Introduction: Uncover the Real Impact of Every Marketing Investment

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

The CMO’s Dilemma: Spending or Investing Wisely?

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

What is Incrementality and Why Is It Your Best Ally?

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

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

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

How to Measure Incrementality: The Tests You Need

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

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

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

2. Holdout Group Tests:

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

3. Econometric Models (MMM with Incremental Component):

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

Incrementality: Your Compass for Testing New Channels

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

Conclusion: Unlock True Potential with Incrementality

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

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

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

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

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

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

The Pillars of Your Data Foundation for AI

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

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

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

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

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

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

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

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

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

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

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

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

What is Clickless Advertising and Why is It Gaining Ground?

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

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

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

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

GMP: Your Ally for Measuring What Cannot Be Clicked

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

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

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

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

Strategies That Work (Even if No One Clicks)

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

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

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

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

Real-Life Cases That Prove It

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

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

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

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

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

Does Your Hotel Speak the Same Language as Your Guests?

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

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

Step 1: Define Your Audience and Identify Key Signals

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

Ask yourself:

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

Some key variables in the hotel sector include:

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

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

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

Step 2: Build Modular and Scalable Creatives in Studio

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

Build a simple data feed featuring:

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

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

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

Step 3: Activate the Campaign in Campaign Manager 360

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

Basic Checklist:

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

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

Step 4: Analyze, Adjust, and Evolve

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

Key metrics to monitor:

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

Iterate and Optimize:

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

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

Conclusion: Personalization That Drives Bookings (and Results)

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

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

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

Introduction: Navigate the Data Maze and Decide with Confidence

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

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

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

Your Measurement Arsenal: When to Use Each Tool

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

1. Attribution

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

2. Marketing Mix Modeling (MMM)

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

3. Budget Allocator

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

4. Brand Lift Studies

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

The Perfect Synergy: How to Combine Your Measurement Tools

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

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

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

Conclusion: Your Marketing Future Depends on Smart Measurement

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

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

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

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

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

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

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

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

Does Google penalize AI-generated content?

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

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

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

How keyword research is evolving with AI

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

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

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

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

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

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

Key takeaways

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

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

Introduction

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

What is CM360?

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

Who uses it?

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

Why is it relevant now?

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

How do we achieve it?

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

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

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

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

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

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

The key is knowing where to focus.

What do we have left to cover?

Optimization of the initial setup

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

Reporting automation

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

Implementation of cookieless strategies

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

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

Why is it important to keep improving in CM360?

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

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

Conclusion: Move forward with a steady pace

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

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

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.

[Date to be agreed] — Making Science, a global consulting firm specializing in AI-powered digital acceleration and performance marketing, has today announced the launch of Creative Hub, a game-changing performance AI tool designed to give marketers full control over how they can create, measure, optimize, and scale creative assets for advertising in the age of generative AI.

Unlike other AI creative development tools available on the market, Creative Hub provides brand teams with full control over the creative process while leveraging advanced generative AI to quantify creative elements, analyze their impact, and provide actionable insights to improve campaign effectiveness. This unique technology empowers marketers to make data-driven decisions about their creative assets, ensuring every visual and message statistically correlates with business KPIs.

Whether it’s the inclusion of people; the number of people; close-ups; distance; light; shade; nighttime or daylight; nature or city backdrop, as just a few examples. Every single creative attribute is analyzed and refreshed so that the creative performance gets stronger, not weaker, over time. This process is a powerful multivariable analysis, with all attributes analyzed together to provide understanding about how one attribute affects the others.

“Automating the creative process with AI isn’t a new concept, but enhancing and optimizing ad creative, with full control, is. Creative Hub represents the next evolution in performance marketing,” said José Antonio Martínez Aguilar (JAMA), Founder and CEO of Making Science. “With Creative Hub, our clients can overcome the challenge of creative fatigue to rapidly refresh creatives based on what the data shows is working without handing over the creative process to a black box. You’re not guessing; you’re optimizing with purpose, while also ensuring that the brand messaging is consistent”.

JAMA’s message is echoed by one of Creative Hub’s early adopters, hotel chain Bahia Principe. 

“Since integrating ad-machina technology into our operations, we have experienced a fundamental transformation in our ability to manage and optimize our visual assets,” said Enrique Ortiz de Zárate, Digital Acquisition Manager at Bahia Principe. “It has allowed us to scale the production and adaptation of our creative to an unprecedented level. We can generate variants of our ads for a myriad of formats and audiences, ensuring that every image, or video we use for our holiday destinations resonates uniquely with the ideal customer. This has given us massive personalization without compromising the visual quality that defines us as a brand.” 

By freeing up the creative teams from the most repetitive tasks, ad-machina has enabled the hotel chain to spend more time on strategic ideation and less on manual adaptation. In turn, the company has experienced a remarkable increase in the relevance and performance of its campaigns, directly linked to the implementation of ad-machina. 

“Our CTR has increased by over 43% and web traffic by more than 8%,” remarked Ortiz de Zárate. “In pure brand terms, demand has grown by almost 27% and clicks by 12.9%, with our average basket value increasing by over 13%. Furthermore, our brand and destination bookings have increased by 68% and revenue by over 61%, in addition to a 28% increase in CVR.”

JAMA explained, “With Creative Hub, ad-machina not only automates 80% of tasks that consume creative time, such as image and video resizing or copy update and variation management, but it goes a step further through the integration of agentic AI. This technology allows not only autonomy but also the decision-making capability and control over every aspect of the campaign—something that becomes fundamental as AI becomes more autonomous.”

Having pioneered the development of automation tools for performance marketing with the launch of ad-machina almost a decade ago, the addition of Creative Hub to Making Science’s ad-machina portfolio is another way in which the company is setting a new standard for the industry. 

Key features and benefits include:

• Quantifiable creativity: Creative Hub fuses AI and traditional ad production to push creative boundaries and turn subjective creative choices into measurable data points.
• Enhanced campaign performance: Clients can achieve up to 20% more sales, 80% faster, through AI-driven creative optimization and rapid asset modification.
• Creative control: Brands can retain full creative oversight while harnessing the power of AI for design and production, ensuring brand integrity and originality.

“The differentiation point for ad-machina tools, including Creative Hub, is performance. Ad-machina was originally developed for Search with textual ads by utilizing the information provided by the consumer to personalize the message. The introduction of generative AI has accelerated the evolution of our software to generate text as well as enable image and video, and empower teams to analyze and optimize each element, resulting in a bigger uplift,” concluded JAMA.

Within the continuously evolving landscape of advertising, Making Science remains ahead of the curve, helping businesses accelerate growth and unlock the full potential of their creative assets.

To find out more about Making Science’s ad-machina platform and Creative Hub, visit www.ad-machina.com

Slow IT is dead. In a world where speed defines winners, sticking to old ways means falling behind. Businesses that fail to innovate at speed while ensuring security and scalability risk being left behind. Traditional IT models can no longer handle the relentless demand for rapid software releases, resilient cloud infrastructures, and frictionless user experiences. This is where DevOps steps in, not as a mere technical fix but as a strategic weapon for survival and growth.

Companies that successfully integrate DevOps see faster time-to-market, reduced costs, and improved system reliability. Research shows that high-performing DevOps teams:

• Deploy software 30 times more frequently than traditional IT teams
• Experience 75% fewer failed deployments
• Recover from failures 24 times faster

As businesses accelerate their cloud adoption, Google Cloud’s DevOps Specialization serves as a benchmark for expertise in delivering these benefits. Making Science recently achieved this specialization, reinforcing our ability to help companies automate operations, enhance security, and scale cloud environments efficiently.

How DevOps Delivers Measurable Business Value

1. Accelerating Software Delivery with Automation

Companies that rely on manual development and deployment processes often struggle with long release cycles and inconsistent software quality. DevOps introduces continuous integration and continuous deployment (CI/CD) pipelines, enabling organizations to:

• Deploy new features faster and more frequently
• Reduce human error by automating repetitive tasks
• Improve collaboration between development and operations teams

Use Case: An e-commerce company struggling with frequent website crashes during high-traffic sales events implemented DevOps automation to streamline deployments. By automating testing and release management, they reduced deployment time from weeks to hours, ensuring a seamless shopping experience for customers.

2. Enhancing Security Without Slowing Innovation

Security is often treated as a separate process, leading to vulnerabilities being detected too late in the development cycle. DevSecOps, a key component of DevOps, integrates security checks from the start, reducing risks while maintaining agility. Businesses benefit from:

• Automated security scans and compliance checks
• Faster identification and resolution of vulnerabilities
• Reduced downtime due to security incidents

Use Case: A financial services company dealing with strict regulatory requirements adopted DevSecOps to automate compliance reporting and security audits. This cut their compliance costs while ensuring that every software update met industry standards.

3. Scaling Cloud Infrastructure Efficiently

Many organizations face challenges in scaling their applications without over-provisioning resources and inflating costs. DevOps, combined with Google Cloud’s scalable infrastructure, enables:

• Auto-scaling to handle traffic spikes efficiently
• Cost optimization by aligning cloud resources with demand
• Improved system resilience with automated failover mechanisms

Use Case: A telecom provider expanded its services to new markets but needed to ensure consistent application performance across different regions. By adopting DevOps practices, they optimized their cloud infrastructure, reducing server downtime and lowering cloud costs. 

Why DevOps is Now a Competitive Advantage

Businesses that embrace DevOps gain operational efficiency, stronger security, and cost savings, but more importantly, they stay ahead of the competition. DevOps is no longer just for tech companies—retailers, banks, healthcare providers, and manufacturers are all leveraging it to:

• Reduce time-to-market for new products and services
• Optimize IT and development costs with automation
• Strengthen security while maintaining agility
• Enhance customer experiences with more reliable applications

With digital transformation accelerating across industries, companies that fail to adopt DevOps risk falling behind. A modern business strategy must include automated, secure, and scalable cloud operations—which is exactly what DevOps enables.

How to Get Started with DevOps for Your Business

Implementing DevOps requires more than just tools; it involves a cultural and operational shift. Here are key steps businesses can take:

1. Assess current processes – Identify bottlenecks in development, deployment, and security workflows.
2. Automate where possible – Introduce CI/CD pipelines, infrastructure as code (IaC), and automated security testing.
3. Adopt cloud-native practices – Use scalable cloud infrastructure, serverless computing, and containerization.
4. Ensure security is built-in – Implement DevSecOps to maintain compliance without slowing innovation.
5. Partner with specialists – Work with certified experts to accelerate adoption and maximize impact.

Future-Proofing Your Business with DevOps

DevOps isn’t just about improving IT efficiency—it’s about enabling business growth. Companies that integrate DevOps into their cloud strategy, security model, and automation efforts gain a significant edge.

Google Cloud’s DevOps Specialization provides reliability for businesses, ensuring they wor with proven experts in cloud transformation. Making Science, with its six Google Cloud specializations, offers end-to-end support for companies looking to:

• Scale cloud operations efficiently
• Strengthen security while accelerating innovation
• Reduce costs through automation and optimized cloud usage
• Improve software reliability and customer satisfaction

Staying ahead in the digital race requires more than just technology… It demands a shift in mindset and strategy.

Want to explore how DevOps can transform your business? Get in touch with our team to discuss a tailored strategy that aligns with your goals.