How do you measure the success of a campaign if no one clicks? In the new cookieless era, the answer is not only possible but essential.

Clickless advertising has gone from being a rarity to a priority for brands focused on brand recognition, mass reach, and effectiveness in environments where the click simply doesn’t exist. With the rise of channels like YouTube on Smart TVs, DOOH, digital audio, and CTV, it is time to move beyond models based solely on direct interaction.

In this post, we tell you what clickless advertising is, why it matters in 2025, and how you can measure it effectively with Google Marketing Platform (GMP) to demonstrate real results in campaigns where visual impact is worth more than the click.

What is Clickless Advertising and Why is It Gaining Ground?

Clickless advertising encompasses campaigns where the goal is not for the user to click, but for them to remember, recognize, and interact with the brand later on. This type of impact is generated in environments where direct interaction is not possible (or does not make sense):

• YouTube on Connected TV
• Spotify, podcasts, or programmatic audio
• DOOH (Digital Out Of Home), such as digital billboards or screens in shopping centers
• CTV (Connected TV)

With the progressive phasing out of third-party cookies and the increase in media consumption without a browser, measuring without clicks is no longer an option—it is a necessity.

📊 According to Nielsen, 65% of offline sales are influenced by advertising without direct interaction.

GMP: Your Ally for Measuring What Cannot Be Clicked

The key is to adopt new measurement tools and methods based on aggregated data, modeling, and first-party data. This is where Google Marketing Platform shines as a comprehensive solution:

🎯 Campaign Manager 360: Measuring Impressions and Viewability CM360 allows you to track impressions, viewability, frequency, and cross-channel reach. It is the central hub for validating that your message has reached the right audience.

🧠 Google Analytics 4: Behavior After Exposure Even without clicks, GA4 helps analyze user behavior after viewing an ad: direct traffic, brand searches, completed forms, etc. Thanks to its advanced attribution models, it compensates for the lack of cookies and protects privacy.

🔗 Integrated Platform: GMP as an Ecosystem The combination of CM360 + GA4 + DV360 + SA360 allows for a holistic view of campaign performance, uniting awareness and performance metrics under one umbrella.

Strategies That Work (Even if No One Clicks)

🧪 Brand Lift and Brand Awareness Use studies like YouTube Brand Lift or post-exposure surveys to measure ad recall, consideration, or purchase intent.

🗺️ Geo-testing and Incrementality Compare exposed and unexposed regions with tools like GeoLift to evaluate the real impact on searches or sales.

👤 First-Party Data and Indirect Signals Analyze direct traffic, brand searches, and completed forms after exposure. Supplement with user panels or surveys.

🔒 Consent Mode v2 and Conversion Modeling Even without cookies, you can estimate conversions with modeling and platforms like Ads Data Hub, ensuring compliance with privacy regulations.

Real-Life Cases That Prove It

• YouTube on CTV: Campaigns with a +20% brand recall, without clicks or calls to action.
• Spotify Ads: Direct correlation between full ad listens and peaks in brand searches.
• DOOH in shopping centers: Increase in store visits (footfall) and geolocated sales following campaigns without digital interaction.

Conclusion: Measuring Without Clicks Is Not Only Possible, It Is Essential

In a cookieless world with increasingly dispersed consumers, clickless advertising represents the natural evolution of digital marketing. It is no longer just about chasing interactions, but about understanding the real impact of the message on the user’s mind and decisions.

GMP gives you the tools to do this with precision, respect for privacy, and an omnichannel approach.

💬 And you, are you ready to measure without relying on the click? If you want to know how to implement this type of measurement in your strategy, let’s talk. Because the future of marketing is not measured in clicks, but in connections.

Does Your Hotel Speak the Same Language as Your Guests?

Imagine seeing an ad for a family vacation when all you’re looking for is a romantic getaway. Frustrating, right? Personalization is no longer a ‘nice-to-have’—it’s a critical consumer demand in the digital landscape, and this is where DCO for hotels (Dynamic Creative Optimization) comes into play.

In this article, we’ll walk you through how to simply and effectively phase a DCO strategy within the hospitality environment, leveraging tools like Campaign Manager 360 (CM360) and Google Studio. If you work in hotel marketing and want to boost your campaigns’ relevance (and results), keep reading.

Step 1: Define Your Audience and Identify Key Signals

Before firing up your creative or tech engines, start with the most important element: people.

Ask yourself:

• Who are my priority users?
• What digital signals can I use for segmentation?

Some key variables in the hotel sector include:

• Travel dates
• Type of accommodation sought
• Geographic location
• Originating channel
• Device type

🧭 A business traveler booking a weeknight stay from a mobile device should not receive the same ad as a family browsing on a tablet on a Sunday afternoon.

Pro Tip: Begin with 3-4 well-defined signals and a controlled set of audiences. Less is often more in the initial phase.

Step 2: Build Modular and Scalable Creatives in Studio

The magic of DCO for hotels lies in the ability to construct ads that automatically adapt to the user. To achieve this, you need to structure your messaging into reusable blocks within Google Studio.

Build a simple data feed featuring:

• Destination (city, region, or experience type)
• Room Type (suite, family, standard…)
• Promotional Benefit (discount, free breakfast, flexible cancellation)
• Call to Action (Book Now, Learn More, etc.)

🛠️ This modular approach allows you to mix and match elements without having to create hundreds of distinct creative variations.

Bonus Tip: Utilize templates that work across both display and rich media formats, ensuring they maintain visual brand consistency.

Step 3: Activate the Campaign in Campaign Manager 360

With the creatives finalized, it’s time to configure the campaign in CM360. This is where you connect the tailored messages with the defined audiences and establish the delivery rules.

Basic Checklist:

• Associate each dynamic creative with the appropriate target audience.
• Apply advanced segmentation (by geography, language, device, frequency, etc.).
• Use the dynamic preview to verify that every combination in your feed is displaying correctly.

🔍 Pre-flight review is crucial to prevent unexpected issues at launch.

Step 4: Analyze, Adjust, and Evolve

A DCO campaign is not a “set-it-and-forget-it” launch. On the contrary, it is a living system that improves with every data point it collects.

Key metrics to monitor:

• CTR per creative combination
• Conversions per message type
• Website dwell time
• Cost Per Acquisition (CPA)

Iterate and Optimize:

• Adjust the creative feed based on real-world performance.
• Add or remove modules according to seasonality or current offers.
• A/B test different CTAs and benefits.

📈 What works for romantic getaways today may not be effective for family stays tomorrow.

Conclusion: Personalization That Drives Bookings (and Results)

Phasing your DCO strategy for hotels isn’t complicated if you know where to start. Define your key signals, build a solid modular foundation, connect everything in CM360, and let the data be your guide.

In a competitive market like hospitality, differentiation means speaking to the right user with the perfect message at the precise moment. With the right tools, you can achieve this without an excessive workload.

👉 Ready to start your first hotel DCO pilot? At Making Science, we help you scale personalized campaigns with a data-driven and creative approach. Contact us and discover how to transform your campaigns into memorable brand experiences.

What is MMM and Why Do You Need It Now?

In the fast-paced world of marketing, CMOs face constant pressure to demonstrate the return on investment (ROI) of every campaign. But how do you truly know what’s working and where to invest the next dollar? This is where Marketing Mix Modeling (MMM) comes in. What exactly is MMM? It’s a powerful analytical technique that uses econometric models to quantify the historical impact of all your marketing activities (digital advertising, TV, radio, print, promotions, etc.) on your sales and other key KPIs. Why is it crucial now? Because in a fragmented data landscape with increasing privacy restrictions, MMM offers a holistic, platform-agnostic view, allowing you to make smarter, data-driven budget allocation decisions. At Making Science, we understand that optimizing spend is vital, and MMM is your perfect ally.

The Budget Allocation Challenge

Traditionally, marketing budget allocation has been a complex exercise, often based on intuition or limited data. With the proliferation of channels and the difficulty of tracking the complete customer journey due to privacy regulations, many CMOs struggle to understand the real impact of each investment. Should you invest more in social media or TV? What’s the saturation point for your investment in a specific channel? Without a robust methodology, these questions remain unanswered, leading to suboptimal decisions and ultimately, lower ROI. This is where MMM truly shines.

MMM: The Science Behind Your Marketing Decisions

Marketing Mix Modeling (MMM) goes beyond last-click attribution, analyzing historical marketing data, sales data, external factors (like seasonality or competitor actions), and macroeconomic variables. By using advanced econometric models and statistical techniques, MMM can:

• Quantify Impact: Determine the incremental impact of each marketing channel on your sales.
• Optimize Allocation: Recommend the optimal allocation of your budget across different channels to maximize ROI.
• Predict Performance: Forecast the future performance of your campaigns based on different investment scenarios.
• Understand Interaction: Reveal how different marketing channels interact with each other, identifying synergies and cannibalization effects.

This comprehensive insight offered by MMM allows CMOs to not only understand what worked in the past but also to plan confidently for the future.

Key Benefits of MMM for CMOs

Implementing Marketing Mix Modeling (MMM) offers significant advantages for any CMO looking to improve their budget decision-making:

• Holistic and Aggregated View: Provides a complete understanding of marketing performance at a macro level, without relying on individual user data, making it ideal for the privacy era.
• ROI Optimization: Identifies the most profitable investments and helps reallocate the budget towards channels with the greatest impact.
• Strategic Planning: Allows for simulating different investment scenarios and forecasting their impact on results, facilitating long-term planning.
• Greater Accountability: Offers a solid, data-driven basis for justifying spending decisions to leadership.

With MMM, CMOs can move from guesswork to precision, ensuring every dollar invested works its hardest.

Empower Your Budget with MMM

In short, Marketing Mix Modeling (MMM) is not just an analytical tool; it’s the new secret weapon for CMOs who want to dramatically improve their budget allocation decisions in an increasingly privacy-centric world. It empowers you to understand the true contribution of each of your marketing efforts and optimize your spending for maximum impact.

Are you ready to stop guessing and start making data-backed marketing decisions? Explore how MMM can transform your strategy! Leave a comment or share this post if you believe MMM is the future of marketing budget optimization. Because in marketing, as in life, “what isn’t measured isn’t improved… and what is modeled, is optimized!”

The search scenery is evolving. We’re witnessing a shift from simple keyword matching to complex interpretations of user intent. Thanks to advances in natural language processing and generative AI such as ChatGPT or AI Mode, search engines are no longer just answering queries. They’re starting to engage in conversations with the users.

This evolution is reshaping how people interact with search engines and, as a result, what SEO means today. Instead of focusing only on keyword placement, we must now understand context, nuance, and user expectations. SEO has become less about visibility and rankings and more about relevance within AI-driven answers.

Generative AI in action: generated content, instant answers & brand visibility

Generative AI is revolutionizing the way companies approach content creation. Brands can now produce SEO-friendly content at scale, brainstorm topics quickly, and streamline their editorial processes. AI tools enable marketers to respond faster to trends and user questions.

On the other side, search engines are leveraging AI to provide instant answers directly within the search results without the need for users to click, altering the value of traditional content placement.

Now, the strategic goal is not just ranking, it’s getting your brand cited as a trustworthy source within those AI-generated responses. Visibility in this new environment requires a deep understanding of how AI interprets and works through information.

Does Google penalize AI-generated content?

One of the most common myths today is that Google penalizes content created with AI. This is not true. What Google penalizes is low-quality, unoriginal, or unhelpful content, regardless of how it was produced.

The foundation remains the E-E-A-T principle: experience, expertise, authoritativeness, and trustworthiness. AI can help scale content, but human review and editing are very important to ensure that the output meets quality standards.

We should think of AI as our first draft assistant, not the final editor.

How keyword research is evolving with AI

Traditional keyword research focused on finding exact-match phrases and long-tail variations, but with AI, we can do better. AI tools now can identify emerging trends, related questions, and semantic clusters that reflect how people actually speak and search.

The new approach changes from asking, “Which keyword should I use?” to “How can I completely cover a user’s intent?” By combining AI-driven insights with real search data, marketers can discover opportunities based on actual conversations rather than isolated keywords.

What do we do in Making Science to appear in conversational search

Appearing in traditional featured snippets is one thing, but getting your content referenced in generative AI answers requires a more refined strategy. Here are some best, tested practices we follow to boost your visibility:

• Answer clear, specific questions within the first few paragraphs.
• Use natural, conversational language. Avoid jargon if possible.
• Implement structured data.
• Build topical authority by covering topics from multiple angles (topical clusters).
• Optimize brand-entity associations by consistently linking your brand to specific themes.

The goal is no longer just to “rank #1,” but to be seen as a credible source by AI systems interpreting search queries.

Key takeaways

• AI is transforming every phase of SEO, from research to content, to the search results themselves.
• Content is still the king, but it must be genuinely useful, accurate, and crafted for real human intent.
• Brands that blend AI tools with strategic thinking and human creativity will gain a significant edge in the evolving search landscape.

Have you wondered why giants like Amazon or Carrefour are investing millions in digital advertising? Or why more and more brands are shifting their traditional media budgets to e-commerce platforms? The answer lies in one phrase: Retail Media.

This new channel is revolutionizing how brands impact consumers at the exact moment they’re ready to buy. In this article, we’ll tell you what Retail Media is, why it has become one of the biggest bets for 2025, and how you can leverage it within your programmatic strategy.

What is Retail Media?

In Retail Media, retailers themselves (physical stores or e-commerce) are responsible for selling advertising space on their websites, apps, or even in physical stores. In other words, they become media outlets. Platforms like Amazon, Carrefour, and El Corte Inglés are already doing this.

These ads appear directly in the consumer’s journey, when they are already Browse to buy, which means the conversion intent is very high.

Why is it Growing So Much?

There are several key reasons that explain the boom in Retail Media:

• The disappearance of cookies: Retailers have extremely valuable first-party data, making them an ideal alternative for cookieless strategies.
• High conversion: Ads are closer to the point of purchase than ever before.
• Environment control: The retailer controls the inventory, data, and results, which offers greater transparency.
• Omnichannel trend: Retail Media also includes in-store formats (screens, digital signage) or retargeting outside the retailer’s environment.

Main Retail Media Platforms

Among the most relevant globally, we find:

• Amazon Ads
• Walmart Connect
• Carrefour Links
• Criteo Retail Media

In Europe and Spain, we also see big players like El Corte Inglés, MediaMarkt, and FNAC embracing this model.

What are the Benefits for Brands?

• Greater precision in segmentation thanks to real purchase data.
• More reliable measurement closer to the business result (direct sale).
• Synergies with programmatic or search campaigns.
• Flexibility in formats: display, search, video, audio, in-store, etc.

And for Retailers?

• New revenue source (monetization of digital inventory).
• Greater control over the messages that appear on their properties.
• Opportunity to create a closed and highly optimizable ecosystem.

Furthermore, they can build their own media network, as Carrefour is doing with Carrefour Links.

How to Integrate Retail Media into Your Programmatic Strategy

Retail Media is not an isolated form of advertising. It can and should be integrated within a complete digital strategy:

• Using DSPs like Amazon DSP or Criteo to activate audiences in secure environments.
• Performing omnichannel measurement, connecting online and offline purchase data.
• Coordinating creatives with flexibility, depending on the retailer.
• Applying CDPs and DMPs to cross-reference your own data with the retailer’s.

Retail Media is not a passing fad; it’s a real transformation in how brands, platforms, and consumers interact. In 2025, it will be a key channel in the media mix, especially in a cookieless environment with more demanding results.

Are you ready to take your media strategy to the next level? The time to explore Retail Media is now.

Have you ever wondered what we need to get the most out of CM360’s capabilities? In this post, we are going to tell you, step by step, why the CM360 optimization journey is long but exciting and what benefits you will get when you know the tool well.

Introduction

In a constantly evolving advertising environment, the question is simple: How to leverage CM360 to achieve more effective digital campaigns? This post will serve as a guide to understand where we are, what we have left to cover, and why it is key to your digital marketing strategy.

What is CM360?

Campaign Manager 360 (CM360) is Google’s platform designed to plan, manage, and measure digital campaigns globally.

Who uses it?

Agencies, advertisers, and marketers who seek to centralize their reporting and obtain unified data.

Why is it relevant now?

The evolution of the cookieless environment and new attribution models force us to rethink what to do and when to maintain advertising effectiveness.

How do we achieve it?

By analyzing what technical and strategic improvements to implement in CM360 to gain time, agility, and precision in decision-making.

Key fact: According to recent studies, companies that master CM360 increase their campaign ROI by 15% to 20%. Ready to discover where to start?

What’s happening today with CM360?
Currently, CM360 is the standard for managing large-scale digital campaigns. However, there is still much room to take advantage of it, especially when we talk about:

• Integration with other tools in the Google stack (such as GA4, DV360, Google Ads, The Trade Desk, Netflix, or Adobe Gen Studio).

• Improvements in advanced reporting to better understand the path to conversion.

• Management of floodlights and audiences that respond to new data-driven models.

The key is knowing where to focus.

What do we have left to cover?

Optimization of the initial setup

Dedicating time to a well-defined structure saves headaches later.
→ Did you know that a clear taxonomy in CM360 reduces errors by 30%?

Reporting automation

A well-configured dashboard saves your team hours and gives you real-time insights.
→ Includes reports like Path to Conversion, Time Lag, or Conversion Funnels.

Implementation of cookieless strategies

With the disappearance of cookies, measurement and activation must adapt. This is where CM360 along with GA4 offers you precise data.

(This is just a visual reference of the type of dashboard you can implement)

Why is it important to keep improving in CM360?

If you want your campaigns to be more effective and your strategy to be more agile, continuing to evolve in CM360 is essential. Every small change directly impacts your ROI and, above all, gives you greater control and transparency over your advertising investment.

Think of CM360 as a treasure map: if you know how to read it well, it leads you directly to the data that will help you grow.

Conclusion: Move forward with a steady pace

In short, there is still much to cover in the world of CM360, but every step you take is an opportunity to optimize results, better understand your audience, and make your advertising investment smarter.

Do you want us to help you get the most out of the tool? Share this post with your team or leave us a comment with your questions! As someone wise said: “It’s not just the destination, it’s the journey.” 🚀

I recently had the privilege of engaging with numerous travel industry professionals at Digital Travel Connect. The energy and insights were fantastic, and it’s always valuable to connect with people facing the same challenges and opportunities. My workshop, in particular, sparked some really important conversations, and I walked away with a renewed sense of the direction travel brands need to take.

One of the most persistent issues raised was the challenge of generic bidding. It’s a David vs. Goliath situation out there. Too many travel operators, especially smaller and mid-sized businesses, are consistently outbid by the major Online Travel Agencies (OTAs) for those crucial generic keywords. This dynamic creates a bottleneck, restricting these operators largely to branded search terms and severely limiting their ability to expand their reach and acquire new customers cost-effectively. We must find strategies to level the playing field and empower these brands to compete for valuable generic traffic.  

Closely related to this is the ongoing puzzle of SEO and landing page optimization. Driving direct bookings is the holy grail for travel brands, as it allows them to maximize margins and own the customer relationship. However, achieving this requires a sophisticated approach to SEO and the creation of compelling, high-converting landing pages. Many brands struggle with this, lacking the resources or expertise to consistently produce optimized content that ranks well and drives action. This is a missed opportunity, as users are searching for information, and we need to ensure our clients’ properties appear at the top of the search results.  

These challenges aren’t just abstract concepts; they have a real impact on the bottom line. Travel brands need actionable solutions that enable them to:

• Compete effectively for generic search traffic, breaking free from the constraints of branded search.  
• Optimize their digital presence to capture more direct bookings, increasing profitability and customer ownership.  
• Deliver personalized, relevant digital experiences that meet the evolving expectations of today’s travelers.  

This is where I believe Making Science can make a real difference. Our expert report, “How automated solutions can transform your performance marketing,” directly addresses these pain points. We delve into the power of AI and automation to revolutionize performance marketing strategies, with a particular focus on our ad-machina technology.

Ad-machina automates and personalizes SEM campaigns at scale. This is crucial for tackling both the bidding and the SEO challenges. By generating highly relevant ads tailored to specific search queries, ad-machina helps brands improve their visibility, increase click-through rates, and ultimately drive more conversions. It also enables the creation of personalized landing pages, ensuring a seamless user experience from search to booking.  

I left Digital Travel Connect energized and optimistic. The travel industry is dynamic and resilient, and by embracing innovative solutions, brands can overcome these challenges and achieve sustainable growth. I encourage everyone to explore our expert report; it provides a roadmap for navigating the complexities of digital marketing and unlocking the full potential of your travel brand.

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We all know that connecting with the right customers is paramount. However, in today’s fast-paced marketing environment, not all customers are created equally – nor should be treated as such.

Marketers need precision, and that’s where the power of AI-driven audience segmentation comes into play. At Making Science, our proprietary solution, Clustering, tackles the challenge of maximizing your marketing impact by separating customers and prospects by behavior. 

Clustering dives deep into behavioral, transactional, and contextual signals instead of relying on outdated demographic assumptions . This allows us to identify distinct user groups based on their actual engagement and purchase patterns. While lookalike audiences can be a part of the strategy, Clustering truly shines when it comes to remarketing and re-engaging your existing customer base – the individuals who have already shown interest in your brand.

Let’s imagine a thriving online retailer brand that specializes in sustainable and ethically sourced apparel. They’ve built a loyal customer base, but their broad marketing campaigns sometimes miss the mark, reaching many individuals with little interest in their unique products.

By implementing Clustering, our retail brand can analyze past purchase history, website interactions (like browsing specific product categories or spending time on their sustainability page), and even responses to previous marketing efforts. This data allows Clustering to identify key audience segments within their existing customer base:

• “Eco-Conscious Enthusiasts”: Customers who frequently purchase items from their sustainable collection and actively engage with content related to ethical sourcing.
• “Urban Style Seekers”: Customers who gravitate towards their trendier, city-inspired pieces and often engage with fashion-forward content.
• “Loyal Repeat Buyers”: Customers with a history of multiple purchases across various product lines, indicating strong brand affinity.
• “Just Browsing”: Customers who aren’t ready to purchase.

These audience segments allow for multiple marketing activation activities. For example, instead of sending generic promotions to their entire email list, they can now tailor their messaging. The “Eco-Conscious Enthusiasts” might receive exclusive previews of new sustainable arrivals or invitations to a webinar on ethical fashion. The “Urban Style Seekers” could be targeted with lookbooks featuring the latest trends and styling tips. And the “Loyal Repeat Buyers” might receive personalized thank-you offers or early access to sales events.

For a digital ads campaign, these audience segments can be sent to ad platforms to help with targeting, bidding and even exclusion lists. While bidding algorithms in these tools provide some level of segmentation, Clustering is based on propensity and predictive modeling. The online retailer can also use these segments for audience expansion or to build similar audiences.   

The impact? By focusing their efforts on high-value segments identified by Clustering, our online retail brand can expect to see a significant boost in sales from their existing customers and a considerable reduction in the media cost it takes to achieve each conversion. Our benchmarks show that businesses leveraging similar AI-powered audience segmentation can achieve a 20% incremental sales increase and a 20% reduction in cost per conversion.

Additionally, all the cluster results are transparent. Normally models are black boxes, but in addition to each cluster, the information about the users in that cluster are also provided. This information could be used to inform creative, website landing pages, messaging and more.

So let’s stop wasting marketing budgets on lukewarm leads. Embrace the precision of AI-powered audience segmentation with Making Science and start connecting with the customers who truly matter. Ready to see how Clustering can transform your marketing results? Reach out to our team today to learn more.

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In the era of automated advertising and artificial intelligence, we have more tools than ever to unlock the full potential of our campaigns. A prime example is Meta’s Advantage+ Shopping Campaigns, where AI plays a fundamental role in optimizing results. These campaigns analyze millions of signals to identify users most likely to engage, purchase, or click on an ad, maximizing performance through data-driven insights.

With automation handling campaigns and audience targeting, creativity becomes the primary focus for optimization. Studies show that creativity is a major driver of campaign performance on platforms like Meta, where brands have only milliseconds to capture users’ attention in an increasingly competitive environment. Additionally, the high volume of ad impressions can lead to creative fatigue, significantly impacting campaign results.

This new digital paradigm highlights the importance of audience automation, but above all, positions creativity as a key lever for advertisers. Recognizing this shift, Making Science launched ad-machina for Social, extending its automated creative generation capabilities from Search and Performance Max to Meta. ad-machina leverages AI to enhance Meta campaign management, helping brands maximize their advertising investments.

What can ad-machina offer you?

ad-machina is designed to help advertisers maximize the value of their Meta campaigns through automation and the use of AI. Through the API, the tool allows campaigns to be created, managed and published in record time, giving advertisers a competitive advantage by significantly reducing execution times while ensuring continuous optimization.

What sets ad-machina apart is its ability to connect to the customer’s first-party data. This opens up a range of possibilities to automate campaigns directly aligned with business objectives, using customized rules such as:

• Automation based on sales data: The advertiser can set up rules so that sale ads automatically include the best-selling or high in-stock products. This not only saves time, but also ensures that ads are always aligned with business needs.
• Adaptation to seasonality and local behavior: for global brands, ad-machina can adjust creatives based on seasonality and local preferences. This is especially relevant for industries like fashion, where demand greatly varies depending on location, seasonality and the weather. By connecting weather data, advertisers can show different product categories for each geographic location. 
• Margin optimization: by connecting product margin data, ad-machina can prioritize the promotion of categories, brands or products that offer higher margins, helping to maximize the value of each euro invested in Meta.

The most disruptive aspect of ad-machina is its ability to apply AI to analyze and improve creative. Meta uses creative as a crucial signal in its Advantage+ campaigns, and ad-machina leverages this intelligence to help advertisers discover which elements within their creative drive better campaign performance.

For example, ad-machina can analyze factors such as:

• Whether the people in the images are smiling.
• Whether natural light is used in the photos.
• The visual style of creativity.

These details, often overlooked because they are difficult to analyze, can make all the difference in a campaign’s performance. Once the technology identifies key success factors, it allows AI-enabled creative to be adapted to incorporate these improvements. This ability to generate new creative quickly solves one of the biggest challenges facing Meta advertisers: creative fatigue.

In a dynamic environment like Meta, where ads quickly reach their fatigue point, the ability to refresh creatives frequently is essential to maintain performance. ad-machina simplifies this process, reducing dependence on creative teams to perform constant refreshes, helping Meta’s algorithms find the right audience through signals like CTR (Click-Through Rate). In automated campaigns like Advantage+, where the audience is no longer selected by the advertiser, CTR becomes a crucial signal to guide the algorithms towards users with the highest purchase intent.

This all happens in real time and without human intervention, allowing advertisers to focus on strategy while the tool takes care of the entire execution. 

Making Science: Leader in AI for Creativity

With ad-machina, Making Science positions itself at the forefront of AI-powered creativity. This tool not only enables advertisers to optimize their campaigns on Meta, but also transforms the way they manage their advertising spend, aligning creative with business needs and using AI to maximize performance.

In an era where automation is redefining digital advertising, creativity is the key to success.  ad-machina empowers brands to thrive in this new era, ensuring campaigns remain fresh, engaging, and highly effective.

The digital advertising landscape is currently undergoing a seismic shift. Third-party cookies, long the backbone of targeting and measurement, are declining. The rise of the Privacy Sandbox has many marketers scrambling to find alternative solutions. Online advertisers are testing platforms with Privacy Sandbox APIs, and one stands tall compared to the rest: Google’s Display & Video 360 (DV360). 

Unlike cookie-dependent platforms, DV360 is built with a privacy-first approach. DV360 offers a variety of alternative targeting and measurement solutions that don’t rely on third-party cookies. This makes it a future-proof option for advertisers navigating the evolving privacy regulations. We will go into more detail on DV360’s performance without the use of third-party cookies and how it compares to the market, unlocking the power of conversion modeling in DV360 to maximize your campaigns performance, as well as how to maximize your return on ad spent (ROAS) with DV360 using optimized bidding.

Google Privacy Sandbox: A Testing Ground for DSP’s

This Google article* highlights that Google has been running experiments using Privacy Sandbox APIs for the web on Google Display Ads and DV360. These experiments had three groups: comparing the use of ads with both third-party cookies & Privacy Sandbox APIs, neither third-party cookies nor Sandbox APIs, and one final group with only Sandbox APIs active. These tests provide a true scope of how viable interest-based advertising is without relying on third-party cookies. While the results are still preliminary, they show promise:

DV360 shows an 86% recovery in advertiser spending compared to the market average, which shows a 60% decrease in publisher revenue without third-party cookies.* 

Although these experiments are in the early stages, same as the Sandbox API, we have a baseline answer for how Google’s DV360 will last without third-party cookies. Although just about every advertiser will be taking a hit without third-party cookies, Google has an answer to minimize the damages.

Conversion Modeling Unlocks Hidden Value

In programmatic advertising, traditional attribution models have limitations. They often struggle to capture the full impact of your campaigns, especially for online-to-offline conversions or complex customer journeys. This is where Conversion Modeling with DV360 steps in, unlocking the hidden value in your campaigns.

As explained in a Google support article** Conversion Modeling utilizes machine learning to estimate online conversions that wouldn’t be directly attributable through traditional methods. This could include conversions happening on other devices, offline interactions, or conversions with a significant delay after exposure to your ad.

Here’s how Conversion Modeling in DV360 benefits your campaigns:

• More Accurate Reporting: By attributing credit for conversions that might have been missed previously, Conversion Modeling provides a more complete picture of your campaign performance. This allows you to make data-driven decisions and optimize campaigns for maximum impact.
• Improved Bidding Strategies: With a more comprehensive view of conversion data, DV360’s automated bidding strategies can be optimized. This ensures your bids are directed towards impressions most likely to result in a conversion, even if it takes time or happens offline.
• Greater Campaign Efficiency: By attributing credit more effectively, you can identify campaigns that are driving conversions, even if traditional models wouldn’t show them. This allows you to allocate your budget more efficiently and focus on the most successful channels.

Important Considerations:

Conversion Modeling is a powerful tool, but it’s important to use it strategically. Here are some things to keep in mind:

• Conversion Modeling is an estimate: While it provides valuable insights, it’s still an estimation. Don’t rely solely on modeled data, but use it in conjunction with your existing attribution models.
• Data Quality Matters: The accuracy of your Conversion Modeling results depends on the quality of your data. Ensure you have a clean and complete data set for optimal performance.

By leveraging Conversion Modeling in DV360, you can gain a deeper understanding of your advertising impact and unlock hidden value in your campaigns. This allows for more accurate reporting, improved bidding strategies, and ultimately, a more efficient and impactful advertising experience.

Expand Your Reach with Precision Using Optimized Targeting

Reaching the right audience is paramount to a successful advertising campaign. Traditional targeting methods can be limiting, but Optimized Targeting in DV3060 offers a powerful solution. This innovative approach leverages machine learning to go beyond your initial audience selections and identify new, relevant users with a higher conversion potential. 

According to the Google support article*** Optimized Targeting utilizes two key elements:

Audience Signals: These are your initial targeting selections, such as demographics, interests, and custom audiences. These provide a starting point for DV360 to identify similar users.

Real-Time Data: DV360 analyzes vast amounts of real-time data on user behavior, campaign performance, and marketplace trends. This allows it to discover new audience segments that share characteristics with your initial audience and are more likely to convert.

Optimized Targeting offers several key benefits. It expands your reach beyond initial audience selections, finding new potential customers. By focusing on high-conversion users, it boosts campaign effectiveness and optimizes budget allocation. Additionally, it reduces the need for constant audience refinement, saving time and effort while maintaining performance.

Here are some tips to maximize the effectiveness of Optimized Targeting with DV360:

• Start with Strong Audience Signals: Provide a solid foundation by choosing relevant and well-defined audience segments.
• Utilize Diverse Data Sources: Integrate data from various sources like Google Analytics and CRM systems to enrich your audience profiles.
• Set Conversion Goals: Clearly define your campaign goals to guide DV360’s targeting algorithms.
• Monitor Performance: Regularly monitor campaign performance to assess the effectiveness of your optimized targeting strategy.

By utilizing Optimized Targeting with DV360, you can reach more relevant audiences, increase conversions, and ultimately achieve your marketing goals. Utilize DV360’s intelligent algorithms to do the heavy lifting, while you focus on crafting compelling ad creatives and strategic campaign initiatives.

Google’s DV360 positions itself as a formidable force in the evolving digital advertising landscape. Its emphasis on privacy coupled with robust tools like Conversion Modeling and Optimized Targeting, make it a compelling choice for marketers navigating the cookie-less future. While the industry faces new challenges, DV360’s adaptability and performance in Privacy Sandbox experiments demonstrate its resilience and commitment to delivering results. By harnessing the power of DV360, advertisers can not only weather the storm but thrive in this new era of advertising. As Google Marketing Platform resellers, Making Science can help elevate your display campaigns using the full capabilities that DV360 has to offer. Reach out to us today to discuss what we can do for your marketing efforts.

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*https://support.google.com/displayvideo/answer/15192137?sjid=3266901102191875360-NC

**https://support.google.com/displayvideo/answer/11905523?hl=en

***https://support.google.com/displayvideo/answer/12060859?hl=en&sjid=3266901102191875360-NC