We just got back from Google Marketing Live 2026, and we’re not going to bury the lede: this was one of the most significant GMLs in years. Google didn’t just announce new features — they announced a fundamentally different vision for how people search, shop, and how brands reach them.

The good news? If you’re working with the right partners and the right tools, this is an enormous opportunity. Here’s everything you need to know.

The Big Shift: AI Doesn’t Just Answer Anymore, It Acts

Google’s Gemini AI has crossed a major threshold. It’s no longer just a chatbot that answers questions. It’s an agent. Something that can browse, decide, and take action on your behalf.

Google called it “decades worth of innovation in one year,” and after sitting through the announcements, we believe them. The era of AI as a novelty is over. This is AI as infrastructure.

1. Google Search Is Now AI Search, and It’s Massive

Here’s a number that stopped us in our tracks: AI Mode in Google Search now has over 1 billion monthly users. That’s not a beta. That’s the main product.

People aren’t just using it more; they’re using it differently. They’re searching earlier in the buying journey, asking big brainstorm-phase questions instead of just bottom-funnel queries. And 75% of people make faster decisions when they start with AI Mode or AI Overviews.

What this means for you:

Your customers are arriving at decisions faster, and they’re doing it through AI-powered search. That means your brand needs to show up in AI answers, not just traditional search results. Google’s advice (and ours): lead with what makes your brand genuinely different, invest in real reviews and original content, and think beyond text-only formats.

One more thing that often gets overlooked: your product feed is your foundation. If Gemini is going to surface your products in AI-powered results, it needs clean, accurate, easy-to-read data to work with. A messy or incomplete feed means missed opportunities no matter how good your campaigns are. Get that right first.

For ads, AI Max is the tool built for this new search reality. It helps your campaigns show up for those long, complex, conversational queries that are now driving huge volume, and it’s showing 27% more conversions than manual campaigns with a $6 ROAS on Search. If you haven’t tested it yet, now is the time.

2. Google Wants to Be Where You Shop, Not Just Where You Search

Google announced Universal Commerce Protocol (UCP): a way for retailers, restaurants, and travel brands to plug directly into a shopping layer that spans Google Search, Maps, and YouTube. We’re talking about booking a hotel inside AI Mode, ordering food directly from Google Maps, or adding a product to your cart while watching a YouTube video.

A Universal Cart powered by Google Pay ties it all together. One checkout experience, across the entire Google ecosystem.

Why this matters: Google is making a very direct play to own the purchase moment, a territory Amazon has dominated for years. For brands, the upside is real: fewer steps between discovery and purchase means more completed transactions. But it requires setup. Retailers will need to connect to UCP. Early movers will have a clear advantage.

3. YouTube Is a Performance Powerhouse (and the Numbers Prove It)

We know some of you still think of YouTube as a brand awareness channel. After GML 2026, that framing needs to go.

The data Google shared was striking:

• 2x higher ROAS on YouTube vs. benchmark
• 86% higher long-term ROAS compared to social platforms
• Google is used in 89% of purchase journeys before social
• And, big news, The Oscars are coming to YouTube in 2029, signaling where premium content is heading

Demand Gen campaigns are maturing fast as YouTube’s performance driver, with new capabilities including placements on Google Maps, creator asset integration, and Gemini-powered audience targeting.

One measurement update worth highlighting: Engaged View Conversions are now a primary metric; these are users who chose to watch at least 5 seconds of a skippable ad. Google is also working to bring YouTube data into third-party attribution tools, which means you’ll finally be able to see YouTube’s true contribution in your existing measurement stack.

The bottom line: If your current campaigns don’t have a YouTube performance component, you’re competing with one hand tied behind your back.

4. Creating Great Ads Just Got a Whole Lot Easier

One of the most exciting developments for day-to-day marketing teams: Asset Studio is now a full AI-powered creative suite inside Google Ads, built on Gemini and Veo (Google’s video generation model). You can paste a URL to generate image assets instantly, create videos directly in the platform, and run one-click A/B tests without needing a data science team to set them up.

But the real game-changer showcased for scaling creative velocity is Google Pomelli.

What is Google Pomelli? It is a Google Labs tool that analyzes your website to build a unique “Business DNA” profile, locking in your exact brand colors, tone, and visual style.

With Pomelli’s Photoshoot feature, marketers and e-commerce brands can turn a simple smartphone photo into a studio-quality lifestyle image that perfectly respects your brand guidelines. It can spit out 10 to 15 on-brand cross-platform ad variations in under 60 seconds, and lets you iterate using natural language (e.g., “make the background darker”).

Why we’re excited about this: Creative drives roughly half of all incremental ad sales. The brands that can test, iterate, and deploy hypotheses fastest will win. And tools like Asset Studio and Pomelli level the playing field for teams of any size.

5. Data Is the Difference-Maker, and a Solid Foundation is Non-Negotiable

Google didn’t sugarcoat this one: “If you aren’t connecting your data, you’re falling behind.”

As AI models shift from basic automation to running your entire marketing ecosystem, your data foundation is absolutely essential. AI is a force multiplier, but it can only scale the quality of what you feed it. If your first-party data is fragmented, siloed, or poorly integrated, your AI campaigns will optimize for the wrong outcomes.

Google introduced robust tools to help solve this, including the Data Manager API and Google Tag Gateway to create a unified customer picture across channels. Brands connecting their first-party data are seeing an 11% increase in incremental ROAS, a number that will only grow as third-party cookies completely vanish.

At Making Science, we excel at turning messy data environments into robust, privacy-first data infrastructures. Whether it’s deploying server-side tagging (sGTM), maximizing first-party data loops, or setting up advanced predictive value-based bidding, we ensure your business has the structural architecture required to feed Google’s advanced AI engine.

A few other measurement highlights we’re ready to deploy for clients:

• Meridian in Google Analytics: Bringing cross-channel MMM (including TikTok, Pinterest, and Snap) into one place.
• Qualified Future Conversions: A metric that finally proves the long-term value of upper-funnel investments.
• Causal attribution for branded search: Now live in Google Ads and GMP.

The infrastructure is there; the question is whether your business is properly connected to it. We don’t just connect it; we optimize it.

6. AI Is Coming to Your Campaign Workflow Too

It’s not just consumers getting AI agents; marketers are getting them too.

AI Brief lets you submit a creative brief in plain conversational language, and Gemini turns it into structured campaign direction. Teams using it early are seeing 15% more conversions at the same cost.

And Ask Advisor is emerging as an AI-powered campaign management interface. The beginning of a future where you optimize campaigns through conversation, not just dashboards.

Our Honest Take

Google Marketing Live 2026 felt different from previous years. Not because the announcements were flashier, but because so many of them are ready now, not coming soon. AI Max, Asset Studio, Pomelli, UCP, Meridian, Demand Gen on Maps, these are things you can act on today.

The brands that will win in this environment are the ones who move. Not perfectly, just forward. Test AI Max. Build a pristine first-party data foundation. Put real budget behind YouTube performance. Start experimenting with creative tools.

Google said it themselves: the only way to win with AI is with AI. We couldn’t agree more, and we’d love to help you figure out exactly where to start.

Want to talk through what any of these announcements mean for your business or audit your current data foundation? Get in touch with the Making Science team; we’d love to dig in with you.

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For years, managing US privacy has been a compliance obstacle course. With California, Virginia, and Colorado each setting its own rules, brands have had to treat every state border like a regulatory speed bump. The recently unveiled Secure Data Act aims to finally smooth out that road. As a Google Marketing Platform (GMP) reseller, we’re keeping a close eye on this because it represents the biggest shift in US data policy to date.

Here is our perspective on what this means for the industry and how you can start preparing today.

One Rule to Rule Them All

For years, California’s CCPA/CPRA served as the de facto national standard simply because it was the most stringent. However, managing a “patchwork” of varying state definitions for “sensitive data” or “biometric info” has created massive operational overhead for brands.

The Secure Data Act proposes a federal preemption, meaning it would replace the confusing web of state laws with a single national standard. For AdTech, this is a win for clarity. It allows brands to build one unified data strategy rather than managing 50 different legal permutations.

Secure Data Act vs. GDPR: The Key Differences

While the Secure Data Act is often compared to Europe’s GDPR, the US approach remains distinct:

• Opt-out vs. Opt-in: While GDPR is built on the foundation of “explicit consent” (opt-in) for almost everything, the US framework generally leans toward a robust “opt-out” model for most data processing, with stricter opt-in requirements reserved specifically for sensitive data.
• Private Right of Action: Unlike some versions of the GDPR, the Secure Data Act seeks to limit “frivolous” lawsuits by narrowing the scope of when individuals can sue companies directly, favoring enforcement through the FTC and State Attorneys General.

Notable Carveouts

It is important to note that even a “national” law has exceptions. The Act includes specific carveouts for small businesses to ensure the compliance burden doesn’t stifle innovation. Additionally, certain types of data already covered by legacy federal laws (like HIPAA for healthcare or GLBA for finance) will likely remain governed by those existing frameworks.

How to Prepare: Start Your 2-Year Countdown Now

The Act provides a two-year “grace period” after passage before enforcement begins. While that sounds like a long time, the infrastructure changes required for compliance are significant.

The Secure Data Act explicitly mentions data minimization—the idea that you should only collect what you actually need for a specific purpose.

• Performing a data Audit can identify if you’re collecting data “just in case” but never using it. If so, you are carrying unnecessary legal risk. In the new federal landscape, lean data is safe data.

If you want to mitigate impact and ensure a smooth transition, here are three additional steps you should take today:

1. Evolve Your Consent Management Platform (CMP)

Standard “Accept All” banners won’t cut it anymore. You need a CMP that supports more granular control. The Secure Data Act emphasizes transparency; your CMP should be configured to handle specific opt-ins and opt-outs for different categories of data processing, ensuring that user intent is passed accurately to your marketing tags.

2. Move to Server-Side Google Tag Manager (sGTM)

This is perhaps the most critical technical shift. By moving your tagging from the “client-side” (the user’s browser) to the “server-side,” you regain control.

• Security: You decide exactly what data is sent to third-party vendors.
• Privacy: You can redact personally identifiable information (PII) before it ever leaves your server environment.

3. Implement Google Tag Gateway

To future-proof your measurement, you need to shift toward a first-party context. Google Tag Gateway allows you to route your data through your own domain. This minimizes the reliance on third-party cookies and ensures that your data collection remains resilient even as browsers and federal laws become more restrictive.

Read our blog post, “Maximizing First-Party Data: How GTG and sGTM Build a Stronger Data Foundation.”

The Bottom Line

The Secure Data Act is an opportunity to simplify. By moving away from a patchwork of state rules and toward a unified federal standard, brands can focus less on legal second-guessing and more on building trust-based relationships with their customers.

Is your measurement stack ready for federal privacy? Reach out to us to learn how we can help you audit your current GMP setup and prepare for the road ahead.

Disclaimer: This is not legal advice. The legislation is yet to be finalized. Please contact your Making Science Account Manager for more information.

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Have you ever felt like your marketing tools speak different languages? It’s common to see discrepancies between platforms, but the reality is that CM360 and GA4 are not designed to compete—they’re meant to complement each other.

In this post, you’ll discover how Campaign Manager 360 and Google Analytics 4 work together to provide a 360º view of your campaigns, and why stopping the comparison is the first step toward success.

The measurement dilemma: Why don’t the numbers match?

To understand this relationship, we need to accept one premise: CM360 and GA4 measure differently because they serve different purposes.

While Campaign Manager 360 focuses on ad exposure (impressions and clicks from paid media), Google Analytics 4 focuses on user behavior within your digital properties.

Trying to force both platforms to show the same numbers leads nowhere. The real value lies in combining their attribution.

1. Attribution vs. Session: Speaking different languages

The key difference lies in their models:

• CM360 uses an ad-centric methodology (view-through and click attribution)
• GA4 is based on events and sessions

CM360 tells you how many users saw an ad and later converted—even without clicking.
GA4 tracks interactions once users land on your site, prioritizing the traffic source that initiated the session.

Understanding this distinction is crucial to avoid undervaluing Display and Video campaigns.

2. The benefits of native integration

By connecting CM360 with GA4, you unlock powerful analysis capabilities:

• Conversion export: View GA4 events directly in CM360 to optimize bidding
• Path analysis: Understand how CM360 ads influence the customer journey
• Shared audiences: Build segments in GA4 and activate them in CM360 campaigns

3. Data quality: The importance of Floodlights

For this setup to work, technical implementation must be solid.

CM360 Floodlights and GA4 events need to be properly configured. This helps eliminate duplication and identify which touchpoints are truly incremental versus merely assistive.

Conclusion: A team, not a rivalry

CM360 and GA4 are not competitors—they’re teammates.

One drives traffic and measures ad impact.
The other analyzes what users do once they arrive.

If you only look at one, you’re seeing just half the story.

Mastering both allows you to make better decisions, optimize investment, and fully understand your performance.

Have you ever felt like your data speaks different languages? In today’s ecosystem—where privacy rules and information sources continue to multiply—having scattered data is like trying to pilot a plane blindfolded.

Data Manager 360 arrives precisely to turn the lights on in the cockpit. This new feature (currently in Alpha) within Campaign Manager 360 (CM360) enables marketing teams to connect, organize, and activate their first-party data seamlessly—without extreme technical complexity.

Why now? Because efficiency is no longer optional; it’s a strategic necessity for any advertiser seeking true personalization in 2026.

What Exactly Is Data Manager 360?

In short, it’s the ultimate bridge between your data warehouses and your advertising activation. Data Manager 360 simplifies signal ingestion from CRMs, data clouds (such as BigQuery), or measurement platforms, centralizing everything into a single hub within the Google Marketing Platform suite.

Key insight: It’s not just about moving data—it’s about making it actionable. This tool eliminates silos between IT and Marketing teams, allowing information to flow into your CM360 campaigns almost in real time.

Strategic Benefits: From Theory to Conversion

Implementing Data Manager 360 in your digital marketing strategy delivers three immediate competitive advantages:

• Simplified activation: Forget complex manual setups. Connect your audiences directly to your line items.
• 360° customer view: By unifying signals, you gain a deeper understanding of the customer journey, enabling far more precise attribution.
• Future-ready in a cookieless world: By strengthening your first-party data strategy, your marketing becomes more resilient to regulatory and technical market changes.

The Alpha Version: Your Opportunity to Stay Ahead

As technology experts, we at Making Science know that testing tools in their early stages makes all the difference. The Alpha version of Data Manager in CM360 allows early adopters to test audience integration and offline conversion measurement with unprecedented agility.

If your team already uses CM360, integrating this data connector is the logical next step to optimize bidding strategies and improve creative performance.

Conclusion: Data Is King, but Management Is the Kingdom

In short, Data Manager 360 isn’t just an “update”—it’s the engine that transforms your data from static numbers into intelligent media buying decisions. We’ve moved from asking “What happened?” to being able to dictate “What do we want to happen?”

My advice: Don’t wait for your competitors to standardize it. The ability to react quickly with clean, connected data is what separates leading brands from the rest.

Would you like to explore the potential of Data Manager in your CM360 campaigns? Leave us a comment or contact our team of experts to help you lead this transition toward data-driven marketing.

Remember: in the world of marketing, whoever has the data has the map—but whoever has the Data Manager has the GPS! 🚗💨

For a long time, Search Engine Advertising (SEA) performance was measured primarily through acquisition KPIs: CPC, CTR, and impressions. While these metrics remain essential, they now tell an incomplete story. In a landscape where media costs are rising and competition is intensifying, simply generating traffic is no longer a competitive advantage in itself.

The real question is no longer just how many users arrive at a site, but what they do once they get there. This is precisely where many SEA strategies lose their effectiveness. At Making Science, we see daily that a campaign’s success doesn’t end with the bid—it extends into the relevance of the destination experience.

The Post-Click Experience: The Conversion Challenge

Users coming from paid campaigns are not “neutral” visitors. They arrive with high intent and specific expectations shaped by a keyword, an ad, or a particular promise. In theory, these are “qualified” profiles with high conversion potential. However, in most cases, these users encounter an experience that fails to meet their expectations: generic landing pages, cluttered Product Detail Pages (PDPs), unclear messaging, or a lack of trust signals. These points of friction may seem minor individually, but collectively, they significantly stifle performance.

When these users leave a site without converting, the problem isn’t the targeting or the relevance of the ads. The budget has already been spent. What’s missing is a cohesive post-click experience. At this stage, performance optimization is no longer about acquisition; it’s about the site’s ability to transform intent into action. This is where Conversion Rate Optimization (CRO) becomes a strategic lever for SEA.

CRO: Maximizing the Value of Your Paid Traffic

Contrary to popular belief, CRO isn’t just “cosmetic” work intended to “improve UX.” In the context of paid acquisition, its role is far more critical: it maximizes the value of the traffic you’ve already purchased. Our integrated approach at Making Science breaks down traditional silos to transform every dollar invested into tangible results.

Optimizing an SEA landing page isn’t just about making it look better. It’s about ensuring the primary message echoes the ad, the value proposition is immediately clear, trust elements address user doubts, and the path to conversion is seamless and obvious.

An “Insight and Data-Driven” Approach

On pages with high exposure via Google Shopping, such as PDPs, every point of friction can impact global performance. CRO allows us to identify these roadblocks, prioritize them, and test them structurally. It replaces guesswork with insight and data-driven decisions. This analytical rigor, combined with our proprietary tools and technological expertise, allows Making Science to raise profitability standards for our partners.

Merging SEA and CRO: A Unified Performance System

In this framework, CRO doesn’t seek to generate more traffic; it seeks to extract more value from every click. This requires a shift in perspective. SEA and CRO should no longer be managed as two distinct silos, but as two components of a single performance system. SEA creates the opportunity by driving qualified traffic, and CRO reveals its value.

SEA teams hold valuable insights: they know which pages receive the most investment and which campaigns drive the highest quality traffic. Meanwhile, CRO teams understand how users interact with those pages, where they hesitate, and what stops them from moving forward. By converging these two worlds, Making Science does more than just manage campaigns—we orchestrate a global growth strategy where media data fuels the user experience, and vice versa.

Ready to turn your clicks into customers? Stop letting your media investment evaporate after the click. Our SEA and CRO experts work hand-in-hand to audit your user journey and maximize your ROI.

As traditional tracking signals disappear, first-party data has become the new foundation of our digital strategy. Privacy regulations continue to tighten, and browsers like Safari (via ITP) are even more aggressive about consumer privacy, making first-party data essential.

At Making Science, we believe a true, end-to-end first-party setup is only achieved when two specific solutions are paired: Google Tag Gateway (GTG) and Server-Side Google Tag Manager (sGTM). While they are often discussed interchangeably, they solve two distinct parts of the data request flow. In the sections below, I will break down the differences, benefits, and ultimately what is achieved when both solutions are paired together.

Understanding the Data Flow: GTG vs. sGTM

To understand why you need both, you have to look at the flow of data from a user’s click to the marketing platform destination.

• Google Tag Gateway (The Initial Handshake): GTG addresses the request from the user’s browser to the GTM container. By loading your scripts via a subdomain you own, you move the tagging technology into a first-party context.
• sGTM (The Command Center): sGTM addresses the subsequent request from your tagging environment to final destinations (like GA4, Meta, or Google Ads). You host the data router, giving you full control over how data is processed, enriched, and anonymized before it leaves your server.

Comparison: Why One Isn’t Enough

While GTG provides a quicker, more resilient connection to Google’s ecosystem, it lacks the transformation power of a full server-side implementation.

Deep Dive: The Making Science POV

It is our stance that a true, end-to-end first-party setup is only achieved when these two solutions are paired.

• Google Tag Gateway handles the “Front-End”: It ensures the initial request from the user’s browser is loaded on an owned subdomain.
• sGTM handles the “Back-End”: It acts as your private data router, ensuring that once the data is collected, you, not the vendor, decide exactly what gets sent and where.

When combined, you aren’t just “fixing” your tracking; you are building a durable, future-proof Privacy-First Data Foundation. This unified architecture provides powerful, compounding benefits:

• Bypassing Signal Loss: Reduces the impact of ad blockers and ITP by masking the data flow within a first-party context.
• Future-Proofing: Shields your measurement strategy from the inevitable removal of third-party cookies.
• Compliance & Control: Centralizes data governance, allowing you to redact or anonymize sensitive info before it ever touches a third-party server.

Data is only as valuable as the foundation it sits on. Using GTG or sGTM in isolation is a step in the right direction, but pairing them creates a closed-loop, first-party ecosystem. This doesn’t just improve your marketing ROI, it protects your most valuable asset: your relationship with your users.

To discuss how this unified architecture can be implemented for your specific needs, please reach out to our team.

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Does today’s measurement ecosystem feel like a puzzle that’s always missing a piece? If you’re a marketing professional, you know that transitioning to more privacy-focused and efficient measurement can feel overwhelming. That’s where Google Tag Gateway comes in—a feature positioned as the ideal “middle ground” for those seeking greater control without the complexity of a full server-side infrastructure.

What Is It and Why Should It Matter to You Today?

Google Tag Gateway is a technical solution designed to act as an intermediary between your website and Google’s servers. Essentially, it centralizes and simplifies the delivery of marketing data without requiring you to implement a full Server-Side Tagging (sGTM) architecture from day one.

Imagine trying to cross a fast-moving river (the end of third-party cookies and increasing browser restrictions). Server-side tagging is the other shore—solid and secure—but building that bridge takes time and resources. The Gateway is the stable walkway that lets you move forward safely, improving website performance and data quality here and now.

The “Younger Sibling” of Server-Side

You don’t always need to go from 0 to 100 overnight. Implementing this method provides immediate benefits that can solve more than one headache for both IT and Marketing teams:

• Reduced browser load: By centralizing requests, you decrease script execution on the client side, helping improve your Core Web Vitals.

• Sensitive data control: It acts as an additional layer to filter or anonymize information before it’s sent to Google, supporting GDPR and privacy compliance efforts.

• First step toward Server-Side: It technically prepares you for a full server-side transition using a simplified cloud configuration—without the heavy deployment required by a traditional server container.

How to Implement This Solution in Your Strategy

To leverage Google Tag Gateway, the process is more strategic than purely technical. It involves configuring your Google Tag (gtag.js) to point to your own subdomain.

This allows cookies to operate within a true first-party context, increasing identifier durability against browser restrictions like Safari’s ITP or Firefox’s tracking prevention policies.

If your goal is to improve campaign attribution, this is the most direct way to prevent your conversions from disappearing into the “signal loss limbo.”

Conclusion: Don’t Wait for the “Perfect Moment”

In short, Google Tag Gateway is the tactical tool every marketer needs to stabilize measurement while the cookieless environment continues to evolve. It offers speed, control, and a solid foundation for the future.

At Making Science, we believe measurement is not a destination—it’s a continuous optimization journey. My professional advice is clear: if you’re not yet ready for the investment or complexity of a full server-side setup, don’t stand still. This “halfway point” is, in reality, a major step forward.

Are you concerned about data loss in your campaigns? Don’t let your measurement strategy fall behind.

Would you like us to help you make the definitive leap to Server-Side implementation? Leave a comment or get in touch—and let’s talk about how to safeguard your data.

Remember: in the world of data, if you’re not running… you’re flying (or at least not losing track).

Do you feel like your company is sitting on a goldmine of data but doesn’t have the right shovel to dig it up? In a digital ecosystem where privacy rules, AI-Driven Marketing has stopped being a future option and has become today’s survival engine.

It’s no longer enough to collect data; the real challenge is activating it in real time. In this post, we’ll explain what this trend is, why it’s critical for your ROI, how to implement it through predictive models, and who is leading the change. Get ready to discover how artificial intelligence can predict your customer’s next move before they even know it themselves.

What Exactly Is AI-Driven Marketing?

AI-Driven Marketing is the use of machine learning algorithms and artificial intelligence to make automated decisions based on data collection and analysis. Unlike traditional marketing, segmentation is no longer based on “intuition,” but on ultra-precise behavioral patterns.

By integrating AI-Driven Marketing into your tech stack, you enable tools to analyze thousands of variables simultaneously to deliver the right offer to the right user.

From Static Data to Predicting CLV

One of the biggest advantages of adopting an AI-Driven Marketing strategy is the ability to calculate Customer Lifetime Value (CLV) predictively.

• Churn prediction: Identify which users are about to leave your brand.

• Propensity models: Discover who is most likely to purchase a premium product.

• Web personalization: Change your homepage content in real time based on interests detected by AI.

Technical Implementation: The Role of CDP and the Cloud

For AI-Driven Marketing to work, you need a solid infrastructure. It’s not just about “installing AI,” but about connecting your data sources (CRM, website, app) into a Customer Data Platform (CDP) and processing them in the cloud (Google Cloud, Azure).

This architecture allows AI-Driven Marketing to feed your Google Ads or Meta campaigns with much richer conversion signals than a simple “click.”

3 Immediate Competitive Advantages

• Budget optimization: Stop bidding on users with low conversion probability.

• Seamless user experience (UX): Less advertising noise, more relevance.

• Scalability: AI works 24/7 optimizing thousands of micro-segments that a human could never manage.

In short, AI-Driven Marketing is the bridge that connects Big Data with business profitability. The key is not having more data, but using artificial intelligence to make that data work for us—predicting behaviors and personalizing experiences at scale.

At Making Science, we believe the future belongs to brands bold enough to automate with purpose. The question isn’t whether AI will change your marketing, but when you will start leading that change.

Do you want to know if your data structure is ready for AI? Leave us a comment with your questions or contact us for a personalized consulting session. Let’s make your data speak!

As the industry moves away from user-level tracking, capturing and measuring marketing value requires a fundamentally new approach. Signal fragmentation and degradation are the defining challenges, leaving traditional attribution models unable to cope. This has prompted marketing and analytics leaders to transition toward sophisticated predictive methodologies, including Marketing Mix Models and experiments, to maintain a competitive advantage by controlling for incrementality.

Working with clients across the spectrum, we often find a lack of confidence, if not an outright gap in attribution, that prevents marketers from applying insights to budget and channel-level optimizations.

The Strategic Anchor: Google Meridian

Google’s Meridian is a next-generation, open-source Marketing Mix Model (MMM) designed for modern marketers. The model moves beyond the black box of proprietary solutions and offers a transparent ground truth for evaluating marketing across channels.

• Privacy-Durable Modeling: Meridian mitigates the risks of signal loss by leveraging aggregated data, ensuring long-term measurement stability.
• Total-Market View: The methodology can incorporate the impact of both digital and traditional media, providing a macro perspective on how cross-channel investments drive business outcomes.
• Transparency for Stakeholders: As an open-source framework, Meridian allows for rigorous auditing and customization to improve both Analytics and Marketing leadership confidence in the underlying data science.

While Meridian provides a strategic measurement foundation, the challenge remains: how do marketers turn macro insights into performance gains?

The Execution Engine: Closing the MMM Insight-to-Action Loop 

OptiPhi, a Making Science proprietary tool, is a bridge between MMM insights and marketing execution. The offering focuses on transforming open-source MMM (Meridian or others) insights into an “always-on” optimization engine. Built to complement a MMM and augment its utility, OptiPhi ensures that high-level media mix goals are reflected in attribution and can inform campaign optimization.

• Reducing Utility Latency:  Traditional MMM results are often delivered quarterly or annually, making them “post-mortems” rather than real-time activation resources. OptiPhi solves this by ingesting the most up-to-date data available and performing monthly retraining. While some tools claim “real-time” updates, we’ve found a monthly cadence is a strategic sweet spot: frequent enough to capture new market shifts, stable enough to filter out daily statistical noise. The result is near real-time insights that allow marketers to pivot budgets with the agility of digital-first attribution without the volatility of over-optimization.
• Scenario Planning: Post campaign measurement is valuable, but OptiPhi empowers marketers to forecast the impact of different budget allocations. By combining optimization results from historical MMM data with OptiPhi predictive models, teams are able to simulate spend scenarios before a single dollar is committed.
• Holistic Attribution: OptiPhi goes beyond high-level media goals by evaluating how different marketing strategies work together to drive conversions. It calculates the incremental value each strategy adds to the collective results. By identifying which tactics are complementary and which are redundant, OptiPhi provides more granular, actionable conclusions. 

The Value Delivered

In an environment defined by signal fragmentation, the combination of Meridian and Making Science’s OptiPhi solution provides the durability of a world-class MMM, the speed and actionability of attribution and budget planning grounded in the MMM.

Leaders who adopt a unified or “trifecta” approach to modern measurement aren’t just measuring performance; they’re using MMMs, Attribution, and Experimentation to engineer their success.

Ready to transform your macro insights into budget-level performance gains?

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 The days of endless online browsing are over. Welcome to Agentic Commerce, the era where your shopping is done for you, not just by you.

For retailers and brands using the Google Marketing Platform (GMP), this isn’t just a technical upgrade; it’s a fundamental reimagining of how you connect with high-intent shoppers. From autonomous digital assistants that research on a customer’s behalf to protocols that turn a search query into a completed purchase in seconds, 2026 is the year retail gets “agentic”.

What is Agentic Commerce? (And Why Should You Care?)

Think of your favorite, most helpful sales associate. Now, imagine that an associate lives in your customer’s pocket, knows their exact style, budget, and past purchase history, and can scour thousands of listings in milliseconds to find the perfect match.

Agentic commerce is an era where consumers delegate parts of their buying journey, like discovery, comparison, and even payment, to intelligent AI systems.

• Discovery moves from keywords to intent: Shoppers no longer type “red sneakers size 10.” Instead, they tell an agent, “Get me ready for the New York Marathon,” and the agent manages the shoes, the energy gels, and the training plan.
• Zero-click transactions: By the end of 2026, experts predict many consumers may stop visiting brand websites entirely for routine purchases, relying on agents to handle the transaction directly.

The New Open Standard: Universal Commerce Protocol (UCP)

To make this seamless future a reality, Google and industry leaders like Shopify, Target, and Walmart have launched the Universal Commerce Protocol (UCP).

Universal Plug-and-Play for Retail

In the past, every retailer had to build a unique connection for every new shopping app or platform. This created a mess of bespoke integrations. UCP essentially provides a common language for agents, businesses, and payment providers to talk to each other effortlessly.

Native Checkout in AI Mode

Google is adding a “Buy” button directly on surfaces like AI Mode in Search and the Gemini app. Because UCP standardizes the commerce workflow, shoppers can check out from eligible U.S. retailers right as they’re researching, using payment methods and shipping info already saved in Google Wallet. Shopify merchants’ products are also now available for purchase on AI chatbots for checkout, including Chat GPT, Microsoft Copilot, and Gemini.

Retailer Tip: Even with this frictionless flow, the retailer remains the Merchant of Record. You maintain control over your business logic, inventory, and, most importantly, the customer relationship.

Supercharging GMP for Commerce

For advertisers, the “agentic” shift is starting across GMP. The goal is simple: move away from fragmented tactics and toward intelligence-driven systems that make marketing more accountable.

1. Activating Commerce Audiences

DV360 now allows brands to leverage first-party shopper data from Commerce Media Networks (CMNs). This means you can target shoppers based on actual purchase intent rather than just broad demographics.

• Precision Targeting: Access audiences like “Toddler shoppers” or “Laundry detergent buyers” directly within the DV360 UI.
• Unified Reach: These audiences can be activated across 3rd-party exchanges, YouTube, and even Demand Gen campaigns.

2. Measuring What Matters (SKU-Level Insights)

The era of “spray and pray” is over. New measurement betas allow retailers to upload offline and online sales data to track performance at the SKU level.

• Closed-Loop Reporting: Finally, retailers will be able to bridge the gap between a CTV (Connected TV) impression and an actual purchase.
• Incremental Growth: Use real-time visibility to adjust campaigns in the moment rather than waiting for end-of-month reports.

3. Branded “Business Agents”

Retailers can now launch their own Business Agent directly on Search. Think of it as a virtual sales associate that speaks in your brand’s voice.

• Custom Training: Agents will have the ability to be trained on your specific product data and customer insights.
• Direct Offers: While a shopper is chatting with your agent, you can present exclusive Direct Offers to close the sale right when they’re ready to buy.

Strategic Trends to Watch in 2026

To succeed in this new era, your data strategy must evolve as fast as AI. Here are three trends that will define the winners:

Moving from Experimentation to Integration

Innovation in the retail space is exploding rapidly. Retailers went from processing 8.3 trillion tokens on Google’s API in late 2024 to over 90 trillion tokens in 2025. This 11X increase shows that retailers aren’t just thinking about agentic commerce – they are already implementing it.

The most successful brands in 2026 won’t be the ones with the biggest budgets, but the ones with the most unified operational foundations. By connecting your first-party data, media, and commerce through tools like DV360 and protocols like UCP, you ensure your brand is “answer-ready” the moment a consumer’s personal AI goes looking for a recommendation.

To learn more about ensuring your brand is ‘answer-ready’ in this new ecosystem, get in touch with our team of experts.

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