of its AI-native events platform designed specifically for Field Marketers, Event Marketers and Demand Gen teams.

The product connects registration, attendance and engagement data directly with Salesforce and HubSpot, allowing event activity to become part of the broader customer and opportunity record. Instead of treating event information as a separate operational dataset, EpochX is designed to put event-sourced activity alongside the other interactions marketing and sales teams already use to evaluate pipeline.

The distinction is important because event technology has historically focused heavily on execution. Registration, venue coordination, attendee management, check-in and communications are necessary components of running an event, but they do not necessarily show whether the event generated meaningful commercial outcomes.

EpochX takes a different approach. Its primary objective is to connect the event experience to pipeline measurement.

For marketers, that means registration and attendance data can flow into the CRM rather than being exported into spreadsheets or manually reconciled after an event. Engagement information can also become part of the buyer journey, making it easier for teams to identify whether event attendees later become opportunities or influence existing deals.

That capability arrives as companies reassess the role of physical events in their go-to-market strategies. After several years dominated by virtual and hybrid experiences, in-person events are once again becoming a significant channel for B2B relationship building.

Freeman's 2025 Gen Z Report found that 73% of working professionals want their employers to spend more on in-person events, while 92% said in-person gatherings help them stay informed about developments in their industries. The figures suggest that physical events continue to provide a form of interaction that digital channels cannot fully replicate.

Gartner has also forecast a broader shift toward offline engagement, predicting that digital fatigue could push CMOs to allocate 70% of their marketing budgets to offline channels by 2028. That forecast is significant for event marketers because increased spending also creates greater pressure to demonstrate measurable business value.

The challenge is that events are difficult to attribute using the same frameworks applied to digital campaigns. A paid search click or email interaction can usually be captured in a marketing platform, while an attendee might meet multiple people, participate in several sessions and have conversations that never enter a database.

Epoch is effectively trying to make the event itself a measurable data layer.

"Every other channel got instrumented over the last decade. Events didn't," said Jade Choy, Co-Founder and CEO of Epoch. She argues that as AI makes digital content increasingly abundant, the value of direct interactions between people becomes more important.

The company is not alone in betting on the renewed importance of events. The broader events market has attracted strategic and financial investment as businesses reassess the role of face-to-face interaction in an increasingly AI-mediated economy. In May, Apollo agreed to combine Questex and Emerald into a B2B events platform, citing the continued value of in-person connections as AI changes how professionals interact.

For technology buyers, however, the more interesting development is not simply the return of events. It is the emergence of event measurement as a marketing infrastructure problem.

Salesforce and HubSpot have become central repositories for many organizations' customer and opportunity data. Yet event platforms frequently operate outside those systems. The resulting disconnect can make it difficult for CMOs to understand how event participation influences pipeline progression.

EpochX's integration-first strategy addresses that problem by placing event activity into the systems where marketing and sales teams already evaluate performance.

This also changes how event teams may be evaluated. Attendance has traditionally been one of the most visible event metrics, but attendance alone does not indicate commercial impact. A smaller executive event that accelerates several high-value opportunities could be more valuable than a large conference with thousands of attendees but limited pipeline influence.

Keith Choy, Co-Founder of Epoch, described this shift as a move from measuring attendance to measuring pipeline velocity — specifically, whether opportunities connected to an event advance in the weeks following it.

That model brings events closer to revenue operations. Instead of asking whether an event was successful based on attendance or participant satisfaction alone, teams can examine engagement, opportunity progression and downstream revenue alongside other demand-generation channels.

Epoch's existing platform, Epoch Engage, focuses on internal events and employee experience programs. EpochX extends that infrastructure into external events designed to generate demand and revenue, moving the company toward its stated ambition of becoming a system of record for events.

The competitive landscape will include traditional event management platforms, marketing automation systems and specialized event attribution tools. Platforms such as Salesforce, HubSpot and Adobe already provide extensive campaign and customer measurement capabilities, while event technology vendors have historically concentrated on registration and event operations.

EpochX's differentiation is its attempt to bridge those two categories.

Whether that approach becomes a meaningful competitive advantage will depend on the quality of its CRM integrations, the accuracy of event attribution and the ability to distinguish genuine event influence from simple correlation.

For enterprise marketing organizations, that distinction will matter. As event budgets increase, executives will demand evidence that physical experiences contribute to pipeline rather than simply generating attendance.

Market Landscape

B2B event marketing is entering a measurement-focused phase. The return of in-person events is creating new opportunities for field and experiential marketers, but increased spending also raises expectations around attribution and revenue impact.

The broader MarTech market has already established CRM systems as the central layer for tracking customer and opportunity activity. Salesforce, HubSpot, Microsoft and Adobe increasingly connect marketing engagement with revenue data, creating pressure for offline channels to become equally measurable.

Event technology has traditionally been more operational than analytical. Registration, ticketing, scheduling and attendee management remain essential, but marketers increasingly need to understand what happens after attendees leave the venue.

This creates an opportunity for platforms that can connect physical experiences with digital customer records and pipeline systems.

Strategic Outlook

The long-term significance of EpochX may extend beyond event management. If events become a more measurable part of the revenue engine, event marketing could move closer to the same performance standards applied to paid media, email and digital demand generation.

AI could accelerate that transition. As generative AI reduces the cost of producing digital content, human interaction may become more valuable as a differentiating channel. But that value will increasingly need to be demonstrated through reliable data.

For event teams, the future may therefore involve less emphasis on attendance alone and more attention to engagement quality, opportunity progression and revenue influence.

Top Insights

• EpochX connects event registration, attendance and engagement with Salesforce and HubSpot, giving B2B marketers a clearer view of event-generated pipeline.

• The platform addresses a persistent measurement gap by moving event activity from spreadsheets and isolated systems into the CRM where revenue teams already work.

• Rising demand for in-person experiences is increasing event investment while simultaneously raising pressure on marketers to prove pipeline and revenue contribution.

• EpochX differs from traditional event platforms by prioritizing post-event pipeline measurement rather than focusing primarily on registration, logistics and event execution.

• The product extends Epoch's internal events platform into external demand generation, creating a broader system for planning, executing and measuring events.

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Fintel Connect has released its 2026 Cost Per Acquisition Guide for Affiliate Customer Growth in Financial Services, offering benchmarks and strategic guidance for financial brands navigating changing acquisition economics. The report examines how AI-driven discovery, affiliate competition and evolving partnership strategies are influencing customer acquisition costs across the U.S. and Canada.

Customer acquisition has become a more complex equation for financial services brands. Rising competition for digital placements, fragmented customer journeys and the emergence of AI-powered discovery are changing how consumers find banking, lending, investing and insurance products.

Fintel Connect is attempting to provide marketers with a clearer benchmark through its newly released 2026 Cost Per Acquisition (CPA) Guide to Affiliate Customer Growth in Financial Services.

The report draws on proprietary benchmarks from thousands of financial affiliate campaigns across the United States and Canada. Rather than treating CPA as a standalone cost-control metric, Fintel Connect argues that financial brands should evaluate acquisition spending against the quality and long-term value of the customers generated through affiliate partnerships.

That distinction is increasingly important in financial services, where the cheapest acquired customer is not necessarily the most valuable one. A customer who opens a bank account, takes a loan or purchases an insurance product can generate materially different lifetime value depending on retention, product adoption, balances and cross-sell potential.

Fintel Connect CEO Nicky Senyard said leading financial brands increasingly need to treat CPA as a performance signal rather than simply a number to minimize. The company's approach emphasizes defining what a high-quality customer looks like and aligning that definition with affiliate partners.

The 2026 guide covers acquisition benchmarks across several financial services categories, including banking, investing, lending, business financial products and insurance. It is designed to help marketers compare their acquisition economics with broader market conditions while identifying the factors influencing performance.

One of the report's more timely areas of focus is the impact of artificial intelligence on affiliate discovery.

Consumers increasingly use AI-powered search and conversational assistants to research financial products. Instead of navigating multiple websites or comparing search results manually, prospective customers can ask AI systems to summarize options, compare providers or explain financial products.

That creates a new visibility challenge for affiliate publishers and financial brands. Traditional search engine optimization has historically focused on ranking pages for specific queries. Generative engine optimization and answer engine optimization introduce another layer in which AI systems synthesize information from multiple sources before presenting an answer.

For affiliate marketers, visibility in these environments could influence referral traffic, brand consideration and ultimately CPA. However, AI-generated discovery also raises questions about attribution. If a consumer encounters a financial product recommendation through an AI assistant before interacting with an affiliate publisher, determining which channel deserves credit can become more difficult.

This is particularly relevant as financial services companies invest more heavily in first-party data, customer analytics and marketing automation. Platforms from companies such as Salesforce, Adobe and Google are increasingly integrating AI into customer engagement and analytics workflows, while financial brands continue to diversify their acquisition channels.

Affiliate marketing offers a different model because brands generally pay based on defined outcomes rather than simply purchasing exposure. That performance orientation can make affiliate partnerships attractive when acquisition costs through traditional digital advertising become less predictable.

At the same time, affiliate programs can become difficult to manage as the number of publishers, placements and customer journeys increases. Financial brands need controls around partner quality, compliance, attribution, conversion definitions and customer value.

Fintel Connect's guide focuses on what it describes as the foundation for high-performing affiliate programs, alongside three principles it says leading brands use to sustain CPA performance and five common CPA mistakes that can restrict growth.

The emphasis on quality is particularly relevant to regulated financial services. Affiliate campaigns must operate within advertising, disclosure and consumer-protection requirements, meaning aggressive acquisition tactics can create compliance risks alongside higher operational costs.

The challenge for marketers is therefore not simply reducing CPA. It is determining the level of acquisition investment that produces customers who meet the company's broader business objectives.

This changes how affiliate programs should be evaluated. A financial institution might rationally accept a higher acquisition cost if the resulting customers demonstrate stronger retention or greater lifetime value. Conversely, an apparently inexpensive acquisition channel can become expensive if it produces low-quality customers or high levels of churn.

The Fintel Connect report arrives at a time when financial marketers are also adapting to a changing discovery ecosystem. Search remains important, but AI assistants, comparison platforms, publishers, influencers and specialized financial content sites are increasingly part of the research journey.

For affiliate managers, the strategic question is becoming broader: where does the customer discover the product, which partner influences the decision, and what happens after conversion?

Those questions move affiliate marketing closer to revenue operations and performance intelligence. Instead of managing partners primarily around commission rates and CPA targets, mature programs can evaluate the entire customer lifecycle.

Market Landscape

Financial services customer acquisition is increasingly shaped by competition across search, paid media, affiliate networks, comparison sites and emerging AI-powered discovery channels.

The affiliate model remains attractive because brands can connect marketing expenditure more directly to measurable outcomes. But rising competition among publishers and advertisers can increase placement costs and make benchmark data more valuable.

AI introduces another variable. Generative search can change which publishers receive visibility and how consumers compare financial products. Brands that previously relied heavily on conventional search rankings may need to evaluate how their products and affiliate partners are represented in AI-generated answers.

For financial services marketers, this means CPA should increasingly be analyzed alongside customer quality, lifetime value, conversion rates, retention and channel attribution.

Strategic Outlook

The next phase of affiliate marketing is likely to be less about achieving the lowest possible CPA and more about optimizing acquisition economics around customer value.

AI-driven discovery could accelerate this transition. As consumers use AI systems to research financial products, affiliate publishers will need stronger content authority and clearer product information, while financial brands will need more sophisticated attribution and partner measurement.

The strongest programs may ultimately be those that connect affiliate data with broader customer intelligence, allowing marketers to determine not just which partners generate conversions, but which partners generate valuable customers.

Top Insights

• Fintel Connect's 2026 CPA Guide provides financial affiliate benchmarks across U.S. and Canadian banking, investing, lending, business and insurance markets.

• The guide argues that financial brands should evaluate CPA against customer quality and business outcomes rather than treating acquisition cost as a metric to minimize.

• AI-driven discovery and GEO/AEO are emerging factors in affiliate visibility, potentially changing how financial products and publishers acquire customers online.

• Rising placement competition makes affiliate benchmarking increasingly important for acquisition teams managing partner economics, conversion performance and customer value.

• Mature affiliate programs can connect CPA with lifetime value, retention and customer quality to make more informed financial services acquisition decisions.

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As buyers increasingly use ChatGPT, Claude and Gemini to evaluate products before making purchasing decisions, marketers are experimenting with strategies designed for AI-assisted research. Good At Marketing, a Google Partner agency based in Boynton Beach, Florida, is calling its approach “Verdict Prompting,” a sales technique that gives prospects a structured prompt and lets their preferred AI assistant evaluate the underlying buying question.

The traditional sales pitch assumes the seller controls the conversation. A salesperson presents the problem, explains the solution and attempts to persuade the prospect to take the next step.

AI-assisted buying is changing that dynamic.

Instead of relying exclusively on a company's website, advertising or sales presentation, buyers can now ask an AI assistant to investigate a product category, compare alternatives, identify weaknesses and explain whether a proposed solution makes sense.

Good At Marketing believes that behavior creates a new opportunity for marketers. The agency has coined the term “Verdict Prompting” for a technique that effectively moves part of the sales conversation into the buyer's own AI environment.

The concept is relatively straightforward. Rather than telling prospects why they should purchase a product, a marketer provides a ready-made prompt that the prospect can paste into ChatGPT, Claude, Gemini or another AI assistant. The prompt asks the model to evaluate a specific technical or commercial question.

The resulting response comes from the AI rather than the seller.

That distinction is central to the agency's argument. Good At Marketing founder Donnie Strompf says buyers increasingly place significant trust in AI-generated recommendations, making it more effective to facilitate the research process than attempt to control it.

The approach also comes with an important limitation: the claims included in the prompt need to be accurate.

If the prompt contains misleading assumptions, an AI model may challenge them or produce an unfavorable conclusion. Good At Marketing therefore positions Verdict Prompting as a strategy that works best when the underlying product or service can withstand scrutiny.

That makes the technique different from conventional prompt engineering designed primarily to influence an AI response. The agency's stated approach is less about manipulating an AI model and more about framing a legitimate question that directs the buyer toward an evidence-based evaluation.

“Ask your AI about your own product first,” Strompf said, arguing that a negative AI verdict should be treated as a product problem rather than simply a marketing problem.

The concept arrives as generative AI increasingly becomes part of the buyer research journey. Google remains a major source of commercial discovery, but AI assistants are adding another layer between a prospect and the companies competing for their attention.

For marketers, this creates a new visibility challenge. Traditional search engine optimization focuses on helping webpages rank for queries. AI-driven discovery can involve a model synthesizing information from multiple sources before presenting an answer to a user.

That makes third-party coverage, authoritative content and consistent factual information increasingly relevant to how companies are represented in AI-generated answers.

Good At Marketing's approach combines those two elements. The agency says its proprietary software can generate earned media coverage for clients, while Verdict Prompting gives prospects a structured way to ask their AI assistants about the problem a product addresses.

The agency developed the approach partly through gocta.ai, an AI lead-intake software product founded by Strompf. One of its Verdict Prompts asks prospects to have their AI analyze why embedded iframe forms can disrupt paid advertising attribution and how native, single-line script implementations can preserve attribution.

The example illustrates how the strategy works. Instead of simply claiming that a particular implementation is better, the prompt asks the buyer's AI to investigate the technical problem and explain its implications.

There are clear parallels with answer engine optimization and generative engine optimization, although Verdict Prompting is more directly focused on the buyer's behavior than on optimizing content for AI crawlers.

The competitive landscape is also evolving. Google is integrating generative AI into search, Microsoft has embedded Copilot across its products, and OpenAI, Anthropic and Google are competing to become the interfaces through which consumers and business buyers conduct research.

That means marketers increasingly have two related visibility problems: appearing in traditional search results and becoming part of the information ecosystem AI systems use when generating recommendations.

Verdict Prompting does not solve the latter automatically. A prompt cannot guarantee a favorable AI response, and different models may reach different conclusions depending on their available information, system instructions and sources.

Its potential value lies elsewhere: it encourages marketers to design sales messaging around questions rather than claims.

That shift could prove important as buyers become more skeptical of traditional promotional content. A prospect who independently asks an AI to evaluate a technical problem may be more engaged than one who simply consumes a conventional advertisement.

The model also creates a useful feedback mechanism for marketers. If prospects repeatedly receive unfavorable answers about a product, the problem may reveal weaknesses in positioning, documentation, customer reviews or the product itself.

For enterprise marketing teams, that suggests a broader lesson. AI search optimization should not be treated solely as a content-generation exercise. Companies need accurate product information, credible third-party coverage and clear evidence that can survive independent evaluation by AI systems and human buyers.

Market Landscape

The emergence of AI-assisted purchasing is creating a new layer in the digital customer journey. Search engines remain important, but AI assistants can now summarize product categories, compare vendors and answer technical questions before a buyer visits a company's website.

Google, Microsoft, OpenAI, Anthropic and other technology companies are competing to shape that research experience.

This changes the role of marketing content. A webpage optimized for a keyword may attract a click, while information cited or synthesized by an AI assistant can influence a buyer before the company is directly contacted.

Verdict Prompting sits within this broader shift toward conversational buying. Its distinguishing feature is that the marketer provides the question while allowing the buyer's AI assistant to provide the explanation.

Strategic Outlook

The technique highlights a potentially important transition from persuasion-led marketing to evidence-led discovery.

As AI becomes a more prominent research intermediary, brands may increasingly need to optimize not only for rankings but also for factual consistency, authoritative third-party references and questions that AI systems can answer accurately.

The long-term advantage may belong to companies whose products, data and reputation remain credible when independently examined. In that environment, marketing can open the conversation, but the product itself has to survive the verdict.

Top Insights

• Good At Marketing's Verdict Prompting gives buyers structured AI questions, shifting part of the sales conversation from traditional advertising into ChatGPT, Claude and Gemini.

• The strategy depends on accurate claims, positioning AI scrutiny as a test of product quality rather than a mechanism for manufacturing favorable recommendations.

• AI-assisted buying adds another layer to search behavior, requiring marketers to consider conversational discovery alongside traditional SEO and paid advertising.

• Good At Marketing combines Verdict Prompting with earned media, aiming to influence both the questions buyers ask and information AI systems may encounter.

• The approach reflects a broader move toward evidence-led marketing as buyers increasingly use AI assistants to research products, services and technical decisions.

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Marketing Evolution is positioning marketing measurement as infrastructure rather than a reporting function with the broad availability of the Substrate, a platform designed to unify fragmented performance data and provide a persistent foundation for measurement, simulation, optimization and AI-driven decision-making.

Marketing organizations have accumulated more technology for managing campaigns, customers and channels than ever before. Yet the systems used to measure marketing performance often remain fragmented, leaving teams to reconcile different definitions, attribution methods and data sources before they can answer a basic question: what actually caused a business outcome?

Marketing Evolution is attempting to address that gap with the broad availability of the Substrate, a platform the company describes as a System of Record for Marketing Performance.

Rather than operating as another analytics dashboard, the Substrate is designed to create a persistent marketing intelligence layer by connecting paid and owned media, CRM systems, offline activity and third-party data. The platform then reconstructs portions of customer journeys that may be missing because of privacy restrictions, disconnected systems or limited channel-level visibility.

That approach is increasingly relevant as marketers navigate a more fragmented measurement environment. The decline of third-party cookies, privacy regulation, walled gardens and the proliferation of advertising platforms have made it harder to build complete customer journeys. At the same time, AI systems are creating new demand for reliable, contextualized data.

Marketing Evolution says the Substrate is designed to move organizations beyond reporting toward reasoning across measurement, simulation, optimization and AI-assisted decisions. Users can access the resulting intelligence through Darwin, the company's conversational interface, or connect it to their own AI models, agents and applications.

The underlying technology is based on Marketing Evolution's Journey Reconstruction and Enriched Data technology, which the company says has been developed over more than 25 years of measurement science. First deployed in 2020, the technology reconstructs customer journeys without depending on cookies or personally identifiable information.

One of the platform's notable claims is its shorter data requirement. Marketing Evolution says the Substrate can build models using as little as three months of historical data, compared with the years of historical information traditionally associated with marketing mix modeling, or MMM. The company also reports less than 1% parameter recovery error, although that figure is based on Marketing Evolution's own testing and should be evaluated against independent benchmarks.

The platform combines MMM, multi-touch attribution and incrementality within a single modeling environment. That is significant because these measurement approaches can produce different answers when operated independently.

MMM typically evaluates the relationship between marketing investment and aggregate business outcomes, while MTA focuses more heavily on customer-level touchpoints. Incrementality testing attempts to establish whether marketing activity caused an outcome that would not otherwise have occurred.

Bringing the approaches into a common intelligence layer could reduce the conflicting recommendations that often emerge when marketing teams use separate measurement systems. The larger objective is to give organizations a consistent foundation for budget allocation and optimization.

The Substrate also attempts to expand measurement beyond digital environments. Marketing Evolution says its platform can extend person-level measurement to television, radio and out-of-home advertising, where exposure data is generally less granular than digital advertising.

That capability places the product in competition with a broad range of marketing measurement and analytics platforms. Vendors across the MarTech ecosystem, including Google, Adobe, Salesforce and other enterprise technology providers, offer increasingly sophisticated analytics and customer intelligence capabilities. Specialized measurement companies compete on attribution, media mix modeling, experimentation and incrementality.

Marketing Evolution's differentiation is its attempt to combine these disciplines with a persistent data layer designed specifically for marketing performance.

The company says the Substrate has already operated in production since 2024 through custom enterprise deployments involving Fortune 500 insurance and financial services organizations and global agency holding companies. In one customer deployment, Marketing Evolution says the system identified data-quality problems affecting 29% of the dataset, saved 240 hours of analyst time and reduced reporting from several weeks to four days. The company says those improvements contributed to a $2.38 million annual run-rate margin benefit.

Those figures are customer and company reported rather than independently audited, but they illustrate the business case Marketing Evolution is targeting: improving measurement infrastructure can have a direct impact on analyst productivity, reporting speed and marketing economics.

The company's CEO Stephen Williams argues that this is where marketing measurement is changing. As AI moves into campaign planning, optimization and execution, performance data becomes more than an input for dashboards. It becomes the context AI systems require to make decisions.

That distinction may prove important. Generative AI can summarize campaign results, but without reliable definitions, historical context and causal relationships, it can simply automate the interpretation of flawed data. A persistent performance intelligence layer could instead provide AI systems with a consistent foundation for reasoning.

Marketing Evolution's relationship with Plus Company provides another example. Plus Company CEO Brett Marchand said the Substrate helped create a unified decisioning platform across its brand portfolio, with the company reporting improvements of up to 35% in return on ad spend and 23% in campaign efficiency.

The broader industry implication is that marketing data infrastructure may become as strategically important as the AI applications built on top of it. As organizations deploy more AI agents and automated decision-making systems, the reliability, lineage and context of the underlying performance data will increasingly determine whether those systems improve marketing or simply accelerate bad decisions.

Market Landscape

Marketing measurement is undergoing a structural shift as privacy restrictions, fragmented media environments and AI adoption challenge legacy attribution models.

Traditional marketing stacks often distribute measurement across separate platforms for analytics, attribution, CRM, media buying and customer data. This can create competing definitions of performance and make it difficult for executives to establish a single view of marketing's contribution to revenue.

The emergence of AI raises the stakes. Gartner has predicted that by 2026, more than 80% of enterprises will have used generative AI APIs or deployed generative AI-enabled applications, up from less than 5% in 2023. The rapid adoption of AI makes the quality of enterprise data increasingly important because automated systems depend on the information and context provided to them.

Marketing Evolution is competing in this environment by treating measurement intelligence as infrastructure. Its closest competitive categories include marketing mix modeling, attribution, incrementality testing, customer data platforms and marketing analytics.

The differentiator will ultimately be whether a unified approach can produce more consistent decisions than organizations achieve by stitching together multiple specialized systems.

Strategic Outlook

The Substrate reflects a broader evolution in MarTech from dashboards toward decision infrastructure.

As AI moves deeper into campaign planning and optimization, marketing organizations will need systems that can preserve historical context, explain where data originated, validate incoming information and maintain consistent definitions across models.

That could make the concept of a marketing performance “system of record” increasingly relevant. The winners in AI-driven marketing may not simply be companies with the most advanced models, but those with the strongest data foundations beneath them.

Top Insights

• Marketing Evolution's Substrate unifies fragmented marketing data, creating a persistent performance intelligence layer for measurement, planning, optimization and AI decision-making.

• The platform combines MMM, multi-touch attribution and incrementality, addressing conflicting measurement results that can complicate enterprise marketing budget decisions.

• Journey Reconstruction technology can rebuild incomplete customer journeys without cookies or personally identifiable information, expanding measurement across fragmented and privacy-constrained environments.

• Marketing Evolution says enterprise deployments have reduced reporting times and uncovered major data-quality problems, highlighting the operational value of stronger marketing intelligence infrastructure.

• As AI becomes embedded in marketing operations, reliable performance data and lineage could become more important competitive advantages than the AI applications themselves.

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