How to Create a Lead Nurturing Flow with Marketing Cloud

In today's digital marketing landscape, automation is key to optimizing the customer experience and increasing conversions. Lead nurturing is a strategy that aims to build relationships with prospects at every stage of the sales funnel through personalized content delivered at the right moment.

Salesforce Marketing Cloud is one of the most powerful platforms for automating and personalizing interactions, making it ideal for implementing this strategy. In this article, we’ll explore in detail how to design an effective lead nurturing flow using this tool, from setting objectives to continuous optimization.

What is Lead Nurturing and Why is It Important?

Lead nurturing involves building relationships with potential customers through relevant, personalized, and continuous communications. Its primary goal is to educate leads and guide them towards decision-making, thereby increasing conversion rates.

Some key benefits include:

  • Higher Conversion Rates: Well-nurtured leads are more likely to make a purchase.
  • Better Customer Experience: Personalization builds trust and loyalty.
  • Optimized Sales Team Time: With an automated flow, the team can focus on qualified leads.

With Marketing Cloud, you can integrate data from multiple sources, automate campaigns, and measure results in real-time, making it an indispensable tool.

Steps to Create an Effective Lead Nurturing Flow

1. Define Your Objectives and Segment Your Audience

Before you start, it's crucial to identify what you hope to achieve with your strategy. Some example objectives include:

  • Increase lead conversions by 20%.
  • Reduce conversion time by 15%.
  • Increase the retention rate of existing customers.

Audience Segmentation

Use tools like Marketing Cloud's Contact Builder to analyze and group your leads by:

  • Demographics: Age, location, gender.
  • Behavior: Cart abandonment, resource downloads, social media interactions.
  • Sales Funnel Stage: Cold or hot leads.

Precise segmentation ensures each lead receives relevant and timely messages.

2. Design the Customer Journey

The Customer Journey is the heart of your lead nurturing strategy. In Marketing Cloud, you can design this journey with Journey Builder, a tool that allows you to map out each interaction visually and logically.

Key Elements of the Customer Journey:

  • Initial Triggers: Define the event that starts the flow, such as subscribing to a newsletter or abandoning a shopping cart.
  • Touchpoints: Include emails, SMS messages, push notifications, or personalized ads.
  • Conditions: Personalize the flow based on lead actions, such as opening an email, clicking a link, or not responding within a specific timeframe.

Practical Example:

Let’s say a user registers on your website. The flow could include:

  • A welcome email with an exclusive discount.
  • A second email with educational content (eBook or guide).
  • A reminder about the initial offer if the user does not make a purchase within 5 days.
  • A personalized SMS with recommendations if the lead abandons their cart.

3. Create Relevant and Engaging Content

Content is the engine that drives your lead nurturing flow. Ensure each piece adds value and motivates leads to move further down the sales funnel.

Key Strategies for Content:

  • Email Marketing:

    • Include an attractive subject line with the main keyword.
    • Personalize the body of the message using the customer’s name and preferences.
    • Add a clear call to action, like "Download your guide now."
  • Landing Pages:

    • Optimize them for conversion, ensuring they are fast, responsive, and visually appealing.
    • Include testimonials or case studies to build trust.
  • Visual Content:

    • Incorporate relevant images and videos.
    • Use SEO-optimized alt text.

Using Einstein Recommendations:

This Marketing Cloud feature allows you to suggest content or products based on previous customer interests and behaviors, increasing relevance and click-through rates.

4. Automate and Measure Results

Automation is one of Marketing Cloud’s main advantages. Set up your flow to work automatically but stay alert to key metrics.

Essential KPIs:

  • Open Rate: Indicates the effectiveness of the email subject line.
  • Click-Through Rate (CTR or CTOR): Measures the interest generated by the content.
  • Conversions: Verifies how many leads completed the desired action.
  • Abandonment Rate: Identifies where leads lose interest in the flow.

Analysis Tools:

Use Marketing Cloud’s dashboards to monitor these metrics and identify areas for improvement.

5. Continuous Optimization

An effective lead nurturing flow must evolve over time. Use the data collected to make strategic adjustments:

  • A/B Testing: Experiment with different subject lines, CTAs, or email designs to identify what works best.
  • Advanced Segmentation: Update your segments with new data to personalize interactions even further.
  • Direct Feedback: Surveys or forms can help you better understand the needs and expectations of your leads.

Practical Example of Optimization:

If you notice a low click-through rate on educational emails, consider adjusting the content to make it more interactive, such as including a tutorial video or explanatory graphics.

Conclusion

Implementing a lead nurturing flow with Marketing Cloud is a strategic investment that can transform the way your business interacts with leads. From initial segmentation to continuous optimization, each step plays a crucial role in the success of your campaign.

With Marketing Cloud, you can not only automate processes but also offer personalized experiences that strengthen relationships with your prospects and customers. Are you ready to take your marketing strategy to the next level?

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The seventh wave of AI is redefining CRM and data strategy

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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?

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  • 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:
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    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…
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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.

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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.
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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
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Conclusion

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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.

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