Ever felt like your ad spend was working hard, but maybe not smart enough? For years, advertisers have chased clicks, conversions, and impressions, often treating all conversions the same. But what if there was a smarter way to tell your digital marketing campaigns to not just find conversions, but to find the best conversions?

That’s what Value-Based Bidding (VBB) does for smart advertisers. This isn’t just a fancy new buzzword; it’s a fundamental shift in how you optimize your ad budget within the Google Marketing Platform, designed to supercharge your return on ad spend (ROAS) and connect you with customers who genuinely matter to your bottom line.

Beyond the Click: The Paradigm Shift to Value

Let’s rewind a bit. Traditional bidding strategies often focus on volume. You might bid to get as many conversions as possible, or to hit a certain Cost Per Acquisition (CPA/targetCPA). And while those metrics are important, they don’t always tell the whole story.

Imagine you’re selling custom-designed sneakers. One customer buys a basic pair for $100. Another buys a premium, limited-edition pair with custom artwork for $500. If your bidding strategy treats both conversions as equal, you’re missing a massive opportunity. The $500 sale is clearly more valuable, yet your campaigns might be optimizing just as hard for the $100 sale. This is where VBB can make all the difference.

Value-Based Bidding assigns a monetary value to your conversions. Instead of simply telling Google to get you “a conversion,” you tell it to get you “a conversion worth X dollars.” This empowers Google’s machine learning to prioritize serving your ads to users who are more likely to generate higher revenue or profit for your business.

Why Google Marketing Platform and VBB are a Match Made in Heaven

The Google Marketing Platform (GMP) is not just a collection of tools; it’s an integrated ecosystem designed for serious advertisers. With components like Search Ads 360, Display & Video 360, Analytics 360, and Campaign Manager 360 working in harmony, GMP provides the robust data infrastructure and powerful machine learning capabilities that VBB absolutely thrives on.

Here’s why GMP is the perfect platform for VBB:

1. Unified Data Insights: GMP allows you to consolidate data from various touchpoints – search, display, video, analytics, and more. This unified view gives you a much richer understanding of customer journeys and, crucially, the actual value different customer segments bring. When you feed this comprehensive data into your VBB strategy, Google’s algorithms have a clearer picture of who your high-value customers are.
2. Advanced Machine Learning: At its core, VBB leverages Google’s sophisticated AI. The algorithms learn from your historical conversion values, user behavior signals, and real-time market dynamics to predict the likelihood of a high-value conversion. Within GMP, these algorithms are supercharged by the sheer volume and quality of data flowing through the platform.
3. Cross-Channel Optimization: With GMP, you’re not just optimizing a single campaign in isolation. Search Ads 360 can manage your search campaigns, while Display & Video 360 handles your programmatic efforts. VBB strategies, especially when implemented across these platforms, allow for a holistic approach where your budget is dynamically shifted towards the channels and audiences most likely to deliver high-value conversions, regardless of where they are in their journey.
4. Granular Control & Automation: While VBB automates much of the heavy lifting, GMP still provides the granular controls marketers need. You can set specific value rules, define custom bidding strategies, and observe the performance with detailed reports. This blend of automation and control is what makes VBB within GMP so powerful.

The Nitty-Gritty: How Does Value-Based Bidding Actually Work?

Implementing VBB effectively involves a few key steps:

Step 1: Defining Your Conversion Values

This is the foundational step. You need to assign a monetary value to each conversion action. This isn’t always as simple as a direct e-commerce sale. For lead generation, you might assign values based on:

• Lead Quality: A whitepaper download might be worth $10, a demo request might be worth $50, and a qualified sales lead might be worth $200.
• Customer Lifetime Value (CLTV): If you have historical data, you can estimate the average revenue a customer brings over their entire relationship with your business.
• Profit Margins: Focus on the profit generated, not just the revenue. A high-revenue, low-margin product might be less valuable than a lower-revenue, high-margin one.

The more accurate and detailed your conversion values, the better Google’s algorithms can optimize. This often involves integrating your CRM or internal sales data with your analytics platform (like Google Analytics 4, which is built for this purpose and integrates seamlessly with GMP).

Step 2: Implementing Conversion Tracking with Value

Ensure your conversion tracking is set up to pass these dynamic values.

• E-commerce: For online stores, this is typically handled by passing the value parameter with your purchase event data.
• Lead Forms: For lead generation, you might need to use custom JavaScript or a Google Tag Manager setup to dynamically assign values based on the form type, product interest, or even post-submission qualification.
• Offline Conversions: For sales that happen offline, you can upload offline conversion data back into Google Ads (and subsequently into GMP) with associated values.

Step 3: Choosing the Right Bidding Strategy

Once your values are flowing, you can select a VBB strategy:

• Maximize Conversion Value: This strategy aims to get the highest total conversion value for your budget. It’s great for when you want to maximize revenue without a specific ROAS target.
• Target ROAS (Return on Ad Spend): This is the holy grail for many businesses. You set a target ROAS (e.g., “I want to get $4 back for every $1 I spend”) and Google’s algorithms will adjust bids in real-time to try and achieve that target by prioritizing high-value conversions.

Step 4: Patience and Iteration

VBB, like any machine learning strategy, needs clean data and time to learn. Allow your campaigns to run for a few weeks, gather sufficient conversion data with values, and then review the performance. You’ll likely need to iterate on your conversion values and ROAS targets as you gain more insights.

The Exciting Benefits: What Can VBB Do for You?

• Boosted ROAS (Return on Ad Spend): By focusing on higher-value conversions, your ad dollars are spent more efficiently, leading directly to a healthier bottom line.
• More Profitable Customers: VBB helps you identify and acquire customers who are more likely to spend more, become repeat buyers, and contribute significantly to your long-term success.
• Smarter Budget Allocation: Instead of simply pouring money into campaigns that generate many low-value conversions, VBB intelligently shifts your budget towards opportunities that promise greater returns.
• Deeper Business Insights: The process of defining conversion values forces you to think deeply about what truly drives value for your business, leading to a better understanding of your customer segments and product profitability.
• Competitive Edge: While many advertisers are still stuck in the “clicks and conversions” mindset, embracing VBB gives you a significant advantage, allowing you to outmaneuver competitors by focusing on actual profit.

Real-World Scenarios Where VBB Shines

Let’s look at some examples:

• E-commerce: A fashion retailer notices that customers who buy high-end jackets also frequently purchase accessories. By assigning a higher value to jacket purchases (due to higher average order value and potential for add-on sales), VBB helps them acquire more of these valuable customers.
• SaaS Company: A software company offers different tiers of subscriptions. A free trial conversion is worth $X, but a conversion to their “Premium” plan is worth $5X. VBB allows them to optimize for users more likely to subscribe to the higher-value plan.
• Education Sector: A university has various courses. Applications for a highly competitive, high-tuition Master’s program are far more valuable than inquiries for a short online certificate. VBB ensures ad spend focuses on driving applications for the most lucrative programs.

Why Now is the Time to Embrace Value-Based Bidding

The advertising landscape is more competitive than ever. Relying on basic bidding strategies means leaving money on the table and falling behind. With increasing privacy regulations and the rise of zero-click search due to AI, first-party data (which forms the bedrock of effective VBB) is becoming even more critical.

Google Marketing Platform, with its robust infrastructure and sophisticated machine learning, is perfectly positioned to help you leverage VBB to its fullest potential. It’s about moving beyond simply counting conversions to truly understanding and optimizing for the value those conversions bring.

Ready to Change Your Strategy?

The transition to Value-Based Bidding might seem daunting at first, especially if you’re accustomed to traditional methods. But the rewards are substantial. It requires a thoughtful approach to data, a clear understanding of your business objectives, and the right tools.

That’s where Making Science comes in.

Our team specializes in helping advertisers like you unlock the full potential of Value-Based Bidding within the Google Marketing Platform. Stop chasing every conversion and start chasing the conversions that truly matter. Let’s make your ad spend work smarter, not just harder.

Ready to transform your Google Marketing Platform strategy with Value-Based Bidding? Contact us today for a free consultation!

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Moving Beyond Conventional Smart Bidding

Automated bidding strategies have evolved from a competitive edge to a market standard. However, for today’s marketing professional, relying solely on standard pixels is no longer enough. The real challenge of Value-Based Bidding (VBB) isn’t just collecting conversions; it’s feeding the algorithm with high-quality signals that reflect your business’s actual financial reality.

Optimizing for “conversion volume” is a thing of the past; optimizing for Customer Lifetime Value (LTV) and profit margins is the present.

The 3 “Blind Spots” Stalling Your Performance

Even with top-tier Search or Social campaigns, most advertisers hit three critical barriers:

1. The Attribution Gap (7-Day Window): Google and Meta algorithms prioritize recent signals. If your sales cycle is long (Real Estate, Education, Banking), the algorithm “forgets” the source of success before the final conversion occurs.
2. Offline Signals and Data Noise: Cancellations, returns, or low-quality leads clutter AI learning, causing you to over-invest in users who don’t generate real value.
3. Signal Scarcity: In niche markets or upper-funnel channels (Display/Video), a lack of conversion volume prevents Smart Bidding from ever leaving the “learning phase.”

Gauss Smart Advertising: The Intelligence Layer for Your AdTech

To bridge the gap between what the algorithm sees and what your business actually needs, we developed Gauss Smart Advertising. This isn’t just a data connector; it’s a proprietary Machine Learning technology that acts as a predictive brain for your campaigns.

How Gauss Transforms Your Bidding Strategy

Instead of waiting for a conversion to happen, Gauss analyzes user behavior in real-time and anticipates their future value:

• Propensity Scoring: Predicts a lead’s purchase probability the moment they enter the funnel.
• Predictive LTV: Estimates a customer’s long-term value, allowing you to bid aggressively for high-value users while saving on low-margin ones.
• Agnostic, Real-Time Activation: Unlike static models, Gauss integrates with any platform (Google, Meta, TikTok, Amazon), sending signals before cross-device traceability is lost.

Real Impact: With Gauss, we have successfully increased our clients’ conversions by 20% and reduced CPA/CPL by up to 50% by eliminating budget waste on non-profitable users.

Take the Leap Toward Profit Bidding

Success today doesn’t depend on the bidding tool itself, but on the quality of the signal you feed it. If you are ready to stop bidding for volume and start bidding for real business value, our team of data scientists and performance experts is ready to help.

Introduction

Imagine walking into a physical store where the staff doesn’t just greet you, but instantly understands your preferences, guides you directly to items that match your style, and even offers you a discount on your favorite brand based on your past purchases. You wouldn’t just be impressed; you’d be significantly more likely to make a purchase and return again. Now, what if your website could replicate this highly tailored, intuitive, and engaging experience for every single visitor, every single time?

This is the profound power unleashed when you strategically combine personalization with your Conversion Rate Optimization (CRO) efforts. This article will meticulously explore what this dynamic duo truly means, why it has become an indispensable element for advancing your digital maturity in a competitive landscape, and provide actionable insights on how to seamlessly implement this integrated strategy to craft an unparalleled user experience. By consciously moving away from a ‘one-to-many’ approach and embracing a ‘one-to-one’ dialogue with your customers, you unlock a new, elevated realm of conversion potential, foster deep customer loyalty, and drive sustainable business growth.

Are you prepared to transcend the limitations of broad-brush marketing and finally engage in meaningful, individualized conversations with your users, transforming casual visitors into committed customers?

Definition

Beyond the First Name: What Personalization Really Means for CRO

True personalization within the context of CRO is far more sophisticated than merely auto-inserting a customer’s first name into an email subject line or a welcome banner. It represents a fundamental paradigm shift: the systematic practice of meticulously crafting uniquely tailored digital experiences for individual users. This tailoring is dynamically informed by a rich tapestry of data, including their real-time behavior on your site, their demographic profile, their geographical location, the device they are using, their previous interactions with your brand across all channels, and even their historical purchase data.

Instead of presenting a static, undifferentiated website to every visitor, personalization empowers you to dynamically alter and adapt various elements of your digital storefront. This includes, but is not limited to, displaying different content blocks, showcasing highly relevant offers, adjusting call-to-actions (CTAs), modifying site navigation, and presenting product recommendations that are inherently more appealing to specific user segments. This isn’t a peripheral add-on or a separate track from your core optimization initiatives; rather, it’s an advanced, integral strategy designed to profoundly enhance every single touchpoint within the user journey, leading to a substantial and measurable uplift in conversion rates.

New Reality

The Synergy: Why Personalization Supercharges Your Conversion Strategy

Traditional CRO methodologies are exceptionally effective at identifying what resonates best with the average user. Through rigorous A/B testing and multivariate testing, we uncover optimal layouts, compelling copy, and effective CTAs that perform well across a broad audience. However, here lies the critical insight: there is no single “average” user. Every visitor arriving on your site brings a unique set of needs, intentions, preferences, and prior experiences. This inherent diversity is precisely where personalization intervenes, serving as the ultimate accelerator for your conversion strategy.

By seamlessly integrating personalization into your existing CRO framework, you elevate your approach from conducting broad A/B tests aimed at a generic audience to executing hyper-targeted, segmented experiments. This powerful synergy initiates a virtuous cycle, creating a self-reinforcing loop of improved performance and customer satisfaction:

• Deeper Relevance: When users are presented with content, products, and offers that are directly pertinent to their immediate needs, expressed interests, or past behaviors, their attention is immediately captured. This dramatic increase in perceived relevance translates directly into higher engagement metrics, longer session durations, and a significantly reduced bounce rate. Imagine a vegan customer visiting a grocery site seeing plant-based recipes highlighted on the homepage, or a new parent being shown baby product bundles instead of general electronics.
• Reduced Friction and Enhanced Flow: Personalization anticipates user needs and proactively removes potential obstacles in their path to conversion. This could manifest in numerous ways: showing recently viewed items prominently, pre-filling forms based on past interactions, suggesting the most relevant shipping options, or displaying location-specific payment methods. By streamlining the user journey and creating a seamless, intuitive experience, you effortlessly guide users towards their desired action, minimizing frustration and decision fatigue.
• Increased Customer Satisfaction and Loyalty: When customers perceive that a brand understands and caters to their individual preferences, they don’t just complete a transaction; they develop a deeper emotional connection and a sense of loyalty. This focus on individual needs fosters a positive brand perception and cultivates advocates who are more likely to return, make repeat purchases, and recommend your brand to others. In an era where customer experience is a key differentiator, this is crucial for long-term success and sustainable growth.

Practical examples

Putting It into Practice: 3 Examples of High-Impact Personalization

So, how does this sophisticated integration of personalization and CRO translate into tangible, real-world applications that deliver a direct and measurable uplift? Here are three powerful yet implementable examples of how you can begin to apply personalization to your website today:

• Dynamic Homepage Banners and Hero Sections: Your homepage is your digital storefront’s main window. Leverage it dynamically. For a first-time visitor, a compelling welcome discount or a clear value proposition statement might be most effective. For a returning customer who has previously browsed specific product categories (e.g., hiking gear, organic coffee, or professional development courses), showcase new arrivals or special offers within those precise categories. For a customer who just made a purchase, suggest complementary products or invite them to review their recent order. This simple but powerful adaptation ensures the first impression is always relevant and impactful.
• Tailored Product Recommendations Across the Site: Move beyond generic “Customers who bought this also bought…” suggestions. Implement advanced “Recommended for You” sections that are driven by each user’s unique browsing history, past purchases, items added to their cart, and even their search queries. This is a foundational tactic for intelligently enhancing cross-sells (e.g., suggesting a lens cleaning kit with a camera) and upsells (e.g., offering a premium version of a software product they’ve viewed). Machine learning algorithms can analyze vast datasets to predict precisely what a user is most likely to be interested in next, creating a truly bespoke shopping experience.
• Geo-Targeted Content and Offers: Your users’ physical location offers a wealth of personalization opportunities. Is a user browsing your site from a city where you have a physical brick-and-mortar store? Immediately display a prominent banner promoting a “Click & Collect” option for local pickup or highlighting in-store promotions specific to that location. If a user is visiting from a region experiencing a cold snap, feature winter coats, heated blankets, or snow shovels prominently on your homepage, rather than swimsuits or gardening tools. This level of location-aware relevance directly drives immediate action by addressing local needs and conveniences.

Conclusion: Be the Bespoke Tailor of E-commerce

In summary, the strategic integration of personalization into your existing Conversion Rate Optimization strategy is not merely an optional enhancement; it is the definitive, non-negotiable step toward achieving true digital maturity and sustained competitive advantage. It fundamentally transforms your website from a generic, static billboard into a dynamic, intuitively intelligent sales assistant that meticulously caters to each user’s unique needs, preferences, and journey stage. This granular focus significantly boosts both your immediate conversion rates and cultivates profound, long-lasting customer satisfaction and loyalty.

Consider the substantial investment many businesses make in expensive Search Engine Advertising (SEA) campaigns, social media ads, and other traffic-driving initiatives. While these campaigns are essential for attracting visitors, they represent only half the battle. If those hard-earned users land on a generic, undifferentiated page that fails to speak directly to their individual needs or interests, a significant portion of your marketing investment is quite literally leaking value. A truly personalized user experience is the crucial mechanism that ensures your valuable traffic converts at its absolute highest possible potential, maximizing your return on investment (ROI).

Trying to treat all your customers identically is akin to a master tailor who only offers “one-size-fits-all” suits. While a lucky few might find a decent fit purely by chance, the overwhelming majority will feel ignored, unaddressed, and ultimately take their business elsewhere, resulting in significant missed opportunities and lost revenue. In today’s hyper-competitive digital landscape, the brands that thrive are those that embrace individual differences, communicate directly, and deliver highly relevant experiences.

So, reflect for a moment: What is one concrete, actionable way you could start personalizing your user journey on your website today? Share your innovative ideas and insights in the comments section below!

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 eCommerce landscape is undergoing a seismic transformation, and at the heart of this change is artificial intelligence in ecommerce. From dynamic personalization to intelligent automation, AI is revolutionizing how online retailers engage with customers, streamline operations, and scale rapidly. But beyond functionality, AI also plays a pivotal role in optimizing ecommerce SEO by enhancing user experience, content performance, and search visibility. This article explores how AI is reshaping eCommerce, with a special focus on SEO applications, AI-powered content creation, and strategic implementation for sustainable growth.

The rise of AI in eCommerce

Once a futuristic concept, artificial intelligence (AI) is now a core driver of innovation in eCommerce. Technologies like machine learning, natural language processing (NLP), and computer vision enable online businesses to analyze behavior, predict intent, and personalize experiences at scale.

Several key factors are accelerating the integration of AI in eCommerce and SEO:

• Rising customer expectations: Shoppers expect seamless, personalized journeys. AI delivers relevant product suggestions, smart search, and real-time support, all of which improve engagement and SEO performance.
• Data overload: Every action online produces data. AI helps process this information to refine targeting, content, site structure, and user flow. These are essential elements of modern SEO.
• Accessible tools and platforms: AI-driven technologies for SEO, automation, and analytics are now widely available, even for smaller businesses.
• Competitive pressure: Businesses leveraging AI stay ahead in rankings, customer experience, and content strategy. Those who don’t risk falling behind in the SERPs.

Key applications of AI in eCommerce

AI is transforming every stage of the customer journey and its impact on SEO is tangible. Here are the most relevant use cases:

1. Personalized product recommendations

AI algorithms analyze browsing and purchase behavior to deliver product suggestions tailored to each user. This boosts click-through rates, conversion, and engagement.

2. Intelligent site search

AI-powered search understands natural language and user intent, delivering more relevant results. This improves UX and reduces bounce rates.

3. AI chatbots and virtual assistants

Chatbots offer instant assistance, helping users navigate, answer questions, and discover products. They increase time on site and reduce exit rates.

4. Fraud detection

While more focused on security, AI’s ability to detect fraud ensures business continuity and protects brand trust, which indirectly supports long-term organic reputation.

5. Inventory optimization

AI helps predict demand, manage SKUs, and automate reordering. This ensures product availability, prevents 404 errors, and supports healthy indexing for an SEO strategy.

6. Dynamic pricing

AI adjusts prices based on demand, competition, and behavior. When integrated with structured data, this can boost visibility in SERPs and AI platforms.

AI-powered content creation and optimization

One of the most disruptive innovations in SEO is AI-generated and AI-optimized content. AI is now capable of supporting the entire content lifecycle, from ideation to performance monitoring.

• Scalable content generation: AI can produce large volumes of SEO-friendly product pages, category descriptions, or blog content quickly and efficiently.
• Real-time SEO optimization: AI tools assist with keyword placement, heading structure, internal linking, and metadata optimization, all essential for ranking.
• Content refreshing and repurposing: AI can identify outdated or underperforming content and suggest updates based on current trends and algorithms.

Content remains king, but AI might be the strategist. For more on this topic, read our article AI Mode: What does it mean for SEO?.

Benefits of using AI for SEO in eCommerce

AI doesn’t just automate, it enhances your entire SEO strategy. Here’s how:

• Improved rankings and traffic: Smarter keyword targeting, optimized content, and enhanced UX drive stronger organic performance.
• Higher engagement signals: Personalized experiences and faster site interactions translate into better dwell time and lower bounce rates.
• Consistent content quality: AI helps maintain tone, structure, and SEO integrity across large-scale content production.
• Automated technical SEO: AI tools flag issues like broken links, duplicate content, or slow pages—and can sometimes fix them automatically.
• Better decisions, faster: AI surfaces actionable insights from SEO data, allowing marketers to test and iterate in real time.

How to implement AI in your SEO strategy

Integrating AI doesn’t require a full overhaul. You can begin with incremental changes:

• Set clear SEO objectives: Define KPIs such as impressions or ranking improvements and align your GEO strategy accordingly.
• Start with SEO quick wins: Use AI for content briefs, metadata generation, keyword clustering, or product copy creation.
• Choose scalable tools: Opt for AI platforms that integrate with your CMS, analytics, and SEO software stack.
• Leverage expert support: Collaborate with SEO and AI specialists to create a roadmap that balances automation with strategy.
• Continuously test and refine: Use testing and search performance data to evaluate impact and guide improvements.

The future of AI in eCommerce and SEO

AI is not just the present, it’s defining the future of how we search, shop, and grow digitally. Expect to see:

• Visual search optimization: AI allows users to search via images. Brands that optimize images with alt text and structured data will stand out.
• Voice search and conversational SEO: AI voice assistants are changing how queries are made, requiring long-tail and natural language content strategies.
• Immersive experiences through AR and AI: AI will support augmented reality shopping environments that are SEO-optimized and user-intent aligned.
• Hyper-personalized content: AI will tailor every interaction and content piece to individual users, increasing relevance and improving rankings.

Our AI and SEO approach at Making Science

At Making Science, we stay ahead of these shifts through a dedicated SEO and Content TECH & AI friendly strategy, powered by our proprietary technology Trust Generative AI. This platform transforms how we scale and optimize content, adapting it to current search engine demands and user behavior.

We guide our clients through this transition, helping them identify opportunities, scale content production, and strengthen long-term organic visibility with confidence.

Want to know how we can help your brand grow? Let’s talk.

Conclusion

Artificial intelligence in ecommerce is more than a trend, it’s the strategic engine behind personalization, automation, and search performance. From improving UX and engagement to optimizing content and metadata, AI empowers brands to scale efficiently and win in the SERPs. As AI continues to evolve, integrating it into your SEO strategy will be key to staying competitive in today’s digital economy.

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.

What if your analysis tool could think with you instead of just giving you data?

Artificial intelligence, especially its generative version, is changing the game for data analysts. It’s no longer just about visualizing; it’s about discovering, predicting, and acting in real-time with unprecedented efficiency.

In this post, we’ll explain what generative AI applied to analytics is, why it’s transforming how data teams work, and most importantly, how you can start using it today to become more productive and generate a greater impact in your organization. Because the future of analytics is already here, and it’s intelligent.

What Does Generative AI Bring to Data Analytics?

Generative AI doesn’t just analyze information: it understands it, interprets it, and proposes solutions. Thanks to advanced models like LLMs (Large Language Models), you can now:

• Ask questions in natural language about your data.
• Generate dashboards automatically.
• Detect patterns or anomalies before they become a problem.
• Automate reports and data narratives in seconds.

This means less time writing code and more time making strategic decisions.

Why Is It a Revolution for Analysts?

Generative artificial intelligence acts as a co-pilot for any analyst: it reduces repetitive tasks, proposes new approaches, and allows for more creative data exploration.

According to Gartner, by 2026, over 50% of analytics tasks will be automated using generative AI.

With this technology, analysts stop being mere “data translators” and become true business strategists.

How to Start Applying It in Your Daily Work

Here are some practical ways to incorporate artificial intelligence into your workflow:

• Analytical chatbots: Ask your data questions without writing a single line of SQL.
• Automatic insight generation: Get summaries and recommendations effortlessly.
• Code assistants: Use tools like GitHub Copilot or Dataiku to speed up your scripts.
• Scenario simulation: Predict future outcomes by simply entering key variables.

🧠 Making Science Tip: Start with small tasks, measure the impact, and scale progressively. The key is to move from curiosity to real adoption.

What About the Risks? Do I Lose Control of the Analysis?

No. On the contrary. Generative AI amplifies your capabilities, but you are still the one making the decisions. The important thing is to maintain a critical eye, always analyzing the model’s outputs and combining them with your expert business knowledge.

Remember: artificial intelligence isn’t here to replace you, but to empower you.

Conclusion: The Time Is Now

Artificial intelligence is no longer science fiction. It’s a real, powerful, and accessible tool for any data analyst. If you want to be more productive, make more informed decisions, and have a greater impact on your organization, it’s time to give generative AI a place in your daily routine.

👉 Are you already using any AI tools in your work? Tell us in the comments!

And if you found this post useful, share it with that colleague who still thinks Excel can do everything 😉

Because in the world of data… Foresighted analysis is twice as effective.

Landing Page Optimization: The Secret to Boosting Your Paid Media ROI

Are you pouring budget into perfectly set-up paid campaigns… and still not seeing the return you expected? You’re not alone. But here’s the twist: maybe your campaign isn’t the problem—your landing page might be.

In this post, we’ll explore how Landing Page Optimization (LPO) can radically improve your Paid Media performance, help you make the most of your investment, and give you the tools to convince your clients and teams to prioritize it.

Whether you’re part of a Paid Acquisition team, a Making Science account manager, or a client trying to scale smarter, this guide is your shortcut to unlocking greater results—without touching your campaign setup.

Why CRO Is Your Paid Media’s Best Friend

Let’s be clear: Conversion Rate Optimization (CRO) isn’t just a nice-to-have. It’s the missing piece in many Paid Media strategies.

You’re likely optimizing your audiences, bidding strategies, creatives, and platforms… but what happens after someone clicks your ad?

If your landing page fails to convert, even the best campaign won’t deliver. That’s where Landing Page Optimization steps in.

Did you know?
Brands that actively run CRO tests can see up to 30% increase in conversions—without increasing ad spend.

What Is Landing Page Optimization?

Simply put, Landing Page Optimization is the process of improving the elements on your landing pages to encourage more users to take action—buy, sign up, request a demo… you name it.

It involves:

• Aligning messaging with your ad copy
• Improving page speed and UX
• A/B testing layouts and CTAs
• Removing friction and distractions

When done right, LPO doesn’t just improve conversions—it maximizes your ROAS (Return On Ad Spend) and makes every click count.

When Should You Prioritize LPO?

Let’s say your:

• CTR is strong ✅
• Campaign setup is solid ✅
• CPC is competitive ✅
• But ROAS is down ❌

That’s your cue.

If you’ve optimized your campaigns and you’re still not hitting targets, it’s time to look at your landing pages.

We often see Paid Media teams focus heavily on traffic—but forget that the true goal is conversion.

How to Sell LPO to Clients and Internal Teams

Here’s how you can pitch Landing Page Optimization with confidence:

1. Speak in ROI:
   Explain how LPO gets more value from the same budget.
2. Share quick wins:
   Clients love tangible results. Show A/B test examples with before/after metrics.
3. Highlight the opportunity cost:
   A weak landing page wastes media spend. It’s like sending traffic into a leaky funnel.
4. Align with business goals:
   Talk about revenue, leads, and growth—not just clicks or impressions.

💡 Pro tip: Ask the client, “What if we could increase your conversions by 15% without increasing your media budget?” That’s the LPO effect.

Real Impact, Real Fast

Unlike some long-term strategies, Landing Page Optimization can bring fast, measurable improvements.

Run a test. Get the data. Optimize. Repeat.

💥 Example: One Making Science client saw a 27% lift in lead volume after 3 weeks of LPO testing—with no increase in ad spend.

Conclusion: Don’t Let a Perfect Campaign Fall Flat

Landing Page Optimization is often the unsung hero of Paid Media success. When campaign setups are already tight, this is where real growth happens.

So next time your ROAS drops despite strong performance metrics, don’t panic. Think landing pages. Think CRO. Think opportunity.

Want to keep your media spend from going down the drain?
Start optimizing where it truly counts—after the click.

👉 Got a landing page in mind? Let’s test it. Let’s improve it. Let’s boost your Paid Media performance—together.

Still sending traffic to the same old page?
You might be paying for visits, not conversions. Let’s change that.

💬 Have questions or success stories? Drop them in the comments—we’d love to hear from you.

📊In today’s fast-paced B2C world, simply having customer data isn’t enough. Businesses are swimming in information – from website visits and past purchases to social media interactions and customer service queries.

💡The real challenge is making sense of it all and using it to genuinely increase sales.

💡This is where Salesforce Data Cloud steps in, offering a powerful way to transform raw data into actionable insights and drive significant growth.

❓What’s the Big Deal with Data in B2C?

Think about it: every customer interaction leaves a digital footprint. For B2C companies, understanding these footprints is key. If you know what your customers like, how they behave, and what their preferences are, you can offer them exactly what they need, at the right time, and through the right channel.

🎯This personalized approach isn’t just a nice-to-have anymore; it’s a sales imperative.

🚀How Salesforce Data Cloud Makes Data Work for You

Salesforce Data Cloud isn’t just another database; it’s a sophisticated platform designed to unify all your customer data in one place. Imagine having a single, comprehensive view of every customer, no matter where their information originated. This “single source of truth” allows you to:

• Understand Your Customers Deeper: By bringing together data from marketing, sales, service, and e-commerce, Data Cloud creates rich, 360-degree customer profiles. You can see their entire journey, from their first interaction to their latest purchase, and beyond.
• Segment Your Audience Smarter: Gone are the days of broad marketing campaigns. With unified data, you can create highly specific customer segments based on detailed behaviors, demographics, and preferences. This means sending the right message to the right person.
• Personalize Experiences at Scale: Once you understand your segments, Data Cloud enables you to personalize every touchpoint. From tailored product recommendations on your website to customized email offers and relevant ad placements, personalization makes customers feel understood and valued.
• Drive Proactive Engagements: With real-time data insights, you can anticipate customer needs and engage them proactively. For example, if a customer browses a specific product category repeatedly, you can send them a timely offer or information about those items, increasing the likelihood of a sale.

💰From Data to Dollars: The Sales Impact

The direct link between Salesforce Data Cloud and increased B2C sales is clear. When you understand your customers intimately and engage with them personally, several things happen:

• Higher Conversion Rates: Relevant offers and personalized experiences lead to more purchases.
• Increased Average Order Value: When customers find exactly what they’re looking for, or discover related products they genuinely need, they tend to spend more.
• Improved Customer Loyalty: Personalized interactions build trust and make customers feel valued, encouraging repeat business and long-term relationships.
• Optimized Marketing Spend: By targeting the right customers with the right message, your marketing efforts become more efficient and yield a better return on investment.

✅The Bottom Line

Salesforce Data Cloud empowers B2C businesses to move beyond scattered data and embrace a truly data-driven approach to sales growth. By unifying customer information, enabling smarter segmentation, and facilitating highly personalized experiences, it allows companies to connect with their customers on a deeper level, ultimately leading to significant increases in revenue and customer loyalty.

🤝Making Science has extensive experience in implementing and optimizing these types of Salesforce solutions, helping businesses unlock the full potential of their customer data to achieve their sales goals.