Leveraging Buyer Intent Data to Target High-Value Accounts: A Guide for B2B Tech & SaaS Marketers

Introduction

With the growing adoption of generative AI, the B2B SaaS landscape today is more competitive than ever. Every company now claims to be AI native, with strings of features being launched within traditional software at breakneck speed. 

Marketing teams leaning heavily on a traditional spray and pray approach for pipeline generation are running the risk of burning through their budgets without realising reasonable ROI. 

The importance of going after the right companies at the right time matters a lot.

The key words here are “right companies” and “right time”. 

How do you determine what the right company is and when the right time is? 

This is where intent data can inform your marketing efforts by enormous amounts.

Intent data reveals how interested a buyer is in purchasing your product. It uses very specific markers that you have set up, such as the number of times a prospect visits your website or downloads your digital assets, et cetera, to understand and infer where that prospect might be in their buying journey and whether you have a shot to swoop in.

In this guide, we will discuss this powerful tool that you have in your arsenal and how you can leverage it to get the most out of your Go-to-Market strategy. 

We will also cover types of intent data, common platforms you can use to collect it, how it complements your existing marketing campaigns, specifically on the ABM side, some pitfalls to avoid and finally, how you can choose the right intent data platform for your business. So, let’s get started.

What Is Buyer Intent Data?

Buyer intent data is behavioural information indicating if a specific company and its stakeholders within it are in the market looking for the same products and services that you also sell. As described previously, intent data tells you how interested a buyer is in purchasing your product.

You can divide the intent data primarily into two types:

First-Party - These are the signals that you get directly from your website or a channel that you own. For example, someone signed up for an upcoming webinar that your team is hosting or downloaded an industry report that you published. Other items that contribute to first party data are website visits, product trials started, and in-product behaviour during a trial period. You can be very confident in the validity of this type of intent data. 

Third-Party - As the name suggests, these are signals from external websites, such as keyword searches and searches on platforms like Gartner and G2. While not as reliable as first-party data, it is an important type for prospects who might not have discovered your brand yet.

There is another type, which is the second-party data, while not used commonly, it’s essentially first-party data captured by an external marketing agency on your behalf. 

Often, we are asked which one is better. And our answer is always to trust the first-party data more, but use both to target the right accounts. 

There are multiple technology platforms that not only help you set up intent tracking on your channels but also provide a slew of third-party data points. Bombora, 6Sense and DemandBase are the three that we like the most.

Why Intent Data Matters for B2B Tech & SaaS Companies

I mentioned in the introduction why marketers should start leveraging intent data more heavily in 2025 and beyond, especially in the technology and SaaS space. 

Let’s explore those in more detail here:

The most significant trend over the last three years has been the emergence of generative AI; both legacy and born-native AI companies are generating a lot of noise in the market. This noise attracts all kinds of buyers. Intent data helps you filter away the non-serious buyers and focus on the serious ones. 

The second point of consideration is that buyers today like to do self-research before speaking to a vendor. Having an insight into where the buyer is in their purchase cycle, what they have researched and what their timeline is to complete the purchase is a powerful use case of intent data.

Next, intent data also helps you identify the persona of your typical buyer. Are they C-level executives, a middle manager or an intern? This helps your Go-to-Market teams to customise their messaging based on the problem faced by each of the personas and even focus on the persona that matters to them the most.

And lastly, if your sales cycles are complex and lengthy, intent data helps you get leading indicators on how your deal is progressing. 

How Intent Data Complements Account-Based Marketing (ABM)

If you have been following our content here at xGrowth and APAC’s B2B Growth Podcast, ABM or Account-Based Marketing, is all about prioritising high-value accounts that meet your ideal customer profile and creating customised target plans for them. 

B2B intent data helps you understand who these high-value accounts are. 

Sure, a high-value account could be the largest business by revenue in Australia, as an example. But for your business, a high-value account could also be a mid-sized company aggressively looking in the market to buy a product or service that you sell.

Outside of providing you with an understanding of who to target, intent data also helps you gather intelligence on what content to create for your next or ongoing ABM campaign. As an example, if you find out that certain sections of your website are more popular than others amongst your target demographic, there is a case to double down on the sections.

Here are some more use cases where intent data complements your ABM efforts.

• Targeting refinement → Think of your ABM list like a guest list for an event. You know who you want to invite (your ICP), but intent data shows you who’s already on their way to the venue. Instead of treating all accounts equally, you can focus your budget and outreach on the ones already showing signs they’re interested.
• Personalisation triggers → This is about changing the conversation to match what the account cares about right now. For example, if a company is researching “data residency in Australia,” your ads, emails, or outreach can highlight your compliance features and local data storage capabilities. That way, they feel like you “get” their priorities, instead of sending them a generic sales pitch.
• Operational workflows → Intent data can act like an early-warning system. When an account suddenly starts researching your solution, alerts can go straight to sales in Slack, ads can automatically turn on for that company, or a tailored email sequence can begin. The idea is to remove manual work so you reach the account while it’s still hot.

Practical Ways to Use Intent Data in Marketing & Sales

To see how intent data works in practice, let’s look at NimbusCRM, a hypothetical SaaS company that has just launched an AI-powered customer support chatbot. Here’s how they use both first-party and third-party intent data to drive adoption:

1. Identify Ideal Customer Profiles (ICP) and Tier Accounts

NimbusCRM defines its ICP as mid-sized SaaS businesses with large customer support teams.

• First-party signals: Using marketing automation tools like HubSpot or Marketo, they track which companies visit their chatbot landing page, download ROI calculators, or register for webinars.
• Third-party signals: Platforms like Bombora or 6sense show which accounts are consuming content around topics such as “AI chatbot for CRM” or “automated ticket resolution.”

Accounts that fit the ICP and show strong signals are flagged as Tier 1 priority targets, while others are nurtured over time.

2. Personalise Messaging and Campaigns at Scale

Intent signals tell NimbusCRM what each account cares about most:

• If third-party data shows research into “reducing call centre costs,” their emails and ads emphasise cost savings and operational efficiency.
• If first-party behaviour includes downloading a “Customer Experience Benchmark Report,” the follow-up focuses on faster ticket resolution and improved CSAT scores.

Marketing automation dynamically adjusts landing pages, emails, and ad creative to reflect these intent triggers.

3. Prioritise Sales Outreach by Intent Level

When intent spikes across multiple signals, sales gets notified immediately.

• Example: An account is flagged by Bombora for researching “best AI chatbots for CRM,” while their Head of Customer Success spends several minutes on NimbusCRM’s pricing page. A Slack alert is triggered, and the assigned rep sends a tailored outreach message, referencing their current research and offering a quick demo.

Lower-intent accounts remain in nurture campaigns until signals grow stronger.

4. Inform Content Strategy

NimbusCRM notices through intent platforms that many accounts are researching “AI chatbot compliance and privacy.”

The marketing team responds with:

• A blog: “How AI Chatbots Can Stay Compliant with Local Privacy Laws”
• A gated compliance checklist for IT and legal teams
• A webinar with an industry data expert

This content not only nurtures engaged accounts but also attracts new ones searching for similar topics.

5. Improve Paid Ad Targeting and Reduce Waste

Instead of targeting every SaaS company in a broad category, NimbusCRM only runs ads where there’s clear buying intent:

• LinkedIn Matched Audiences and Google Ads Customer Match campaigns are set up against intent-flagged companies.
• Retargeting ads are automatically triggered if someone from a priority account visits the chatbot landing page, encouraging them to sign up for a free trial.

The result: less wasted spend and higher-quality leads.

6. Highlight SaaS-Specific Use Cases (Retargeting & Upsell)

• Retargeting prospects: If G2 Buyer Intent shows a company comparing CRM chatbot providers, NimbusCRM serves targeted ads such as “Faster AI Chatbot Deployment With NimbusCRM.”
• Upselling customers: If an existing CRM client starts reading blog posts about “AI automation in customer success,” their account manager proactively introduces the chatbot as a natural extension of their current plan.

By combining first-party signals from their own website and CRM with third-party intelligence from platforms like Bombora, 6sense, and G2, NimbusCRM ensures that marketing and sales focus on the right accounts, at the right time, with the right message.

Challenges and Pitfalls to Avoid

Alright, we've discussed the relevance of intent data and how you can utilise it to support your ABM campaigns. This section will cover some of the common pitfalls to avoid. 

The two biggest ones that we always warn our customers about are as follows:

1. Not using third-party data and first-party data in combination with each other: I highlighted this before, but to truly understand your prospect’s intent, you need to know two things: 
   • They are searching for the service or the product you offer in general
   • They have spent time on your website and other channels. 

Solely relying on the third-party intent data is the most common mistake we have seen marketing teams make.

Some marketers may argue that there could be instances where all they have is the third-party intent data, and that is fine to get started with, but remember to bake in the direct signals from your social and online channels as your business gains more traction.

1. Not contextualising the intent: This involves not collecting the right context when gathering first-party intent data. 

Going back to the example of our hypothetical company, NimbusCRM, imagine they have created a report on how customer support managers can implement a generative AI chatbot. 

To download this report, they ask for the user’s email address, name and phone number. While it’s good that the Nimbus team kept the form simple, without doing further research on the designation of the person downloading the asset via third-party tools such as LinkedIn, that intent signal can be misleading, i.e. what if it was an intern who downloaded that report and not the customer support manager they were hoping to target. 

Contextualising and enriching intent is critical to ensure you are using it correctly.

Choosing the Right Intent Data Tools

As we come close to the end of this guide, I wanted to answer another burning question that marketing teams ask us: How do I choose the right intent data tools?

At xGrowth, we have a 4C+2 framework. It has six dimensions that you can evaluate any platform on. The scoring scale could be anything. Our motivation for this framework is also to shift your question from “Which tool is the best?” to “Which tool is the best fit for our business needs?”

Conclusion

I hope that you found value in this guide. We at xGrowth believe that consistently identifying and targeting high-intent accounts across multiple channels can be a solid differentiator for any business driven by its marketing strategy. 

It complements your ABM efforts, ensuring you spend your time and money in the right places. 

If you would like to partner with us or know more about how we work with intent data and ABM for our customers, fill out the form below to get in touch with our ABM strategist.