2 April, 2025 BY Luz Castillejo Flor

Amazon revolutionizes the AI landscape with Nova Act.

In the ever-evolving world of artificial intelligence, Amazon has taken a bold step with the launch of Nova Act, a revolutionary platform designed to transform how we interact with AI in the web environment. This innovation not only empowers developers but also opens new possibilities for both B2B and B2C companies.

In this article, we will explore what Nova Act is, how it can benefit various industries, and how its implementation in large enterprises can maximize its potential.

What is Nova Act?

Nova Act is a platform designed to allow developers to create sophisticated AI agents that can autonomously navigate the web. Imagine a world where AI agents can not only collect data but also interact with web pages, perform complex tasks, and provide real-time solutions. That is the power that Nova Act places in the hands of developers.

Key Features of Nova Act

  1. Autonomous navigation: AI agents can visit websites, analyze content, and perform specific tasks without human intervention.

  2. Dynamic interaction: The ability to complete forms, click on links, and even extract and process data useful for business decisions.

  3. Continuous learning: Nova Act utilizes advanced algorithms that enable agents to learn and adapt with each interaction.

Benefits for B2B Companies

In the B2B space, Nova Act offers a sea of opportunities. Companies can use these agents to automate data acquisition processes, competitive analysis, and customer relationship management.

Use Case: Data Acquisition Automation

Imagine a digital marketing company that needs to collect data from various advertising campaigns across multiple platforms to create detailed reports. With Nova Act, AI agents can navigate advertising platforms, extract relevant data, and autonomously generate reports, saving time and reducing human errors.

Use Case: Customer Relationship Management

Companies can program agents to regularly visit key client websites, gather information on product updates, and generate alerts for the sales team. This allows for a proactive response to customer needs and improves long-term relationships.

Benefits for B2C Companies

For B2C companies, Nova Act can significantly enhance the customer experience and optimize customer service operations.

Use Case: Automated Customer Service

Through Nova Act, companies can create AI agents that interact with customers on their websites, answering frequently asked questions, providing personalized product recommendations, and even assisting in the purchasing process. This not only improves customer experience but also frees up human resources for more complex tasks.

Use Case: Personalized User Experience

Imagine an AI agent that analyzes visitor behavior on a website in real time and adapts the visible content based on their preferences and past behaviors. This not only increases customer satisfaction but also improves conversion rates.

Implementation in Large Enterprises

The implementation of Nova Act in a large company requires a well-planned strategy to maximize its benefits. Here are some recommended steps:

Step 1: Needs Assessment

Identify areas within the company where AI agents can add the most value. This could include data operations, customer service, or logistical processes.

Step 2: Development and Training

Collaborate with developers to create customized agents that align with the company's objectives. Ensure that key personnel are trained to work with the agents and maximize their efficiency.

Step 3: Monitoring and Adaptation

Establish a monitoring system to evaluate the agents' performance and make adjustments as needed. Adaptability is key to ensuring that AI agents remain relevant and useful.

Conclusion

Nova Act is set to revolutionize the artificial intelligence landscape in the web space. Companies, both B2B and B2C, can leverage this technology to significantly improve their operations, optimize customer service, and gain a competitive edge in the market.

With careful implementation and strategic planning, Nova Act has the potential to transform the way businesses interact with artificial intelligence, taking efficiency and personalization to the next level.

Undoubtedly, we are witnessing a new era in AI development by Amazon.

 
PREVIOUS
NEXT

EXPERT TIPS

Subscribe to boost your business.

LATESTS ARTICLES

16 July, 2025 POR Alba Fiorella Aviles
crm Data management AI Automation

The seventh wave of AI is redefining CRM and data strategy

Artificial intelligence is not just another improvement: it is, in the words of George Colony, CEO of Forrester, the seventh wave of transformation that will redefine the technology sector. This change directly affects CRM, analytics, and marketing automation, forcing companies to adapt or be left behind.File:George Colony in 2011.jpg
SEGUIR LEYENDO
14 July, 2025 POR Luz Castillejo Flor
Marketing strategy Tracking data stratergy third-party cookies

How the end of third-party cookies impacts your marketing strategy

The announcement of the definitive elimination of third-party cookies marks a turning point in the digital ecosystem. This is not just a technical adjustment in browsers: we are talking about a structural change in the way companies collect data, activate advertising campaigns, and manage customer relationships.

And although it may seem like a distant issue or one exclusive to large corporations, the reality is that it affects any business that uses digital advertising, email marketing, retargeting strategies, or affiliate programs.
That’s why understanding its impact and knowing how to prepare is key to staying competitive.

What are third-party cookies and why are they disappearing?

Third-party cookies: the foundation of digital marketing until now

A third-party cookie is a file placed on your browser by a provider other than the website you are visiting.
For example, if you visit a blog that uses Google or Facebook ads, those systems install cookies that track your behavior—even when you browse other sites.

Thanks to those cookies, advertisers could:

  • Follow you throughout your browsing.

  • Show you ads based on your interests and behavior.

  • Measure the impact of their campaigns.

  • Build detailed profiles without requiring you to register or provide data.

In short: third-party cookies were the backbone of programmatic advertising and retargeting.

Why are they being eliminated?

The official reason is user privacy protection.
More and more users demand control over their personal data and how it’s used. Regulations like GDPR in Europe and CCPA in California have forced major players (Google, Apple, Mozilla) to move toward a more privacy-friendly model.

But there is another angle:
Google, owner of Chrome and a leader in digital advertising, is redefining the game to maintain market control and limit competition. By eliminating third-party cookies, Google ensures that only those who manage first-party data or operate within its platforms can effectively reach users.

The three major pillars changing after the elimination of cookies

1. Campaign measurement and attribution

Until now, measuring the impact of a multichannel campaign (ads, email, web visits) relied on attribution models based on cookies.
For example:

If a user saw an ad on Instagram, clicked on a Google ad, and then made a purchase on the website, cookies helped trace that path.

What happens without third-party cookies?

  • Conversions attributed to third parties will decrease.

  • The user journey will be harder to track.

  • “Last-click” or “multi-touch” measurement becomes less reliable.

How to adapt?

  • Prioritize first-party data measurement by connecting your CRM with analytics platforms.

  • Implement solutions like Google Enhanced Conversions or server-side tagging, which allow more accurate measurement without relying on cookies.

  • Explore proprietary attribution models, such as integrating sales or CRM systems with analytics tools.

2. Audience segmentation and activation

The end of retargeting as we knew it.
Without third-party cookies, platforms can no longer create audiences based on behavior across different websites. This directly affects:

  • Programmatic advertising.

  • Dynamic retargeting campaigns.

  • Affiliate campaigns based on cross-site tracking.

How to adapt?

  • Enhance your first-party data: encourage registration, subscriptions, and account creation.

  • Use activation tools like Customer Match (Google Ads) or Audiences (Meta), which let you upload your own data to reach those users on their platforms.

  • Work on lookalike strategies based on your own customer data, not third-party data.

  • Leverage contextual advertising by showing ads related to the content being consumed—without needing to know the user’s identity.

3. First-party data management and value

The direct consequence of this change is that first-party data becomes the most valuable asset of a digital company.
Without the ability to buy audiences based on cookies, you need to build your own database with real, interested users with whom you can maintain a direct relationship.

This means:

  • Developing acquisition strategies based on value: lead magnets, quality content, incentives for registration.

  • Creating automated, personalized communication flows from your CRM.

  • Focusing on the quality of the relationship, not just the quantity of impacts.

How to adapt?

  • Strengthen your lead generation strategies and improve your registration forms.

  • Implement a CDP (Customer Data Platform) if you handle large volumes, or ensure your CRM is well integrated with your marketing platforms.

  • Take care of the user experience to avoid intrusive practices like aggressive pop-ups or forced capture.

What alternatives does the market propose after the elimination of cookies?

  • FLoC and Privacy Sandbox (Google): Google proposes alternative systems based on cohorts, where users are grouped by interests without being individually identified. These proposals still generate debate over their effectiveness and privacy.

  • Data Clean Rooms: Secure environments where data from different parties (advertisers, platforms) can be matched without revealing user identities. Costly but necessary for major advertisers.

  • Contextual advertising: Making a comeback. Showing ads related to the content being visited, with no need to know who the user is.

  • Server-side models: Collecting and activating data from the server side is a technical alternative for measuring and segmenting without relying on traditional cookies.

What should companies do to adapt (and not just survive)?

  • Invest in a data strategy:
    Organize, structure, and connect your databases with your marketing tools.
    First-party data is a strategic asset—not just a list of emails.

  • Train your teams:
    Not just the marketing department. Sales, customer service, IT… everyone needs to understand the value of data and how it’s managed.

  • Strengthen customer trust:
    Transparency and good privacy management will be differentiators. Clearly explaining how you use data builds trust and, in the long term, conversion.

  • Commit to personalized omnichannel experiences:
    The CRM should be the center of a strategy where the user receives coherent impacts across all channels (web, email, app, social).

  • Prepare for new measurement methods:
    Invest in server-side solutions, predictive models, and tools that allow you to measure impact beyond cookies.

Conclusion: Threat or opportunity?

The end of third-party cookies is not the end of advertising or digital marketing.
It is the beginning of a new paradigm where companies that invest in:

  • Building their first-party data.

  • Truly integrating their systems.

  • Personalizing based on a deep understanding of the customer.

… will be the ones to take the biggest slice of the pie.

Because if one thing is clear, it’s that data remains important…
You just have to earn it now.

Schedule a meeting

SEGUIR LEYENDO
9 July, 2025 POR Luz Castillejo Flor
data base data architecture data quality

No solid base, no AI performance: the challenge of the Data Foundation

In a business context where AI has become the new standard for efficiency and scalability, many organizations face a paradox: they have advanced technology, but they fail to achieve consistent results. The issue usually isn’t the algorithm—it’s the foundation. The Data Foundation is the true determinant of success or failure for any AI, automation, or CRM strategy.

This is confirmed by the latest TDWI (Transforming Data With Intelligence) study, published in June 2025, which warns that more than 49% of companies still lack a database ready to scale artificial intelligence projects.

The Data Foundation: more than just infrastructure

Having a modern data platform doesn’t mean having a solid foundation. The TDWI study emphasizes that an effective Data Foundation must meet three conditions:

  • Data quality and governance from the source
  • Scalable and connected architecture
  • Real-time activation capability

When a company fails in any of these three areas, AI becomes more of a promise than a real business lever.

Key findings from the study

Here are some of the main conclusions of the report:

Only 10% of companies claim to have a fully operational Data Foundation.
40% report severe limitations due to poor data quality, silos, or outdated processes.
Most organizations suffer from fragmentation across data sources, preventing a 360-degree view of the customer.
55% of companies already using AI operationally do so despite their technical limitations, not because of their strengths.

In other words, many companies are running with a backpack full of ballast. And that limits the performance of their AI, automation, or CRM tools.

Why does this matter for your CRM or marketing?

At Hike&Foxter, we see it frequently: companies investing in advanced CRMs, analytics platforms, or generative AI engines… without first securing the technical and structural foundation of their data.

The result:

  • AI models that fail in production.
  • Automations triggered incorrectly.
  • Unreliable analytics reports.
  • Inconsistent customer segmentations.

All of this can be avoided with a well-designed Data Foundation, connected to key processes and with controlled data flows.

How to build a real Data Foundation

These are the phases we recommend implementing if you want to turn your data architecture into a competitive advantage:

1. Technical and functional audit

Before incorporating AI, it's important to review:

What data sources exist and how they are integrated
The degree of duplication, obsolescence, or noise they contain
Where the main bottlenecks are (latency, format, access)

2. Standardization and governance

Without a common taxonomy and control rules, any automation attempt will be fragile. This involves:

Defining unified structures (customers, products, interactions…)
Establishing automatic validation rules
Creating clear roles: who creates, modifies, or validates data?

3. Connected and flexible architecture

A data warehouse alone is no longer enough. You need to:

Connect CRM with analytics, automation, and digital channels
Use scalable environments (Snowflake, BigQuery, Azure Fabric)
Consider data mesh or federated architecture if there are multiple business units

4. Real-time activation

The value of AI lies not just in predictive analysis but in its ability to act.

Therefore:

Connect your Data Foundation with activation tools (such as Customer Data Platforms, personalization engines, RPA)
Ensure data flows in real time
Prioritize use cases with direct business impact (retention, up-selling, lead scoring…)

Conclusion

Investing in AI, automation, or CRM platforms without a solid Data Foundation is like building a house on sand.
Before thinking about “which model to use,” you should ask yourself “what data feeds it and how is it governed?”

A robust and well-connected infrastructure not only improves your current projects but also prepares you for what’s next: autonomous agents, contextual decisions, predictive personalization, and end-to-end automation.

Want to strengthen your Data & Tech Foundation?

At Hike&Foxter, we help you build the digital foundations your business needs to grow with confidence.

Schedule a meeting

SEGUIR LEYENDO
9 July, 2025 POR Luz Castillejo Flor
Artificial Intelligence digital transformation Google I/O search engine

Google transforms its search engine with Artificial Intelligence.

In May 2025, Google took a decisive step toward transforming the world’s leading search engine.
At its highly anticipated annual developer event, Google I/O, the Mountain View-based company unveiled a host of innovations powered by artificial intelligence (AI) that not only enhance user experience but are set to redefine how we interact with digital information.
SEGUIR LEYENDO
VIEW MORE
data
Mallorca 184, 08036
Barcelona, Spain