HubSpot connects with ChatGPT for generative AI-powered analysis

Generative artificial intelligence is no longer a futuristic promise — it's now a concrete tool for improving commercial performance. More and more companies are integrating models like ChatGPT and Claude into their CRM systems to streamline processes, generate automated content, personalize interactions, and enhance decision-making.

At Hike & Foxter, we know this first-hand: just yesterday, our co-CEO Eric Morera hosted a webinar where he demonstrated, step by step, how to use HubSpot’s new Deep Research connector with ChatGPT and Claude.

Portada Webinar Deep Research

Attendees received a list of curated prompts, two official HubSpot guides to properly configure the integration, and the full webinar recording.

In this article, we’ll explain why this integration could be a turning point in your digital strategy, how to implement it securely and effectively, and which real-world use cases are delivering the greatest impact for our clients.

Benefits of integrating generative AI into your CRM

The combination of generative AI and CRM is transforming how businesses engage with customers and manage internal operations. Some of the key benefits include:

1. Automating repetitive tasks

Models like ChatGPT and Claude can draft follow-up emails, meeting notes, ticket replies, and prospecting messages automatically and in context.

2. Boosting sales team productivity

By offloading operational tasks to AI, sales and marketing teams can focus on strategy, creativity, and customer relationships.

3. Personalization at scale

Generative AI can tailor messages and content based on each customer’s behavior, context, and preferences — with no additional effort.

4. Fast, contextual insights

Integrating tools like ChatGPT into your CRM enables natural language queries. For example: “What were the highest-value deals closed last quarter?”
And you’ll get a direct answer based on your CRM data

5. Intelligent workflow activation

AI doesn’t just respond or analyze — it can also trigger automated actions (create tasks, update properties, move deals along the pipeline) based on user or customer inputs.

HubSpot and ChatGPT: a pioneering integration

On June 4, 2025, HubSpot announced the launch of its first advanced research connector with ChatGPT. This allows marketing, sales, and service teams to interact with their CRM data directly from ChatGPT and extract strategic and operational insights in real time.

This integration signals a new era for CRM and generative AI — one focused on turning data into useful decisions at speed.

In addition, HubSpot released more than 100 updates focused on AI, data quality, and operational efficiency across all its Hubs, reinforcing its commitment to building a smarter CRM ecosystem.

How this integration works in practice

During Eric Morera’s webinar, he demonstrated how the connector enables you to:

  • Query and analyze CRM data using natural language through ChatGPT or Claude.
  • Receive contextual commercial insights and log them directly into HubSpot.
  • Use structured prompts to explore segments, identify opportunities, or generate content.

This approach allows you to extract real value from AI without leaving the HubSpot ecosystem — with full visibility and traceability.

Recommendations for implementing generative AI in your CRM

1. Start with a clear, high-impact use case.

2. Ensure proper data governance: validate what data you share with external AI tools.

3. Train your sales and marketing teams for everyday use.

4. Integrate AI outcomes into automated processes — AI alone isn’t enough; it must be activated.

5. Measure time saved and conversion improvements as key success metrics.

Conclusion

The integration between HubSpot and ChatGPT sets a new standard for how CRMs can help businesses become more agile, personalized, and effective. At Hike & Foxter, we’re working with clients to turn these advances into measurable results.

If you want to explore how to apply this technology to your business, contact us. We’ll help you design and implement secure, scalable solutions that combine generative AI, automation, and CRM.

Would you like the full list of prompts we shared during the webinar? Just email us at marketing@hikefoxter.com and we’ll send it to you.

To stay updated on our next webinars and content about AI, CRM, and automation, follow us on Instagram and Linkedin.

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HubSpot connects with ChatGPT for generative AI-powered analysis

Generative artificial intelligence is no longer a futuristic promise — it's now a concrete tool for improving commercial performance. More and more companies are integrating models like ChatGPT and Claude into their CRM systems to streamline processes, generate automated content, personalize interactions, and enhance decision-making.

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

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.

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.

data
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Barcelona, Spain