The martech world spent the last few years talking about the death of third-party cookies. Chrome’s Privacy Sandbox timelines kept shifting. Marketers kept waiting. Some companies are prepared. Many didn’t.
In 2026, the waiting game is over. Whether or not Google follows through on full cookie deprecation, the market has already moved. 64% of firms are using data clean rooms. Privacy regulations are tightening across regions. And B2B buyers expect personalization without feeling surveilled.
First-party data isn’t just an alternative to third-party cookies. It’s becoming the foundation of every effective martech stack. This blog looks at why, and more importantly, how B2B companies can build a first-party data strategy that actually works.
What Is First-Party Data (and Why It Matters More Now)
Let’s get the basics right. First-party data is information you collect directly from your audience through your own channels, such as your website, app, email, events, product, and CRM. It includes behavioral data (pages visited, content downloaded, features used), transactional data (purchases, subscriptions), and declared data (form fills, preferences, survey responses).
Third-party data, by contrast, comes from external sources that track users across the web, typically through cookies or data brokers. It’s been the backbone of digital advertising for two decades.
The shift is straightforward: first-party data is more accurate, more compliant, and more trustworthy. You know where it came from. You know how it was collected. And your customers consented to share it.
For B2B SaaS companies in particular, first-party data is often richer than anything a third-party provider can offer. Your product usage data alone, which features accounts' use, how often they log in, and where they get stuck, tells you more about buying intent than any cookie trail.
How First-Party Data Fits into the 2026 Martech Stack
The modern B2B martech stack has a lot of moving parts: CRM, marketing automation, ABM platforms, analytics tools, content management, and ad platforms. First-party data is the thread that connects all of them.
The Customer Data Platform (CDP) is the Central Hub
CDPs have moved from “nice to have” to essential infrastructure for companies serious about first-party data. A CDP pulls data from every touchpoint, website, email, product, CRM, events, and creates a unified profile for each account and contact.
U.S. B2B martech spend is forecast to approach $14 billion by 2027, and CDPs are a growing share of that investment. About 20% of B2B companies currently have planned CDP investments, and that number is climbing fast as the value becomes clearer.
For B2B specifically, CDPs like Salesforce Data Cloud and Adobe Real-Time CDP now offer B2B editions that create unified profiles at both the account and contact level. This matters because B2B buying decisions involve committees, not individuals. You need to see how the CTO, the VP of Engineering, and the procurement lead are all engaging and connect that to a single account view.
Connecting CRM, Product Analytics, and Website Data
One of the biggest challenges in B2B martech is data fragmentation. Your CRM has one view of the customer. Your website analytics platform has another. Your product team has usage data sitting in a completely different system. Marketing automation captures email engagement but not product behavior.
First-party data strategy in 2026 is about unification. The goal is a single dataset where CRM data (deal stage, account owner, contract value), website behavior (pages visited, content consumed, pricing page views), product usage (feature adoption, login frequency, support tickets), and email engagement (opens, clicks, unsubscribes) all feed into one view.
Without this, even the best AI tools and ABM platforms are working with incomplete information. You can’t personalize effectively if you only see a fraction of how an account interacts with your brand.
Replacing Third-Party Cookies: What Actually Works
The cookie replacement conversation has been going on for years. Here’s what’s actually working for B2B companies in 2026.
Intent Data Built on First-Party Foundations
Intent data hasn’t gone away; it’s shifted. The most reliable intent signals in 2026 come from layering your first-party engagement data with consented third-party sources. Platforms like Bombora, 6sense, and G2 Buyer Intent still provide valuable third-party signals, but companies that also track how target accounts engage with their own content, website, and product have a significant advantage.
The combination matters. Third-party intent tells you an account is researching your category. First-party data tells you they’re specifically interested in your solution. Together, they give you confidence in both timing and relevance.
Zero-Party Data: Letting Customers Tell You What They Want
Zero-party data is a subset of first-party data that customers explicitly share with you through preference centers, interactive quizzes, onboarding surveys, and feedback forms.
This is gaining traction in B2B for a simple reason: it cuts through the inference game. Instead of trying to figure out what an account cares about based on browsing behavior, you ask them. A well-designed preference center on your website or a quick onboarding questionnaire after a demo signup gives you actionable information that no cookie could ever provide.
The challenge is making it worth the customer’s time. Nobody fills out a 20-field form for fun. The best zero-party data tactics offer something in return: a personalized benchmark report, a tailored product recommendation, or simply a better user experience.
Data Clean Rooms for Privacy-Safe Collaboration
Data clean rooms are becoming a standard part of the B2B martech toolkit. With 64% of firms already using them, they’re no longer experimental.
A clean room lets two organizations (say, your company and a media publisher, or your company and a data partner) match their datasets without either party seeing the other’s raw data. This is critical for privacy compliance while still enabling audience targeting and measurement.
For B2B marketers, clean rooms are particularly useful for enriching first-party data with partner data, running co-marketing campaigns with shared audiences, and measuring campaign impact across channels without relying on cookies.
Using First-Party Data for AI Personalization
One of the most valuable things first-party data does in 2026 is power AI-driven personalization. But there’s a line between “helpful” and “creepy,” and B2B marketers need to be aware of it.
Personalization That Adds Value
The best AI personalization uses first-party data to make experiences more relevant, not more invasive. This looks like showing a returning visitor content related to the topics they’ve previously explored. Or dynamically adjusting a website’s homepage to highlight use cases relevant to the visitor’s industry. Or sending email sequences that adapt based on which content the recipient actually engaged with, not just what list they’re on.
The key is that personalization should feel helpful, not surprising. If a prospect has been reading your blog posts about data governance and you follow up with a case study about data governance in their industry, that’s useful. If you reference specific pages they visited in a cold email, that’s uncomfortable.
The Role of AI in Making First-Party Data Actionable
Raw data isn’t useful on its own. The real value comes from AI models that can analyze first-party data and surface patterns humans would miss. Predictive lead scoring models that identify which accounts are most likely to convert based on behavioral patterns. Content recommendation engines that suggest the right asset for each stage of the buyer journey. Churn prediction models that flag at-risk accounts based on declining product usage.
But here’s the catch: these models are only as good as the data they’re trained on. Garbage in, garbage out. That’s why data quality and unification (covered above) aren’t just nice operational improvements; they’re prerequisites for AI personalization that actually works.
First-Party Data and LLM/AI Search Visibility
Here’s a trend that’s catching many B2B marketers off guard: AI-generated search results and LLM-powered answer engines (like Google’s AI Overviews, Perplexity, and ChatGPT) are changing how B2B buyers discover information. AI Overviews now appear in roughly 30% of B2B searches.
What does this have to do with first-party data? More than you’d think.
Your content strategy, fueled by first-party insights about what your audience actually cares about, determines whether AI systems reference your brand in their answers. Companies that create original, experience-based content built on proprietary data (customer research, benchmarks, product insights) are more likely to be cited by LLMs than those publishing generic, commodity content.
First-party data gives you a content advantage: you know the exact questions your audience is asking (from search data and support tickets), the specific challenges they face (from customer interviews and product analytics), and the outcomes they achieve with your solution (from usage data and success metrics). That knowledge lets you create content that’s genuinely unique and authoritative, exactly what both search engines and AI systems are looking for.
Building a First-Party Data Strategy: Where to Start
If you’re a B2B SaaS company or technology firm looking to build (or improve) your first-party data strategy in 2026, here’s a practical starting point.
First, audit what you’re already collecting. Most companies have more first-party data than they realize; it’s just scattered across disconnected systems. Map out every touchpoint where you capture data: website, product, CRM, email, events, and support.
Second, unify your data. This is where a CDP or a well-configured CRM like HubSpot becomes critical. The goal is a single account and contact view that every team can access.
Third, establish consent and governance practices. First-party data’s biggest advantage is trust; don’t undermine it with sloppy collection practices. Make consent clear, honor preferences, and build systems that can handle data deletion requests.
Fourth, activate the data. This means connecting your unified data to your marketing automation, ABM platform, and sales tools so that insights actually inform action. Data sitting in a dashboard nobody checks is worthless.
Fifth, close the loop. Track how first-party data-informed campaigns perform compared to campaigns that relied on third-party signals. This feedback loop is what turns a data strategy into a competitive advantage.
The Smarketers’ Perspective
At The Smarketers, first-party data is at the core of how we build marketing programs for our B2B clients. As a HubSpot Gold Partner, we help companies implement and optimize HubSpot as their central data hub, connecting website behavior, email engagement, CRM data, and campaign performance into a single, actionable view.
Our ABM programs are built on this foundation. When we run 1:1 or 1:few ABM campaigns, the personalization isn’t surface-level. It’s informed by real engagement data from the accounts we’re targeting. And when we implement demand generation strategies, the scoring models and nurture sequences are powered by first-party signals, not borrowed audiences.
The companies that invest in first-party data infrastructure now are the ones that will have a lasting competitive edge, not just in marketing, but in every customer-facing function.
Frequently Asked Questions
How do you replace third-party cookies with first-party data in your martech stack?
Start by ensuring every customer touchpoint feeds data into a centralized system (CDP or CRM). Use website tracking, product analytics, email engagement, and event data as your core sources. Layer in consented third-party intent data for breadth. Over time, your first-party data becomes more reliable and actionable than any cookie-based source.
What are practical ways small B2B SaaS companies can collect first-party data without annoying users?
Focus on value exchange. Offer personalized recommendations in return for onboarding questionnaires. Use progressive profiling instead of long forms. Track product usage behavior (it’s the richest data source and requires zero form fills). And make preference centers genuinely useful, let users control what content they receive.
Is investing in a CDP worth it just to activate first-party data across email, ads, and AI tools?
For mid-market and enterprise B2B companies, yes, if your data is currently fragmented across multiple tools. A CDP pays for itself by reducing wasted ad spend, improving personalization quality, and giving every team access to the same account intelligence. For smaller companies, a well-configured HubSpot or Salesforce instance can serve as a lightweight CDP.
How do you connect first-party data to AI search and LLM experiences so your brand shows up in answers?
Create content informed by proprietary data, original research, customer benchmarks, and product insights. Structure it for AI consumption with clear answers, FAQ sections, and schema markup. Monitor how AI platforms reference your brand using LLM monitoring tools. And keep publishing consistently, because AI systems weigh freshness and depth of expertise.
Key Takeaways
First-party data isn’t a trend; it’s the foundation of modern B2B marketing. In 2026, the companies that have clean, unified, and activated first-party data will outperform those still relying on third-party signals for targeting, personalization, and measurement.
The technology exists. CDPs, HubSpot, and data integration tools make it more accessible than ever. The real differentiator is whether your team treats data infrastructure as a strategic priority or an afterthought.
Looking to build a first-party data strategy that powers your ABM and demand gen programs? The Smarketers can help you get it right from the start.
