The legal world isn’t known for moving fast. But in the Asia-Pacific region, one technology shift is accelerating faster than precedent-heavy industries typically allow: AI-driven document management.

NetDocuments, widely regarded as one of the most secure and trusted intelligent DMS platforms in the legal field, has announced 72% year-over-year growth in APAC. That’s a staggering number for a sector where digital transformation often resembles cautious tiptoeing more than rapid adoption.

More than 20,000 legal professionals across Australia, New Zealand, Singapore, and Japan now rely on NetDocuments—not just for storing documents, but for using generative AI, workflow automation, and embedded legal intelligence to get work done faster and more securely.

NetDocuments’ rapid expansion points to a broader trend: law firms in APAC aren’t just warming up to AI—they’re actively operationalizing it.

Why APAC Law Firms Are Choosing NetDocuments Over “Upgrade-Only” DMS Projects

For many firms, the original plan was modest: update the document system, modernize storage, check a box, move on.

But once firms start evaluating NetDocuments, the scope typically expands.

That’s what happened at Norman Waterhouse. IT Manager Frederik Schwim explains it plainly:

“We were planning a DMS upgrade as an isolated project—then we realized NetDocuments came with far more functionality. We achieved several tech goals with a single implementation.”

Instead of separate projects for document automation, AI insights, contract review tools, or judicial trend analysis, NetDocuments bundles these into an integrated platform.

This isn’t just a DMS anymore—it’s an intelligent legal operations layer.

AI Where Lawyers Actually Work: Inside ndMAX

The star of NetDocuments’ APAC growth story is ndMAX, the company’s AI and workflow automation suite. Where many legal AI tools sit outside standard workflows—requiring uploads to third-party systems or new interfaces—NetDocuments brings AI directly to the heart of everyday legal work.

ndMAX Legal AI Assistant

Lawyers can ask questions across the entire document corpus and get instant, context-aware answers. Unlike general-purpose AI tools, responses stay fully contained within the firm’s DMS—critical for maintaining privilege and confidentiality.

Agentic Editing in Microsoft Word

This is where things get interesting. Instead of switching apps or relying on an assistant tool, lawyers can request edits from inside Word:

• Ask for restructuring

• Generate suggested revisions

• Apply edits automatically

• Turn insights into actionable changes instantly

For legal professionals drowning in version control and document markups, this is a productivity lifeline.

ndMAX Studio

A collection of pre-built AI apps for common legal workflows, including:

• Document classification and profiling

• Contract review against playbooks

• Judicial decision trend analysis

• Automated document assessments

These aren’t “experimental features”—firms are already using them to build consistent, repeatable workflows across practice groups.

AI App Builder

NetDocuments gives firms the flexibility to customize the out-of-the-box apps or build their own. For APAC firms seeking tailored automation—rather than one-size-fits-all AI—this is a key differentiator.

Secure AI: The New Battleground for Legal Tech

While AI enthusiasm is high, legal skepticism is higher—especially around confidentiality, data exposure, and compliance.

APAC firms routinely cite security and control as the biggest hurdles to adopting generative AI. That’s where NetDocuments stakes its strongest claim: AI is embedded in the platform itself, never requiring lawyers to copy, paste, or upload sensitive content into external systems.

Ron Dutta, Director of IT at McCullough Robertson, summed it up:

“For all the excitement around AI, it brings concerns around integration and confidentiality. NetDocuments’ integrated approach eliminates the risks of external AI tools.”

In other words: AI that stays inside the firm’s security perimeter is AI lawyers feel comfortable using daily.

A Region Ready for AI—But Cautious About How It’s Delivered

APAC law firms aren’t simply adopting NetDocuments because it’s an AI-enabled DMS. They’re choosing it because it aligns with their practical, long-term technology strategies.

Take McInnes Wilson, whose CIO Robyna May emphasizes the importance of both capability and responsibility:

“Our focus is making AI a natural, accessible part of everyday legal work. NetDocuments’ strategy aligns with ours—and lets us deploy AI safely and responsibly.”

This theme repeats across the region:

• Legal teams want more automation.

• They need AI that’s embedded, not bolted on.

• They prioritize secure, compliant systems that maintain client trust.

• They want tools that reduce friction, not add steps.

NetDocuments checks all these boxes—explaining its accelerating adoption curve.

Why APAC Is Becoming a Hotbed for Legal Tech Innovation

APAC firms are moving faster than many expect. While U.S. and U.K. firms often dominate legal tech headlines, APAC’s transformation is uniquely compelling.

Three forces are driving it:

1. Rapid modernization cycles

Many firms are shifting from legacy, on-prem systems straight to cloud-native, AI-ready platforms—skipping the half-measures common in older markets.

2. A strong focus on operational efficiency

APAC firms face competitive pressure to deliver high-quality work at scale, especially in fast-growing markets like Singapore and Australia.

3. A cultural emphasis on secure innovation

APAC firms want cutting-edge tools—but not at the expense of confidentiality or client obligations. NetDocuments’ embedded-AI approach fits that mindset.

The Bigger Picture: The Legal DMS Is Becoming the AI Hub

Historically, a DMS was just… a repository. A necessary but unexciting piece of infrastructure.

But with generative AI’s rise, the DMS becomes something entirely different:

• a training ground for firm-specific insights

• an engine for workflow automation

• a secure environment for AI content generation

• a central hub for drafting, reviewing, analyzing, and updating legal documents

NetDocuments’ APAC growth reflects a broader shift: law firms no longer see the DMS as storage. They see it as the core of their AI strategy.

And in a profession built on written work, that shift is monumental.

NetDocuments’ Path Forward in APAC

For Head of APAC Jennifer Cathcart, the momentum is clear:

“Legal technology innovation in APAC is thriving as firms embrace AI. Our Intelligent DMS vision is helping legal teams focus on serving clients—not wrestling with workflows.”

With demand rising for integrated AI systems—and concerns growing about fragmented third-party tools—NetDocuments is well positioned to continue its APAC expansion.

If the current trajectory holds, 72% YoY growth may soon look conservative.

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Elastic—best known as The Search AI Company—has landed in the Leader category of the IDC MarketScape: Worldwide Observability Platforms 2025 Vendor Assessment, a signal that the company’s OpenTelemetry-first, AI-powered approach is resonating with enterprises wrestling with swelling data volumes, hybrid architectures, and accelerating performance demands.

IDC’s endorsement highlights what observability buyers are increasingly prioritizing: open standards, correlation across signals, intelligent automation, and cost-governance levers built directly into the pipeline.

Elastic checks all those boxes—and then some.

Why IDC Says Elastic Stands Out

The MarketScape report points to Elastic’s “open standards–first architecture”, which reduces tooling fragmentation by natively ingesting OpenTelemetry data and tracking signals across logs, metrics, traces, and real user monitoring (RUM). That means teams can move from detection to decision without ripping out instrumentation or duplicating data pipelines across complex, hybrid, and multicloud estates.

In plain English: Elastic simplifies observability without forcing teams to rewire everything.

IDC adds that Elastic is a fit “when an open standards observability platform with Prometheus and OpenTelemetry alignment, RUM/APM correlation, and petabyte-scale retention controls is needed.” Not many vendors can comfortably support observability at petabyte-level scale while keeping ingestion pathways flexible and manageable.

Elastic’s Observability Pitch: AI-Native, OTel-Native, Operationally Pragmatic

Elastic Observability positions itself as the platform that unifies operational and business data, enabling SRE teams to detect and resolve issues faster by connecting performance signals to actual customer experience.

That connection—tying telemetry to business outcomes—is increasingly where enterprises want to go. If the homepage latency spike correlates with a revenue drop or a checkout failure, teams need that insight in real time, and ideally without stitching together multiple tools.

Elastic’s approach includes:

• Full OpenTelemetry-native ingestion (no adapters or conversions required)

• Zero-code auto-instrumentation across major languages

• Correlated logs, metrics, traces, and RUM/APM views

• Broad connector coverage for hybrid and multi-cloud sources

• Enterprise-grade support and governance controls

Shannon Kalvar, research director at IDC, sums it up:

“Elastic links technical performance to customer experience and business context out of the box… The platform’s extensibility and role-appropriate views support shared context across DevOps while maintaining cost governance levers at scale.”

That last point—cost governance—is becoming a major battleground across observability vendors. Elastic’s retention controls and scalable ingestion pipeline appear to have stood out to IDC evaluators.

Streams and EDOT: Elastic’s Latest Innovations

Elastic isn't just leaning on past credibility—it’s pushing new capabilities at a steady clip.

EDOT for OpenTelemetry Support

Elastic recently expanded its enterprise support through its EDOT (Elastic Distribution of OpenTelemetry) initiative, providing deeper coverage for organizations adopting OTel at scale.

Streams: AI-Powered Log Intelligence

Perhaps the most forward-looking addition is Streams, an agentic, AI-driven experience that reinvents how teams work with logs. Instead of manually filtering, wrangling, and enriching log data, Streams helps SREs jump straight into the “investigator” role.

Traditional log search patterns are often slow and mentally taxing. Streams is Elastic’s attempt to move log analysis closer to natural-language investigations, abstracting away the noise and complexity that bog down incident response.

As Elastic’s senior vice president of Software Engineering Santosh Krishnan puts it:

“Our mission is to help teams move from reactive troubleshooting to proactive, intelligent operations that make digital experiences fast, reliable and resilient… Streams and Agent Builder accelerate how teams derive value from signals and build AI agentic workflows.”

This framing aligns with a broader industry trend: observability is transitioning from a detection toolset into an intelligent automation and decisioning layer.

The Bigger Market Context: Observability Is Evolving—Fast

Elastic’s Leader position also reflects a shifting competitive landscape. The observability market once revolved around dashboards and alerting. Now, enterprises want:

• OpenTelemetry-native ingestion (without proprietary lock-in)

• AI-assisted correlation and summarization

• Cost controls baked into the pipeline

• Unified data storage instead of tool sprawl

• Support for hybrid, legacy, and cloud-native workloads

• Faster path from signal to root cause

Elastic’s pitch—an open, scalable, search-driven approach—resonates strongly as companies rethink their observability architectures to manage soaring data volumes and escalating cloud costs.

Being named a Leader in the IDC MarketScape validates Elastic’s position among vendors racing to deliver AI-powered, OTel-aligned observability platforms at enterprise scale.

Is Elastic’s Open Standards Strategy Paying Off?

IDC’s language suggests a clear “yes.” OpenTelemetry is quickly becoming the backbone of modern observability stacks, and Elastic’s full embrace of OTel—not as a bolt-on but as a core ingestion path—gives it strategic advantage.

For organizations struggling to unify distributed telemetry from microservices, mobile sessions, edge workloads, and legacy systems, Elastic offers:

• a single ingestion strategy

• a unified data model

• AI-powered correlation

• and petabyte-scale retention without ballooning costs

It’s a compelling formula at a time when platform consolidation is accelerating.

The Bottom Line

Elastic’s recognition as a Leader in the IDC MarketScape for Observability Platforms underscores the company’s momentum as enterprises shift future observability investments toward AI-driven, OTel-native architectures.

With innovations like EDOT support and Streams, combined with scalable ingestion pathways and strong cost governance, Elastic is positioning itself as one of the few platforms capable of handling modern observability complexity at truly massive scale.

Whether SREs are looking to accelerate triage, unify telemetry, adopt OpenTelemetry more cleanly, or reduce tool fragmentation, Elastic’s offering is increasingly viewed as a safe—and strategic—bet.

Get in touch with our MarTech Experts.

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Builder.io today launched Fusion 1.0, a major milestone in AI-assisted software development and the first AI agent designed to connect the entire product lifecycle—from requirements and design through code implementation—inside one unified workflow.

Today’s product organizations rely on a constellation of siloed tools: PMs write specs in Jira, designers build UI flows in Figma, and engineers translate both into code inside an IDE. Each handoff increases friction, slows iteration, and introduces misalignment. Fusion 1.0 collapses that gap by enabling all three roles to work together directly on the live product with AI acting as a shared, context-aware collaborator.

A Unified AI That Understands Design, Code, and Product

Fusion 1.0 natively integrates with Slack, Jira, Figma, and GitHub, allowing teams to work inside the tools they already use while eliminating the traditional disconnect between ideation and implementation.

• Tag @Builder.io in Slack to convert a team discussion into a structured feature request.

• Assign a Jira ticket to the Builder bot to automatically generate a new branch and begin implementation.

• Designers can work in a visual canvas that writes real, production-ready code using existing component libraries and design tokens.

• Developers can review PRs that Fusion automatically updates based on their feedback.

At its core is Fusion’s context engine, which understands a team’s design system, component architecture, APIs, and data sources. That allows it to generate code aligned with existing patterns, fill in missing context, adapt to evolving requirements, and improve with every commit and review.

Builder.io says Fusion has already transformed over 10 million designs and PRDs into production features across some of the world’s largest enterprise organizations.

AI Collaboration Without the Handoffs

Builder.io CEO Steve Sewell argues that most AI tools supercharge individuals—but not teams. Fusion aims to change that dynamic.

“Most AI tools today make individual contributors faster but leave teams disconnected,” Sewell said. “Fusion 1.0 is different — it lets PMs, designers, and engineers build together in one environment where code is the common language. It's how software teams finally move from handoffs to collaboration.”

That shift is already visible in live team workflows. One UX design lead at a global enterprise services company described the impact:

“We’ve done this live in team meetings — people throw out an idea, and we just build it in front of them. What used to take months now happens instantly. Once leadership saw that, they said, ‘We need this everywhere.’”

Enterprise-Grade from Day One

Fusion supports the architectures and frameworks enterprises already run, including:

• React and modern component-driven JavaScript frameworks

• Custom internal design systems

• Multi-layered, legacy enterprise architectures

• MCP server support for databases, APIs, and deployment tools such as Supabase, Netlify, and Zapier

Additionally, Fusion offers:

• Granular permissions and role-based access control

• AI model flexibility across OpenAI, Anthropic, and Google

• Secure alignment with corporate governance and compliance requirements

The result is an AI agent flexible enough for startups yet powerful and controlled enough for large enterprises operating at scale.

The Bigger Picture: AI Is Rewriting the Software Development Stack

Fusion 1.0 reflects a growing shift: AI isn’t just accelerating coding—it’s rearchitecting how teams collaborate. The next wave of enterprise software doesn’t replace developers; it removes the artificial barriers between product, design, and engineering, allowing teams to iterate in real time on the actual product instead of documents about the product.

Builder.io’s Fusion stands out by grounding this vision in a team-first, code-backed environment that works inside existing enterprise ecosystems.

Get in touch with our MarTech Experts.

E-commerce may be the fastest-moving channel in fast-moving consumer goods, and NielsenIQ (NIQ) wants to be the source of truth for brands trying to keep up. The consumer intelligence giant has rolled out its enhanced FMCG E-commerce Measurement Solution in Indonesia, Singapore, and Thailand, promising a unified view of digital sales performance aligned with the company’s widely used Retail Measurement Service (RMS) for offline markets.

The timing is no accident. Southeast Asia has quietly become the third-largest e-commerce market on the planet, and by 2030, NIQ projects that 30% of all FMCG retail sales in Asia will come from e-commerce. That shift is being driven not just by online enthusiasm but by the region’s increasingly fluid, hybrid shopping behavior—consumers browsing online, buying offline, discovering in-store, and completing purchases digitally.

In other words: omnichannel is no longer a strategy. It’s reality.

A Market Growing Too Fast for Partial Data

Over the past five years, Southeast Asia’s FMCG e-commerce market has doubled, and NIQ expects it to double again within five years. The biggest boosts come from Thailand, Vietnam, and the Philippines—now among the fastest-growing digital commerce economies globally—while Indonesia accounts for more than half of the region’s online FMCG sales and remains its economic anchor.

This explosive growth has pushed brands to demand more complete, harmonized visibility across channels. NIQ’s answer is an e-commerce measurement model built to match its RMS standard: unified definitions, consistent frameworks, and the ability to compare performance apples-to-apples—whether the sale happened in a hypermarket or on a marketplace app.

“Brands need more than surface-level insights,” said Josh Morgan, APAC E-commerce Lead at NIQ. “They need harmonized data that gives a true view of FMCG performance across channels.”

Inside NIQ’s Enhanced Online Measurement Stack

The new solution blends trusted ePOS RMS data with validated alternative data, covering retailers that don’t provide direct feeds—a major gap in many markets. NIQ’s data science team then layers machine learning models and expert validation on top to close the loop.

Key components include:

• RMS ePOS data: NIQ’s gold-standard retail dataset spanning market share, pricing, distribution, and promotional impact.

• Alternative online sources: Capturing performance across non-cooperating digital retailers—critical in Southeast Asia’s fragmented e-commerce landscape.

• Advanced modeling: Machine learning algorithms refine completeness and accuracy.

• NIQ Discover: A unified analytics platform offering monthly refreshed insights, customizable dashboards, and omnichannel comparisons at a global or local level.

The result: brands get a single, harmonized, RMS-aligned view across online and offline FMCG performance—something no other provider offers at this scale in Southeast Asia.

Who Benefits—and How

NIQ’s unified dataset is pitched as a competitive advantage for teams that increasingly rely on omnichannel visibility to make fast decisions.

• E-commerce leaders get RMS-level accuracy for competitive tracking and brand performance.

• Insights teams avoid spending half their week reconciling inconsistent definitions across channels.

• Category managers can spot early demand signals and online category swings.

• Sales leaders can strengthen retailer negotiations with verified, comparable data via NIQ Discover.

In a market where category growth can spike—or stall—overnight, aligned measurement is becoming a strategic weapon rather than a reporting necessity.

Why This Matters Now

Southeast Asia’s FMCG landscape is evolving faster than most global markets, fueled by mobile-first consumers, hyper-promotional marketplaces, and a wave of new digital-first brands. But with complexity comes opacity. Between marketplace ecosystems, inconsistent reporting standards, and non-cooperating retailers, brands often rely on patchwork visibility and guesswork.

NIQ argues the industry can’t afford that anymore.

By aligning e-commerce tracking to its RMS standard, the company is handing brands a single source of truth for FMCG performance across the full omnichannel ecosystem. That consistency unlocks better forecasting, more confident category expansion, and sharper digital investment decisions.

And in a region where e-commerce is outpacing traditional retail by orders of magnitude, a unified measurement framework may soon move from nice-to-have to mission-critical.

NIQ’s Competitive Positioning

The company’s pitch distills down to four differentiators:

• Unmatched Accuracy: RMS ePOS data plus validated alternative online sources.

• Unrivaled Coverage: Major FMCG categories across dominant e-commerce channels and retailers.

• Omnichannel Advantage: Seamless integration of online and offline insights through NIQ Discover.

• Local Expert Support: Ground-level guidance for converting insights into action.

For FMCG manufacturers navigating one of the world’s most dynamic digital marketplaces, the promise is simple: see more, understand more, act faster.

Get in touch with our MarTech Experts.

Marchex is doubling down on its AI strategy—and eyeing a major expansion of its business model. The conversational intelligence company reported third-quarter 2025 earnings while revealing an agreement in principle to acquire Archenia, a fast-growing customer acquisition platform built on AI-verified outcomes.

The move signals Marchex’s push beyond insights and analytics into a broader, vertically aligned AI-driven outcomes ecosystem—one the company believes will redefine how enterprises qualify, convert, and measure customers across channels.

Q3: Revenue Dip, But Strength in Bookings and EBITDA

For the third quarter ended September 30, 2025, Marchex delivered results that show a business in transition but tightening its operational discipline.

Q3 2025 financial highlights:

• Revenue: $11.5M, down from $12.6M YoY

• Net loss: $1.0M (flat at $(0.02) per share)

• Adjusted EBITDA: $0.6M vs. $0.3M YoY

• Adjusted EBITDA ex-reorg costs: $1.1M

• Adjusted non-GAAP EPS: $0.00 vs. $(0.01) YoY

While the company continues to experience revenue migration dilution tied to its ongoing platform overhaul, it’s seeing strong traction in sales activity.

Troy Hartless, president of Marchex, highlighted that Q3 brought the highest sales bookings of the year, adding:

“As we near completion of our technology platform migration, we improved Adjusted EBITDA to $1.1 million—up roughly 50% from Q2—and we believe we’re gaining visibility into sustainable sales growth heading into 2026.”

Marchex expects Q4 revenue and EBITDA to be sequentially lower due to seasonality and final migration impacts, but says bookings momentum and new product launches are setting up 2026 for a return to growth.

2026 Outlook: Growth Returns—and Margin Expansion

Marchex is projecting a 10% revenue growth run-rate in 2026, supported by:

• Expanded AI product offerings

• Completion of its platform migration

• Increased sales bookings across enterprise accounts

The company also believes Adjusted EBITDA margins could reach 10% or more next year as revenue grows and operating expenses decline.

AI Product Momentum: Benchmarks, Optimization, GPT Search, and Vertical Intelligence

If 2024 was about rebuilding, 2025 has been about launching. Marchex’s product roadmap is heavily weighted toward new AI modules designed to close the loop from insights to action.

AI Benchmarking

Launched in October, Industry Benchmarking adds competitor and industry-level KPIs inside the Key Insights Dashboard. Enterprise users can now compare performance against peers with prescriptive recommendations for improvement.

AgentAI Optimizer

Coming soon, this module evaluates the performance of third-party AI agents—an emerging but critical need as enterprises deploy large fleets of AI-driven automation tools.

Marchex Engage GPT

Expected later this quarter, this LLM-powered search engine lets businesses query their structured enterprise data using conversational prompts—a business-specific GPT built for Fortune 500-scale search.

New Vertical AI Solutions

Marchex is expanding into industries where conversations directly drive revenue outcomes.

• Healthcare AI Solution:
  Helps providers more accurately attribute patient leads, prioritize high-value appointments, and detect engagement gaps.

• Senior Living AI Solution:
  Surfaces prospect needs, improves marketing efficiency, and analyzes reasons for move-in or rejection.

Marchex says its verticalized AI models deliver “prescriptive analytics uniquely calibrated to each industry’s omnichannel conversational trends.”

The Big Move: Marchex to Acquire Archenia

The headline beyond earnings: Marchex has entered an agreement in principle to acquire Archenia, an AI-driven customer qualification and acquisition company that specializes in performance-based, outcome-driven results.

The proposed deal structure includes:

• $10M convertible promissory note at 6% interest

• Convertible at $1.80 per share

• Additional earn-out of up to 4M shares tied to revenue/EBITDA milestones across two 12-month periods

• Closing targeted for 1H 2026, pending audited financials, fairness opinion, and shareholder approval

A special committee of independent directors has approved moving forward due to related-party considerations among some Archenia sellers.

Who Is Archenia?

Archenia brings something Marchex lacks: AI-verified, pay-for-outcome conversion capabilities.

The platform:

• Uses real-time AI signals and natural-language analytics to detect consumer intent

• Validates outcomes such as appointments, sales, or high-intent conversations

• Optimizes campaigns dynamically across channels

• Serves major verticals including insurance, home services, healthcare, and automotive

Archenia estimates $17M+ in revenue for 2025 and positive Adjusted EBITDA, with roughly $14M delivered through Q3 (unaudited).

Why This Acquisition Matters

If completed, the combination would give Marchex a rare vertically integrated stack across:

1. Insights – Conversational intelligence, benchmarking, and GPT-powered analytics

2. Actions – AgentAI and AI-driven optimization

3. Outcomes – Pay-per-event conversions validated by Archenia’s AI models

This is exactly where the market is heading. As AI rewires how enterprises measure marketing, sales, and customer interactions, traditional cost-per-click or cost-per-lead models are losing relevance. Pay-per-event is rising—and Marchex wants to own the full pipeline.

Strategic upside includes:

• Larger addressable market

• Cross-sell and bundling potential

• Revenue scale approaching $60M annually

• Target growth of 15–20% in 2026

• Potential adjusted EBITDA margins exceeding 10%

The story is becoming clear: Marchex is positioning itself not just as a conversational intelligence vendor—but as a full-stack AI customer acquisition engine.

The Bottom Line

Marchex’s Q3 may look modest on paper, but the underlying signals—rising bookings, a stronger AI roadmap, and the potential Archenia acquisition—paint a picture of a company preparing for an aggressive 2026.

If the deal closes, Marchex would enter the new year with a scaled, end-to-end platform spanning insights, decisions, and outcomes—exactly the direction the AI-powered marketing and sales industries are moving.

Get in touch with our MarTech Experts.

SiteOne Landscape Supply—the only national wholesale distributor in the landscape supply market and a fixture in the professional contractor ecosystem—has picked Goodway Group as its new paid media strategy partner. It’s a notable move for a 600+ location operator that has grown largely through acquisitions and regional dominance but now wants to modernize its marketing engine to match the digital sophistication of adjacent B2B sectors.

For Goodway Group, a self-styled challenger agency specializing in measurement-led growth, the partnership is a chance to flex its full-funnel media, analytics, and customer-journey muscle in a category that has historically lagged behind other B2B verticals in digital transformation. And for SiteOne, the decision signals a shift from tactical media buying to measurable, data-informed business acceleration—particularly as the company pushes deeper into pro-heavy categories like agronomics, irrigation, nursery, lighting, and hardscapes.

The partnership begins not with a buy, but with a blueprint: a multi-phase onboarding and planning program designed to unify media, data, and creative under a single measurement framework. In other words, SiteOne is trading in disparate campaigns for a clean, centralized, accountable growth operating system.

Why This Partnership Matters Now

The landscape supply market is a fragmented, service-heavy industry where purchase decisions are influenced as much by availability and local relationships as by brand equity. Historically, media investment in this category skewed conservative—focused on trade media, sponsorships, and digital point solutions with limited attribution.

But that model is straining under emerging pressures:

• Professional contractors expect digital convenience.
  They want on-demand inventory visibility, frictionless ordering, and personalized insights across desktop and mobile—fast.

• Competitors are getting smarter with audience segmentation.
  Regional players and DTC disruptors are using first-party data and vertical AI to break into categories once dominated by legacy distributors.

• Measurement gaps limit marketing performance.
  With fragmented analytics, it’s difficult to tie media spending to outcomes such as revenue, retention, and customer lifetime value.

Goodway Group’s pitch, according to both sides, was less about channel execution and more about tearing down these silos.

“SiteOne has an ambitious vision for growth,” said Paul Frampton-Calero, CEO of Goodway Group. “We’re excited to help modernize its media strategy, connecting every investment to measurable outcomes and building scalable pathways for B2B audiences.”

That emphasis on measurable business impact—not impressions or click-through rates—aligned with SiteOne’s evolving priorities.

“We were looking for more than a media buyer,” said Erin Edstrom, Vice President of Integrated Marketing at SiteOne. “Goodway Group demonstrated that from the start. Its approach to uncovering consumer insights, passion for accountability, and customer-first approach were clear differentiators for us.”

Inside the Partnership: Media as a Business Lever, Not a Cost Center

Goodway’s work with SiteOne will include several strategic components that point toward a deeper transformation:

1. Competitive Market Analysis

SiteOne competes across multiple local markets with drastically different dynamics. What works for irrigation buyers in Arizona isn’t what moves hardscape contractors in Michigan. Goodway’s role includes dissecting these differences and mapping out where media can influence revenue at the category and location level.

2. Budget Scenario Modeling

For an enterprise with hundreds of branches, spend allocation is more complex than shifting dollars between channels. It requires modeling:

• regional category maturity

• customer mix (residential vs. commercial pros)

• historical seasonal cycles

• supply chain constraints

• competitive intensity

Goodway’s models are intended to help SiteOne understand where incremental spend yields incremental profit—something the brand has struggled to quantify in the past.

3. Full-Funnel Measurement Framework

The core of the engagement is a measurement redesign meant to tie upper-funnel brand activity to lower-funnel revenue and contract value. This includes:

• Unified KPIs across categories

• Multi-touch attribution for B2B buyer journeys

• Connection of media outcomes to CRM and sales data

• Insights on audience conversion paths

In practice, this means that if a lighting contractor in Denver sees a brand video, downloads a spec sheet three weeks later, and places a bulk order two months after that, SiteOne will actually be able to see the influence of its media spend on the deal.

3. Customer Journey Simplification

Professional contractors move quickly and often default to the distributors who save them time. SiteOne wants to build loyalty not by broadcasting more ads but by removing friction from discovery, ordering, and service. Goodway’s role here includes:

• Identifying attention breakpoints

• Creating clearer paths between interest and purchase

• Personalizing messaging by professional segment

• Coordinating creative and data to reduce noise and increase conversion

In short, the agency is trying to engineer repeatable, scalable loyalty rather than one-off wins.

What Makes This Partnership Different?

Most agencies in SiteOne’s space focus on digital execution—programmatic, paid search, or social. But Goodway is positioning itself as a transformation partner, emphasizing measurement-driven modernization and full-funnel accountability.

A few factors make this move stand out:

A Step Toward B2B Media Maturity

The pro landscape market is not traditionally a hotbed of cutting-edge media strategy. Bringing in an agency known for sophisticated measurement frameworks signals SiteOne’s intention to modernize the category.

A Tight Connection Between Media and Revenue

SiteOne is not just funding ads—it’s building a system where media and revenue performance are threaded together. That shift mirrors what we’re seeing across B2B sectors like manufacturing, logistics, and construction technology.

The Timing Is Ideal

With digital adoption rising among contractors, and the industry facing supply chain challenges and competitive disruption, the opportunity to use smarter media to shape loyalty is larger than it was even two years ago.

The Market Trend: B2B Brands Race to Modernize Media

Goodway’s win reflects a broader shift in B2B advertising. As AI-powered analytics, intent data, and first-party data standardization accelerate, B2B brands are rethinking how they track and optimize customer journeys.

Three trends stand out:

1. AI-Driven Personalization Moves from Luxury to Necessity

Even in a traditionally analog industry like landscaping, professional buyers expect Amazon-level predictability. AI helps:

• anticipate demand cycles

• identify at-risk accounts

• segment by project type

• recommend inventory and services

This context makes Goodway’s measurement-first approach appealing to enterprises like SiteOne.

2. Media Investments Require Board-Level Proof

Marketing budgets are under more scrutiny than ever. Agencies that can demonstrate revenue impact—not just awareness—are winning more RFPs.

3. The B2B Buyer Journey Has Become Nonlinear

Buyers toggle between research, peer reviews, mobile ordering, onsite needs, and relationship-based decisions. Measurement-driven orchestration becomes critical. The buyer is in control; the brand needs the analytics to keep up.

Potential Outcomes: What This Could Mean for SiteOne’s Future

While the partnership is still in its early stages, several strategic outcomes appear likely:

1. Stronger Category-Level Growth

With clearer insight into category-specific opportunities—nursery vs. hardscapes, irrigation vs. lighting—SiteOne may uncover pockets of growth previously hidden in fragmented data.

2. More Efficient Media Spend

Scenario modeling could shift SiteOne from broad, national messaging toward precision-located, category- and customer-specific activation.

3. Better Contractor Retention

Simplifying the contractor journey is one of the highest-impact levers in the pro supply market. Improved experience and personalization tend to drive disproportionate repeat purchases.

4. A More Modern, Scalable Marketing Engine

If SiteOne integrates Goodway’s measurement frameworks across its growing network, it could build one of the more sophisticated B2B media infrastructures in its sector.

A Win for Goodway, A Signal to the Market

For Goodway Group, this client win reinforces its positioning as a challenger agency focused on measurable growth. In a landscape where many agencies still sell impressions, Goodway sells outcomes quantified through data, analytics, and customer understanding.

For SiteOne, it marks a milestone in its marketing sophistication journey—an intentional shift toward a long-term, measurable, tech-enabled strategy designed to support both organic growth and acquisition-driven expansion.

As professional contractors increasingly expect digital precision and frictionless service, this is the kind of transformation that will separate the legacy distributors that thrive from the ones that get disrupted.

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In an advertising landscape defined by fragmentation, siloed workflows, and platform sprawl, Frost & Sullivan has named Basis its 2025 Customer Value Leader for the global demand-side platform (DSP) market—an award reserved for vendors who don’t just move with the industry but help rewrite its rules. The consulting firm argues that Basis’ unified, AI-driven platform tackles one of modern advertising’s biggest headaches: the chaos created when marketers must stitch together CTV, DOOH, social, search, display, audio, and more without a single pane of glass.

The award underscores a trend that has been bubbling for years but is now impossible to ignore: Advertisers are tired of juggling point solutions. They want orchestration. They want automation. They want transparency. And critically—they want all of that without losing performance.

Frost & Sullivan’s full analysis is available via Basis, but the summary is clear: the company’s platform and operating philosophy represent a meaningful shift in how DSPs are expected to serve brands and agencies in a multi-channel world.

DSPs Are Being Forced to Grow Up—and Fast

The DSP market didn’t start out fragmented; it became fragmented. As new channels emerged—CTV, streaming audio, in-game ads, DOOH—the tech stack ballooned. Instead of unifying, most vendors built add-ons and extensions, leaving buyers to navigate a maze of interfaces, workflows, and attribution blind spots.

Frost & Sullivan doesn’t mince words in its report:

“It is no longer sufficient for a DSP to excel in a single channel. Brands and agencies now demand a single, cohesive interface to orchestrate, measure, and optimize cross-channel and cross-device campaigns harmoniously.”

This is the problem Basis claims to have solved. While many DSPs are busy playing channel catch-up, Basis has spent years building (and rebuilding) an operating system that automates everything from planning and media buying to reconciliation, invoices, reporting, and analytics.

The result: a workflow that resembles a true full-lifecycle advertising platform rather than a patchwork of vendors strapped together with spreadsheets.

Why Frost & Sullivan Picked Basis

To win Frost & Sullivan’s Customer Value Leadership award, companies must excel not only in product innovation but also in measurable customer success, ROI, and long-term partnership value. Basis checked boxes across all criteria—and then some.

Three themes stood out:

1. A Unified, Modular Media Environment

Basis brings planning, execution, optimization, financial operations, and analytics under one roof. No hopping between ad servers, billing systems, DSPs, social dashboards, and spreadsheets.

This centralization matters more in 2025 than ever. As marketers adopt signal diversity strategies (post-cookie), first-party data enrichment, and advanced audience modeling, the ability to manage campaigns across the full journey becomes a competitive advantage.

2. AI That Thinks in Customer Context

Not all AI in ad tech is created equal. Many platforms stitch in AI tactically—an optimization toggle here, an automated bid model there.

Basis takes a different tack. According to Frost & Sullivan, the platform analyzes over 30 brand-level targeting parameters every six hours, re-optimizing against models trained on each client's business.

That means the machine isn’t just predicting who will click—it’s evaluating who drives value.

3. A Customer Philosophy Built for Longevity

One of the most overlooked frustrations among enterprise advertisers is losing historical campaign intelligence when switching agencies or tools. Basis aims to solve this by allowing customers to own their full tech stack and their media data outright.

This gives marketers control over long-term learnings—critical for brands that juggle multiple agencies or rely on in-house teams.

Inside Basis' Platform: What Makes It Different

Basis markets itself as the industry's leading advertising automation platform, and in this context “automation” isn’t shorthand for bidding algorithms. It’s a structural overhaul of the digital advertising supply chain.

Planning & Media Activation in One Place

Marketers can build media plans—across programmatic, direct, search, and social—without leaving the platform. The handoff from plan to execution happens instantly, killing the spreadsheet bottleneck that plagues agencies everywhere.

Intelligent Targeting & Optimization

Basis' AI engine pulls from:

• proprietary optimization models

• 30+ real-time targeting dimensions

• brand-specific performance signals

• cross-channel device and audience mapping

Frost & Sullivan highlighted that this cadence of recalibration (every six hours) is unusually aggressive compared to traditional DSP cycles.

Financial Actualization & Reconciliation

This is the part no marketer loves but every CFO obsesses over. Basis automates invoice matching, reconciliation, vendor payments, and the financial chain that typically eats up weeks of manual labor.

Analytics & Transparency

All campaign data—across channels, formats, and teams—lives in one interoperable environment, avoiding the disconnected dashboards that plague most operations.

Customer Partnerships as a Strategic Pillar

One of Frost & Sullivan’s strongest compliments centers around Basis’ service model.

Because advertisers own their historical media data, the platform isn’t a lock-in tool—it’s a partner enabler. Marketers can switch agencies, build hybrid teams, or bring operations in-house without losing institutional knowledge.

This philosophy is one reason Basis has maintained strong renewals and deep multi-year enterprise relationships in an industry notorious for churn.

“Automation is about empowering people to work more effectively by simplifying and streamlining repetitive and complex tasks,” said Grace Briscoe, EVP of client development at Basis. “Frost & Sullivan’s recognition… underscores the value we have been delivering to marketers for more than two decades.”

Programmatic’s Broader Shift: The Market Wants Fewer Silos, More Intelligence

Basis' win reflects a macro shift happening across the advertising ecosystem:

1. The Consolidation Wave Is Accelerating

Agencies and brands are replacing six or seven-point tools with unified platforms. Not because consolidation is trendy—but because operational drag kills ROI.

2. AI Is Becoming the Differentiator Among DSPs

Bid shading and pacing algorithms used to be the bragging point. Now it’s enterprise-grade intelligence capable of analyzing:

• brand-specific outcomes

• signal decay

• creative impact

• multi-touch attribution

• real-time contextual trends

DSPs that can’t evolve beyond tactical AI are already falling behind.

3. Transparency Is No Longer Optional

The market has grown intolerant of black-box AI, opaque fees, and limited data portability. Basis’ open, customer-owned data model aligns directly with this trend.

4. Cross-Channel Integration Is the New Table Stakes

A DSP limited to programmatic is as outdated as a CRM that only stores email addresses. Brands want search, social, display, audio, DOOH, CTV, and direct buys in one orchestrate-and-optimize environment.

What This Recognition Means for the DSP Market

Frost & Sullivan’s award doesn’t just validate Basis; it spotlights a broader redefinition of what a DSP must be in 2025 and beyond.

Basis Raises the Bar for Competitors

Legacy DSPs now face pressure to:

• unify workflows

• invest in brand-specific AI

• deliver transparent data models

• simplify financial operations

• prioritize customer ownership over vendor lock-in

Most will need substantial rebuilding to catch up.

Agencies Gain Leverage

Agencies frustrated with tool fragmentation may see Basis as an opportunity to modernize operations without adding more software—and without sacrificing performance.

Brands Get a Blueprint for Modern Ad Ops

Enterprise advertisers looking to cut inefficiencies (and headcount bloat) may see Basis as a template for how to run leaner, smarter media organizations.

The Bottom Line

Frost & Sullivan’s 2025 Customer Value Leadership award places Basis at the center of the conversation about the future of DSPs—one where automation, transparency, and unified operations matter more than bid mechanics or channel bragging rights.

By centralizing planning, activation, optimization, financial workflows, and analytics in one AI-powered environment, Basis isn’t simply offering a DSP. It’s selling an operating system for modern advertising—one built to survive the next decade of channel proliferation, signal loss, and measurement disruption.

For a market desperate for simplification and intelligence, Basis’ approach is increasingly hard to ignore.

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Fintel Connect has dropped a new reality check for financial marketers: in the AI era, banks are losing the visibility game—and affiliate publishers are winning it. The company’s latest industry report, Competing for Visibility in the Age of AI (2025/2026), breaks down how large language models source financial information and what it means for the institutions that depend on consumer discovery.

The key finding is blunt. More than 60% of AI-generated financial content comes from affiliate publishers, not the institutions that actually provide the products. While that may surprise traditional marketers, it aligns with a growing shift toward zero-click search, where AI summaries replace the need for a direct website visit.

AI Favors Affiliates, Not Banks

According to the study, AI systems consistently pull from consumer-facing financial guides produced by major affiliate players like NerdWallet, Bankrate, and Investopedia. These sites have spent years optimizing for credibility, structure, and breadth—features that large language models tend to reward.

Fintel Connect CEO Nicky Senyard says this shift underscores a larger change in how trust and visibility are built.

“Our goal has always been to help financial brands grow through partnerships grounded in transparency and performance,” Senyard said. “As AI changes how consumers search and trust information, affiliates are becoming a critical pipeline of information for the LLMs.”

That pipeline now has outsized influence. When AI tools summarize credit card options, savings rates, or loan products, the underlying data often originates from affiliate content—not the bank’s own site.

Zero-Click Search Is Reshaping Marketing Strategy

Financial marketers have traditionally relied on paid search, SEO, and direct site traffic to bring customers into the funnel. Zero-click search disrupts all three. Because AI-generated answers rarely require a click-through, visibility now depends on whether an institution’s product data appears in the sources AI trusts most.

Fintel Connect’s findings reinforce a trend that has been building across the search landscape. In the consumer tech sector, Google’s Search Generative Experience has already reduced traditional organic visibility for many brands. The financial industry is now facing a similar transition—but with higher regulatory stakes.

Affiliate publishers, with their deep content libraries and structured comparison formats, now serve as a primary point of entry for AI training models. Banks without strong affiliate pipelines risk slipping out of the conversation entirely.

Why Affiliates Are Winning the LLM Game

There are several reasons AI systems lean so heavily on affiliate content:

• Structured data formats make product comparisons easy to parse.

• Frequent updates ensure rate and offer information stays fresh—something AI models favor.

• High domain authority signals reliability to both search and AI systems.

• Consumer-first content language maps closely to the natural queries users ask LLMs.

Banks, by contrast, often struggle with rigid product pages, compliance-heavy language, and slower content updates. Even well-known institutions rarely produce the type of informational guides that AI systems prefer.

What This Means for Banks, Credit Unions, and Fintechs

The report suggests a clear path forward: strengthen affiliate relationships or risk disappearing from AI-driven financial discovery altogether.

Senyard notes that the research offers a roadmap for institutions adapting to fast-changing search mechanics. “This research gives financial institutions a window into that evolving landscape and shows how to strengthen affiliate relationships to ensure their products stay visible,” she said.

That visibility is now tied directly to revenue. If AI summaries highlight a competitor’s product because the model draws from affiliate comparisons, a bank may lose a customer before they ever reach its website.

In a marketplace where consumers increasingly trust AI assistants to filter financial options, product placement within affiliate content becomes a critical competitive lever.

The Bigger Industry Picture

Other sectors—insurance, travel, ecommerce—have experienced similar shifts. In each case, aggregators and comparison sites became gateways to visibility long before AI arrived. The financial industry is now confronting the AI-enhanced version of that trend.

With regulatory pressures pushing institutions toward clearer disclosures and more standardized information, the affiliate model may become even more influential. AI tools prefer consistency, and affiliates offer it at scale.

A New Playbook for Financial Visibility

Fintel Connect’s report signals that the era of controlling your own digital visibility through owned content is fading. The companies that adapt quickest will treat affiliate ecosystems not as optional marketing channels but as essential infrastructure for AI relevance.

The takeaway is simple: If financial brands want to shape AI-generated search results, they must ensure their product data lives where AI systems are already looking.

And right now, that place is not their own website.

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