What is Customer Intent Data and How to Use It in B2B Marketing

We’re facing a crisis of relevance that’s costing businesses literally millions in wasted B2B marketing resources and missed opportunities. According to McKinsey, 57% of sellers admit they barely glance at content produced by their marketing teams, dismissing it as generic and unresponsive!

But amidst this challenge lies a huge opportunity. Customer intent data, including buyer intent. One large telco, harnessing the power of Intent Recognition and Generation (IRG) technology, saw their contact rate for opportunity creation surge by 15% and their overall opportunities skyrocket by 53%.

This isn’t an isolated success story. Foundry’s recent survey of 500 B2B technology marketers reveals a trend that’s impossible to ignore. For the third consecutive year, satisfaction with Account-Based Marketing (ABM) is soaring. An overwhelming 93% of respondents rated their ABM efforts as extremely or very successful, up from 84% last year. A staggering 91% of them are leveraging customer intent data to prioritize accounts, identify relevant content, and build targeted account lists.

The message is clear: in today’s B2B landscape, customer intent data is a must have. But how do you harness this powerful tool for B2B marketing? How do you transform raw data into a marketing strategy that not only captures attention but drives measurable results?

That’s precisely what we’re here to unpack. In this comprehensive guide, we’re going to explore what customer intent data is, why it’s crucial for B2B marketing, and most importantly, how you can leverage it to supercharge your marketing efforts.

What is Buyer Intent Data?

Let’s start with the basics. Customer intent data is information that indicates a prospect’s likelihood to purchase your product or service. It’s essentially digital body language that signals a company’s interest in solving a particular problem or exploring a specific solution. Understanding consumer intent allows businesses to tailor their marketing strategies and product designs to better meet customer needs and intentions.

Types of Intent Data

There are primarily two types of intent data: first-party and third-party. First-party intent data is information you collect directly from interactions with your own digital properties, such as your website, email campaigns, or social media channels. This data is incredibly valuable because it’s specific to your brand and offerings. Collecting customer feedback through surveys and feedback tools can enhance the value of first-party intent data by providing direct insights from customers.

On the other hand, third-party intent data is collected from external sources, often aggregated from various B2B websites, forums, and platforms. This type of data gives you a broader view of what your potential customers are interested in across the internet, not just on your own properties.

Why is Intent Data Important for B2B Marketing?

In the B2B world, the buying process is complex and often involves multiple decision-makers. Intent data helps you navigate this complexity by providing insights that can transform your marketing and sales approach.

Firstly, it allows you to identify prospects who are actively researching solutions like yours. This means you’re not shooting in the dark, but targeting companies that have already shown interest in what you offer.

Secondly, intent data helps you understand what stage of the buying journey your prospects are in. Are they just starting to explore solutions, or are they close to making a decision? This knowledge allows you to tailor your approach accordingly. Understanding customer preferences in the buying stages is critical for accurately anticipating customer intent and improving marketing strategies.

Moreover, intent data enables you to customize your messaging to address the specific needs and interests of your prospects. Instead of generic outreach, you can craft personalized communications that resonate with what your prospects are actually looking for.

Lastly, intent data allows you to prioritize your outreach efforts for maximum impact. Just by focusing on the prospects showing the highest intent, you can allocate your resources more efficiently and increase your chances of success.

At CustomerBase, we’ve seen how powerful this can be. By aligning marketing, sales, and leadership around a unified data layer, teams can collaborate on shared insights and execute strategies with consistency. This alignment is crucial for making the most of intent data and driving real results.

The Benefits of Using Intent Data in B2B Marketing Strategies

In my years at Sumo Logic and now at CustomerBase AI, I’ve seen firsthand how intent data can transform B2B marketing. In this section I want to share some of the main benefits I’ve observed, from significantly improved lead quality to shorter sales cycles. Additionally, intent data can enhance customer satisfaction by addressing customers' needs and pain points more effectively.

1. Improved Lead Quality.

One of the biggest challenges I faced as a Sales Development Representative at Sumo Logic was ensuring that we were focusing on high-quality leads. It’s a common problem in B2B marketing and sales – you might have a large number of leads, but how many of them are actually likely to convert?

This is where intent data shines. By helping you identify prospects who are actually in-market for your solution, understanding the customer's intent significantly improves the quality of your leads. Instead of casting a wide net and hoping for the best, you can focus your efforts on companies that have demonstrated a genuine interest in solutions like yours.

This shift from quantity to quality can have a profound impact on your marketing and sales efficiency. Your teams spend less time chasing unqualified leads and more time engaging with prospects who are likely to convert. The result? Higher conversion rates, more efficient use of resources, and ultimately, better ROI on your marketing and sales efforts.

2. Enhanced Personalization.

Today, generic, one-size-fits-all approaches simply don't cut it anymore. Buyers expect personalized experiences that speak directly to their needs and challenges. Intent data is transformational in this regard.

With intent data, you can tailor your messaging to address the specific pain points and interests of your prospects. For instance, if intent data shows that a prospect has been researching cloud security solutions, you can reach out with content and messaging that specifically addresses cloud security, rather than your general product offerings.

This level of personalization can significantly improve engagement rates and conversion rates. It shows prospects that you understand their needs and have solutions that are relevant to them. It's the difference between shouting into the void and having a meaningful conversation with someone who's actually interested in what you have to say.

3. Optimized Marketing Spend.

Marketing budgets are always under scrutiny, and as marketers, we're constantly asked to justify our spend and show ROI. Intent data can be a powerful ally in this regard.

Instead of spreading your resources thin trying to reach everyone, you can concentrate on those who are most likely to convert.

This might mean adjusting your ad spend to target companies showing high intent, or focusing your content creation efforts on topics that your high-intent prospects are researching. The result is a more efficient use of your marketing dollars, with a higher return on investment.

4. Shortened Sales Cycles.

Time is money, especially in B2B sales where sales cycles can stretch on for months. Intent data can help you shorten these cycles by enabling you to engage prospects at the right time with the right message.

When you know a prospect is actively researching solutions like yours, you can reach out proactively with relevant information. This timely outreach can help you get your foot in the door earlier in the buying process, positioning you as a helpful resource rather than an interruption.

Moreover, by tailoring your approach based on the prospect's demonstrated interests, you can move conversations forward more quickly. You're not wasting time on irrelevant pitches or features – you're addressing the specific needs and concerns that the prospect actually cares about.

5. Increased Win Rates.

At the end of the day, it all comes down to closing deals. Intent data can significantly boost your win rates by ensuring that you're not just targeting the right companies, but engaging them in the right way at the right time.

By aligning your outreach with a prospect's current interests and needs, you're more likely to resonate with them. You're not just another vendor – you're a solution provider who understands their challenges and can offer relevant solutions.

Furthermore, intent data can help you identify and address potential objections before they become roadblocks. If you know what topics a prospect has been researching, you can proactively address concerns or misconceptions, smoothing the path to a successful deal.

How to Collect and Analyze Intent Data

Collecting and analyzing intent data effectively is a challenge. Businesses can determine customer intent by leveraging AI to automate the gathering of multiple data points and analyze customer behaviors within their funnels. Let me share some of my insights and tips on how to do it the right way.

1. First-Party Intent Data Collection.

Collecting first-party intent data is all about maximizing the insights you can gain from your own digital properties. It starts with implementing robust website analytics to track user behavior. This goes beyond just page views – you want to understand how users are interacting with your site, what content they're engaging with, and what actions they're taking.

Use marketing automation tools to monitor email engagement. Track not just open rates, but also click-through rates, time spent reading emails, and which links are being clicked. This can give you valuable insights into what topics and offers are resonating with your audience.

Don't forget about content downloads and webinar attendance. These are strong indicators of interest and can help you understand what topics your prospects are most interested in. For SaaS companies, product usage data can also be a goldmine of intent signals, showing you which features users are engaging with most.

2. Third-Party Intent Data Sources.

While first-party data is invaluable, third-party intent data can give you a broader view of your market and potential customers. There are several reputable providers of third-party intent data, each with their own strengths and methodologies.

TechTarget, for instance, provides intent data based on users' interactions with their network of technology-focused websites. G2 offers intent data based on user behavior on their software review platform, while ZoomInfo provides intent data along with their B2B database.

When choosing a third-party intent data provider, consider factors like the breadth and depth of their data sources, the relevance of their data to your specific industry and target market, and how easily their data can be integrated with your existing systems.

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3. Analyzing Intent Data.

Collecting intent data is just the first step – the real value comes from how you analyze and act on this data. Start by establishing a clear ideal customer profile (ICP). This will help you focus your analysis on the signals that are most relevant to your business.

Next, define the key intent signals that matter for your business. These might include specific topics being researched, engagement with certain types of content, or particular actions taken on your website or product.

To make sense of large volumes of intent data, leverage AI and machine learning algorithms. These can help you identify patterns and trends that might not be immediately apparent, and can predict which prospects are most likely to convert based on their intent signals.

Finally, integrate your intent data analysis with your CRM and marketing automation platforms. This allows you to act on intent insights in real-time, triggering automated workflows or alerting sales reps to high-intent prospects.

At CustomerBase AI, we've developed a powerful data science framework to develop insights from deal data. This allows us to help companies validate their ICP by looking into past won and lost deals to understand who they should be targeting. By combining this historical analysis with real-time intent data, we can provide a comprehensive view of who to target and when.

How to Implement an Intent Data Strategy in Your B2B Marketing

When we started CustomerBase AI, one of our biggest challenges was integrating intent data into our marketing strategy effectively. It’s not just about having the data. It’s about knowing how to use it. It's important to note that implementing customer intent strategies in your marketing campaigns can generate data that not only helps sales teams but also informs product creation and enhances customer experience metrics.

Step 1: Define Your Objectives.

Before diving into intent data, it's crucial to clearly outline what you want to achieve. Are you looking to improve lead quality? Increase conversion rates? Shorten the sales cycle? Or perhaps you're aiming to expand into new markets?

Your objectives will guide every aspect of your intent data strategy, from the types of data you collect to how you analyze and act on it. Be specific in your goals – instead of a vague aim like "improve marketing performance," set concrete objectives like "increase MQL to SQL conversion rate by 20% within six months."

Step 2: Identify Your Ideal Customer Profile (ICP).

You can't effectively use intent data without a clear understanding of who your ideal customer is. At CustomerBase, we help companies validate their ICP by analyzing past deals. This ensures that your intent data strategy is focused on the right targets from the start.

Your ICP should go beyond basic firmographics like company size and industry. Consider factors like technology stack, business challenges, growth stage, and buying process. The more detailed your ICP, the better you'll be able to interpret and act on intent signals.

Step 3: Choose Your Intent Data Sources.

Based on your objectives and ICP, select the most appropriate intent data sources. This will likely be a combination of first-party and third-party data. Your first-party data will give you deep insights into how prospects interact with your brand specifically, while third-party data can provide a broader view of your prospects' interests and activities across the web.

Consider the strengths and limitations of each data source. For example, your website analytics might give you detailed information about how prospects engage with your content, but it won't tell you what they're researching on other sites. A third-party intent data provider might give you that broader view, but may not have the granularity of your first-party data.

Step 4: Integrate Intent Data into Your Tech Stack.

For intent data to be truly valuable, it needs to flow seamlessly into your existing marketing and sales tools. This might involve integrating with your CRM system to enrich prospect profiles with intent data, connecting to your marketing automation platform to trigger intent-based campaigns, or setting up custom dashboards for easy visualization of intent trends.

The goal is to make intent data accessible and actionable for your entire team. A sales rep should be able to see relevant intent signals directly in their CRM when they're looking at a prospect. A marketer should be able to easily segment their database based on intent signals for targeted campaigns.

Step 5: Develop Intent-Based Marketing Campaigns.

Now that you have intent data flowing, it’s time to put it to use. Develop marketing campaigns that leverage this data to deliver more relevant, timely, and effective communications to your prospects. To create effective campaigns, it is essential to understand customer intent by analyzing their interactions and feedback.

For example, you might create targeted email campaigns based on specific intent signals. If a group of prospects has been showing interest in a particular feature or solution, you can send them content that speaks directly to that interest.

Consider personalizing your website experience for high-intent visitors. This could involve dynamically changing the content or calls-to-action based on what you know about the visitor’s interests and intent.

Account-based advertising campaigns can be supercharged with intent data. Instead of targeting all accounts equally, you can focus your ad spend on the accounts showing the highest levels of intent, increasing your chances of engagement and conversion.

Don’t forget about sales enablement. Create content and resources that help your sales team leverage intent data in their outreach. This might include email templates tailored to different intent signals, or battle cards that address the specific pain points and interests indicated by a prospect’s intent data.

Step 6: Align Sales and Marketing Efforts.

One of the key benefits of intent data is its ability to align sales and marketing teams. Ensure that sales has visibility into marketing-captured intent signals, and that marketing is aware of sales interactions and can support accordingly.

Both teams should be using the same criteria to evaluate opportunities. At CustomerBase AI, we've seen how powerful this alignment can be. When sellers are evaluating opportunities on the same objective fit criteria as marketing, misunderstandings go down, and pipeline quality goes up.

Consider implementing regular meetings between sales and marketing to discuss intent data insights and coordinate strategies. This collaboration can lead to more effective campaigns, better-quality leads, and ultimately, more closed deals.

Step 7: Monitor, Measure, and Optimize.

Implementing an intent data strategy is not a one-and-done process. It requires continuous monitoring, measurement, and optimization. Regularly track the performance of your intent-based marketing efforts.

Key metrics to monitor include engagement rates of intent-based campaigns, conversion rates from MQL to SQL, sales cycle length for intent-influenced deals, and win rates for intent-identified opportunities.

Use these insights to refine your approach over time. Maybe certain intent signals are more predictive of success than others, or perhaps some campaigns are particularly effective with high-intent prospects. By continuously learning and adjusting, you can maximize the value you get from your intent data.

Advanced Techniques for Leveraging Intent Data in B2B Marketing Strategies

As we’ve grown CustomerBase AI, we’ve continuously pushed the boundaries of what’s possible with intent data. Here are some of the more sophisticated techniques we’ve developed and implemented.

Predictive Lead Scoring

Take your lead scoring to the next level by combining intent data with other firmographic and behavioral data. This allows you to create sophisticated models that not only identify which leads are most likely to convert, but also predict when they're likely to be ready for sales engagement.

For example, you might assign higher scores to leads that not only fit your ICP, but are also showing high levels of intent around topics relevant to your solution. You could also factor in the recency and frequency of intent signals, giving more weight to prospects who are showing sustained or increasing interest over time.

Intent-Based Account-Based Marketing (ABM)

Intent data can supercharge your ABM efforts by helping you identify which accounts within your target list are showing the highest levels of interest. This allows you to focus your resources on the accounts most likely to convert, maximizing the efficiency of your ABM program. Identifying customer intent is foundational for crafting effective ABM strategies and improving overall engagement.

Consider creating tiered engagement strategies based on intent levels. High-intent accounts might receive more personalized, high-touch outreach, while lower-intent accounts could be nurtured with more general awareness-building content.

Competitive Intelligence

Intent data isn't just about understanding your prospects – it can also provide valuable insights into your competitive landscape. By analyzing which competitors your prospects are also researching, you can gain a better understanding of your market position and refine your messaging accordingly.

For instance, if you notice that prospects researching your solution are also frequently looking into a particular competitor, you might create content that directly addresses how you differentiate from that competitor. Or, if you see prospects researching alternative approaches to solving the problem your product addresses, you could create educational content that highlights the benefits of your approach.

Content Optimization

Use intent data to inform your content strategy. Analyze which topics and types of content are driving the most engagement among high-intent prospects. This can help you focus your content creation efforts on the areas that are most likely to drive conversions.

You might discover, for example, that prospects showing high intent are particularly engaged with how-to guides or case studies in a specific industry. Armed with this knowledge, you can prioritize creating more of this type of content, ensuring that you're providing value to your most promising prospects.

Intent-Driven Personalization at Scale

Leveraging AI and machine learning, you can automate personalization based on intent signals. This allows you to deliver highly relevant experiences to a large number of prospects simultaneously.

For example, you could set up systems that automatically adjust email content, website experiences, or ad messaging based on the specific intent signals a prospect is showing. This level of personalization, delivered at scale, can significantly improve engagement and conversion rates.

How to Overcome Common Challenges with Intent Data

Working with intent data isn’t always easy. Personally, I’ve encountered numerous obstacles when implementing intent data strategies. From data quality issues to privacy concerns, and the ever-present challenge of aligning sales and marketing teams, I’ve seen it all.

Some of these challenges are important to overcome, especially as AI tools and chatbots increasingly resolve customer requests independently by understanding customer intent and enhancing customer experience. Here are some of the most common challenges with customer intent data:

Data Quality and Accuracy

One of the primary challenges with intent data is ensuring its quality and accuracy. Not all intent signals are created equal, and it's crucial to be able to distinguish between genuine interest and noise.

To overcome this challenge, work with reputable data providers and continuously validate the quality of your data against actual outcomes. Regularly analyze the correlation between intent signals and conversions, and be prepared to adjust your strategy based on what you learn.

It's also important to combine multiple data points rather than relying on a single signal. For example, a prospect downloading a whitepaper might indicate some level of interest, but if they've also been visiting pricing pages and requesting a demo, that's a much stronger indicator of genuine intent.

Privacy and Compliance

Privacy laws like GDPR and CCPA are strict and companies must handle customer data carefully.

This isn't just about avoiding fines – it's about maintaining trust with your prospects and customers.

To navigate this challenge, ensure your intent data practices are compliant with relevant regulations. Be transparent about your data usage and provide clear opt-out options. Consider working with legal experts to review your data practices and ensure you're on the right side of the law.

Intent data doesn't have to mean invading privacy. Focus on aggregate trends and anonymized data where possible, and always prioritize providing value to your prospects rather than just collecting data for its own sake.

Data Overwhelm

Intent data can provide a wealth of information, but that abundance can sometimes be overwhelming. It's easy to get lost in the data and lose sight of what's actually important.

To combat data overwhelm, use AI and machine learning tools to help process and analyze data. These tools can help identify the most relevant signals and patterns, allowing your team to focus on insights rather than drowning in data.

It's also crucial to focus on the most relevant signals for your business. Not every piece of data is equally valuable. Work with your teams to identify the key indicators that truly matter for your business, and prioritize those in your analysis and decision-making.

Sales and Marketing Alignment

While intent data can help align sales and marketing, achieving this alignment in practice can still be challenging. Different teams may interpret data differently, or may not fully understand how to leverage intent insights in their day-to-day work.

To overcome this, implement regular cross-team meetings to discuss intent data insights. Create shared KPIs that encourage collaboration rather than competition between sales and marketing. Provide training to both teams on how to interpret and act on intent data, and celebrate successes that come from collaborative, data-driven efforts.

Timing and Relevance

Even with intent data, engaging prospects at exactly the right time with the right message can be tricky. A prospect's needs and interests can change quickly, and what was relevant yesterday might not be today.

To address this challenge, develop a robust lead nurturing strategy that responds to different levels and types of intent signals. Use automation to ensure timely follow-up based on intent signals, but also give your teams the flexibility to override automated processes when human judgment suggests a different approach might be more effective.

Regularly review and update your content and messaging to ensure it remains relevant to your prospects' evolving needs and interests. And always be ready to pivot your approach based on new intent signals or changing market conditions.

The Future of Intent Data in B2B Marketing

As we look to the future, several trends are shaping the evolution of intent data in B2B marketing. Understanding these trends can help you stay ahead of the curve and continue to maximize the value you get from intent data.

Advanced AI algorithms will enable even more accurate prediction of purchase intent and optimal engagement strategies. We’re moving beyond simple rule-based systems to sophisticated models that can identify complex patterns and make nuanced predictions of user intent.

In the near future, we can expect AI to not just identify purchase intent, but to provide detailed recommendations on how to engage with each prospect based on their specific intent signals and characteristics. This could revolutionize how we approach personalization and lead nurturing.

We’ll see increased integration of intent data with other data sources, providing a more holistic view of prospect behavior and needs. This might include combining intent data with technographic data, firmographic information, and even macroeconomic trends.

The result will be a much richer understanding of each prospect, allowing for even more targeted and effective marketing and sales strategies. Imagine being able to not just know that a prospect is interested in your solution, but understanding exactly why they’re interested and how it fits into their broader business strategy.

Technology advancements will allow for more real-time capture and actioning of intent signals, enabling even more timely and relevant engagement. Instead of relying on weekly or monthly data updates, we’ll be able to respond to intent signals almost instantaneously.

This could lead to incredibly responsive marketing systems that can adjust messaging, content, and offers in real-time based on a prospect’s current behavior and interests. The line between marketing automation and real-time personalization will become increasingly blurred.

Intent data will drive increasingly sophisticated personalization, not just in marketing messages, but across the entire customer journey. From the first touch point to post-sale support, every interaction will be tailored based on a deep understanding of the customer’s needs and interests.

This level of personalization will extend beyond just content and messaging. We might see intent data influencing product recommendations, pricing strategies, and even product development priorities.

Conclusion

Intent data has the power to transform B2B marketing, enabling more targeted, relevant, and effective engagement with prospects. When you understand what intent data is, how to collect and analyze it, and how to implement it in your marketing strategy, you gain a significant competitive advantage in today's crowded B2B landscape.

At CustomerBase, we're passionate about helping B2B companies achieve repeatable growth through data-driven insights. Our platform is built from the ground up to replicate the way a seller does research, taking a validated ICP and monitoring the market to discover these companies. We regularly monitor to identify companies shifting in and out of ICP, ensuring you're always focused on the best opportunities.

The key to success with intent data is not just having the data, but knowing how to use it effectively. It's about aligning your entire organization - from leadership to marketing to sales - around a unified view of your market and your customers.

It's also important to keep in mind that it's an iterative process. Continuously test, learn, and refine your approach. And most importantly, always keep your customer at the center of everything you do.