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.

Are you investing heavily in digital ads but not seeing the sales growth you expect? You drive traffic, your campaigns are running, but the final conversion numbers feel lackluster? What if you could significantly increase your revenue without spending a single extra euro on advertising?

This is where Conversion Rate Optimization (CRO) comes in. This post will show you what CRO is, why it’s the non-negotiable core of any modern digital plan, and how you can use it to transform your e-commerce performance. A strong CRO strategy is not just about small tweaks; it’s about fundamentally enhancing the user experience to maximize the value of every single visitor.

Ready to turn more clicks into loyal customers? Let’s dive in.

Beyond the Acronym: What is CRO?

At its heart, Conversion Rate Optimization (CRO) is the systematic process of increasing the percentage of website visitors who take a desired action — whether that’s making a purchase, signing up for a newsletter, or filling out a contact form.

It’s not about guesswork or blindly changing the color of a button. True CRO is a blend of art and science. It involves deep analysis of user behavior, data-driven hypotheses, and rigorous A/B testing to understand what truly motivates your audience. The ultimate goal is to remove friction and make it as easy and enjoyable as possible for a user to convert.

Why Your E-commerce Can’t Afford to Ignore CRO

In a competitive market, driving traffic is expensive. Whether you’re investing in SEA, social media, or content marketing, every visitor comes at a cost. CRO is what ensures that investment isn’t wasted.

Think of it this way: if your website converts at 1% and you get 1,000 visitors, you get 10 sales. If you can achieve a conversion uplift to 2% through a smart CRO strategy, you’ve just doubled your sales to 20 from the exact same amount of traffic.

This is the power of optimization. It’s about squeezing more value from the traffic you already have, leading to:

• Higher ROI: Get more revenue from your existing marketing spend.
• Better Customer Insights: Learn what your customers actually want and need.
• Enhanced User Experience: A happy user is more likely to return and become a loyal customer.

The Pillars of a Powerful CRO Strategy

A successful CRO process isn’t random; it’s a continuous cycle built on a solid foundation. This is how a professional strategy works:

1. Analyze & Research: We start with data. Using tools like Google Analytics, heatmaps, and session recordings, we identify where users are dropping off or struggling. This isn’t just about numbers; it’s about understanding the why behind user actions.
2. Hypothesize: Based on the analysis, we form a clear, testable hypothesis. For example: “We believe that by simplifying the checkout form from five steps to three, we will reduce cart abandonment by 15% because it reduces user effort.”
3. Test & Implement: We use A/B testing to compare the original version (Control) against the new version (Variation). This lets data-driven decisions—not opinions—determine the winner. The winning version is then implemented.
4. Learn & Repeat: The process never truly ends. Every test provides valuable insights that fuel the next round of optimizations, creating a cycle of continuous improvement and conversion uplift.

CRO: The Engine That Powers Your Entire Digital Investment

Here’s the most critical takeaway: CRO maximizes the effectiveness of everything else you do.

You can have the best SEA campaigns in the world, driving thousands of highly qualified users to your site. But if they land on a page that is confusing, slow, or untrustworthy, that ad spend is effectively wasted. A poor user experience is the silent killer of ROI.

A robust CRO strategy works hand-in-hand with your acquisition channels. By constantly enhancing your landing pages and checkout flows, you ensure that the traffic you pay for has the highest possible chance of converting. A small uplift in your site’s performance can be the difference between a break-even campaign and a highly profitable one.

Conclusion: Stop Filling a Leaky Bucket

In summary, CRO is far more than a technical tactic; it is the strategic heart of digital success. It’s the disciplined process of understanding your users, enhancing their journey, and ensuring every euro you invest in marketing delivers the maximum possible return.

At Making Science, we see CRO as the essential bridge between attracting an audience and growing a business. Ignoring it is like trying to fill a leaky bucket—you can keep pouring more water in, but you’ll never get full.

What’s the biggest friction point you’ve noticed on your own e-commerce site? Share your thoughts in the comments below!

Stop filling the leaky bucket. Start plugging the holes with a solid CRO strategy and watch your business thrive.

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.

In the fast-paced world of customer service, every second counts. Customers expect quick, efficient, and personalized support, while businesses strive to optimize their operations and keep agents productive. This is where Salesforce Service Voice comes in, a game-changer designed to seamlessly integrate voice capabilities directly into the agent’s workspace, leading to significant enhancements in both agent productivity and customer satisfaction.

The Challenge: Balancing Speed with Quality

Traditionally, handling customer calls has often meant agents juggling multiple screens, systems, and applications. This fragmented workflow can lead to delays, errors, and a frustrating experience for both the agent and the customer. Agents spend valuable time searching for information, while customers wait on hold or have to repeat their issues. This inefficiency directly impacts resolution times and, consequently, customer happiness.

How Salesforce Service Voice Transforms the Service Experience

Salesforce Service Voice tackles these challenges head-on by bringing the power of the contact center directly into the Salesforce Service Cloud console. This integration offers several key benefits:

• Unified Agent Workspace: Agents no longer need to switch between different applications. Voice calls are seamlessly routed and managed within the Service Cloud console, where all customer data, case history, and relevant information are readily available. This single pane of glass reduces clicks and context switching, allowing agents to focus on the conversation.
• Real-time Customer Insights: As a call comes in, Service Voice intelligently pulls up the customer’s complete profile, including past interactions, purchase history, and even sentiment analysis from previous calls. This instant access to crucial information empowers agents to provide personalized and informed support from the very first “hello.”
• Automated Call Logging and Wrap-up: After a call, Service Voice can automatically transcribe the conversation and even summarize key points, creating a detailed call log. This drastically reduces the time agents spend on post-call administrative tasks, freeing them up for more customer interactions.
• AI-Powered Assistance: Leveraging Salesforce’s Einstein AI, Service Voice can offer real-time suggestions and knowledge articles to agents during a call. This intelligent guidance ensures agents have the right answers at their fingertips, leading to faster resolutions and fewer escalations.
• Enhanced Coaching and Quality Assurance: Call recordings and transcriptions provide valuable data for supervisors to coach agents effectively and ensure consistent service quality.

The Impact: Happier Agents, Happier Customers

The benefits of Salesforce Service Voice are tangible and far-reaching:

• Increased Agent Productivity: By streamlining workflows, automating tasks, and providing instant access to information, agents can handle more calls, resolve issues faster, and reduce their average handling time. This leads to a more efficient contact center operation.
• Boosted Customer Satisfaction: Customers receive faster, more personalized, and accurate support. They feel heard and understood, leading to higher satisfaction, increased loyalty, and a stronger brand reputation.
• Reduced Agent Burnout: A less fragmented and more efficient workflow reduces stress and frustration for agents, contributing to a more positive work environment and lower attrition rates.

The Bottom Line

Salesforce Service Voice is more than just a telephony integration; it’s a strategic tool that redefines how B2C companies deliver customer service. By uniting voice capabilities with comprehensive customer data and AI-powered insights, it empowers agents to be more productive and effective, ultimately leading to exceptional customer experiences and a significant competitive advantage.

In the ever-changing and highly competitive retail landscape, achieving sustained growth requires an approach that leverages customer data and evolving shopping patterns, embraces cutting-edge AI technology for speed and scale, and seamlessly integrates online and offline customer journeys. 

At Making Science, our proven omnichannel retail innovation framework, powered by advanced AI and built upon the robust Google Marketing Platform (GMP), is designed to help retailers not only meet but exceed their performance objectives.

Our framework is designed around three foundational pillars: unifying and leveraging the deep first-party data that almost all retailers have within their walls, activating marketing strategies through best-in-class technology solutions, and enabling your organization’s data readiness for a future with advanced AI. 

Unifying First-Party Data: Your Foundation for Success

At the core of any successful AI-driven strategy lies high-quality data. Most omnichannel retailers have no shortage of first-party and sales data stored within their walls; it’s just a question of how to use it in a privacy-compliant way. As a retailer, we emphasize the critical importance of collecting comprehensive, accurate, and real-time customer and conversion data, whether you operate online, offline, or both.

By leveraging the Google Marketing Platform, organizations can effectively unify and deploy their first-party data, creating a rich and actionable foundation for AI success. This robust data pipeline is the fuel that powers AI, enabling it to remix, scale, and optimize campaigns with unparalleled efficiency. Ensuring privacy-compliant data inflow into Google platforms is paramount for achieving optimal and lasting results. 

Fueling Intelligent Activation: Maximizing Performance Across Channels

Leveraging the cutting-edge AI innovations within Google Ads and Google Marketing Platform is a key step in driving superior digital ad performance. 

This includes embedded AI tools like Performance Max, which optimizes campaigns across Google’s entire inventory, from Search and Shopping to YouTube and Gmail. When activated within GMP’s Search Ads 360 (SA360), retailers are able to maximize performance through goal-based bidding with deduplicated conversion data, powered by Google’s auction-bidding technology. This ensures that every bid aligns with real business goals, maximizing conversion rates and return on ad spend.

Shifting from Search to Video and Display, Google’s Demand Gen campaigns, run in GMP’s Display & Video 360 (DV360), are utilized to spark discovery and capture new demand earlier in the marketing funnel. By serving visually appealing, multi-format ads on Google’s most impactful surfaces like YouTube and Discover, we can boost brand presence and foster increased consideration. The integration with DV360 unlocks advanced capabilities such as unified customer views, reach and frequency management, and third-party brand safety verification. 

Enabling Data Readiness for Advanced AI: The Test & Learn Imperative

The journey to AI excellence in retail is continuous and can feel uncomfortable at times. Adopting a “test and learn” mindset, encouraging ongoing experimentation and optimization, can help to ease this transition and allow you to see which combination of tools works best for your organization.

Through the Google Marketing Platform, retailers are best positioned to integrate and scale more advanced AI features, including by licensing specialized third-party AI technology. This readiness ensures that as AI evolves, so too does your marketing strategy, allowing for agile adaptation and sustained competitive advantage.

Key Takeaways for Retail AI Innovation:

• Your Data Equals Your Success: Data is the fuel that powers AI to remix, scale, and optimize your campaigns. AI can only be effective when we feed it good data to make good decisions. From tagging to 1PD connections, ensuring that your privacy-compliant customer and conversion data coming into Google is accurate, complete, and real-time will ensure your success.
• Leverage Google AI Innovation: Here we have shown the strategies and benefits of combining Google Ads AI innovation with best-in-class enterprise Ad Tech from the Google Marketing Platform. From Pmax to Demand Gen, retailers who activate within GMP are able to unlock advanced marketing features.
• Think Omni Retail: We have to meet our customers where they are today. While e-commerce and online shopping get a lot of attention, offline physical stores remain the core of many retailers’ businesses. For these retailers, we must consider foot traffic in physical stores.
• Embrace a Test & Learn Mindset: And finally, it is essential that we embrace a test and learn philosophy. Working with partners like Google and Making Science, we can help to separate the signal from the noise, working in collaboration over time, to grow your business.

Retailers can unlock unprecedented levels of performance, drive profitable growth, and remain at the forefront of AI-powered marketing. To learn more about how to adopt this framework, get in touch with our specialist team at Making Science.

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In today’s crowded digital marketplace, e-commerce businesses face a relentless challenge: standing out and converting browsers into loyal buyers. Generic, one-size-fits-all approaches simply don’t cut it anymore. Customers expect experiences tailored specifically to them. This is where Salesforce Personalization unlocks a powerful advantage, transforming how online retailers connect with their audience and directly leading to a significant boost in e-commerce sales.

Why Personalization is No Longer Optional for E-commerce

Think about your own online shopping habits. Are you more likely to buy from a store that remembers your preferences, suggests products you genuinely might like, or sends you offers relevant to your past purchases? Chances are, the answer is yes. In fact, studies consistently show that consumers prefer personalized experiences and are more likely to convert when they receive them. Without personalization, e-commerce businesses risk losing customers to competitors who offer a more relevant and engaging journey.

How Salesforce Personalization Fuels Sales Growth

Salesforce Personalization isn’t just about adding a customer’s name to an email. It’s a sophisticated platform that uses data and artificial intelligence to understand individual customer behavior and deliver truly unique experiences across every touchpoint. Here’s how it drives sales:

• Real-time Behavioral Insights: Salesforce Personalization continuously collects and analyzes customer interactions on your website, app, and other channels. It understands what products they view, what they add to their cart, what they click on, and even how long they linger on a page. This real-time understanding allows for immediate, relevant responses.
• Dynamic Product Recommendations: Based on individual Browse history, purchase patterns, and even the behavior of similar customers, the platform can display highly relevant product recommendations. This could be “customers who bought this also bought…” or “you might like this based on your recent views,” significantly increasing the likelihood of an impulse or add-on purchase.
• Personalized Website Experiences: Imagine a homepage that changes for each visitor, highlighting products they’ve shown interest in, or promotions relevant to their past interactions. Salesforce Personalization can dynamically adjust content, banners, and even navigation paths to create a unique and highly engaging Browse experience.
• Tailored Email and Mobile Campaigns: Moving beyond generic newsletters, Salesforce Personalization enables segmented and individualized email campaigns. This means sending abandoned cart reminders with relevant product suggestions, personalized sale alerts, or follow-up emails based on recent purchases, all designed to encourage conversion.
• Optimized Offers and Promotions: By understanding a customer’s value and preferences, businesses can deliver targeted discounts and promotions that are more likely to resonate and drive a purchase, avoiding wasted marketing spend on irrelevant offers.

The Tangible Impact on Your Bottom Line

The direct result of implementing Salesforce Personalization is clear:

• Higher Conversion Rates: When product suggestions are relevant and experiences are tailored, customers are far more likely to complete a purchase.
• Increased Average Order Value (AOV): Effective recommendations encourage customers to add more items to their cart, boosting the overall value of each transaction.
• Enhanced Customer Loyalty: A personalized experience makes customers feel valued and understood, fostering stronger relationships, encouraging repeat purchases, and turning one-time buyers into lifelong advocates.
• Reduced Cart Abandonment: Timely, personalized reminders and incentives can bring customers back to complete their purchases, recovering potentially lost sales.

The Bottom Line

In the competitive e-commerce landscape, personalization is no longer a luxury; it’s a strategic imperative for sustainable growth. Salesforce Personalization provides the tools to understand your customers deeply and engage with them on a truly individual level, directly translating into higher conversion rates, increased sales, and a stronger, more loyal customer base.

There’s a question that marketing teams are asking more and more often—and it’s not “Should we do influencer marketing?” It’s: How can we integrate it better? 🤔

Because it’s no longer about one-off campaigns or scattered creative collaborations throughout the year. Influencer marketing has earned its place—not as an add-on, but as a strategic growth channel that drives results on multiple fronts: attention, affinity, conversion, community, content, and insights. 📈

The difference now isn’t whether you’re doing it. It’s where you place it within your brand and business architecture. 🧠

And that requires a shift in perspective, from viewing influencers as occasional activations to understanding their cross-functional role within the brand ecosystem.

We’ve identified four key principles that are making a difference in the strategies that actually work. They’re not magic formulas, but they do define how leading brands are integrating this channel with clarity and vision. 🚀

When Content Connects, Business Grows

Leading brands don’t see creator content as a tactical boost or a nice-to-have inspirational touch. They integrate it as a core part of their communication, distribution, and audience relationship systems. Because they’ve grasped something essential: content with credibility moves people more than any brand promise can.

When a brand expresses itself through people with cultural authority, it’s not just seen. It’s felt. And what is felt is remembered. Shared. Bought. Defended.

We’re not talking about a trend or a new performance channel. We’re talking about a sharper, more genuine way to connect with people—where attention is no longer bought, but earned. And it’s earned with content that delivers value, reflects values, triggers emotion, and builds conversation. 💬

According to the 2025 Social Media Study by IAB Spain, 48% of users say they check social media before making a purchase, and 44% state that their final decision was influenced by the content they saw there. This percentage rises to 66% among Generation Z. This shows that when content truly connects with the audience, it directly impacts buying behavior. 📱🛍️

A Living Network of Influence—Not Just a Collection of Collaborations

The strongest strategies aren’t measured by the number of posts or the variety of profiles in a spreadsheet. They’re measured by the consistency of the relationship between brand, creator, and audience. 🔁

The value isn’t only in the content that gets published, but in what that content builds over time: narrative, reputation, positioning.

That’s why more brands are thinking in terms of networks of affinity, not “influencer lists.”

They’re not chasing follower counts—they’re seeking alignment. They build long-term relationships with people who share their vision, codes, and style. And that allows them to amplify their message naturally, broadly, and meaningfully across channels. 

The difference between an influencer campaign and an influence strategy is simple: One makes an impact. The other makes an impact and sustains it.

According to CreatorIQ’s 2024 Benchmark Report, brands that foster long-term partnerships with creators see up to 38% higher engagement rates compared to one-off collaborations.

Influencer Marketing Is Not Just Communication—It’s Brand Intelligence

One of the greatest strengths of creator content is that it doesn’t just create impact. It reflects, informs and measures. Every piece of content, every reaction, every comment… is a live source of cultural data. 📡

It tells us how your audience speaks. What moves them. What they share. What they question. What they reject.

That’s why a well-integrated strategy not only drives media or sales KPIs—it also enhances positioning, the funnel, and business insights. The channel works best when it’s not operating in isolation, but when it’s connected to everything else. It’s not just another puzzle piece. It’s the thread that can tie many pieces together—and give them meaning. 

Integration Isn’t Doing More—It’s Making Everything Work Together

Here’s one of the most common mistakes: confusing integration with accumulation. You don’t need more formats, more platforms, more scattered actions. You need your pieces to speak to each other. Influencer marketing should drive business, not just visibility. And your brand should show up where things are happening—not as a spectator, but as a part of the culture. 💡

The value doesn’t lie in “trying new things.” It lies in consolidating learnings, scaling what works, and sharpening what resonates. It’s not about making noise—it’s about having relevant presence. 📍

It’s not about putting your logo in more places, but about placing it in the right contexts, with the right people, in a consistent and coherent way. 

We see this every day. And if you’re reading this, you probably already know that it’s no longer about simply being present… it’s about doing it right.

Because in the end, the difference between just another campaign and a channel that reshapes your brand’s trajectory lies in how you choose to integrate it from now on.

Are you ready to make the leap and take your brand to the next level? 🚀

Last week, Campaign’s Media360 event in Brighton brought together a vibrant community of marketing and media professionals. The strong attendance and a packed agenda covering key trends, challenges, and opportunities clearly demonstrated the industry’s keen engagement. For Nick Waters, Global CEO Northern Europe at Making Science, the event offered a unique lens through which to view the evolving UK media landscape, delivering some surprising insights beyond the usual headlines.

Beyond the Usual Agenda: The Power of Resilience and Contrarian Thought

The event kicked off with a truly engaging interview with Jamie Laing, whose natural energy immediately set a dynamic tone. From his conversation, two powerful messages resonated deeply with Nick: the vital importance of resilience – the unwavering ability to push past countless “no’s” – and the courage of contrarian thinking, daring to make the illogical choice when intuition calls. This prompts Waters to question whether our industry has perhaps become too comfortable simply following the obvious path.

The Elephant in the Room: Where Was the AI Conversation?

Perhaps the most striking observation from Media360 was the unexpected underrepresentation of Artificial Intelligence. In an era where AI dominates global headlines and is undeniably central to the future of nearly every industry, its relatively limited presence in the content stream was notable. This raises crucial questions for Nick: Does the UK marketing community feel entirely on top of these rapid developments, is there an element of complacency, or has the truly transformative power of AI yet to be fully appreciated within this market? A direct consequence was also a noticeable lack of discussion around the agency ecosystem’s role in guiding advertisers through this monumental shift.

A Clear Spotlight: The “Media for Good” Movement

In stark contrast to the quietness around AI, the theme of “media for good” commanded significant attention. Discussions prominently featured topics such as diversity in media, pressing sustainability initiatives, decarbonization efforts, and the critical importance of supporting quality journalism. This strong emphasis clearly signals a significant and positive priority for the UK industry.

Navigating Channel Dynamics and Demographic Shifts

The event also provided fertile ground for debates on evolving media channels. The enduring relevance of Television, despite fragmentation and the rise of social media, was a key point. The notion that “social media killed the TV star” was confidently dismissed, underscoring TV’s continued powerful influence on national social culture. Discussions around the impact of Gen Z were also present, though the consensus suggested that their material influence on reshaping the industry is still an evolving story, perhaps predictably so given their nascent professional journey.

Conclusion: Re-evaluating Industry Priorities for the Future

Media360 offered a compelling snapshot of the UK media landscape’s current focus. With “media for good” so prominently featured and AI surprisingly relegated to the periphery, Nick Waters’ core question echoes: Has the UK industry truly found the right balance in its attention to what truly matters for tomorrow? At Making Science, we firmly believe that future success lies in a holistic approach, where societal responsibility goes hand-in-hand with an aggressive embrace of technological innovation, particularly AI. It’s about leveraging cutting-edge tools to enhance human impact and drive meaningful, sustainable growth for our clients.

At Making Science, we’ve always been committed to staying ahead of tech transformation. We’re excited to share that our UX/UI department is evolving into CX/AX Design – a change that represents our vision for the future of digital experiences.

This transition comes at a pivotal moment. After years of remarkable growth and innovation at Making Science, we’ve witnessed firsthand how rapidly the technology landscape is transforming. This evolution in our approach isn’t merely a rebranding – it’s a strategic shift that prepares our clients for the next wave of digital engagement.

Why we’re expanding our focus

For years, User Experience (UX) and User Interface (UI) have been the industry standard terms for describing digital product design. These concepts have served us well, focusing our attention on creating intuitive, beautiful interfaces for human users.

However, as noted UX pioneer Jakob Nielsen recently observed in his article “Hello AI Agents: Goodbye UI Design, RIP Accessibility,” we’re entering an era where direct human interaction with interfaces may no longer be the primary mode of digital engagement.

At Making Science, we’ve anticipated this shift. By expanding our focus to Customer Experience (CX) and Agent Experience (AX), we’re ensuring our work remains relevant and impactful in an increasingly AI-mediated world.

The dual future of design with CX and AX

Customer experience (CX)

CX takes a holistic view that extends beyond interface interactions:

• The entire customer journey across all touchpoints
• Emotional responses and satisfaction at each stage
• Brand perception before, during, and after engagement
• Seamless integration of online and offline experiences
• Service design and delivery

While UX focuses on how users interact with specific products, CX considers the entirety of a customer’s relationship with a brand or organization.

Agent experience (AX)

Here’s where we’re truly breaking new ground. Agent Experience (AX) recognizes the emerging reality that AI agents will increasingly mediate between humans and digital services:

• Designing for AI agents that navigate interfaces on behalf of users
• Creating structured data and content that both humans and AI can efficiently process
• Developing interaction patterns optimized for both direct human manipulation and agent-based operations
• Ensuring our digital products work seamlessly in an agent-first ecosystem

Transforming possibilities for our clients

This evolution significantly expands what we can deliver:

• Comprehensive ecosystem design: We now address not just how your product works, but how it fits into your customers’ lives and interacts with emerging technologies.
• Future-proofed digital assets: Your digital presence will be prepared for both traditional human users and the coming wave of AI agent interaction.
• Strategic advantage: Our approach bridges UX fundamentals with business strategy and technological innovation, positioning your brand ahead of competitors.
• Excellence across all touchpoints: While expanding our scope, we remain committed to creating beautiful, usable interfaces for direct human interaction.

Our unique AI methodology 

At Making Science, we’ve been developing our proprietary Synthetic Users Methodology to gain unprecedented insights into how both humans and AI agents interact with digital experiences.

This methodology has become our own “search for intelligent life” – uncovering behaviors and patterns that traditional methods simply can’t detect. The insights we’ve gained have been instrumental in our evolution toward CX/AX Design, allowing us to create experiences that not only meet current needs but anticipate future demands.

Honoring fundamentals while embracing the future

This strategic shift doesn’t abandon the principles that have guided exceptional design for decades. Rather, it expands our perspective to address new realities. The fundamentals of human psychology, visual design, and usability remain relevant – but they’re now applied in increasingly sophisticated contexts.

As Nielsen points out, AI agents don’t replace human users – they serve them. Our goal remains creating exceptional experiences that serve human needs, whether directly or through technological mediation.

Partner with Making Science

As we embrace this new approach, we invite forward-thinking organizations to join us in exploring the expanded possibilities of CX/AX Design. The tech landscape continues to evolve at a breathtaking pace, and together, we can create solutions that work brilliantly today while anticipating the needs of tomorrow.

Ready to transform your digital experience?

Our CX/AX Design team is ready to help elevate your digital presence. Whether you’re looking to enhance your customer journey, prepare for an AI-first future, or simply create more engaging digital experiences, we have the expertise and vision to help you succeed.

Are you tapping into the full potential of your digital data or just scratching the surface? Google Analytics 4 is here to change the rules of the game… but only if you know how to play.

📍 Introduction

Since its launch, Google Analytics 4 (GA4) has positioned itself as the new standard in digital analytics. But what makes it so special? And why are so many companies looking for Data Analyst profiles specialized in GA4?

In this post, we explore what GA4 is, why it has replaced Universal Analytics, what this change implies for your company, and how an analyst can turn data into real growth. If you manage digital channels, ecommerce, paid media or UX, then read on.

💡 Fun fact: according to Google, more than 50% of companies that have migrated to GA4 are still not properly exploiting their data due to a lack of analysts or advanced configuration.

🎯 What makes GA4 different?

1. It measures people, not just sessions

GA4 focuses on the user, not on visits. This allows you to analyze the real journey of your customers across channels, devices and platforms.

It no longer matters how many users visited your site, but who they are and what they do.

2. Personalized events: you decide what matters

No more measuring only page views. In GA4 you can track specific interactions: clicks, forms, scrolls, downloads etc. And the best part: everything is flexible, without depending on your IT team at every step.

3. Predictive models within everyone’s reach

GA4 gives you predictions such as conversion or abandonment probability, so you can prioritize actions based on data, not assumptions.

🧠 What if you knew which users are about to stop shopping… before they do?

4. Goodbye cookies, hello privacy

GA4 complies with regulations such as GDPR and adapts without cookies, which is key if your company wants to continue to scale without penalties.

👨‍💻 Why do you need a Data Analyst with GA4 experience?

It is simple: because having data is not the same as understanding it. Let alone acting on it.

✔️ An analyst turns data into decisions

• Configures relevant events and conversions
• Detects opportunities and problems before anyone else
• Relates data to business: sales, leads, profitability

✔️ Able to design useful dashboards for each team

A good analyst doesn’t just extract data, he translates it for Marketing, Product or C-Level. The result? Aligned teams and faster decisions.

✔️ Automate, predict and scale

With GA4 and BigQuery, your Data Analyst can build attribution models, automated reports, or identify hidden patterns that make (or lose) you money.

📌 Raw data is just noise. Advanced analytics turns it into music for your business.

🔚 Conclusion 

Google Analytics 4 has redefined how we measure and understand the digital experience.
However, to take advantage of its full potential, you need a Data Analyst who knows how to extract it, customize it and align it with your business strategy.

At Making Science, we help companies like yours turn analytics into impact. If you’re ready to transform your data into decisions, it’s time to take the next step.

🎯 Do you already have the person to turn your GA4 into a growth engine?

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Because data doesn’t change your business. The decisions you make with it do.