Unlocking the Potential of Performance Max: ad-machina for PMax is here

In the current competitive and unpredictable landscape, there is the challenge of connecting with customers at the right time and place. To effectively address this challenge with the right message, it is imperative to automate campaigns and optimize performance cost-effectively. The new Google Ads campaign type, Performance Max, offers the opportunity to establish an omnichannel and automated presence. Are you prepared for the amount of content generation required for this type of campaign? Can you afford to manually update all the assets of your company constantly? ad-machina makes it easier.

But first, what is Google Performance Max? 

Google Performance Max represents a paradigm shift in digital advertising, offering businesses an unprecedented level of control and optimization. Leveraging advanced machine learning algorithms, Performance Max enables advertisers to maximize their reach across all Google channels, including YouTube, Display, Search, Discover, Gmail, and Maps. But, it’s not as straightforward as it may seem. PMax campaigns demand a significant amount of content generation, which can prove to be overly demanding for the marketing department. For example, a key challenge in setting up a Performance Max campaign isn’t just about deciding on the bidding strategy or targeting the audience. It’s also about ensuring there’s a diverse range of assets available for each channel and an updated database. This is where ad-machina comes into play, enabling businesses to leverage PMax effectively while efficiently optimizing the team’s time.

What is ad-machina for PMax?

ad-machina arrives to help you optimize all your Performance Max campaigns. We provide substantial benefits such as streamlining the process of optimizing PMax campaigns, enabling companies to customize their ads with text, image and video based on search terms, and automating the adaptation of ads to changes in the business landscape. As a result, it’s crucial to synchronize Performance Max campaigns with these daily tactical and strategic decisions.

It offers three key enhancements:

• Enhanced assets
• Adaptive listing groups
• Fine-tuned search themes and audiences

Enhanced assets

ad-machina for PMax optimizes asset creation through automated processes, minimizing dependence on the creative team. By producing textual and audiovisual content for Performance Max campaigns, the platform incorporates essential details like offers, maximum discounts, minimum prices, and flagship products. Moreover, ad-machina strategically integrates the brand into visual assets, boosting brand visibility. This approach not only guarantees maximum impact but also facilitates precise measurement and optimization of visual creative templates, representing a significant advancement in campaign effectiveness and efficiency.

Adaptive listing groups

ad-machina for PMax transforms listing group management by integrating various data sources. By seamlessly connecting with Google Merchant feed and first-party data such as offer calendars, category manager recommendations, and insights from competitiveness monitoring tools, ad-machina for PMax establishes a strong basis for dynamic product grouping. This fusion of information facilitates agile decision-making, enabling precise adjustment of listings based on factors like price competitiveness, product margins, offer schedules, and category manager priorities. The outcome is a flexible and strategically aligned product lineup, poised for optimal profitability. This pioneering approach offers a substantial competitive advantage in the online marketplace.

Fine-tuned search themes and audiences

ad-machina for PMax employs sophisticated analysis of account search term history to curate the most impactful search themes for each listing group. This process guarantees peak performance by eliminating redundancy among asset groups. Furthermore, ad-machina doesn’t stop at search themes; it also crafts custom audiences. This innovative feature is designed to equip the Google Ads algorithm with the most refined signals available. These signals are characterized by their specificity and coherence, ensuring a targeted approach that maximizes campaign effectiveness. This strategic combination of search themes and custom audiences sets the stage for optimal results in online advertising efforts.

Conclusion

We know that having Google PMax is essential to maximize the performance of your campaigns, however having ad-machina for PMax is taking it a step further. You’ll still be able to communicate with your target audience through the appropriate channels, but with ad-machina, we make it easier for you to find the right message.

In today’s data-driven world, businesses require robust and scalable database solutions to manage their ever-growing data. Google Cloud Platform (GCP) offers a robust suite of database solutions designed to meet various needs, from small projects to large-scale enterprise applications. 

Each database model in Google Cloud  is tailored for specific use cases, balancing cost-effectiveness with powerful features like serverless architectures. This approach, where Google Cloud manages the server infrastructure and scaling, is particularly beneficial for databases by simplifying operations, enhancing scalability, and improving fault tolerance, all without manual server management intervention. 

In this blog post, we will explore the diverse range of databases available within Google Cloud, focusing on their unique capabilities and use cases across different categories: relational, in-memory, document, and key-value databases.

Why is this topic important?

Selecting the right database solution is pivotal for companies striving to thrive in the digital era. Efficient data management not only enhances application performance but also ensures seamless scalability to accommodate growing data volumes. Moreover, robust database solutions contribute to improved data security, compliance adherence, and overall operational efficiency. By understanding the features and benefits of different database models within GCP, businesses can make informed decisions that align with their specific requirements and long-term objectives.

The complexity of managing diverse data sets, ensuring high performance, maintaining scalability, and optimizing costs poses significant challenges for businesses. Traditional database solutions often struggle to keep pace with evolving demands, leading to performance bottlenecks, scalability issues, and inflated operational costs. Moreover, ensuring data security and compliance in an increasingly interconnected digital ecosystem presents additional challenges. GCP’s database solutions address these challenges by offering advanced features, seamless scalability, flexible pricing models, and robust security measures, empowering businesses to overcome obstacles and drive innovation.

Google Cloud Database Solutions: A spectrum of power and flexibility

GCP boasts a variety of database models, each catering to specific use cases. Whether you require the versatility of relational databases, the lightning-fast speed of in-memory solutions, or the scalability of NoSQL options, Google Cloud has you covered with four different types of database solutions -Relational, In-Memory, Document, and Key-Value- tailored for enhanced performance, scalability, cost efficiency, simplified management, and robust security. 

From Memorystore’s fast speeds to Cloud Spanner’s global consistency, GCP ensures efficient application functionality and user experience. As data volumes grow, GCP databases seamlessly scale while offering flexible pricing to optimize costs. Fully managed services free development teams from infrastructure management, allowing focus on innovation, while robust security features prioritize data protection.

Relational Databases: Ensuring data integrity and simplifying complex queries for business applications

1. Bare Metal Solution for Oracle

For users seeking minimal latency and optimal performance, GCP’s Bare Metal Solution is a standout choice. This setup is ideal for Oracle databases, providing direct access to hardware without the abstraction layers typical in virtualized environments. This results in reduced overhead and enhanced efficiency—key for applications demanding high-speed data processing.

2. Cloud SQL: Fully Managed and Scalable

Cloud SQL caters to those needing a managed relational database with robust features. It supports seamless migrations, integrates flawlessly with other GCP services like GKE and GCE, and ensures data security through encryption both at rest and in transit. Its flexible pricing adapts to various organizational needs, making it a go-to for diverse applications.

3. AlloyDB: The Popular Powerhouse

AlloyDB stands out in GCP’s portfolio as a highly popular choice, thanks to its advanced features over traditional PostgreSQL. This database supports massive scalability and high performance with its columnar data model and intelligent caching mechanisms. While AlloyDB’s cost might be higher, its capabilities justify the investment for enterprises requiring cutting-edge database technology.

4. Cloud Spanner: Global Consistency Redefined

Unique among its peers, Cloud Spanner offers a globally distributed design while maintaining strong consistency and a near-perfect uptime SLA of 99.999%. This database is ideal for applications that require reliable, wide-reaching data access without compromising on performance.

In-Memory Database: Enabling real-time experiences and lightning-fast data retrieval for users

For applications requiring ultra-fast data access, Memorystore provides in-memory data storage with response times under a millisecond. Available in both basic and standard tiers, it offers configurations tailored to different reliability and performance needs, including fault recovery and scalable resources.

Document Database: Offering flexibility to store and manage evolving data structures for content-rich applications

Firestore excels in managing document-oriented data with ease. It offers real-time synchronization, offline access, and robust query capabilities, making it perfect for dynamic apps that need to stay updated continuously. Its serverless approach ensures developers can focus on building features without managing the underlying infrastructure.

Key-Value Database: High performance and scalability for frequently accessed data, enhancing responsiveness 

When handling vast amounts of data with low latency, Cloud Bigtable is the solution. It supports extensive scalability and integrates seamlessly with the Hbase API, making it suitable for high-throughput applications such as real-time analytics and ad-tech.

Choosing the Right Database in Google Cloud Platform

The choice of a database in GCP largely depends on specific application needs and budget constraints. While AlloyDB currently stands as a popular choice due to its advanced features and broad adoption within Google’s services, each database model offers unique benefits. Understanding these options will help you select the most appropriate database solution, ensuring your applications run efficiently and cost-effectively.

Making Science: Your Trusted Guide in the GCP Database Landscape

Making Science has a wealth of knowledge and experience in navigating the world of GCP databases. Our team can assist you in assessing your needs, identifying the perfect database solution, and ensuring seamless integration within your GCP environment. Contact Making Science today and unlock the full potential of your data with the power of GCP’s database solutions!

In today’s digital landscape, APIs (Application Programming Interfaces) are key enablers of innovation, collaboration and digital transformation. They enable seamless communication and data exchange between applications, fostering collaboration and driving the creation of next-generation digital experiences. But managing APIs effectively can be a complex challenge. This is where Apigee by Google Cloud Platform comes in, a tool that empowers users to manage APIs with unparalleled scalability, security, and performance.

What is Apigee?

Apigee is a leading API management solution that empowers businesses to take control of their API strategy, acting as a front-end to backend services through proxies to the APIs themselves. These proxies manage backend service traffic, enforcing policies like rate limiting and security measures. Apigee supports various protocols including REST, SOAP, GraphQL, gRPC, and OpenAPI.

It goes beyond simply managing APIs; it unlocks significant business value by ensuring scalability, security, and performance. This blog post dives into the core functionalities of Apigee and explores how it can transform your business.

Basic Concepts:

What is an API?

APIs (Application Programming Interfaces) are sets of protocols that enable different software applications to interact and share data. They define methods and data formats, establishing a contract for integration within software development. Within Google Cloud, APIs are seen as standardization tools that allow developers to harness GCP services and integrate them seamlessly into their applications.

What is a RESTful API?

RESTful APIs adhere to REST (Representational State Transfer) principles, known for their speed, scalability, and flexibility in data handling. They facilitate data access through HTTP requests and are widely used in contemporary software development for their ability to interface with varied computing resources such as storage, databases, and machine learning services.

Apigee’s Powerhouse Features:

• AI-Powered Design: Duet AI streamlines API design using natural language, ensuring clear specifications and faster development.
• Enhanced API Hub: Manage APIs effectively with open-standard specs, auto-generated code (proxies, integrations), and support for Vertex AI/ChatGPT deployments.
• Advanced Security: Machine learning safeguards your APIs with automated threat detection and actionable recommendations.
• High-Performance Proxies: Unmatched traffic management and reliability ensure smooth API experiences.
• Deployment Flexibility: Apigee Hybrid offers hybrid and multi-cloud deployment options for on-premise or cloud environments.
• Simplified Development: Streamlined tools for design, testing, and documentation empower developers to build robust APIs efficiently.

Apigee: Powering Business Value Through Innovative Use Cases

Apigee goes beyond simply managing APIs; it empowers businesses to achieve real-world results. Here’s how Apigee tackles common challenges and unlocks strategic value:

• Fuel Cloud-Native Development: Build modern, scalable applications with on-demand scaling and load balancing capabilities.
  Unlock Legacy Data: Modernize legacy systems by creating secure, RESTful APIs that expose valuable functionalities. Apigee’s API proxies help modularize components for easier integration.
• Unmatched Security and Governance: Secure web applications and APIs with a layered approach combining Apigee, Cloud Armor, and reCAPTCHA Enterprise. Safeguard your APIs with advanced security features like automated threat detection, access controls, and API quota management. Maintain data privacy and ensure compliance with industry regulations.
• Monetize Your APIs: Generate new revenue streams by creating monetizable APIs with flexible pricing models (subscriptions, freemium, pay-per-use). A developer portal within Apigee streamlines discovery and consumption, fostering a thriving developer ecosystem.
• Empower Developers: Provide intuitive tools for API design, testing, and documentation, accelerating developer onboarding and innovation. Duet AI further streamlines development by generating code and specifications from natural language descriptions.
• Bridge the Digital Divide: Act as a bridge between legacy systems and modern cloud applications. Expose legacy functionalities through secure APIs, enabling seamless data exchange and a smoother digital transformation journey.
• Optimize Operations: Automate API management tasks, freeing up IT resources for strategic initiatives. Gain valuable insights from analytics dashboards to optimize API offerings and ensure smooth, reliable operations with features like traffic management, throttling, and security enforcements.

Investing in the Future

Apigee is a future-proof solution that scales with your business needs. Its multi-cloud support allows for flexible deployment across on-premise, private cloud, and public cloud environments. Additionally, Apigee readily integrates with other Google Cloud Platform services, creating a powerful ecosystem for building and managing scalable, secure, and innovative applications.

By leveraging Apigee’s comprehensive API management capabilities, businesses can unlock significant value, driving revenue growth, fostering innovation, and achieving a competitive edge in the digital landscape.

Unleashing Apigee’s full potential requires expertise alongside the technology. Making Science, a leading digital consultancy can help. Our certified professionals will partner with you to design a customized Apigee plan that tackles your specific needs, from legacy modernization to monetization. Contact us today to unlock Apigee’s power and embark on your future-proof API journey.

Cloud computing has revolutionized application development, and serverless computing is emerging as a powerful force within this landscape. This approach streamlines the process by offloading server management to cloud providers, allowing developers to focus solely on core functionalities.

While the term implies an absence of servers, serverless computing  refers to a development model where server provisioning and management become the responsibility of the cloud provider. Developers write code and define triggers (events) that initiate code execution. This frees them from the burden of infrastructure maintenance,  enabling:

• Faster development cycles: Focus on core functionalities instead of server management.
• Improved scalability: Automatic scaling based on traffic fluctuations ensures smooth operation.
• Reduced costs: Pay only for the resources used, eliminating fixed server costs.

Why serverless computing?

With the exponential growth in cloud computing, an increasing number of companies are opting for Serverless solutions. This style of developing and deploying applications continues to transform the tech industry due to its capacity to accelerate development processes, scalability, and efficiency.

Serverless architecture allows developers to focus on application logic without having to manage the underlying infrastructure. Therefore, they are only responsible for programming functions and trigger events. Meanwhile, cloud service providers are in charge of managing the infrastructure, ensuring automatic scaling and billing only for the resources used.

It is worth noting that serverless does not mean there are no servers involved but rather that by adopting this solution, the team gets rid of the responsibility of managing and maintaining the infrastructure, delegating that responsibility to the service provider.

Serverless Tools provided by Google Cloud

Google Cloud stands out as a leader in serverless solutions, offering a robust suite of tools and features for developing and deploying highly scalable web and mobile applications without the necessity of managing servers.

The Google Cloud serverless model scales servers automatically according to traffic and with a pay-as-you-go model: 

• Cloud Functions: It is a function service that allows you to execute code in response to events (such as HTTP requests, Pub/Sub notifications, or changes in Cloud Storage). You only pay for the runtime of the code, making it a cost-effective solution for short-duration workloads or traffic spikes.
• Cloud Run: It is a serverless service that allows you to run containers on an infrastructure managed by Google. It is similar to Kubernetes but without the complexity of cluster management. It also adjusts automatically to traffic, billing for the resources used.

Additional Google Cloud Serverless Services:

• Cloud Storage: Secure and scalable data storage, working in along with Cloud Functions.
• Cloud SQL: Managed relational database integrated easily with Cloud Functions.
• Cloud Spanner: Globally distributed database for applications with high availability and scalability requirements.

Benefits of using Serverless Solutions powered by Google Cloud

Among the main advantages provided by Serverless solutions, we can highlight the way in which it allows its clients to save money and accelerate the development of applications.

Google Cloud Serverless clients deploy their applications 95% faster and reduce infrastructure costs by 75%. That is why at Making Science, we use and continue to train with the latest technologies, thus taking advantage of the underlying benefits.

The main advantages provided by this technology include the following:

• Development in any language: Developers can write code in any language or framework, such as Python, Java, JavaScript, Node.js…

• Enhanced Developer Productivity: With this architecture, the service provider is responsible for the automatic scaling, updating the operating system, and provisioning the infrastructure. This allows the development teams to focus on innovation and not infrastructure, thereby increasing the company’s productivity.

• Pay-per-use model: Serverless platforms, such as Cloud Run or Cloud Functions scale automatically based on the number of running instances needed to handle incoming requests. So, when there is no traffic, the service automatically scales down to zero. Therefore, customers only pay for the resources they are using, unlike servers that are constantly running.
• Usage visibility: The Serverless Model provides visibility into system and usage information, including user times.

Conclusion

In recent years, there has been a significant increase in the adoption of serverless technologies. According to a serverless technology survey by O’Reilly in 2019, over 40% of organizations have adopted this serverless technology.

Making Science champions innovation through serverless computing with Google Cloud Platform. This approach streamlines development by offloading server management, allowing our team to focus on core functionalities.  Leveraging Google’s robust infrastructure ensures exceptional quality and performance.  Furthermore, the pay-per-use model optimizes costs, fostering sustainable growth as Making Science stays at the forefront of technological advancements.

Delivering exceptional customer service is not just a competitive advantage; it is a prerequisite for long-term success. Technology streamlines operations in today’s business landscape, while human interaction injects vitality. Yet, bridging human expertise and availability can prove challenging. Enter ChatBot Technology is revolutionizing client engagement by leveraging AI and natural language processing. It’s the go-to for companies aiming to enhance communication and customer experiences. Let’s explore what makes Einstein ChatBot exceptional and the industry’s top choice!

Salesforce Einstein ChatBot harnessing Salesforce’s AI capabilities, empowers businesses to integrate chatbots into diverse real-time customer engagement processes. With its advanced Natural Language Processing (NLP) and machine learning, the chatbot comprehends customer requests and delivers relevant responses. Enabling Einstein ChatBot via native Salesforce settings eliminates integration complexities.

Furthermore, seamless integration with Salesforce’s CRM tools enhances customer experiences. Einstein bots excel in aiding customers, addressing queries, and augmenting customer support representatives’ insights. They analyze data, predict outcomes, suggest optimal actions, and streamline automation across tasks.

Understanding customer expectations is pivotal and Salesforce chatbots delve into backend systems to guide agent actions. Complex issues trigger seamless transfers to available Live Agents. Subsequently, agents can review bot-customer interactions for adequate support provision. Einstein ChatBot revolutionizes customer engagement through its dynamic AI-powered assistance and deep integration with Salesforce’s ecosystem.

Why Should You Use an Einstein Bot?

Consider these points when considering the adoption of Salesforce Einstein Bot:

• Faster Responses: Unlike email, text, calls, or social media, it delivers faster responses to frequently asked questions, bolstering customer engagement.
• Time Efficiency: Einstein Bot’s intelligent solutions save customers and support reps time, enabling agents to focus on strategic aspects of their roles.
• Reduced Cases: Addressing a wide array of questions curtails the need for cases to escalate to live agents, thus lowering case volumes.
• Intelligent Functionality: Leveraging Natural Language Understanding (NLU), Einstein bots continuously learn and evolve, enhancing their intelligence and capabilities.
• Rapid Query Resolution via Knowledge Articles: Einstein ChatBot harnesses Salesforce’s knowledge base to provide accurate responses, leveraging NLP to match customer queries with relevant articles. This enhances the customer experience through quick and precise answers derived from a product, service, and standard issue information repository.

Looking Ahead: The Future of Customer Engagement with AI

Salesforce Einstein ChatBot represents a significant leap forward in customer service, blending AI efficiency with the nuanced understanding of human agents. Its ability to deliver swift responses, manage time effectively, and reduce case loads while continually learning from interactions makes it an invaluable asset for any forward-thinking business.

At Making Science, we specialize in harnessing such cutting-edge technologies to not only meet current demands but to anticipate future needs. Our approach is to partner with you to ensure these tools are integrated smoothly and effectively, empowering your business to deliver exceptional customer experiences.

A Benchmark of Models for a Call Center Analytics use case

Call centers are one of the main communication channels between customers and companies. The calls to/from the call center contain a gold-mine of valuable information about the customer and its relationship with the companies. At Making Science we are helping customers leverage this value in the business delivering significant ROI on conversational analytics projects.

Before the advent of the modern speech-to-text models, it was almost impossible to process these calls on an industrial scale, since it was a manual process. A very resource-intensive one.

Modern speech-to-text models allow companies to convert call audio records into text, and analyze them to extract valuable insights. With this technology, transcribing a single call can take as little as 4 seconds. However, in-production systems have many challenges:

1. PII(personally identifying information) data in call center audios: these calls may contain several pieces of sensitive information (names, addresses, credit card numbers, etc.). If the transcripted calls are stored without PII remotion, this may lead to a potential data leakage.
2. Audio records caveats: depending on the call center setup, the records may be stored as mono or stereo audio files. In terms of this particular use case, this has a deep impact. If the audio is stored as a mono file, the recording from the call center operator and the recording from the caller are in the same audio channel; they aren’t separated. In this case, besides the speech-to-text model, an additional diarization step must be included to separate the parts of the audio that belong to each speaker.

From the previous discussion, it is possible to conclude that an in-production audio transcription system must have two core components: the transcription module itself (the one that converts the audio into text) and an anonymization module (to remove all the sensitive data from the transcripts). The following image shows a high-level architecture for this solution.

Figure 1. High-level architecture for an audio transcription module.

Implementing an end-to-end speech-to-text system for call center records is the first step required to extract value for the transcripts by adding other features on top of it. Some of these features are:

1. Topic modeling. To know which are the topics discussed in every single conversation.
2. Sentiment analysis. To know the client’s sentiment regarding the brand and/or about the outcome of the call.
3. Script monitoring. To validate if the call center operator is following the script and analyze the impact of script variations in the communication output.

From audio to text on an industrial scale – the current landscape

To convert audio to text, there are many different speech-to-text models. At Making Science, we compared several models to see which one performs better. The benchmark dataset we used is the Gridspace-Stanford Harper Valley speech dataset, which contains 1446 call center conversations manually transcribed. These recordings are divided into two audio files, one for the call center operator and the other for the caller. Because of that, no diarization is required.

The metric used to evaluate the model’s performance is WER (Word Error Rate). This metric quantifies the mistakes made by the model, taking into account the substitutions, the mistaken insertions, and the deletions done by it. The lower the WER is, the better the model performance is. Since the WER can be greater than one, it isn’t a transcription accuracy percentage. The WER metric is defined as:

Besides how the WER is, there are also other relevant metrics to evaluate which model is the best one for an industrial-scale application. For example, a few relevant dimensions to take into account for this decision are:

• How much does it cost to translate a minute of audio?
• The latency if your use case requires rapid translation and analytics; how long does it take for the model to transcribe audio?
• Parallelism if your use case has a large number of users waiting for “intelligence”; how many API requests per unit of time can the model provider handle?
• The Privacy; How does the model provider handle our data? Is it possible to deploy a private instance of the model?

For this benchmark, we considered several models from different providers. Also, we tried models that allow the user to deploy a private instance of it and models that are available via a public API. The results we obtained are available in Table 1.

Table 1: benchmark results for speech-to-text task.

Key takeaways:

1. Google speech-to-text models are the best-performing models at the time of this benchmark(lower WER) for both agent and caller transcriptions.
2. In general, the models tend to transcribe better the agent audio than the caller audio. This is an expected behavior because, in general, the audio quality for the agent audio is better.
3. Whisper V3 has quite good performance, especially for the caller audio. However, the Whisper model doesn’t support diarization. Because of that, to use it in a production environment when audios can be mono audios, a diarization module should be developed (using, for example, pyannote).

Keeping Pace with Speech-to-Text Advancements

In the fast-paced world of speech-to-text technology, it’s crucial to keep pace with innovation. The performance benchmarks we rely on today may shift as advancements continue.

At Making Science, we understand the importance of adaptability and regularly update our approach to ensure we harness the best tools for unlocking customer insights. Stay informed, stay agile, and stay ahead with us as your analytics ally.

The Surprising Reality of Mobile Web Accessibility

One might think that it’s a battle won. Web accessibility has been a resonating theme for over two decades now, emphasizing the importance of ensuring an inclusive online experience for all users. 

65% of web traffic in Europe comes from mobile devices, and Google has clearly indicated its support for mobile-optimized websites by favoring them in its ranking.

Mobile Optimization: Expectation vs. Reality

Nowadays, all advertisers should have a mobile-optimized website that adheres to the basics of accessibility – how could it be otherwise?

However, despite advancements, the reality is quite different. A study conducted by Making Science in 2022 shows that, among other findings, 72% of the websites of the companies from the IBEX 35 (Spain’s principal stock exchange), exhibit mobile accessibility deficiencies.

Similarly, we still encounter clients asking us to audit their website, only to find that the design was not initially intended for mobile.

This is particularly serious because not optimizing the experience for the majority of traffic exposes one to losing conversion points, leads, and sales.

Responsive Design vs. Mobile First.

Moreover, just because a website displays decently on a mobile device doesn’t mean it’s optimized for the best conversion. To explain, the term “responsive” is not equivalent to “Mobile First.”

When designing a website, there are generally 2 or 3 versions for different device types: Desktop, Mobile, and sometimes Tablet. There are fundamentally two ways to work: either start with mobile and progress to larger formats, known as “Mobile First”, or the other way around. This first approach makes the most sense since it caters to the majority of users, leveraging additional space on desktop.

The other approach, unfortunately still too common, goes in the opposite direction, known as “Graceful Degradation.” The designer starts with the largest version and then adapts it to mobile. This is not the right approach as it optimizes work for a minority, requiring adjustments for content and functionality in a confined space.

You might say, “But if we’re talking about ‘Graceful Degradation,’ it can’t be that bad.” Let me give you an example to explain why it’s not the case.

Imagine a product website presenting its main selling points to visitors. On the desktop version, a common way to present them would be using elements called “Cards,” with 3 or 4 cards in a row. This layout is suitable for a large horizontal screen but we can immediately intuit that it doesn’t fit very well into a vertical screen. 

When translated to mobile, these cards often end up either in a horizontal carousel or a simple vertical stack, neither of which is optimal. In the first case, the user will have to interrupt his horizontal scroll to scroll horizontally in order to see the info. (Spoiler: he won’t do so, and will lose an important part of the product pitch.)

Vertical stacking is a better option, but in terms of design and space optimization, it’s really not that great. 

The Case for Progressive Enhancement

Working in the direction of “Progressive Enhancement,” starting with mobile, forces us to optimize information presentation for mobile constraints, resulting in a better-adapted version.

Here, all information is visible on a single screen, giving the user access to all arguments in a nutshell.

The errors caused by the Desktop First approach can be even more dramatic and lead to significant drops in conversion. For example, forgetting to provide a mobile user with a link to return to the filtered list from a product page because the Desktop version lacks it (desktop users are generally relying on the browser’s back button).

Breaking Free from Old Design Habits

Unfortunately, many agencies and designers still follow a Desktop First approach, either out of habit or comfort.  It’s more rewarding to design a beautiful layout on a large screen than starting with mobile.  Another downside is that since mobile design comes at the end of the creation process, it often gets rushed to meet deadlines.

It’s time for agencies and designers to break free from old habits and prioritize the quality of the user experience across all platforms.

Advertisers must also ensure that teams responsible for designing digital assets opt for a “Progressive Enhancement” approach, starting with mobile. This represents a strategic approach to overcome constraints while ensuring a consistent and optimal user experience.

The journey towards universal web accessibility and an exceptional user experience requires constant evolution of methodologies and a reassessment of established practices. Only those who anticipate these changes and adopt innovative approaches can hope to stay in sync with the growing expectations of users.

It is very common to hear the word phishing in our day-to-day life, sometimes we are even able to use it without really knowing what the meaning of this word is. The purpose of this Blog Post is to provide a deeper understanding of the most prevalent and dangerous cyber-attack technique: phishing.

Exploring the world of phishing

Phishing is a type of cyberattack designed to target individuals through emails, text messages, phone calls or other forms of communication. Its primary goal is to trick the recipient into performing actions desired by the attacker, such as revealing financial information or login credentials to corporate systems or other sensitive information.

As a form of social engineering, phishing involves psychological manipulation and deception, where threat actors pose as trusted entities to induce users to perform specific actions, such as clicking on malicious links, downloading and installing malicious files, or disclosing private information such as bank account numbers or credit card details.

What distinguishes phishing and makes it especially dangerous is that its success depends on human action. Even if advanced security measures are implemented, a simple user error can compromise an entire company.

The Impact on the Organization

Phishing attacks can have a variety of consequences, the most common of which are:

• Data loss
• Compromise of accounts and login credentials
• Ransomware and/or malware infections
• Financial losses and fraud from banking transactions

Advanced phishing strategies

As all technologies evolve, so do phishing campaigns. Attackers learn from their mistakes and improve their strategies, making them more difficult to identify. Recently, a new strategy has been discovered that we want to address in this article. It involves phishing that spoofs Meta for Business, using a Salesforce website as a bridge to direct the user to a seemingly secure target.

It starts with an email pretending to be from Meta for Business, informing the user of a violation of the community rules that involve account deletion (1). This type of campaign is targeted, as it addresses the user by name. Although the sender of the email is noreply@salesforce.com, which is suspicious, it is a trusted domain that avoids detection by conventional filters and generates fewer doubts in the user. The email includes a button to send an appeal.

If the user clicks the button, he is directed to a Salesforce-hosted website (2), requesting an identity verification via hCaptcha (3). Once the verification is completed, the user is left vulnerable to the attack (4). 

In this case, the page was hosted by Salesforce, but any other platform can act as a bridge. This pattern is persistent and, despite technical efforts, many sites manage to go undetected. By contacting the Salesforce team, it has been possible to remove the intermediate page and block the mailing from Salesforce.

How to identify the threat?

As we have seen, phishing is a type of attack that is characterized by its versatility, so there is no exact method to identify it. However, there are signs that will give us a clearer picture of whether the email we have in front of us is legitimate or not:

1. Pay attention to the sender: Verify that the sender is consistent with the content of the email. In the case mentioned above, the email pretended to be from Meta for Business but came from a Salesforce address, a clear indicator that it was not legitimate.
2. Review images and links: By hovering the mouse over images, buttons, or links, you can view the address to which they redirect. It is crucial to verify that the domain matches the owner of the client or partner. Platforms such as VirusTotal can help to check the legitimacy of domains.
3. Check typography and special characters: Legitimate emails follow specific typography standards. Atypical elements may indicate a phishing attempt.
4. Verify through regular channels: If the sender claims to be part of your organization, use regular communication channels to confirm their identity. The CEO fraud case is also a very common attack.

Protecting ourselves in the digital world.

In summary, phishing is a persistent threat that is continually adapting. Awareness, education, and the use of security technologies are essential to be protected. Being informed and vigilant helps build a safer and more resilient digital environment against this growing threat. In a world where cybersecurity is crucial, prevention and attention to detail are critical to avoid falling into phishing traps.

From the very heart of blockchain technology, a quiet revolution is stirring the foundations of the web as we know it. A new era is upon us, where digital pioneers rise to reclaim the throne of digital sovereignty, and decentralization takes center stage. Web3 beckons us back to the protocols that birthed the internet, offering transparency, freer systems, and a renewed online interaction structure that removes intermediaries.

The Promise of Web3: A Shift Towards Decentralization

Let’s focus on what Web3 brings to the table: a transformative network that combines the advanced functionality and user interfaces of Web2 with the neutrality of Web1’s protocols. Unlike the centralized databases of tech giants, Web3 allows us to store information across distributed public databases, harnessing blockchain technology, and potentially resolving issues of trust and transparency.

Imagine extending community-based domain protocols, creating an internet layer free from corporate governance. This enables direct connections between audiences and platforms without algorithms or ads, akin to using email, but with the added capability to develop functionalities atop the protocol—ushering in decentralized finance and autonomous organizations that challenge traditional structures.

Learning from the Past and Navigating the New Web

The battle between Encarta and Wikipedia in the early 2000s is a telling historical parallel. Encarta’s centralized model was supplanted by Wikipedia’s decentralized, community-driven content control. This shift indicates how a decentralized approach can be more aligned with user needs and preferences, foretelling the potential advantages of Web3.

In Web3, we use wallets and tokens on various blockchains, interacting with Smart Contracts. While this may seem daunting, it’s a learning curve comparable to the advent of the internet or smartphones. Web3 introduces new concepts like NFTs and DAOs, and paradigm shifts that demand a deeper understanding, yet the innovation potential is as vast as the challenges we face.

Cryptographic Ownership and Exchange

Tokens symbolize ownership in this new web. They’re cryptographic units of value created by entities, and they come in different types, such as NFTs, which follow the ERC-721 standard. Wallets are programs that allow us to autonomously transact with our tokens. They serve as our interface with the blockchain, the decentralized database that records token ownership, and smart contracts are the self-executing agreements that facilitate this trustless exchange.

Comparative Analysis Between Web1, Web2, and Web3:

Before we delve further into the implications of Web3, let’s take a moment to compare the three generations of the web:

Use Cases: Web3 in Action

Web3’s potential is not limited to theoretical discussions; it’s already causing ripples across various industries. Let’s delve into some tangible applications that illustrate the power of Web3 in the real world:

• Supply Chain Management:  Utilizing blockchain technology, Web3 enhances supply chain transparency, allowing us to track the journey of products from manufacturer to consumer. This not only ensures authenticity but also greatly improves the efficiency of tracking items in real-time, a crucial factor for recalls or verifying the supply chain’s integrity.
• Insurance: Smart contracts in Web3 are set to revolutionize the insurance industry. By automating claims processing, these contracts execute when predefined conditions are met, minimizing the possibility of fraudulent claims and ensuring that genuine claims are paid out more quickly and efficiently.
• Telecom: Web3 technologies are reinventing the telecom sector with NFT-based mobile identities. These digital identities are secure and portable across services, offering a new level of control and personalization for users while also opening up possibilities for cross-service integration and loyalty programs without compromising privacy.

Conclusion and the Road Ahead

In conclusion, as we stand at the dawn of an internet revolution that lays a new conceptual framework for the future, we must also acknowledge the accompanying challenges, such as an increased risk of scams and the steep learning curve for new users. History shows that once technology solves a problem, it becomes a staple in our lives—like fire, airplanes, and the internet. Innovations may evolve, but the solutions they offer create lasting impact. The shift from Web2 to Web3 is underway; it’s not a question of if, but when it will become mainstream. The time to educate ourselves and safely navigate this new frontier is now.

If you’re ready to unlock the potential of Web3 and transform your business operations, Making Science is here to guide you every step of the way.

As we wave goodbye to 2023 and prepare to embrace the opportunities of the coming year, it’s a perfect time to look ahead toward the future. What innovations and technological advancements await us in the new year and beyond?

From evolutionary to revolutionary changes, thoughtful consideration of how new technologies might affect your business could provide strategic advantages. With this in mind, let’s explore the top tech trends Gartner predicts will play a significant role in 2024 and beyond.

What trends will shape 2024?

1. AI Trust, Risk and Security Management (AI TRiSM)

As the adoption of Artificial Intelligence (AI) continues to accelerate, organizations are increasingly seeking frameworks to manage the associated risks and ensure responsible AI development. AI Trust, Risk, and Security Management (AI TRiSM) is emerging as a prominent approach, offering a comprehensive approach to governance, trustworthiness, fairness, reliability, robustness, transparency, and data protection for AI models.

This framework is gaining traction due to its demonstrated ability to enhance the success of AI projects, increase model precision, and promote fairness in AI-driven applications. Additionally, it emphasizes the importance of continuous model monitoring to ensure that interpretability and explanations remain consistent throughout the AI lifecycle. Organizations that embrace AI TRiSM are laying the foundation for responsible and trustworthy AI deployments that deliver real business value.

2. Continuous Threat Exposure Management (CTEM)

Cybersecurity remains a top priority. organizations seek pragmatic and systemic approaches to optimize their risk mitigation strategies. CTEM, emerges as a forward-thinking approach that aligns exposure assessment cycles with business projects and threat vectors, ensuring security efforts align with organizational objectives.

Beyond traditional vulnerability management, CTEM addresses both patchable and unpatchable exposures, recognizing the need for comprehensive risk mitigation. To validate security controls and prioritization decisions, it incorporates an attacker’s perspective, simulating real-world attacks to test the resilience of defenses. This evidence-based approach shifts focus from tactical responses to informed decisions based on threat analysis, enabling organizations to effectively address emerging threats and enhance overall cybersecurity posture.

3. Sustainable Technology

As the world confronts pressing environmental, social, and governance (ESG) issues, Sustainable Technology stands as a compelling framework for digital solutions to foster positive change: environmental technologies that safeguard the natural world, social technologies that promote human rights and well-being, and governance technologies that strengthen ethical business practices.

Effective implementation of Sustainable Technology hinges on selecting relevant technologies aligned with industry priorities and stakeholder expectations. Cloud services, AI, and other innovative tools can play a transformative role in driving sustainability initiatives.

4. Developer-Driven Self-Service: Platform Engineering

In the pursuit of rapid software delivery and enhanced developer productivity, Platform Engineering focuses on constructing and maintaining self-service internal platforms as layers of abstraction for streamlining the development process and easing the cognitive burden for developers.
By carefully curating reusable, composable, and configurable platform components, knowledge, and services empowers developers to independently manage and develop applications while guaranteeing reliability and security.

This approach not only optimizes the developer experience but also expedites time to market and augments business value. To effectively implement Platform Engineering, organizations should treat the platform as a product, actively engaging with end users to identify and prioritize their requirements. Additionally, fostering a product management culture promotes open communication and collaboration between platform engineers and end users, enabling continuous improvement and feedback loops.

5. AI-Augmented Development

This approach leverages AI technologies like GenAI and Machine Learning (ML) to aid software engineers across the development lifecycle. These tools seamlessly integrate into developers’ environments, helping generate application code, convert legacy code to modern languages, facilitate design-to-code transformation, and improve application testing. 

By automating routine tasks and offering intelligent guidance, AI-augmented development significantly boosts developer productivity, allowing them to concentrate on higher-level tasks like crafting innovative business applications. This not only streamlines the development process but also empowers developers to efficiently deliver software solutions, keeping pace with the escalating needs of today’s businesses.

6. Industry Cloud Platforms

In the dynamic landscape of modern business, Industry Cloud Platforms (ICPs) can revolutionize the way organizations approach IT infrastructure and solutions. These platforms seamlessly integrate underlying SaaS (Software as a Service), PaaS (Platform as a Service), and IaaS (Infrastructure as a Service) services into a unified offering crafted specifically for distinct industries. This tailored approach addresses the unique challenges and requirements of each industry, providing a comprehensive solution that optimizes IT capabilities and drives business success.

At the heart of ICPs lies composability, a key feature that empowers organizations to flexibly combine and customize platform functionalities to align with their specific needs. This agility enables businesses to swiftly adapt to evolving market trends and business requirements, fostering innovation and resilience. Moreover, ICPs are designed with industry-specific outcomes in mind, ensuring that the platform’s features and capabilities are tailored to address the mission-critical priorities of each vertical segment. This focus on industry-specific value ensures that organizations maximize the return on their cloud investments and gain a competitive edge.

7. Intelligent Applications

Intelligent Applications, infused with AI capabilities and diverse data sources, are revolutionizing organizational interactions with users. They offer real-time insights, personalized experiences, and predictive features beyond traditional functionalities. By analyzing user behavior and external trends, these applications proactively cater to user needs, enhancing experiences and driving superior outcomes. This data-centric approach empowers informed decision-making, operational optimization, and competitive advantage.

This paradigm shift in business interactions is driven by Intelligent Applications, leveraging AI and data to transform customer experiences, streamline operations, and foster innovation. They position organizations to flourish in the dynamic digital landscape.

8. Democratized Generative AI

Democratized Generative AI (DGAI) is revolutionizing how organizations operate and engage with stakeholders in the digital realm. By democratizing content creation, it boosts productivity through automation, cuts costs, and empowers a wider workforce with new skills and opportunities. Its personalized content capabilities enhance customer experiences, while unified data access aids decision-making and workflow efficiency. 

As DGAI evolves, its impact promises to transform industries, streamlining processes, elevating customer interactions, and transform how virtually all enterprises compete by empowering users across roles.

9. Augmented Connected Workforce

As remote work persists, Augmented Connected Workforce (ACW) seamlessly integrates intelligent technologies and analytics to empower employees with the tools and insights crucial for success. This approach bridges human expertise with technological capabilities, enabling better decision-making, heightened productivity, and a more adaptable workforce ready to tackle the demands of the digital age.

Beyond individual empowerment, it drives organizational agility by rapidly acquiring new skills and adapting to market shifts. It fosters a motivated workforce, enhancing retention and reducing turnover costs. As workplaces embrace automation and AI, it prepares employees to thrive in this intelligent setting.

10. Machine Customers

Businesses will cater not only to human customers but also to machines. Proliferating connected products with purchasing autonomy in 2024 and beyond will disrupt trillions in sales as non-human economic actors impact business models. Innovatively serving algorithmic customers presents new opportunities for those adapting early.

These non-human economic players, enabled by connected devices, signify a paradigm shift in commerce. With an estimated 15 billion connected devices by 2028, poised to engage in transactions independently. Their impact extends across business realms, offering expanded consumer markets, personalized experiences, streamlined operations through automation, and invaluable data insights for market research and product development.

Conclusion

The opportunities and challenges these emerging technologies present are complex to navigate.  By carefully considering strategic implications and staying informed about the evolving landscape, technology leaders can position their organizations to capitalize on promising innovations while mitigating risks.

As we venture into the future, we’re committed to being your trusted partner, staying ahead of the curve, and delivering value through responsible innovation. At Making Science, we’re ready to ride the wave of these technological advancements, guiding you on your journey from insight to actionable strategy. 

Understand emerging influences, equip yourself to seize opportunities, and safeguard your organization’s future success!