GEO webinar: AI’s new frontier of brand visibility

GEO webinar: AI’s new frontier of brand visibility

A webinar on how to harness the power of GEO

With AI-powered tools like Chat GPT, Perplexity and Gemini transforming how people search for and consume information, the SEO playbook is racing to keep pace. There’s a lot of information swirling around, but amidst the hype sits an important truth: if your marketing and communications plans for the next quarter aren’t addressing how your brand shows up in generative engines, you’re already falling behind.

As organizations look to swiftly mobilize on the topic, there’s no shortage of content offering top ten tips and failsafe strategies. From shifting focus to long form content, doubling down on influencer activity to building your profile on Reddit. But for those without endless resources or the ability to effortlessly pivot their entire marketing strategy, how do you identify which of the possible plays will make the most difference to your business?

Access the recording of our recent webinar, hosted live on September 2, 2025, to uncover:

  • The evolving GEO landscape
  • Navigating the myriad tools available
  • Actionable strategies and quick wins to enable PR, content and digital teams to impact GEO outcomes
  • Ways we can start to set KPIs and meaningfully measure effectiveness in this dynamic field.

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What’s next?

GEO webinar: AI’s new frontier of brand visibility

Access the recording of our recent webinar on GEO (Generative Engine Optimization), hosted live by Niall Moran on 9/2/2025, and learn how to keep up with AI's new frontier of brand visibility.

Unified Marketing Measurement

Unified Marketing Measurement (UMM) unites MMM, MTA, and testing into one system for a complete view of marketing ROI. Discover how UMM links long-term brand impact with real-time insights—read the full guide.

Report: Marketbridge recognized in the Marketing Measurement Landscape

Marketbridge recognized in the Marketing Measurement and Optimization Services Landscape, Q3 2025. Access the report to evaluate providers, scenarios, and key capabilities.

Unified Marketing Measurement

Unified Marketing Measurement

An approach that combines MMM, MTA, and testing into one system for measuring marketing effectiveness

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Introduction: Long-Run impact, meet realtime insights

Traditionally, last-touch, MMM, MTA, and testing results were all used to separately measure marketing’s effectiveness. While each approach had its advantages (and limitations), they seldom agreed, leading to frustration.

Unified Marketing Measurement (UMM) integrates testing, marketing mix modeling, and multi-touch attribution into a single, reproducible system built on a near-real-time longitudinal human record (LHR) inside a composable marketing data lake.

For brands and companies that have not started with marketing effectiveness, starting with a UMM approach saves future model integration headaches, and isn’t much more difficult than standing up an MTA or MMM on their own.

Quick links

What is UMM and how does it differ from traditional MMM or MTA?

Unified Marketing Measurement integrates econometric analysis (marketing mix modeling or MMM), behavioral customer analysis (multi-touch attribution or MTA), and in-market testing to drive a complete and consistent picture of marketing effectiveness. Typically, it also is more ambitious in scope, taking long-run brand effects, pricing, and distribution choices into account to paint a complete causal picture of revenue. UMM is much faster than typical MMM, because econometric results are driven into an MTA-like longitudinal human (or account, in the case of B2B) record. At the same time, it does not suffer from “offline blindness” as does MTA.

What types of data does UMM integrate (e.g., media, sales, CRM, external factors)?

The best UMMs integrate a comprehensive set of stimulus data—anything that might drive sales (or whatever your dependent variables of interest is). These data typically include first- and third-party paid digital media touches; “above the line” advertising; earned media and PR; CRM touches like email and direct mail; pricing; distribution channel; macroeconomic factors; and competitive activity.

The key difference from traditional MMM is that these are gathered at the lowest level of granularity possible—ideally the individual, time-stamped level—and then only aggregated later when required. This ensures that a consistent set of training data for both behavioral and econometric models.

UMMs should also integrate a formal ledger of test results, in a machine-readable format like JSON. As new test results are acquired, they should be efficiently ingested into the ledger, and then used as priors for the unified model.

How does UMM handle cross-channel attribution?

Because UMMs look at all distribution channels—for example, retail, direct, and platform—they must take cannibalization into account (or, in rare cases, a beneficial effect.) In essence, when a channel like retail is added, this typical depresses sales through, say direct. Reach and price are the key drivers of this effect, but UMMs should give channel strategists what they need to make route-to-market decisions.

How does UMM handle incrementality?

Incrementality should be the standard output of the UMM. In other words, each reported metric—such as ROAS (return on ad spend)—should (1) not be duplicative with any other stimulus channel, and, (2) should take the base, or “what would have happened without marketing”, into account.

This can be a challenge with MTA solutions, which typically start with a sale and work backward to divvy up credit to the various channels that “touched” the sale, but UMM solutions solve for this by deriving causality from more sophisticated econometric (MMM) analyses.

What modeling techniques are used?

UMMs rely on Bayesian regression for the MMM step, causal inference for the testing step, and machine learning techniques like logistic regression or Shapley values for the MMM step. Each solution uses slightly different methods, but the most important thing to look for is parsimony. Overly complex methods can easily create nice looking but incorrect results.

How frequently is the model updated and refreshed?

The MMM component of a UMM, which is the main causal engine, is typically refreshed at three levels. First, daily contribution re-estimations can be accomplished easily without rebuilding coefficients. In essence, this means that each channel’s impact will change based on its spend and the sales observed, but the causal relationship between spend and return will not be updated.

Second, coefficients can be reupdated frequently as new data come in. This “mid-level” refresh uses the same model structure, but allows the causal “power” to change, between, say, paid social video and sales. This is a lighter lift and might be redefined weekly.

Finally, the overall model structure—which includes the taxonomy of stimulus channels and how they interact—is typically rearchitected quarterly.

The beauty of a UMM solution, however, is that the MTA component is updated in near real-time. While the causal inputs might not change as frequently, a CMO should be able to understand marketing’s performance on any given day.

How does UMM integrate with our existing tech stack (BI tools, CDPs, cloud platforms)?

UMM models should sit on top of an owned marketing data lake that takes inputs via API from martech tools and CDPs, but should not exist inside these tools. Martech tools are inherently siloed—even if vendors claim to have a comprehensive view. Outputs can certainly be integrated into existing BI tools (like Looker or PowerBI).

What is the onboarding process like, and how long does it take to be fully operational?

Universal Marketing Measurement is not software. It is a system and way of thinking for marketing analytics that includes data, people, models, processes, and reports, so “onboarding” is probably not the right way to think about. That being said, a UMM approach should start producing results within six months, and should be fully mature after about a year. A typical realistic timeline:
  • Months 0-3: Data lake built and starting to be hydrated; draft marketing mix model built; first tests designed
  • Months 4-6: First “final” MMM model built; priors ingested from initial rounds of tests; draft MTA model built
  • Months 7-9: First “final” MTA model built; priors ingested from MMM; initial real-time results flowing
  • Months 10-12: Results tuning; testing “factory” up and running; real-time results embedded in marketing and financial dashboard for the company

Can UMM handle both online and offline data sources?

UMM is tailor-fit to handle both online and offline data sources. Because the MMM portion can estimate any stimulus impact due to its use of econometric time series analysis, all marketing touches’ impacts are estimated. Offline touches are then probabilistically imputed into the MTA portion to get a real-time view of impact. Tests are also perfect for measuring offline impact. For example, geographical tests with synthetic controls can be used to measure the incremental impact of almost anything—and these results can then be imported into the MMM and ultimately the MTA component to understand impact.

How does UMM quantify marketing ROI across channels and campaigns?

Because UMM calculates ROI at the individual level (whether a new customer, won deal, or sale), it is relatively straightforward to calculate return on any dimension. A well designed and enforced taxonomy is critical, of course.

Concretely, say we wanted to calculate ROI for the Social-Video channel. We would sum the incremental contribution (in dollars of revenue or profit) of Social-Video across the timeframe of interest, and then crosswalk back to the promotional table for each of the attributed Social-Video part-worths to understand working dollar spend that drove these part-worths. At this point, ROI can be attained by dividing contribution by spend. These calculations can be scaled across the entire dimensionality of stimulus and response—including channel, campaign, product line, content, and basically any other relevant cross-section or categorical variable.

Can UMM simulate budget reallocation scenarios or forecast outcomes?

UMM can provide scenario functionality just like a traditional MMM, leveraging the econometric (MMM) layer of the solution. This includes optimizing budgets for a given objective function and a set of constraints. Forecasting functionality is best handled with the record-level layer. Because each touch has a probabilistic impact and a time component, it is possible to build future forecasts as a “layer cake” of each likely conversion, by day, based on marketing plans.

Why Marketbridge for UMM

Recognized as a notable vendor in Forrester’s “Marketing Measurement and Optimization Services Landscape, Q3 2025,” marketers choose Marketbridge because we deliver transparent, custom-built measurement solutions that solve for complex channels, brand effects, and speed-to-insight—built inside their own environment.

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Fresh and new thinking from our experienced team of marketing strategists, data scientists, and statisticians on trends, methods, and industry use cases in Go-to-Market.

CMO’s guide to needs-based marketing

CMO’s guide to needs-based marketing

Why product-first strategies fall short and how needs-based marketing delivers relevance and results 

Marketers are under pressure to create more relevant, personalized experiences. Too often, the focus begins with the product instead of the buyer. Needs-based marketing offers a smarter approach by prioritizing customer needs, supported by AI, and activated through automation. This guide uncovers evolving motivations and helps align strategy and content with intent, ultimately creating more relevant journeys that lead buyers to the right solution at the right time. 

 

Download the guide to learn how to: 

  • Anticipate and uncover real customer needs beyond demographics and personas
  • Leverage AI and automation to detect needs earlier and scale more flexible, and personalized journeys
  • Introduce product messaging at the right time,not every time
  • Build internal alignment for a needs-first approach across teams
  • Deliver content aligned to evolving motivations and behaviors

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Peer insights webinar: Navigating Medicare and Medicaid marketing, sales, & retention in a dynamic environment

Peer insights webinar: Navigating Medicare and Medicaid marketing, sales, & retention in a dynamic environment

Hear how leading organizations are adapting their strategies in the face of rising costs and shifting consumer behavior

Access the recording of our recent Peer Insights Webinar, hosted live on July 8, 2025, to uncover:

  • The impact of policy and congressional budgeting on dually eligible and Medicaid members
  • The Medicare demographic tipping point
  • Low trust and its implications on mix and messaging decisions
  • The marginal CAC / marginal CLV tradeoffs being made by carriers and brokers

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5 B2B marketing trends you need to know in 2025

5 B2B marketing trends you need to know in 2025

From seismic shifts in B2B purchase behavior to the rise of GenAI, we’re in a time of massive change, for B2B buyers and marketing leaders alike. Those looking to win simply can’t afford to stand still.

Our expert agency team has their eye on the biggest trends shaping the future of B2B, and they’ve been taking notes. Explore our latest guide—no form required—for five key trends every B2B leader should know, plus actionable tips to stay ahead.

With trends ranging from GenAI to creative design to influencers in B2B, this will help you stay ahead for the rest of 2025. 

2025 marketing strategy benchmarks

2025 marketing strategy benchmarks

2025 marketing strategy benchmarks

High-performing marketing teams build smarter strategies from the start

What separates leading marketing teams from the rest? It’s not just bigger budgets—it’s sharper thinking, deeper audience insights, and more disciplined planning. This report uncovers the mindset, strategies, and investments that drive marketing success, based on our annual survey of marketing leaders across industries. Designed for CMOs and senior marketers, the marketing strategy benchmarks offers a data-backed roadmap to build stronger, more scalable go-to-market strategies in 2025.

This report covers

  • What high-performing marketing teams do differently
  • How they plan, prioritize, and operate for impact
  • Where they focus across the funnel—and what’s underutilized
  • How they allocate budget and adopt new technologies like AI
  • Clear next steps to help your team keep up—and catch up

Insights for more effective marketing strategies

Whether you’re building next year’s marketing plan or realigning in-flight efforts, this report offers clear, actionable guidance to move from reactive to revenue-driving.

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The state of healthcare digital CX

The state of healthcare digital CX

How consumer expectations are reshaping payer and provider go-to-market strategies

Digital expectations, rapid technological advancements, and changing regulations are reshaping how consumers buy health insurance and access healthcare. Today’s consumers demand seamless, personalized, and digitally integrated experiences, driving payers and providers to evolve or risk falling further behind.

We surveyed 1,000+ privately insured individuals (across ACA, Group, and Medicare Advantage plans) to uncover key CX trends across three areas:

  • Purchasing health insurance 
  • Accessing healthcare services
  • Engaging in health and wellness activities

Within each area, we highlight survey findings, strategic implications and provide actionable insights to help payers and providers refine their CX strategies and boost engagement in today’s increasingly digital and consumer-driven market.

Select insights from the report:

  • Digital enrollment must boost member confidence: Consumers who work with agents report about 23% higher enrollment satisfaction compared to those who enroll without an agent.
  • Pharmacy BOPIS usage is 22% across segments: Group members use ‘buy online purchase in-store’ the most at 26%.
  • Health insurers trail other insurers in using email to communicate with members: 58% of consumers with homeowners’ insurance said email was a top communication channel from their insurer vs. 49% for those with medical health insurance.

Unlock key insights for CX success

Download “The state of healthcare digital CX” report to explore how consumer expectations are reshaping payer and provider go-to-market strategies and discover how to navigate today’s rapidly evolving CX landscape.

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2025 B2B sales benchmarks

2025 B2B sales benchmarks

High-growth sales teams don’t just execute better—they think differently

What drives B2B SaaS sales teams to outpace their peers and achieve 20%+ YoY revenue growth? They’re not just working harder—they’re approaching sales with smarter strategies and tighter alignment. This first edition of our annual survey uncovers the mindset, tactics, and structures that set these high-growth leaders apart. Designed for sales leaders and CROs, it provides a clear roadmap to evaluate and activate growth opportunities with precision.

This report covers

  • Key differences between sales team archetypes: Steady Builders, Market Contenders, and Growth Leaders
  • Essential attributes of high-performing sales organizations
  • Building blocks to advance to the next level of growth
  • Five priority actions for sales leaders heading into 2025

Select insights

  • 33% of high-growth companies set targets based on opportunity potential rather than existing revenue.
  • Growth leaders employ documented, long-term growth plans and segment-specific strategies while aligning closely with marketing teams
  • Leading sales teams operate with an average of three customer segments compared to two or fewer for lower performers.
  • Industry-specific targeting and account ownership strategies drive greater efficiency, with single account ownership boosting ACVs by 40% compared to hunter-farmer models.
  • Growth leaders align sales compensation with strategy, ensuring motivation and clarity of focus.

Whether you’re looking to optimize sales operations, align your team with strategic goals, or unlock the next level of performance, this report offers the clarity and direction needed to succeed in an increasingly competitive B2B SaaS landscape.

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The impact of AI on go-to-market strategies, programs, and investments

The impact of AI on go-to-market strategies, programs, and investments

Research and insights from high tech market leaders

Generative AI (GenAI) is beginning to revolutionize sales and marketing by enabling highly personalized customer interactions, automating complex processes, and providing deep data-driven insights. To explore this further, we surveyed high tech market leaders. The resulting insights can help inform the future of marketing and sales motions—and where to place investments to deliver more effective and efficient Go-to-Market (GTM) strategies—in the age of AI.

This report covers

  • Top areas of expected AI disruption
  • Timeframe for adapting new GTM models
  • Most promising areas for GTM disruption
  • Reimagining jobs to be done within marketing, sales, and strategy
  • Key inputs needed to optimize GTM performance in the AI era
  • Delivering on the promise—top areas of investment needed

Select insights

  • 60% of respondents believe changing “Competitive Landscape” is the top area of expected disruption.
  • Over 54% of respondents recognize the urgency to explore new growth opportunities and fund these initiatives more swiftly due to the rapid pace of AI innovation.
  • 58% of respondents predict the most significant change in selecting channels and routes to market.
  • While all leaders recognized the need for substantial investment requirements, not all agreed on where.

Whether you’re navigating the impact of AI on customer personalization, content development, or strategic agility, this report provides the insights needed to stay ahead of the curve.

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Build a more effective and durable revenue engine through customer success

Build a more effective and durable revenue engine through customer success

Transform your customer success function into a powerful engine of growth

Customer Success (CS) has evolved from a reactive customer service role into a strategic imperative for B2B organizations. This marks a fundamental shift towards proactive engagement, focusing on developing enduring partnerships and driving mutual success.

That’s why we’ve developed an actionable approach to transform CS functions from cost centers into powerful engines of growth. By deeply integrating CS with strategic business objectives, companies enhance customer satisfaction and retention—as well as unlock new revenue opportunities through upselling, cross-selling, and strong customer advocacy.

Download the framework for all the details on transforming your CS function and get our checklist of six to-dos.

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