Introduction: The Secret to Maximizing Every Dollar of Your Media Investment

CMOs, do you ever feel like even when you increase marketing spend, results aren’t growing at the same rate? You’re not alone. This phenomenon, known as diminishing returns, is one of the biggest challenges in media spend optimization. But what exactly does it mean, and how can you avoid it? It refers to the point where adding more investment to a marketing channel no longer produces a proportional increase in results. It’s an economic concept that, when applied to marketing, explains why continuous growth in investment doesn’t always translate into unlimited growth in sales or leads. Why is understanding this crucial? Because ignoring it can lead you to waste valuable resources on saturated channels, instead of optimizing your budget for maximum impact. In this post, we’ll reveal how to identify and overcome diminishing returns so your investment works smarter.

What are Diminishing Returns in Marketing?

Imagine you’re watering a plant. At first, every drop of water helps it grow. But if you keep adding water non-stop, the plant drowns. Similarly, in marketing, there’s an optimal investment point for each channel. Before that point, every additional dollar generates a positive and increasing ROI. However, once you reach that threshold, each extra dollar begins to generate less impact, to the point where the additional investment might yield no benefit or even a negative one.
This concept of diminishing returns doesn’t mean you should stop investing, but rather that you need to be smarter about where and how much you invest. The problem this understanding solves for CMOs is precisely how to avoid channel saturation and ensure every part of the budget goes where it can generate the greatest incremental value.

How to Identify Diminishing Returns in Your Channels

Recognizing diminishing returns is the first step to optimizing your spending. Here are some warning signs:
Flat or declining response curves: If you graph your investment in a channel versus the results obtained (sales, leads, etc.), and the curve starts to flatten or even decline, you’re experiencing diminishing returns.

• Increasing CPA/CPL: If the cost per acquisition (CPA) or cost per lead (CPL) for a channel increases significantly as you ramp up investment, it’s a clear signal.
• Decreasing ROAS/ROI: A declining return on ad spend (ROAS) or ROI despite increased investment also indicates you’re reaching the saturation point.
  For precise detection of diminishing returns, tools like Marketing Mix Modeling (MMM) are fundamental, as they analyze the incremental impact of every dollar invested in each channel.

Strategies to Overcome Diminishing Returns and Optimize Your Budget

Once you’ve identified the points of diminishing returns, it’s time to act. The key isn’t to cut your overall marketing budget, but to reallocate it more effectively.

• Smart Budget Reallocation: Identify the optimal point: Use advanced models to determine the ideal investment in each channel before returns start to diminish.
  Shift investment: Move funds from channels already showing diminishing returns towards those that still have growth potential or are under-invested. This could mean exploring new channels or formats.
• Creative and Message Optimization: Sometimes, diminishing returns aren’t due to channel saturation, but rather message or creative fatigue. Experiment with new creative approaches, audiences, or segmentation within the same channel.

• Multi-Channel Analysis (MMM and Attribution): Combine Marketing Mix Modeling (MMM), which gives you a macro view of impact, with more granular attribution models. This will allow you to understand not only the direct effect of each channel but also the synergies and the role of each touchpoint in the customer journey, thus avoiding saturation. At Making Science, our integrated solutions like Optiphi are designed precisely for this.

Conclusion: Turn Challenge into Opportunity with Diminishing Returns

Understanding and managing diminishing returns is vital for any CMO looking to maximize the efficiency and impact of their marketing investment. It’s not about spending less, but about spending smarter. By identifying when a channel reaches its saturation point, you can strategically reallocate your resources, explore new opportunities, and ensure every dollar generates maximum value.
Are you ready to stop wasting and start optimizing your marketing budget? Seize the opportunity to turn diminishing returns into a competitive advantage! If this post has opened your eyes, leave us a comment or share it. Because true marketing wisdom isn’t just about investing more, but about investing wisely!

Introduction: Uncover the Real Impact of Every Marketing Investment

CMOs, in a world where every dollar counts, how do you know if your marketing campaigns are generating a real impact and not just “cannibalizing” results you would have achieved anyway? The answer lies in incrementality. This powerful metric allows you to go beyond correlation to understand causality – that is, what part of your results is directly attributable to your marketing efforts, and not to external factors or organic demand. This post will guide you on what incrementality is, why it’s vital for your marketing models, and how you can use it to test new channels with confidence. Get ready to unlock the true potential of your budget.

The CMO’s Dilemma: Spending or Investing Wisely?

The big challenge for CMOs today is how to test and use incrementality to effectively test new channels. It’s easy to fall into the trap of only optimizing what’s easy to measure (like last-click), but this doesn’t always reveal the incremental impact of a campaign. The problem isn’t just spending, but spending intelligently. You need to know if your additional investment in a channel is truly bringing in new customers or sales, or if you’re simply paying for conversions that would have happened anyway. Incrementality solves this dilemma, offering a clear view of the added value of each action.

What is Incrementality and Why Is It Your Best Ally?

Incrementality measures the difference in consumer behavior (e.g., conversions, sales) between a group exposed to a marketing action and an unexposed control group. It’s not just about attribution, which assigns value to each touchpoint; incrementality validates whether that touchpoint generated the result, or if it was merely a bystander.

Think of incrementality as the true thermometer of ROI. It’s crucial for several reasons:

• Avoid wasted spend: It helps you identify where you’re over-investing without getting incremental results.
• Optimize budget allocation: It allows you to reallocate funds to the channels and campaigns that truly drive growth.
• Validate new channels: It offers a robust framework for testing the effectiveness of new platforms or strategies before scaling investment.

How to Measure Incrementality: The Tests You Need

To measure incrementality, controlled experiments are often used. These are some of the most common methods:

1. Geo A/B Tests (Geo-experiments):

• How it works: You divide your geographical markets into “treatment” groups (where the campaign or new channel is launched) and “control” groups (where it’s not launched). You compare performance between both groups to isolate the incremental impact.
• When to use it: Ideal for testing the incrementality of high-impact channels (TV, OOH) or for evaluating the potential of new markets. It requires good geographical segmentation and sufficient scale.

2. Holdout Group Tests:

• How it works: Within your target audience, you hold out a small percentage that won’t be exposed to the campaign or the new channel. Then, you compare their behavior with that of the exposed group.
• When to use it: Excellent for measuring the incrementality of digital campaigns (display, social media, email marketing) where it’s easier to create control groups at the user level. It’s a practical way to understand the incrementality of your actions.

3. Econometric Models (MMM with Incremental Component):

• How it works: Advanced Marketing Mix Modeling (MMM) can incorporate incrementality analysis by quantifying the incremental impact of each channel over time, beyond baseline demand.
• When to use it: For a holistic and strategic view, when you seek to understand the incremental impact of all channels and their interactions in the long term.

Incrementality: Your Compass for Testing New Channels

Incrementality is not just a metric; it’s a mindset. It allows you to approach the exploration of new channels on a scientific basis. Instead of making a large investment and crossing your fingers, you can design an experiment, measure the incremental impact, and make data-driven decisions about whether a new channel truly adds additional value. This reduces risk and ensures your resources are optimally allocated. The key is to be methodical and have the right tools to implement and analyze these incrementality tests.

Conclusion: Unlock True Potential with Incrementality

In modern marketing, moving from superficial attribution to incrementality analysis is a quantum leap towards true ROI optimization. It allows CMOs not only to understand what works, but how much more it works thanks to their investment. By mastering the techniques to measure incrementality and applying them to test and validate new channels, you can ensure that every dollar of your marketing budget generates significant incremental impact.

Are you ready to stop guessing and start measuring the true impact of your marketing? Explore incrementality and transform your investment decisions! Tell us in the comments: What has been your biggest learning when trying to measure the incremental impact of your campaigns? Because, in the end, the true magic of marketing isn’t in spending, but in the incrementality you generate.

Introduction: The Attribution Challenge in a Cookie-less World

In today’s dynamic digital marketing landscape, CMOs face a monumental challenge: how to measure the true impact of every marketing investment when user privacy is paramount? The post-cookie era has left a void, making it difficult to understand which channels and touchpoints truly drive conversions. This is where attribution becomes the indispensable compass. But how can we gain a clear, actionable view of attribution in an environment with increasingly strict data regulations? The answer lies in the adoption of advanced predictive models. This post will explore how these tools are redefining budget decision-making, allowing marketing leaders to optimize their strategies with confidence and precision.

The Problem with Traditional Attribution

For years, attribution relied on simplistic models like “last-click” or “first-click,” which failed to capture the complexity of the customer journey. These models, often dependent on third-party cookies, are now insufficient. The demise of cookies and growing privacy concerns have created a “privacy gap” that directly impacts CMOs’ ability to make informed decisions about their marketing budget allocation. Without a clear understanding of what drives performance, decisions become less strategic and more speculative, potentially leading to inefficient spending.

The Solution: Predictive Models and Machine Learning

The key to closing this gap lies in the power of predictive models and machine learning. These technologies allow for the analysis of large volumes of first-party and contextual data, identifying patterns and correlations that traditional methods cannot. By leveraging sophisticated algorithms, we can go beyond simple correlation to understand causation, assigning appropriate credit to each touchpoint in the customer journey, even in scenarios with limited or anonymized data. This not only improves the accuracy of attribution but also allows CMOs to anticipate trends and proactively optimize their campaigns.

Tangible Benefits for CMOs

For CMOs, implementing predictive models for attribution translates into tangible benefits:

• Optimized Budget Decisions: By understanding the true ROI of each channel, CMOs can allocate their budgets more intelligently, maximizing the impact of every dollar spent.

• Improved Customer Experience: Accurate attribution allows for personalized interactions and more relevant messaging, enhancing the overall customer experience.

• Privacy Compliance: These models are designed to operate with aggregated and anonymized data, ensuring compliance with privacy regulations like GDPR and CCPA.

• Competitive Advantage: Companies that master predictive attribution will gain a significant advantage by being able to react faster to market changes and consumer preferences.

Conclusion: The Future of Attribution is Predictive

In summary, attribution in the privacy era is no longer an unsolved puzzle. Predictive models offer a clear roadmap for CMOs, enabling them to make informed and strategic budget decisions, even in an evolving data landscape. It’s time to move beyond guesswork and embrace the power of artificial intelligence to unveil the true impact of your marketing efforts.

Are you ready to transform your attribution strategy and take your marketing to the next level? Share your thoughts and experiences in the comments! Because as the famous marketing consultant said, “To measure is to know, but to predict is to master.”

Introduction: Are You Ready to Optimize Your Media Investment Like Never Before?

In the competitive world of marketing, CMOs know that every dollar counts. It’s no longer enough to launch campaigns and hope for the best; you need data, strategy, and the ability to adapt quickly. This is where Optiphi comes in. But what is Optiphi? It’s our advanced solution that integrates Marketing Mix Modeling (MMM), attribution models, and a powerful Budget Allocator to give you a 360° view of your media performance. Why is it crucial for you? Because it allows you to simulate and compare different investment scenarios to maximize your results, regardless of your time horizon. How does it achieve this? Let’s dive in.

The Challenge of Media Planning in the Short, Medium, and Long Term

Media planning is both an art and a science. The real challenge for CMOs is balancing short-term tactics to achieve immediate goals with long-term strategic investments that build brand and loyalty. How do you ensure your budget is optimally allocated for both, without sacrificing one for the other? Traditional approaches often fall into the trap of short-term vision, neglecting the cumulative impact. This is where the versatility of Optiphi becomes your greatest asset.

Optiphi in Action: 3 Scenarios for Your Media Strategy

Optiphi offers you the flexibility to model and compare different budget allocation scenarios, allowing you to tailor your strategy to your specific objectives. Let’s look at three clear examples:

Scenario 1: Short-Term Conversion Maximization

If your goal is to drive immediate conversions and meet quarterly sales targets, Optiphi helps you identify the channels and investment combinations that generate the highest sales volume in the shortest time. Using the latest attribution insights and channel elasticity analysis, Optiphi will recommend where to invest aggressively to see quick results. This is ideal for promotional campaigns or periods of high product demand.

Scenario 2: Balancing Growth and Sustainability in the Mid-Term

For a mid-term view, Optiphi allows you to balance achieving sales goals with building a solid foundation for future growth. Here, the tool considers not only direct conversions but also the impact on brand awareness and customer loyalty. Optiphi will show you how to distribute your budget to maintain a steady flow of new acquisitions while strengthening your relationship with existing customers, optimizing your investments with a 6 to 12-month perspective.

Scenario 3: Long-Term Brand Building and Leadership

When the goal is market leadership and building a strong brand in the long term, Optiphi focuses on MMM to analyze the long-term effects of your investments. It considers carryover effects and synergies between channels that may not show immediate ROI but are fundamental to the brand’s sustainable health and growth. Optiphi will help you justify investments in channels that have a slower but deeper impact on brand perception and preference, ensuring your long-term budget aligns with your company’s strategic vision.

Conclusion: The Power of Flexible Planning with Optiphi

In summary, Optiphi is more than just a tool; it’s a strategic partner that empowers CMOs to make budget allocation decisions with confidence and precision. By integrating MMM, attribution, and a budget optimizer, it offers you the ability to simulate and adapt your media strategy to any time horizon, maximizing your ROI and ensuring the fulfillment of your objectives, whether short, medium, or long-term.

Ready to transform your media planning and see the true potential of your investment? Discover how Optiphi can be your competitive advantage! If you found this post helpful, share it with your team, and tell us, which of these scenarios resonates most with your current challenges?

Introduction: Before AI, the Data Foundation. Are You Prepared?

Artificial Intelligence (AI) is transforming the business landscape, promising unprecedented efficiencies and new avenues for growth. But how ready is your company to ride this wave? Many CMOs jump into the “AI chaos” without a solid foundation, forgetting that AI is only as good as the data that feeds it. This post will guide you on what you need to build a robust data base that allows your company to fully leverage the potential of AI. We’ll help you understand what, why, when, and how to prepare your data for this revolution. Because without a good Data Foundation, AI is nothing more than an empty promise.

The CMO’s Dilemma: Data for AI, Where to Start?

The enthusiasm for AI is contagious, but it can also be overwhelming. Many CMOs ask themselves: “Do I need a massive data lake? Is my current data good enough? How do I prevent AI investment from becoming a black hole with no return?” The main problem is that without a clear strategy for data management and quality, AI implementation becomes a challenging road full of obstacles. It’s not just about collecting data, but about having correct, clean, and accessible data. This is where the “Data Foundation” becomes your number one priority before diving into AI projects.

The Pillars of Your Data Foundation for AI

For AI to truly work for your company, especially for a CMO, you need to build a solid Data Foundation. Think of it like the foundations of a building: if they’re not strong, the structure will collapse.

1. Impeccable Data Quality:
   • What does it mean? Your data must be accurate, complete, consistent, and up-to-date. Incorrect or incomplete data will lead to flawed AI models and wrong decisions. Imagine a personalization campaign based on outdated customer data: the result would be a poor experience and a loss of trust.
   • How to achieve it? Implement rigorous data cleaning, validation, and standardization processes. Regular audits are key.
2. Unified Data Integration:
   • What does it mean? Data from different sources (CRM, ERP, marketing platforms, web, apps) must be connected and accessible in a single location or through a unified system. AI needs a holistic view of the customer to generate truly valuable insights.
   • How to achieve it? Use Data Warehouses, Data Lakes, or Customer Data Platforms (CDP) that allow for consolidating and harmonizing information.
3. Clear Data Governance:
   • What does it mean? You must have clear policies and procedures on who can access data, how it’s used, and how it’s kept secure and compliant with regulations (GDPR, CCPA, etc.). Trust and privacy are fundamental to any successful AI initiative.
   • How to achieve it? Establish clear roles and responsibilities, define security standards, and ensure staff training. AI is a powerful tool, but its ethical and legal use is non-negotiable.
4. Data Access and Usability:
   • What does it mean? Data must be easily accessible to the teams that need it (data scientists, marketing analysts) and be in a format that allows them to work efficiently with it.
   • How to achieve it? Invest in visualization tools and analytics platforms that facilitate the exploration and use of data to feed your AI projects.

AI Doesn’t Wait: How to Start Your Data Transformation

You don’t need to have everything perfect to start, but you do need a clear strategy. Here’s a simple guide:

• Assess your current state: Conduct a data audit to identify gaps in quality, integration, and governance.
• Prioritize: Focus on the most critical datasets for your initial AI projects (e.g., customer data for personalization).
• Invest in technology and talent: You’ll need appropriate tools and a team with the necessary skills to manage and prepare data for AI.

By laying these foundations, your company will not only be ready to implement AI solutions effectively but will also build a sustainable competitive advantage.

Conclusion: AI Is the Future, But Your Data Is the Present

Artificial Intelligence offers a universe of possibilities for CMOs, from campaign optimization to personalization at scale. However, the success of AI directly depends on the quality and structure of your data. Don’t leap into the void; invest first in a solid Data Foundation. It’s the key to making your AI models accurate, relevant, and most importantly, actionable.

Are you ready to build the Data Foundation your AI strategy needs? Start auditing your data today and lay the groundwork for an AI-powered future! Leave your comments or share this post if you believe data quality is the true superpower behind successful AI. Because in the world of AI, data isn’t the fuel, it’s the engine!

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.

Introduction: Navigate the Data Maze and Decide with Confidence

CMOs, do you sometimes feel lost in a sea of data and measurement tools? You’re not alone. With so many options available, from attribution to Marketing Mix Modeling (MMM), knowing what tool to use and when is crucial for making informed decisions. This post is your compass. We’ll explain the main measurement tools (what they are, why, when, where, who, and how to use them) to help you build a solid data foundation and avoid the “AI chaos.” The goal is for you to master your measurement strategy, maximizing the impact of every marketing euro. Ready to unravel the mystery?

The CMO’s Challenge: Too Many Tools, Too Few Clear Answers?

The problem isn’t a lack of data, but rather data saturation and confusion about how to turn it into actionable insights. Many CMOs face the question: “How do I build my data foundation before diving into the ‘AI chaos’?” The answer lies in a clear understanding of the available measurement tools and how they fit into your overall strategy. Not all tools are suitable for everything, and knowing when to apply each one is the key to smart investment and data-driven decision-making.

Your Measurement Arsenal: When to Use Each Tool

For a complete and effective measurement strategy, you need a well-defined arsenal of tools. Here, we explain the most important ones and their purpose:

1. Attribution

What is it? Attribution assigns credit for a conversion to one or more touchpoints in the customer journey. Common models include first-click, last-click, linear, or data-driven. When to use it? It’s ideal for understanding short-term, user-level impact and optimizing specific digital campaigns. For example, if you want to know which ad or keyword led directly to a sale. It’s fundamental for granular measurement. Key Advantage: It allows you to optimize the performance of active campaigns and the allocation of your budget within digital channels.

2. Marketing Mix Modeling (MMM)

What is it? MMM is an econometric technique that measures the impact of all marketing activities (online and offline) on sales and other KPIs over time, considering external factors. When to use it? It’s perfect for medium- to long-term strategic planning, budget allocation between channels (TV, digital, print, etc.), and optimizing overall marketing ROI. It helps you understand diminishing returns and the real effect of your investment at a macro level. Key Advantage: It offers a holistic and platform-agnostic view, which is crucial in a cookie-less world, and it’s excellent for strategic measurement.

3. Budget Allocator

What is it? A tool that uses attribution and MMM data to recommend the optimal allocation of your marketing budget across different channels and campaigns, based on your objectives (maximize sales, ROI, etc.). When to use it? When you need to make quick and precise decisions about where to invest your next dollar, or to simulate different investment scenarios and see their impact. It’s the bridge between analysis and practical measurement action. Key Advantage: It translates insights into actionable recommendations for maximum efficiency.

4. Brand Lift Studies

What is it? Studies that measure the impact of your advertising campaigns on brand metrics such as awareness, consideration, preference, or purchase intent. When to use it? For branding campaigns or when the main objective is not a direct conversion, but rather building the brand and its long-term perception. It complements performance measurement. Key Advantage: It quantifies the intangible value of brand building.

The Perfect Synergy: How to Combine Your Measurement Tools

The key is not to choose one over the other, but to understand how they work together. A comprehensive measurement strategy often involves:

• MMM for long-term strategic allocation and understanding macro factors.
• Attribution for optimizing specific digital campaign performance and short-term impact.
• Budget Allocator for translating MMM and attribution insights into dynamic investment decisions.
• Brand Lift Studies to ensure that performance investments don’t sacrifice brand health.

By combining these tools, CMOs can build a robust Data Foundation that not only prepares them for the future of AI but also enables them to make much smarter and more efficient marketing decisions today. Effective measurement is the basis of everything.

Conclusion: Your Marketing Future Depends on Smart Measurement

In today’s complex marketing ecosystem, success is not a matter of luck, but of precise measurement and a clear strategy. By understanding the strengths and the right time to use tools like attribution, MMM, budget allocators, and brand lift studies, CMOs can move from uncertainty to confidence. It’s the path to building solid data foundations that will not only help you avoid the “AI chaos” but also drive you toward sustainable growth.

Ready to organize your measurement strategy and unlock the true power of your data? Start evaluating your tool arsenal today! If this post was helpful, share it and tell us, what is your biggest challenge in marketing measurement? Because at Making Science, we believe that to measure is to know, and to know is power!

For years, SEO professionals treated monthly search volume as the compass that guided every strategy. We picked topics, set priorities, and measured the potential of a keyword almost exclusively by that number.

But by 2025, that approach feels outdated. Google isn’t just showing blue links in the SERPs anymore. It now presents results through features like AI Overviews and AI Mode (already live in some regions), delivering direct, AI-generated summaries instead of a list of links.

Meanwhile, users are shifting their behavior. Increasingly, they’re asking questions directly to ChatGPT, Gemini, Claude, or Perplexity rather than typing into a search bar. In this context, searches aren’t keywords anymore, they’re conversational prompts. And right now, there’s no reliable public data to tell us the “volume” of those queries.

If you’re waiting for your SEO tool to catch up with the trend… you’re already behind.

Why Predictive SEO Matters

Predictive SEO doesn’t sit around waiting for data to confirm a trend. It takes the lead.

• It spots early signals using tools like Google Trends or AnswerThePublic.
• It creates content before the metrics are visible, by tapping into Reddit, X, Quora, Feedly, niche forums, or Google News.
• It’s optimized for conversations, thinking about how a user would phrase a question to a chatbot — or how Google might condense an answer in AI Overviews.

The First-Mover Advantage

In this new world of conversational search, being the first source cited by an AI model is a huge competitive edge.
Once a chatbot or Google references your content in its responses, dislodging it becomes extremely difficult.

How to Adapt Today

1. Keep an eye on forums and social platforms to spot weak signals early.
2. Write answers to complex questions that are clear, structured, and genuinely helpful, the way an AI assistant would.
3. Shift your focus to intent, not exact keywords: create content that solves problems, not just content that ranks.

Conclusion

Predictive SEO is the strategy that ensures your brand shows up in AI-driven answers.

It’s no longer just about hitting Google’s front page. It’s about becoming the trusted source that AI models cite when users ask questions. That’s the real visibility frontier in 2025.

At Making Science, our SEO & Content team has already made this approach to the foundation of how we create and optimize content.

👉 So let me ask you: are you making sure your brand — or your clients’ brands — appears in AI’s answers?

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.

In 2025, Google rolled out a major update with the launch of AI Mode, which is already live in the U.S., UK, and India (as of 30th July). This new feature is shaking up how people search. Unlike the AI Overviews we’ve seen in the past, AI Mode is a separate tool that uses generative AI to give you detailed answers directly on the search page. In this post, we’ll take a closer look at how it works, what it means for SEO, and how businesses can adapt to this new way of searching.

1. How does Google’s AI Mode work?

AI Mode is powered by Google’s Gemini 2.5 model, a super advanced language model that is designed to give you detailed answers to complex searches. Instead of showing directly a list of web pages, AI Mode breaks down your search into smaller pieces of content (chunks), running parallel searches to get data from different sources and creating a single response. This answer appears directly on the search page, so you don’t have to click through to other websites.

What makes AI Mode different? 

The main difference it brings to the table is that it can handle different types of inputs, like text, voice, or even images. Users can upload a photo and ask follow-up questions, interacting with the AI in a more conversational way. Plus, the AI can adjust its responses over time based on your previous conversations. For example, if you ask a broad question and then follow it up with something more specific, AI Mode will refine its answer to give you more detailed info.

2. What does AI Mode mean for SEO?

AI Mode brings a new set of challenges for SEO professionals, especially when it comes to traffic and click-through rates (CTR). In traditional search, users are shown a list of websites to click on, but in AI Mode, users are getting answers directly on the search page. This could mean fewer clicks to external websites, as the AI can sometimes fully answer the query right there.

Some reports have shown a drop in CTR, since users can get the information they need without leaving the search page. However, this doesn’t mean you lose visibility entirely. Even if users don’t click through, your content can still be exposed if it’s referenced in the AI-generated answers. Plus, Google has noted that users are often spending more time on the search page, asking follow-up questions and diving deeper into topics. This could actually lead to more engagement in the long run. Besides, boosting brand awareness is a crucial element of any successful marketing strategy, and this presents a prime opportunity to gain an advantage. 

3. New SEO metrics to focus on

With the rise of AI Mode, some traditional SEO metrics like clicks and rankings don’t carry the same weight anymore. Impressions are now more important than ever. However, there are also new metrics to keep an eye on:

• Visibility in AI Search features: This metric tracks how often your content appears in AI-generated elements like Featured Snippets, Knowledge Panels, and AI Overviews. Tools such as Semrush and Ahrefs can help monitor these appearances, providing insight into your content’s reach within AI interfaces.
• Branded search volume trends: Monitoring the frequency of searches for your brand name helps assess brand awareness and the effectiveness of AI-generated content in driving recognition. An increase in branded searches indicates that AI systems are referencing your content while also enhancing your brand’s visibility.
• User engagement metrics: Metrics such as bounce rate, time on page, and interaction depth provide insights into user satisfaction. AI systems consider these signals when determining content relevance, making them crucial for understanding how users interact with your content.

These new metrics focus on user intent and understanding how well your content is engaging with people—rather than just focusing on clicks alone.

4. What do we do in Making Science to perform better in AI Mode?

To help you get noticed in AI Mode, we follow these proven best practices:

• Ensure crawlability and indexing: AI Mode relies on Google’s crawling and indexing system, so we have to be sure our content is easy to access and index by Google systems. This means checking for any crawl errors and ensuring we’re not blocking anything relevant with robots.txt.
• Create high-quality content: Content that is thorough, authoritative, and effectively answers users’ questions is more likely to be featured by AI Mode. Google systems still favor high-quality content, so we should keep focusing on providing value (maybe more than ever!) for them.
• Review and apply structured data: Structured data like schema markup can help Google have a better understanding of our content, especially when it comes to media like images or videos.
• Optimize for user experience: While AI Mode may reduce clicks, the overall user experience still matters. A fast, mobile-friendly, and easy-to-navigate site is key in our strategy.

Key takeaways

Google’s new AI Mode is essentially a smart chatbot built directly into the search page, designed to answer complex questions in conversation style. This is changing the game for websites because the AI often answers questions directly, meaning fewer people click on the traditional blue links.

For businesses, the new goal is to become a trusted source that the AI quotes in its answers. The best way to do this is by building a strong, reputable brand and creating genuinely helpful content that offers unique, real-world experience and insights that only a human expert can provide.