We are thrilled to share the insights into common challenges and provide a perspective with best practices that can improve the effectiveness of partner marketing.

In response to uncertain times shaped by geopolitics and tech changes, marketers are focusing on specialization, teaming up with partners to better understand customers, and prioritizing community collaboration. Partner marketing allows for deeper engagement within existing accounts, aiming to tap into additional potential rather than solely pursuing new clients. This approach aims to uncover competitive advantages and enhance understanding of the customer base.

The impact of Gen AI

Generative AI tools like ChatGPT offer significant potential but shouldn’t be viewed as the ultimate solution for all marketing needs. While these tools can efficiently summarize, draft plans, or outline ideas, they’re not a universal remedy for content or automation. Future advancements in AI analytics are expected to enhance customer understanding and predictive capabilities. Despite the high demand for content, emphasis should be placed on quality and differentiation rather than solely quantity.

Deeper customer insights with intent data

Intent data and its associated tools significantly influence partner marketing relationships by enabling a deeper understanding of customer needs and timing. This data helps in aligning partner efforts with customer demands and preferences. Collaborating with third-party agencies serves as a quicker route to success by leveraging their expertise. Partner marketing and Account-Based Marketing (ABM) share a common goal of illuminating customer preferences and tailoring services accordingly, relying on informed decision-making for better customer outcomes.

Internally and externally, partner marketing faces several challenges:

1. Regional differences: execution speed can vary due to fragmentation in language, culture, and currency, making it tougher in Europe/EMEA compared to the US/North America.
2. US-Centric focus: many tech companies primarily concentrate on the US market, leading to potential communication gaps and a lack of focus on other markets.
3. Building long-term relationships: partnering difficulties arise when key personnel change roles or depart, impacting the effectiveness of agreements and sometimes rendering them less valuable than promised.
4. KPI Focus vs. closing deals: a shift from focusing solely on Key Performance Indicators (KPIs) towards evaluating the actual progress in closing deals is necessary.
5. CFO resistance: convincing financial decision-makers of the clear Return on Investment (ROI) in partner marketing efforts remains a hurdle.
6. Attribution challenges: identifying the contributions of different marketing efforts towards sales and complying with legal constraints in sharing customer information poses challenges.
7. Sales-Marketing alignment: collaboration and alignment between sales and marketing departments are vital; however, there can still be disparities in perception, data interpretation, and goal setting.
8. Divergent goals: misalignment in goals between sales and marketing teams can lead to varied behaviors, affecting overall performance.

The over-arching theme is clear, the hurdles we encounter are not unique to any one organization; they are shared experiences that bind us together. Through these sessions, our goal is to provide authentic value and encourage the sharing of insights within the partner marketing community. We will be delighted host you and hear from you during the future sessions in 2024. Should you wish to join and contribute, I invite you to reserve a seat at our next dinner. Please reach out to me, at Raj_Ram@foundryco.com

About Foundry Global Partner Marketing Solutions Our dedicated Global Partner Solutions practice can help you navigate the unique and complex challenges of partner marketing, and help you drive positive business outcomes through collaboration. By implementing practical strategies and leading-edge marketing solutions, we help you elevate and communicate the value of your partnerships and drive return on investment. We can be there every step of the way from messaging, content, strategy and production services.

In this blog, I will dive into some of the key takeaways from Foundry’s 2023 Security Priorities study and explore security leaders’ emerging concerns, such as the viability of cyber risk insurance, and the transformative impact of artificial intelligence.

Top priorities – much of the same

Security priorities haven’t changed that much, and that’s probably a good thing. Those priorities have for years reflected on how CISOs view the risks that they face and how they allocate resources to manage those risks. As always, they need to be appropriately prepared to respond to a security incident whether it be ransomware, a data breach or whatever. They’re constantly focused on improving the protection of confidential and sensitive data. New this year, they’re very focused on how to improve the security of their cloud data and systems as their organizations have invested greater resources in, and trust in, cloud solutions. As CISOs play a greater and greater role in leading IT infrastructure, the importance of leveraging their resources to boost corporate resiliency is the number 4 priority.

• Be appropriately prepared to respond to a security incident (e.g. ransomware, data breach, etc.)
• Improve the protection of confidential and sensitive data
• Improve security of our cloud data and systems – new this year
• Upgrade IT and data security to boost corporate resiliency

Cyber risk insurance – worth the investment?

This year’s security priority study drilled into the topic of cyber risk insurance. Over the past decades CRI has become an increasingly important vehicle for offloading risk but the challenging nature of insuring against damages caused by cyber-attacks has become increasingly difficult to manage and expensive to afford. 52% of this year’s respondents agreed that cyber risk insurance is a key part of their strategy to offload risk, but they also feel that CRI is becoming too expensive and that insurers are demanding too much to make CRI worth the effort. As they found themselves managing the renewal process this past year 44% said it to was more difficult than in prior years. Additionally, liability caps on individual policies are driving more than one-third of CISOs to stack their policies – essentially buying multiple policies to spread out the risk and gain the levels of coverage that they need.

AI – a mixed bag

One would be hard pressed to find a topic generating more debate among security professionals than artificial intelligence. Fully two-thirds of those surveyed this year indicated that they are using AI to enable their security technologies, most notably in threat detection, malware detection, automation alert and triage, real time risk prediction, and incident response. Many are seeing real benefits, such as faster identification of unknown threats, an acceleration in the detection and response times, and the use of AI to sift through large amounts of data faster than any previous solutions.

They also found AI effective at eliminating time-consuming tasks that can reduce the employee workload and allow their security organizations to be more proactive and offer faster remediation of threats. But, of those security leaders using AI in their security solutions 28% are not yet seeing any benefits. We’re early in the adoption of AI and we can expect to see this area evolve rapidly, but solution providers touting their AI capabilities need to do a better job of helping their customers identify the benefits from this new technology if they hope to be successful.

The bottom line

The adoption of artificial intelligence presents both promise and challenges, with a majority reaping benefits in threat detection and response, but a notable fraction yet to realize its full potential. In the world of cybersecurity, adaptability remains at the forefront, ensuring that organizations stay one step ahead in safeguarding against complex threats. I outline how the CSO and CISO are better aligning with the board of directors to prepare for these future threats and abide by new regulations in my other blog, The evolving challenges and the growing risks of the CSO.

However, the key to success isn’t just investing in tools, it’s about strategically setting up your tools in a way that they talk to each other and work together smoothly. When integrating martech tools, it’s all about ensuring that your team can work smarter, not harder. Marketers use more than 12 different tools on average. Such an abundance of tools can be a challenge to manage, integrate, and scale. 

In this complex environment, a pivotal question emerges: How can businesses make sure their marketing tools work well together and are easy to manage and grow as the business expands? 

The holy grail of succeeding is following the integration strategy where it’s a with everything else that is around it (think solar system). This is like 90% of your success.

Nadia Davis, Director of Revenue Marketing, PayIt 

Understanding the modern B2B marketer’s tech stack

What is a martech stack?

A martech stack (short for marketing technology stack), is a comprehensive collection of various software tools and technologies that marketers and businesses use to plan, execute, manage, analyze, and optimize their marketing efforts and strategies. It allows businesses to centralize data, automate processes, gain insights into customer behavior, monitor the competition, and tailor marketing campaigns to specific target audiences.  

A well-constructed martech stack is essential for modern marketing operations, as it helps businesses stay competitive and adapt to the ever-evolving digital marketing landscape. 

What tools should be in your martech stack?

The tools in your martech stack need to be tailored to your specific organization and strategically chosen, so you are confident your investments will set you up for success. For example, let’s look at a small startup vs a large established enterprise.  Say the small startup we’re looking at has limited resources, and aims to establish an online presence, generate leads, and track basic website analytics. They might look for a single marketing tool that offers lighter version of each of these functions, that has a user-friendly interface, is cost-effective, and has essential features tailored for startups.  

On the other hand, the established enterprise has a comprehensive marketing strategy involving multi-channel campaigns, multiple functional and technical departments, personalized customer experiences, and in-depth data analysis. They might look for an integrated set of marketing tools that offer advanced features such as AI-driven customer segmentation, real-time campaign optimization, and detailed ROI analysis. With a larger team and more complex goals, the enterprise organization would benefit from a sophisticated and scalable tool. 

There are a few common tools that every marketer should consider adding to their tech stack. These include: 

• Customer relationship management platforms (CRM) 

centralize your customer and prospect data, enabling targeted campaigns and personalized communication. 

• Marketing automation platform (MAP) 

streamline and scale your marketing efforts. These systems automate repetitive tasks such as email campaigns, lead nurturing, and social media posting, saving time and ensuring consistency. Additionally, they offer data-driven insights, enabling optimization of marketing strategies for improved efficiency and effectiveness.  

• Content management systems (CMS) 

Content management systems empower efficient content creation, organization, and distribution. They enable marketers to easily manage and update website content, blogs, and other digital assets, ensuring consistency and relevance. 

• Account-based marketing (ABM) 

Account-based marketing software enables highly targeted B2B marketing strategies. ABM platforms facilitate the identification of high-value accounts and decision-makers within those accounts, allowing marketers to deliver personalized content and messaging. ABM drives more meaningful interactions, accelerates the sales cycle, and enhances alignment between marketing and sales teams.  

• Generative AI 

Gen AI is on the rise among B2B marketers. In fact, 89% of IT decision-makers are either researching or using AI technology. Gen AI tools empower marketers by automating content creation, enabling personalized communication, analyzing vast datasets for valuable insights, and more. 

• Intent data 

Perhaps one of the most important components to your martech stack, is intent data. Incorporating intent data into your martech stack is essential as it provides valuable insights into potential customers’ buying behavior and interests. 

The data integration problem

What’s the point of having all these tools if they can’t work or communicate with one another? 

However, 52% of marketers say martech stack integration is the most challenging barrier to harnessing marketing technology trends. With so many tools, utilizing integrations to their fullest extent and connecting your data is easier said than done. 

Not properly integrating contact information across your martech systems can cause an array of challenges such as: 

• Underutilization of expensive integrations 
• Marketing and sales silos 

• Issues with data quality/standardization 
• Difficulty measuring ROI 

The key to properly utilizing the entirety of your tech stack lies in successful data integration. When done right, it unlocks the full potential of your martech stack, paving the way for cohesive, efficient, and insightful marketing strategies. It’s not just about having the tools; it’s about making them work together, ensuring that your investment translates into tangible results and meaningful insights. 

Let’s say a SaaS software company is faced with the challenge of enhancing their customer experience across various touchpoints. They have a robust martech stack, including CRM software, email marketing tools, social media analytics, and customer support tools. Individually, these tools provided valuable insights, but that’s the problem – they’re siloed. These siloed tools have led to issues in communication among their marketing and sales teams, struggles with understanding insights, and inaccurate measurements of ROI. 

Their solution? Placing focus on linking customer information across all tools and systems and creating a unified view of each customer. Analyzing integrated data allows them to optimize their strategies, resulting in increased sales, higher customer satisfaction, and measurable ROI. Successful integration transformed their martech stack into a powerful tool for efficient, insightful, and cohesive marketing strategies.  

How is this integration accomplished? 

Integrating your martech systems and data 

How can you properly integrate your martech systems and ensure a seamless data flow? Whether you’re expanding your existing tech stack or evaluating new tools, there are key steps to follow. 

1. Align your goals 

Before making any purchase, align your decisions with your long-term strategy. Avoid impulse buys and quick fixes, because often, shiny new software is just that – exciting new toys that will go on the back burner in a few months if they don’t make an impact on your goals, processes, or efficiency, or if they are a hassle to cross-communicate with your existing tech.  

Engage both marketing and sales teams to establish clear goals, and to determine if a new tool fits into your existing processes and contributes meaningfully to your objectives. Aligning goals from the get-go will allow for better collaboration throughout the implementation and integration processes. 

2. Audit your current tech stack/processes

Is your current tech stack delivering as expected? Is data connected between marketing functions, and between marketing and sales? To truly perform a comprehensive audit, involve multiple areas of your business in the audit like marketing, sales, customer success, and product. Ask critical questions:  

• Are your systems working efficiently?  
• Is the data reaching where it needs to be?  
• Is there a well-defined process for transferring marketing leads to the sales team?  
• Is there a system for sales to provide feedback on lead quality and customer interactions to marketing? 
• Is anything missing or a pain to find when you need it? 

When expanding your tech stack or evaluating new tools, prioritize platforms that support the integration and analysis of cross-functional and cross-channel information. Ensure that these tools can communicate valuable insights for your marketing strategies.  

3. Map your data strategy 

Once you’ve set your goals and audited existing systems, map out a comprehensive data strategy. Visualize how data will move within your organization. Consider the entire journey, from data collection points to storage, processing, usability, and measurement.  

Identify the touchpoints where data enters and exists in your system. Understand how different teams interact with this data at various stages. For instance, data collected by the marketing team may need to be integrated with the CRM used by the sales team. Establish robust integration processes that enable the smooth flow of data between different systems. Use APIs and data connectors to link your martech tools, CRM systems, and data warehouses, ensuring that insights are accessible where it’s needed.  

Here is an example of what a data map might look like: 

Once you’ve mapped your data strategy, take time every quarter to monitor performance and assess whether the chosen tools and processes are meeting your goals efficiently. 

4. Choose the right data vendors 

It’s not just about finding vendors; it’s about finding reliable partners. Ensure the data complies with privacy policies, including GDPR and CCPA regulations. Poor-quality data can hinder the integration process and compromise the efficiency of your tech stack. Seamless integration of insights into your martech stack is vital for real-time decision-making. Vendors offering APIs and integration support facilitate the flow of information across your systems, enabling timely and relevant marketing actions. 

One source of truth 

A well-integrated martech stack serves as the single source of truth for both marketing and sales data. Everyone is reading from the same page of the same book, eliminating confusion and ensuring that decisions are based on unified, accurate information. Key benefits of this include: 

• Marketing and sales alignment 

Cohesion between marketing and sales strategies leads to a unified approach. Also facilitating personalized and efficient customer interactions, promoting effective lead nurturing and engagement strategies. 

• Streamlined workflows 

Automated processes that reduce manual interventions and eliminate redundant tasks.  

• Enhanced insights 

Access to in-depth, actionable insights derived from unified data, enables data-driven decision-making and strategic planning. 

• Improved marketing attribution 

Enables accurate tracking of marketing efforts, attributing conversions and sales to specific channels and campaigns, providing a clear understanding of return on investment. 

Conclusion  

Constructing a powerful B2B marketing strategy requires the right tools, thoughtful planning, and seamless integration. Your martech stack isn’t just an assortment of software; it’s a dynamic ecosystem where every tool communicates, collaborates, and contributes to the overarching success of your marketing initiatives. 

B2B marketing has a data problem. 

And no, I am not talking about scarcity of data (in fact there’s an abundance of it). I’m talking about the gap that exists when it comes to connecting data for B2B go-to-market motions. 

The problem is as B2B data continues to explode, this gap continues to grow. What’s happening is vast reservoirs of data are getting wasted as they remain hidden and unused in unstructured, disconnected, and siloed states across the organization.  

Basically, our data is getting unused, resulting in a less than pleasant buyer’s experience. And things aren’t getting better. 61% of tech marketers in Foundry’s agree that the purchase process is becoming increasingly complex. 

Connected data in marketing

Anytime we hear “connected data” for B2B marketing; we normally hear it in the context of attribution and ROI measurement.  

While that is certainly true; there are several other use-cases where we need connected data, such as:  

• Customer experience 
• Audience targeting 
• Campaign optimization 
• Personalization 
• Attribution (no doubt) 
• Pipeline Forecasting 

In B2B marketing, “connected data” refers to the integration and utilization of data from various sources and touchpoints to create a unified and comprehensive view of a company’s target audience or customer base. It involves gathering, analyzing, and leveraging data from multiple channels and platforms to gain insights, make informed decisions, and optimize marketing efforts. 

In contrast to B2B, B2C has been quick to adopt connected data infrastructures by leveraging CDPs and building a 360-degree view of the customers. In fact, most major B2C brands have a unified customer profile. This single view of the customer results in a highly personalized consumer experience through personalized digital campaigns. For example: you buy a T-shirt at GAP, almost instantly you find your inbox filled with emails showcasing their upcoming promotions. Or, when you step into a shopping mall, you might receive push notifications via SMS or in-app alerts, perfectly tailored to your preferences. Even a visit to their website yields personalized content and recommendations, all thanks to this connected data ecosystem. 

B2B certainly doesn’t have that level of sophistication… However, there are valid reasons for that.  

With , 25 people making a decision, and more revenue at stake, the B2B buying journey is complex. And to add a layer of obfuscation, data is coming in from dozens of channels and an average of . The problem is, as helpful as these tools are, they often don’t do a great job of talking to each other, or even speaking the same language. 

Challenges in B2B data integration

Instead of connected data, B2B companies typically rely on their as the single source of truth for all customer-related things.  

Even with connectors from , ABM tools, and sales engagement platforms don’t have the robustness of a CDP. One of the key issues being that most activation and buyer engagement happen outside of the CRM and are almost impossible to store and . This disjointed data landscape poses significant challenges for B2B enterprises, especially those striving for integrated marketing. 

Integrated marketing has been flavor of the day for a lot of B2B enterprise marketers for a while now. A quick search with and this is the definition we get: “Integrated Marketing is a holistic approach to marketing communication. It ensures that all forms of communications and messages are carefully linked together. At its core, it’s about aligning all communication channels, from advertising and PR to direct marketing and digital, to work in unison.”  

This leaves us with one large issue as marketers… 

You simply cannot run a properly integrated marketing campaign without a connected data infrastructure.  

Building a connected data infrastructure

Consider the following scenario: you’re a B2B cyber security company running an integrated campaign targeting the top 500 Financial Services companies globally. Let’s say you’ve crafted a whitepaper and intend to promote it through a multi-channel strategy, encompassing display ads, paid social, content syndication, and webinar series. 

The first challenge you’ll face is how to create audience segments for each of these channels. Do you use a list of URLs or IP addresses? What about the buying teams within these orgs, how do you target them? And once you build an audience, how do the different channels talk to each other and optimize targeting based on engagements on other channels? 

Here is where you run into the data problem. When dealing with fragmented and outdated data, it becomes nearly impossible to pinpoint the precise individuals to target within various buying teams. Additionally, it’s challenging to discern which channels are resonating with your audience and igniting meaningful engagements. 

Instead, connected data might look something like this…  

The CIO at Big Bank has seen your ad five times in the past week. Because of this, an automated response sends her an email invitation for your upcoming webinar. However, if she already registered for the webinar, the system would intelligently exclude her from the content syndication program to avoid redundancy. This is exactly what B2B companies should be doing. ����’s a perfect example of what a truly connected data infrastructure might look like. 

Companies, like SAP, have taken substantial strides through initiatives like the . They’ve assembled teams of data scientists to build extremely sophisticated models by ingesting both 1^st and 3^rd party data across multiple sources. The outcomes include a 300% increase in deal size and a 2-3X increase in conversion rate from pipeline to revenue.  

But let’s be realistic… not every B2B marketing organization can build a data science team. However, there are still actionable steps you can take towards creating a connected data system.  

Account and contact level data

Connected data systems mean account and contact level data must be connected. 

Account level data encompasses information about the organizations or companies you are targeting. But without contact data, it’s impossible to truly understand the context behind your accounts and who key decision makers are. 

Contact-level data focuses on the individuals within your target organizations. However, when it comes to contact-level intent, it’s not just about knowing that “Jane,” a marketing manager, downloaded a piece of content. It’s about understanding Jane’s place in the buying team for a martech solution. Is Jane a decision maker, an influencer, or an individual contributor in the buying process? What’s important is having a deep understanding of a contact’s role, seniority, and function within their organization.  

Imagine you’re a marketer for a B2B company, and you’ve identified that “Jane” holds a high-ranking position that gives her decision-making authority. Knowing this, you can tailor your engagement accordingly. Since she’s the decision maker, focus on presenting in-depth product information and value propositions.  

This deep understanding of contact-level data, tied to accounts, enhances your overall context of an organization’s dynamics. This not only empowers you to engage individuals more effectively but also enables you to grasp how their role aligns with the overarching objectives of their organization, allowing you to map contacts to specific buying teams. 

Data unification 

Your data must be set up in a way that allows you to monitor all the account and contact behaviors within your sphere, connecting where data is coming from to how it moves through your system. This means that from the moment you receive data, such as a form submission, you can pinpoint its source, and track lead progression as they interact with various touchpoints. This thorough monitoring continues until you hand it over to your sales team, who, in turn, can follow the lead’s interconnected path. 

For example, you’re a B2B software company receiving a form submission on your website. To ensure a streamlined data flow, you set up a direct data pathway: 

• Instant data capture: when a contact submits their info, your system grabs details like company name, industry, and how they found you. 
• Tagging and integration: leads get unique tags (e.g., “LI2023” for LinkedIn) in your CRM. 
• Progress tracking: your system tracks their interactions, like downloading e-books or attending webinars. 
• Sales alert: high-intent leads trigger sales notifications with comprehensive profiles. 
• Personalized engagement: sales tailors their approach based on lead engagement, boosting conversion chances. 
• Data analysis: after conversion, you analyze the journey to pinpoint top-performing channels. 

Another way to ensure this is by having all contacts and accounts that come in follow standardized procedures, so data integration flows seamlessly.  

Without a proper process for normalizing and collecting data, achieving connected data is considerably more challenging. For instance, say you encounter because of the way your Salesforce communicates with HubSpot, HubSpot now has approximately 40 distinct Adobe accounts. This hinders your ability to measure Adobe’s performance as a unified entity. Rather than analyze one Adobe account, you’re forced to analyze 40 separate instances of Adobe. 

A well-structured process ensures that all Adobe accounts and contacts are accurately categorized and connected within your database. This provides a unified view of Adobe’s engagement and behavior, allowing you to easily access a single, consolidated Adobe account profile.  

Adaptable infrastructure 

You need to be adaptable. What I mean by that is having the ability to optimize your strategies in real time based on what’s happening. 

Say you’re a B2B cyber security company running an ad campaign. During the campaign, you start noticing significant interest in data encryption content. This suggests that your audience is particularly interested in data encryption, and they’re responding positively to ads shown alongside such articles.  

With a flexible, connected data infrastructure, you would react to this in real time by contextually optimizing for placements within data encryption related articles. You might even adjust the ad copy and imagery to further align with the audience’s interests.  

Or say you spot an account displaying significant intent visiting your booth at an event. And at the event, your sales team logged information saying “Hey, we spoke to Jane at Pfizer during SaaStr.” A connected data infrastructure seamlessly funnels this data point into your system. From here, instead of having Jane in the audiences she started in, she is targeted with ads built specifically for her heightened interest level. 

This level of adaptability and granular targeting is precisely what a connected data system provides, allowing you to respond dynamically to the ever-evolving landscape, even drilling down to specific geographic regions as your strategy and audience demands. 

Conclusion

We’ve all heard the phrase “data is the new oil.” While this certainly is true, as B2B marketers we run the risk of misusing this precious commodity without a connective tissue tying the pieces together. The foundation of every marketing campaign should be built upon a connected data layer that ties firmographic, behavioral, and campaign engagement data together into one consolidated view. If done right a connected data layer should enable precise targeting, personalized engagement, and measurably better campaign outcomes.

So, as we continue to refine our marketing strategies and adopt new tools, let’s prioritize building a connected data infrastructure as the cornerstone of our marketing excellence.

What makes intent so confusing and difficult to get right? What does it REALLY mean? What makes an intent signal, and what makes one signal better than the other? And most importantly, how do you go about harnessing them in support of best-in-class B2B demand generation? 

The what and why of intent signals? 

Intent signals are specific observable activities exhibited by an employee of a company or the company as a whole, that indicate their current or potential need for a product or service. It comes in a wide variety – ranging from various locations to various types. However, not all intent signals are created equal. Here, we’ve categorized intent signals into five types, which all mean different things, and require different kinds of actions to take full advantage of them.

The five main types of intent signals are: 

• Engagement – what are specific actions employees within organizations are taking? 
• Research – what are people in the organization researching and reading online? 
• Hiring – what types of roles are organizations trying to hire and grow teams for? 
• Technographic – what types of technologies did the organization start to use or drop? 
• Company event- what newsworthy activities have occurred within an organization that can tilt the scale for purchasing decisions?  

In aggregate, these signals are generated by customer actions and behaviors. These actions and behaviors can be measured by marketers when observing several types of channels like email, web, social, or ads. On the other hand, other signals are more difficult to track, like face-to-face meetings, search queries, and water cooler chats! Putting all these signals together is like following the breadcrumbs your buyers are dropping.  

Now, let us dive into the nitty gritty and break down what each type of intent signal is, and why each is significant in optimizing your intent strategy.  

1. Engagement intent signals

Think of engagement signals as little clues that potential buyers give off when they are in the market for what you are offering. Engagement intent signals refer to specific actions that potential buyers take to indicate their active interest in your brand or product. These signals could come from various actions such as: likes, follows, comments, downloads, going to conferences, or visiting event booths.  

Engagement signals are broken down into two categories: 

• Public – An action that is publicly observable, for example, a like or comment on your company’s or competitor’s LinkedIn. While these signals are great, context is necessary. Just because someone liked your LinkedIn post about company culture, does not mean they are ready to make a purchase. 
• Private – An action that not everyone has access to. For example, a research whitepaper is downloaded, or content is read on a publishing site. These signals can be of much higher value because they are proprietary.  

Engagement signals are valuable because they show you that your brand is top of mind for buyers. They demonstrate an active connection between the prospect and your brand or content.  

Let’s say you have a prospect who just downloaded one of your eBooks and tuned in to an online seminar you hosted. These actions are like bright neon signs saying, “Hey, I’m really interested in what you offer!” Armed with this insight, you can then craft a highly customized follow-up strategy that caters precisely to the prospect’s individual interests and requirements. This approach allows you to nurture the prospect by delivering targeted content that aligns with their demonstrated areas of interest, ensuring a more effective and engaging interaction.

2. Research intent signals

Imagine someone has just started the buyer‘s’ journey – they are surfing the web, checking out blogs, and visiting websites. These actions send out what we call “research signals.” Research signals are more of a passive signal since the prospect is simply surfing the web and not taking any active, public action. 

Understanding research intent provides a sort of roadmap for your next strategic moves. You can use this data to identify what topics buyers are researching, what they are interested in, and which part of the buying journey they are in. Once you know that, you can then determine the best ways to follow up and engage your potential buyer. For example, say you are a CRM provider, and you notice that a prospect just did an online search for “what is the best CRM.” This signals that whoever is researching this topic is beyond awareness and starting the consideration stage research. With this knowledge, you could then begin to target them with ads about your brand and solutions. 

3. Hiring intent signals

Hiring signals are mainly job postings.  

Hiring signals let you know a company has money, and they are ready to spend it. For example, if a company is hiring for various tech positions, chances are that they are expanding, and could use scalable technology of a certain type. Or, if a company is hiring a whole team of developers, they could need better devops systems. 

4. Technographic intent signals

Technographic data is a popular commodity by which we track what technologies a specific company is using. We turn this information into intent signals by tracking when someone started to use a technology or stopped using another one! 

For example, say the product you are selling is a Salesforce app. In this case, you would want data signaling if a prospect recently began using Salesforce as their CRM. This information can assist you in determining what buyers are in market and tailoring your outreach to their specific needs. 

5. Company activity intent signals

Activity intent signals encompass meaningful or newsworthy events for a company. These could be things like; a company just opened a new office location, a company successfully ran a series funding, or even if a company laid x number of people off. Think about these signals like little alarms that go off when something interesting happens in a company’s world and they would inexplicably create changes within the organization.  

Each of those activities has implicit signals of intent. In the example of raising funding, it would signal a company is flushed with cash right now – of course, they are going to be spending money, and you want them to spend it with you. 

‘How?’ Painting the full intent data picture

So, here is the deal: figuring out ‘what’ each intent signal means and ‘why’ it matters, that’ is the straightforward part. The hard part is understanding ‘how’ to combine all these signals together and leverage them in a way that paints a full picture of the buyer‘s’ journey.  

What makes “doing intent right” is understanding that buying is not only happening in one place – it is happening on social media, blogs, news, job postings, apps, phone calls, it is even happening at the water cooler. Buying happens everywhere, it is not just one source or one signal that is the silver bullet. It is the context of all signals that are put together like a puzzle to create the customer journey. 

How do marketers leverage different intent signals to paint the full picture? Two ways: 

1. Consider each signals different meaning and weigh them appropriately 

Because not all signals are created equal, we must figure out how to prioritize them. This involves assigning a level of importance or a ‘score’ to each signal based on its relevance and context. 

Now, when you add up all these scores from different intent signals, you get a prospect’s “total score.” (Well… usually there’s more to it than just adding up a bunch of numbers, but you get it.) This total score is like a key that helps us understand where a prospect stands in their buying journey and guides us on how to approach them. This way, we are not just guessing; we are using data to understand where prospects are and how best to follow up with them. 

2. Adopt the most 360-degree view possible

Marketers must be able to capture and contextualize various kinds of intent and arrange those signals accordingly.  

The best way to think about this is by imagining a timeline view of a prospect’s journey – In the beginning, say a prospect has just started reading blogs. At this point, you would not immediately have a salesperson calling them. But then the same prospect posts a few job openings, now it is a promising idea to run some ads. And then they begin engaging with your content, that might be the golden moment for a salesperson to reach out. ����’s how you use intent signals to understand and act on the buyers’ journey that makes intent data a truly valuable and powerful tool. 

Don’t let anyone convince you differently – a single web visit or download may mean nothing, but within the timeline of events, it might just be the signal you need to close that million-dollar deal!  

Conclusion

You’ve heard marketers say it plenty of times – not all intent data is created equal. But that’s what makes intent signals so valuable. We continue to strive to understand better, the what and ‘why’ behind each type of intent signal, so we can understand ‘how‘ to optimize the customer’s journey the best. 

Would it not be an ideal world where we could always provide prospects with the exact information, they need at the exact time they need it and eliminate all guesswork? 

The reality is sales and marketing misalignment is extremely common. So common that only about of B2B organizations have actually aligned their teams successfully through collaborative efforts that drive revenue, conversion, and overall growth. 

However, the results of a unified team speak for themselves. Aligned teams are more efficient at closing deals and reduce customer acquisition costs (CAC) by . 

While aligning your marketing and sales teams might seem like a no-brainer, many teams continue to struggle with true alignment, which involves not only coordinating goals and strategies but also fostering a shared understanding of the buyers’ journey. So, what does it take to turn these teams from acquaintances (or even frenemies) to collaborative partners? While there isn’t one easy fix, there is one major commonality sitting at the intersection of these two teams. Their buyers. 

How connected data can help 

Just as individuals possess distinct qualities, interests, and potential, leads also exhibit varying degrees of readiness to engage and convert. 

Consider leads as a spectrum of opportunities. Some leads might be highly interested and proactive, actively seeking information about your offerings and showing strong intent to make a purchase. On the other hand, some leads might be just starting to explore their options and require more nurturing before they are ready to commit. Say marketing passes on 100 leads, and 79 of those are later disqualified by sales, that signifies a major misalignment between the marketing team’s targeting and sales’ expectations.  

This disconnect can turn into a vicious cycle – a lack of faith in the leads sales is being handed means they are less likely to follow up. If leads aren’t being nurtured or there isn’t a feedback loop informing marketing of the problem, marketers get frustrated and can lose the motivation to spend time, energy, and budget driving better leads.  

The solution? Understanding where each lead stands on this spectrum allows these teams to tailor their strategies accordingly. Sales can engage high-intent leads with targeted and persuasive messaging, while leads in the early stages might benefit from additional marketing nurture and educational content to guide them through their decision-making process. This distinction in lead readiness is crucial for sales and marketing teams. 

This is where intent data comes in. 

Building trust with data provenance

Data provenance refers to information about the source or origin of data. This includes details about where the data was initially collected or generated, who collected it, when it was collected, and under what conditions.This plays a significant role in establishing mutual trust between marketing and sales and acts as a bridge by providing valuable insights into lead behavior and qualification. 

Organizations gain a clearer understanding of the “why” behind leads, such as origin, qualification, and readiness for engagement. This information helps establish a solid process and rationale for passing leads from marketing to sales and enhances the handoff process. Moreover, intent data offers a glimpse into the actions and interactions of leads, answering the crucial “why” behind a lead’s readiness for engagement. This transparency not only boosts confidence in lead quality but also ensures that leads are nurtured and engaged based on their demonstrated interests and behaviors. 

Building more efficient processes 

Connected and reliable data is the driving force behind this collaboration. 

High-quality, accurate, reliable, and comprehensive intent data empowers marketing to focus on the best channels and best audiences. It also motivates sales to do something with them. Whether that’s initial nurture, following up on active deals, or even re-engaging closed lost accounts. This data-driven alignment fosters a culture of trust and cooperation, as teams can rely on accurate information to guide their strategies and decisions. 

Steps to making it happen

Ultimately, marketing and sales want the same thing – to effectively convert buyers into loyal clients. This is only possible when marketing is optimized to scale demand based on a lead performance feedback loop so that sales are empowered to follow up confidently. Armed with connected data, marketing teams can provide context on readiness, priorities, and more.  

How do you properly build that bridge? Here are six actionable steps to align marketing and sales in your organization. 

1. Revisit your ideal customer profile (ICP) 

Revisiting your ideal customer profile (ICP) is a crucial first step that sets the foundation for effectively utilizing intent signals. 

In order to actually understand and act on intent insights, both teams must agree on who exactly they are targeting. Revisiting your ICP entails a comprehensive evaluation of the characteristics, attributes, and behaviors that define your most desirable customers, such as: 

• Demographics: characteristics such as age, gender, location, company size, industry, and job title. 
• Firmographics: company revenue, number of employees, geographic locations, and organizational structure. 
• Technographics: the technology stack and tools that a company uses. 

In addition to these, you should also consider similarities among your top customers and areas you have been able to up/cross-sell into. 

Defining your ICP should be a joint effort across your organization so teams have a shared understanding of the ideal customers to target and can collaborate effectively to align strategies with intent. 

Note: ICPs are not a one-and-done deal. The market is always evolving, which means your ICP will periodically need updating. You may need to recruit the help of your customer success team and set up quarterly calls to check in on customer satisfaction or ask questions about your hero customers (who has been successful, and who have they successfully upsold?). Include sales in the conversation as well, inquire about new or larger opportunities in a certain vertical or deals that aren’t converting as well as they used to. Involving marketing, sales, and CS gives you valuable information from different vantage points to decide if your ICP needs updating and how to define it.  

2. Identify weak points  

Take a good, honest look in the mirror at your current lead generation and automation processes. Do you like what you see? Or are there workflows or strategies you could clearly improve? 

Identifying weak points is like shining a spotlight on areas that need improvement. While this step can be difficult to do, it’s necessary to identify which areas can be optimized for success, then prioritize solutions based on impact and lift to solve them. Try asking yourself and your team the following questions: 

1. Where could data be better connected, utilized, or reported on? 
2. What data is missing that could improve alignment of marketing and sales strategies, collaboration, and overall success? 
3. What does the data we have now tell us about potential shortfalls? 

Addressing these discrepancies in conversion rates requires open communication, collaboration, and a shared understanding of data-driven insights. A plan of action could include setting up regular meetings between marketing and sales teams to discuss performance, challenges, and opportunities. 

Other areas that could identify weak points include: 

• ICP/Firmographics 
• Lead quality 
• Content/personalization 
• Pipeline velocity 
• Operational efficiency – example: form fills booking directly from a submission 

Best practice is to perform a sales and marketing alignment audit. Have marketing audit their process and ask sales to do the same. Set up a time for your teams to come together and identify areas containing gaps, and brainstorm processes to improve. 

3. Prioritize in-market buyers

Unite both teams under a common objective: identifying and engaging with leads displaying active buying intent.  

Leveraging intent data allows you to understand and agree on exactly what “in-market” means for your organization. Intent data reveals which prospects are engaging with relevant content, visiting your website, and exhibiting signs of purchase readiness. You may identify prospects based on a combination of factors such as specific content interactions, frequency of website visits, engagement with certain product pages, and explicit indications of purchase intent. 

To use intent insights effectively you’ll need to establish clear lead-scoring definitions and segment those accordingly. At its most basic, intent data reveals who is in-market to buy, but dig a bit deeper to answer questions about how your marketing and sales teams should target certain prospects. 

Common ways to prioritize and score leads include: 

• MQL (marketing qualified lead): Leads that have shown interest and engagement with marketing efforts, such as downloading content, attending webinars, or signing up for newsletters. They meet certain predefined criteria set by marketing and have shown enough interest to be passed on to the sales team. 
• SQL (sales qualified lead): Leads that have been further evaluated by the sales team and deemed ready for direct sales engagement.  
• BANT: A lead qualification framework that assesses a lead’s budget, authority, need, and timeline to determine their readiness for sales engagement and likelihood to convert. 
• SAL (sales accepted lead): Leads that have been reviewed and accepted by the sales team for further engagement. While not fully qualified, they show potential and are worth pursuing. 

Once this is identified, you can determine which leads need what.  

For example, SQLs may continue to receive marketing emails, but the content strategy may evolve to incorporate heightened social proof and tactical insights. 

4. Centralize your data

Connected data is only valuable if made easily available for both your marketing and sales teams.  

Ensure that both teams have access to the same information and can track lead interactions, behaviors, and engagement. One way to do this is by integrating your CRM system to allow seamless data sharing between marketing and sales. This integration enables a real-time flow of information about lead interactions, preferences, and behaviors, fostering a sense of unity and a shared mission. Within your integrated CRM, you should automate alerts and notifications to inform sales teams when high-intent leads engage with specific content or reach certain thresholds to facilitate timely follow-up. 

����’s important to continuously monitor the integration and data flow to identify and address any issues. Regularly review the effectiveness of intent data and make necessary adjustments. This enables both teams to access, leverage, and collaborate effectively with intent signals. 

5. Map your content strategy 

A large part of marketing’s job is to identify why people have a certain pain and educate buyers on solutions by providing valuable insights. 

However, that important messaging can be clouded by misalignment between marketing and sales. Marketing and sales must have consistent content and messaging when helping solve buyers’ pain points. 

Using intent allows you to deliver the right content to the right leads at the right time. Once leads have been segmented and prioritized based on intent, map your existing content to their specific needs and interests. This will identify any content gaps that should be filled with new content.  

One approach to this is to map your content based on lead scores: 

This ensures that your content aligns with the varying levels of awareness and engagement among leads, ultimately guiding them through the buyer’s journey more effectively. Sales should communicate what content resonates with leads and what additional areas need to be addressed back to marketing so that both teams are delivering content aligned with what buyers want. 

6. Communication is key

After all, collaboration between teams really comes down to the people. One of the best ways to centralize efforts is by establishing a feedback loop between marketing and sales, whether that’s a Slack channel, a weekly stand-up meeting, shared reporting, or other means of joint collaboration. This encourages open communication about lead quality and the performance of marketing efforts. 

Before and after intent data 

Let’s look at an example of what collaboration might look like before and after adjusting your organization’s alignment strategy: 

Measuring results

Regardless of any gaps, marketers and salespeople are driving the same thing: revenue. 

Measuring the results and success of aligning marketing and sales with intent data involves tracking various key performance indicators (KPIs) that reflect the effectiveness of your efforts. Analyze the impact of connected data and aligned strategies on lead quality, conversion rates, revenue generation, and more: 

• Lead quality 
• Conversion rates 
• Sales velocity 
• Return on investment (ROI) 
• Quality of engagement 
• Sales acceptance rate 

Regularly analyze these metrics over time to gauge the ongoing impact of aligning marketing and sales. Keep a constant feedback loop between teams and adjust your strategies based on the insights gained, continuing to refine your approach to maximize success. 

����’s important to talk to your teams and understand their point of view on alignment efforts by utilizing surveys or feedback mechanisms to gauge the perception of alignment between teams and assess whether they feel more aligned and collaborative. As results from joint efforts present themselves, make a point to celebrate success — recognize and celebrate joint successes achieved through aligned efforts and celebrate wins together to foster a sense of collaboration and motivation within both teams. 

Conclusion

Reliable and integrated data allows B2B organizations to bridge the gap between marketing and sales efforts to generate and scale revenue. Marketing is confident in the leads they are generating for sales, so sales teams are empowered to reach out with relevant content to in-market leads. By aligning teams through intent and connected data, you’ll see more collaboration, better results, smooth optimizations, and a streamlined path to your revenue goals. To learn more about using intent data to achieve your goals, check out our intent activation guide. 

In recent years, B2B buyer journeys have become increasingly complex and nonlinear. With buyers gathering information across many channels between product sites, review sites, social media, webinars, Slack communities, events, and more…. ����’s almost impossible to capture all the potential data points a buying group may take on the path to a purchase.  

It becomes even more complicated when you take into account that buying groups now have up to 14-23 different stakeholders on average (). To leverage intent in order to find and target the right accounts, you’ll need more than just your own CRM data. Let’s get into what separates first, second, and third-party intent data,  how you can leverage each source, and how to combine them for best results. 

First-party intent data

 is information collected about your audiences from your owned digital properties. Some signals indicate topic interest, such as registering for a webinar or downloading a case study. Others are more explicit signs of purchase intent such as exploring pricing. This is your most impactful and reliable source of intent data, but if you only rely on first-party intent data, you only see information from buyers who land on your website. 

Examples include:

• Website visits and page views
• Webinar attendance 
• Form fills

How can I use first-party intent data? 

What’s the point of intent data if you can’t activate it? Let’s talk about three first-party intent data use cases: Discovering new market segments, conducting ad retargeting campaigns and identifying specific areas of focused interest. 

Discovering new market segments 

If you know your ICP has historically been small to midsize health insurance companies, but an analysis of your first-party data (i.e., website visits, social engagement) shows heightened activity from large hospitality companies, you can create targeted ABM campaigns that solve problems for a new market segment that you identified. 

Ad retargeting campaigns 

Another opportunity to leverage first-party intent data is with retargeting campaigns. With average first-time conversion rates being around 2% according to industry data, retargeting is essential to help marketers reel in interested buyers who left their website without converting. Deploying retargeting strategies across display, search and social can improve the performance of your ABM campaign efforts. For example, you can show LinkedIn ads to a retargeting audience segment based on pages they visited, ads they interacted with, or videos they watched. Another useful tactic is using bid adjustments on paid search, where you tell Google you’re willing to bid more to be seen by your retargeting audience specifically.

Identifying specific areas of focused interest 

In a , it’s explained that when deeper in the buying cycle – the buyer starts to hone in on specific areas of interests or concerns. They are visiting specific product pages or engaging with certain website CTAs. These first-party signals allow marketers to customize content and offers for sales follow-up.    

Benefits vs. limitations of first-party intent data  

First-party intent data is cost-effective and privacy-friendly; however, it lacks the scope and scale offered by third-party intent data. First-party intent data is a win-win for you and your buyers. Privacy concerns are kept to a minimum because your company is responsible for collecting, storing, and retaining data, so you don’t need to rely on third parties to ensure compliance with data protection regulations such as GDPR. 

To use intent in your ABM campaigns to its full potential, you need software that can . Why? Because with first-party intent data, you’ll get strong, reliable buyer signals, but with limited scope. Whereas with third-party intent data, you’ll reach more in-market buyers, but you’ll need to sift through a lot of noise (i.e., signals showing general interest in your category rather than buyer intent) to identify actionable insights. 

The key to leveraging buyer intent data is combining first and third-party intent to give you the most comprehensive and accurate buying signals of your target accounts, thus enabling you to engage those accounts with relevant ads and sales plays in your ABM campaigns.

Second-party intent data

When discussing intent data sources, second-party intent data is often left out of the conversation. ����’s a relatively unique type of data sourced from another organization’s first-party data. The main second-party intent data offerings for B2B marketers come from software review sites like  or . 

Examples include:

• Product category engagement 
• Product vendor engagement
• Customer surveys 

How can I use second-party intent data?

You can download second-party intent data directly from the source or utilize an ABM platform to leverage it more effectively. Our  allows marketing and sales teams to identify lower-funnel buyer signals and act on them.

For example, let’s say you sell project management software and you want to target companies researching your industry category and competitors. You can identify audiences researching product pages for project management companies like Monday.com or Basecamp and nurture them with relevant competitive differentiation messaging. If these accounts begin to positively engage with your content, you can automatically activate sales follow-up with . 

Benefits vs. limitations of second-party intent data  

Because second-party intent data is sourced from lower-funnel buying signals, they are strong predictors of purchase intent. This is a double-edged sword as this data will not reveal top-of-funnel activity, so it won’t be as helpful in reaching accounts that have just identified their problem, potentially making for an uphill battle against your competitors. 

Third-party intent data

Third-party intent data consists of research and buying activity occurring on channels and properties owned by others, allowing for a broader view of your market. Third-party intent reveals account interests and topics across the internet but it does not necessarily indicate buying intent.  

Examples include:

• Visits to industry publications
• Watched a video in your category 
• Read analyst guide
• Online searches
• Researched a competitor   

How can I use third-party intent data?

 allows marketers to orchestrate the buying experience from the top of the funnel through the middle of the funnel and fill your pipeline. For example, with   audience criteria, you can identify accounts surging on relevant topics, and nurture them using multistage, multichannel tactics, including personalized display ads, website messaging, and SDR outbounding all based on the initial topic surge. 

Benefits vs. limitations of third-party intent data

With third-party intent data, you’ll have access to a large volume of buyer activity. However, when compared to first-party intent data, third-party intent data is less reliable. This is why depending solely on third-party intent data can be a problem when trying to identify buying signals. When dealing with a large volume of data, you’ll need to cut through the noise to identify reliable signals of buyer intent. 

uses first and third-party intent data signals paired with website and CRM activity to identify which accounts should be prioritized for sales outreach. With proprietary algorithms to provide a single score to prioritize accounts, Smart Score factors in baseline activity for accounts and spikes of activity that account for size and historical data.

Get the most out of intent data with a combination of first-party, second-party and third-party data

One of the most effective ways to leverage all intent data types, whether first, second, or third-party intent, is to run them through an ABM platform and use that as a decision engine to automatically execute the next best steps depending on the activities that each account is showing interest in. In a , Andre Yee explains that sourcing third-party data, first-party data (CRM data, marketing automation and website analytics) and offline data sources then scoring them and triggering the right multichannel, multistage play is the key to shaping the buyer experience for your prospects. A data-driven approach will help marketing and sales to identify the best plays over time to drive pipeline and increase revenue. 

ABM orchestration pairs best with Foundry Intent

By pairing multiple types of intent data with ABM orchestration, you can achieve fuller coverage of your total addressable market in real time. Foundry Intent is a combination of intent data collected from your website, social media interactions, engagements across the public web, research signals on global content, and Foundry’s proprietary audiences from their publishing network, and events data.

Conclusion

First-party, second-party and third-party intent data are each valuable to marketing and sales teams but the quality of intent data is only as good as the sources it draws from. Not all data is created equal. There are nuances between each type of intent data that must be considered to fully comprehend buying intent and action on it. The true power of intent data comes from connecting the dots between all three sources in order to customize your buyer’s experience throughout their buying journey.

See how you can bolster your intent data strategy with first-party contact-level Foundry intent.

For me, productivity doesn’t hit until I’ve had my morning cup of coffee. In comparison, I like to think about ABM as a cup of coffee for sales. Using an ABM strategy will provide your sales team with the fuel they need to get the needle moving on pipeline, and here’s how.

1. ABM creates a shortened sales cycle

One way ABM acts as a shot of espresso is by shortening your sales cycle. Harvard University found that at least 25% of B2B sales cycles take a minimum of 7 months to close. Long B2B sales cycles create frustration for sales representatives and leave ample room for lost opportunities. 

By identifying high-intent accounts early in the buyer’s journey, ABM shortens the sales cycle, earning you more MQA to SQA conversions and new business. Identifying accounts early in the buyer’s journey enables your sales outreach to be personalized with catered messaging and content even before a prospect fills out a form. Starting with a targeted list of accounts allows you to provide prospects a unique personalized experience from the get-go, helping eliminate time wasted prospecting unfit accounts. A  found that individual stakeholders who perceived supplier content to be tailored to their specific needs were 40% more willing to buy from that supplier than stakeholders who didn’t. Getting  in front of the right buyers at the right time will significantly reduce the time it takes for your sales team to win deals. 

2. ABM prioritizes quality leads over quantity

It shouldn’t be about counting the number of leads you have, but rather assessing their value to pipeline – ABM prioritizes quality over quantity. No matter how many MQAs are identified, it doesn’t matter if they don’t close or become SQAs. Rather than being in the dark, ABM lights up the funnel, providing a targeted list of prospects for warm outreach.

Using , ABM can help to answer the burning question of who should sales reach out to right now? Hot or not?

In a  centering on the topic of intent, the evolution of buyer behavior in the past decade and its impact on the modern purchase journey is discussed. “Buyers are now waiting longer to raise their hands and show interest, beginning the purchase journey anonymously,” says Yee. In order to know what accounts (known or unknown) are showing intent, ABM paired with intent data can identify and influence buyers early enough to address pain points throughout the purchase journey. With more visibility into real-time buyer interests and behaviors, both marketing and sales teams are more equipped to engage key stakeholders and win over target accounts. Leveraging both ABM and 1st-party and 3rd-party intent will grow pipeline and make a real impact on revenue.

3. ABM aligns your marketing and sales teams

Marketing and sales both want the same thing, more revenue. So what’s with the disconnect? , only 8% of B2B companies have sales and marketing departments that are tightly aligned. Lack of unity and lead quality between sales and marketing has become a significant hindrance to revenue teams in the ever-evolving B2B landscape. 

ABM provides visibility into key account insights to align marketing and sales with data-driven campaigns. Sales can be more productive because their TAM (total addressable market) is being prioritized with data, which means marketers focus their efforts on warming up accounts before activating sales plays.

In turn, marketers provide salespeople the confidence that they’re reaching out with the correct messaging, to the right people. Serving as the , ABM allows both to work together to plan messaging tracks, agree on intent-based campaign triggers, and reference the same reporting. A study done by  found B2B organizations with tightly aligned sales and marketing operations grew their revenues 24% faster in a three-year period compared to those whose teams work separately.

These aligned and focused efforts between marketing and sales will help skyrocket productivity and pipeline growth through a data-driven market approach.

Marketing & sales alignment .

“One big differentiator for us when it comes to account visibility has been the ability to layer real-time intent data into our audiences,”

Flexera’s Manager of Global Demand Generation. 

 armed with visibility into account insights was able to generate over . With a real-time intent integration, Flexera manages dynamic audiences and scales personalized campaigns for high-fit, high-intent accounts.

Simply put, the ultimate goal of any marketing and sales team is to increase sales conversions and revenue, and ABM makes that possible. See how ABM can be the productivity boost you’ve been searching for.

‍Is your intent data fit for purpose in Europe? 

Most of the world is heading down a one-way street toward GDPR-style privacy regulation. But the road in question is long, and speed of travel is variable. This opens up challenges along the way.

In this blog post, we’ll look at one in particular: the question of what happens when US-based ABM platforms can’t supply their European customers with locally compliant intent data.

In North America, ABM platforms, and their bundled data sources, typically generate a flood of intent data for use in ABM campaigns.

However, for companies in Europe that have either selected the wrong ABM platform (or had it selected for them by marketing HQ in North America), the flood is reduced to a trickle. Building Target Account Lists (TALs) for ABM campaigns under these circumstances becomes impossible.

The problem is simple: many US ABM platforms lack a source of GDPR-compliant data that detects behavioural signals among B2B buyers in Europe.

Given the costs of compliance, this is not a problem these vendors are likely to tackle any time soon. For European ABM teams struggling with this problem, there’s only one solution: find a platform that can supply compliant local data, generated by local sources. For subsidiaries of US corporations operating in Europe, this may well involve augmenting an existing global platform provider with an alternative that will turn that trickle into a flood of compliant regional intent data.

How big is Europe’s intent data problem?

The intent-based datasets that cause problems for European ABM practitioners are based on bidstream data, generated by programmatic ad exchanges where advertisers buy digital advertising inventory.

The process exposes information about both the user and the content they’re consuming. In the US, it’s not unusual for outsiders to pull this data from ad exchanges, harvesting it without user consent. From the ad exchange, these datasets make their way into the market for third-party intent data.

In the US, bidstream data remains widely exploited. In Europe, bidstream data continues to be harvested, but GDPR effectively prohibits selling on the contact details behind the data. For obvious reasons, this drastically limits the extent to which European marketers can exploit bidstream data collected in Europe. It also explains why the flood of bidstream data visible on ABM platforms in North America still frequently turns into a trickle in Europe.

For a couple of years now, we’ve been looking at the results of our  worldwide and wondering whether the anecdotes we hear about intent data in Europe are reflected in the findings.

Our surveys tell us that European ABM teams are enthusiastic users of intent data, but sometimes struggle to use it successfully.

First, let’s look at European enthusiasm for intent data. According to our most recent survey, almost two-thirds (62%) of European ABM teams use intent data to generate TALs for use in ABM campaigns. (That’s a higher proportion than North America, where 50% are using intent data for these purposes.)

Yet the same survey also tells us that European practitioners face significant challenges with intent data. 

Notably, these challenges don’t occur in the downstream phases of ABM activity. Indeed, when it comes to campaign orchestration and engaging accounts, the proportion of European practitioners who regard these aspects of their ABM as challenging is typically smaller than the global average.

In Europe, the big pain points lie upstream, precisely where intent data makes its biggest contribution. In particular, end-user pain tends to cluster around prioritising accounts for ABM nurturing (a challenge for 49%) and creating TALs (a challenge for 35%).

European respondents are also less likely than their counterparts in North America and Asia to use scored intent data to prioritise accounts (in Europe only 26% strongly agree that they do this, compared with 44% in North America). The European marketers we surveyed are also less enthusiastic about using intent data to identify which content should be served within campaigns.

Correlation isn’t causation. Nevertheless, we’re increasingly convinced that these pain points are associated with failed attempts to use bidstream-based intent data.

Finding a solution that works in Europe

For European marketers struggling with bidstream intent data bundled with a US ABM platform, the solution involves making the transition to a platform – like Foundry – that can provide the necessary volumes of compliant intent data.

The intent data that Foundry supplies to users of its platform in Europe is 100% non-bidstream and GDPR compliant. ����’s our own first-party data, derived from our parent company Foundry’s proprietary publishing, events and content syndication businesses. Our intent data is also human verified, which is another way of saying that users have consented to its use in a way that’s GDPR-compliant while registering to read content, watch a webinar or attend an in-person conference. ����’s also structured so that you can use it to identify individual prospects as well as accounts showing high levels of intent. As you’d expect, we enrich our own data with compliant add-ons from social media, blogs, and job boards. We make all of our data feeds easy to use – without expert analytics assistance – within Foundry itself.

If your organisation has rolled out a non-compliant platform in Europe as part of a global deal, making the transition to a compliant ABM platform for regional use may involve internal negotiations. In many cases, the sales organisation can become a valuable ally in these negotiations.

Other questions to explore include the extent to which any new solution for Europe will need to interface with other parts of your organisation’s global martech stack. In addition, efforts are already under way inside many large and medium-sized organisations to consolidate SaaS subscriptions as markets slow down. Particularly if the finance organisation is involved in a similar initiative inside your organisation, European ABM teams can expect to have to demonstrate the opportunity costs of the failed solution alongside the anticipated benefits of the new solution.

Marketers planning to adopt an ABM platform for use in Europe should test the intent data coverage that comes bundled with each platform. (You can do this by asking your supplier to run coverage tests in the territories you care about.) Where you see plenty of data returned against queries on the platform, this suggests the presence of GDPR-compliant data collection methods (i.e. not based on bidstream data). However, where the flow of data for Europe becomes a trickle, you are most likely dealing with a data provider that is not GDPR-compliant, and who may be using bidstream data.

Beyond compliance: other reasons to avoid bidstream data

In conversations about test results with different vendors, it’s worth being aware of a few additional issues with bidstream data.

For example: carrying out tests of the kind we have just described will allow you to assess the volume of intent data, but not its quality. In this area, too, bidstream data tends to underperform. Because of the limitations of ad exchange architecture, it tends to include a significant number of false positives (in other words, it frequently identifies intent where there is none). 

Internal research we have conducted here at Foundry . Third-party intent data sold by publishers like Foundry, generates far fewer false positives precisely because it is human-verified, which means we can more accurately interpret user behaviour and restrict the volume of false positives.

Our research tells us that our intent data typically generates in-market account discovery at 2-3X the rate of intent data from one of our closest rivals. All other things being equal, we also know that the deals generated by our intent data are on average 50% larger than those generated by that same rival.

Another potential issue with ABM datasets is whether they can supply you with more than account-level information generated by IP matching. For example: your third-party intent data might suggest that a specific Fortune 100 company in a specific location is very interested in securing their edge computing infrastructure. In theory, this is excellent news. But this news only becomes actionable if accompanied by a named contact (or a selection of them). In the absence of this, your sales team will find it challenging to identify which of the hundreds of potential decision-makers at Company X is leading that effort to secure the company’s edge infrastructure.

These might look like knotty subtleties. But the quality of the intent signals you use to generate leads really does matter. Using the right data from the very start allows you to maximise the yield of high-quality leads ready for sales activation.

Have your ABM campaigns in Europe been affected by poor quality intent data? If so, : we stand ready to help your organisation migrate to an ABM platform that enables efficient and effective campaigns in European B2B markets.

So, to really make the case, you’ll need solid stats and research to back you up.

We’re here to make things a bit easier and save you some research. We’ve compiled 30 of the top stats on why ABM could be the solution your marketing and sales teams are looking for. Here are 30 galvanizing account-based marketing and intent data statistics to share with your team, decision makers, or anyone involved in adoption across departments.

But first, let’s talk basics.

What is account-based marketing?

Account-Based Marketing is a B2B marketing strategy in which sales and marketing teams work closely together to target, reach, and close deals with high-fit accounts.

What is intent data?

According to Foundry, “intent data is information that captures a person’s digital behavior and provides insight into their interests, needs, and purchase intentions. It can include data such as website visits, search terms, content downloads, social media activity, and more. The goal of intent data is to provide marketers and sales teams with a more complete understanding of a potential customer’s behavior and preferences, allowing them to deliver more targeted and personalized communications.”

Why are ABM and intent data powerful together?

ABM and intent data are often used together as a powerful tool for B2B marketers. Here are a few reasons why ABM and intent data work so well together:

• Enhanced targeting  
• Personalization
• Sales and marketing alignment

Show me the numbers!

Account-based marketing stats

ABM is not a buzzword anymore.

1. The value of ABM is widely recognized across the B2B SaaS industry. 94% of marketers rate ABM as extremely or very important to their business objectives. ()
2. 91% of businesses running programs for at least six months. ()
3. 45% of marketers are in the early stages and testing their ABM program. ()
4. ABM continues to be a top B2B priority with substantial commitment and investment. 28% of the 2022 marketing budget was dedicated to ABM and 71% of companies will increase ABM spend in 2023. ()
5. 67% of brands leverage account-based marketing. ()
6. Traditional marketing efforts are not working anymore. 61% of marketers identify high-quality lead generation as their biggest challenge. ()

ABM results and ROI

����’s frustrating when you invest in a new software or strategy and the results and ROI just aren’t there. Luckily the majority of ABM marketers have seen favorable results:  

7. 76% of B2B marketers who used ABM in 2020 reported an increased ROI compared to other forms of marketing. ()
8. 87% of B2B marketers said that the ROI of ABM initiatives outperforms other marketing investments ()
9. ABM programs had a 20% lift in average deal size compared to traditional demand generation programs. ()
10. 84% of marketers feel their ABM efforts have been very/ extremely successful over the past 12 months. ()
11. The most common metric marketers use to track ABM is revenue won. ()

Align marketing strategies and tactics with sales

ABM works to align marketing and sales teams:

12. Marketing aligns marketing and sales teams on a common strategy. 70% of marketers say their alignment is strong with their sales team. ()
13. Additionally, 66% say ABM is significantly improving marketing and sales alignment. ()
14. ABM contributes to more upsells and renewals. 80% of marketers say ABM improves customer lifecycle value. ()
15. Aligned teams close more and churn less. Businesses with strong sales and marketing alignment are 67% more effective at closing deals and 58% better at retaining customers. ()
16. Teams with great sales-marketing alignment close up to 38% more deals. ()

Personalization statistics

ABM and personalization go hand-in-hand!

17. 80% of consumers are more likely to buy when brands offer personalized experiences. ()
18. 56% of marketers recommend using personalized content to achieve ABM success. ()
19. The most common challenge with ABM is delivering a personalized experience. ()
20. 93% of companies experience a lift in conversion rates from personalization. ()

Account targeting statistics

ABM is all about account targeting and having a strongly defined ICP.

21. 57% of professionals say their companies target 1,000 accounts or under with ABM. ()
22. Organizations with a strong Ideal Customer Profile (ICP) — which is similar to a buyer persona — achieve 68% higher account win rates. ()
23. “Researching Accounts” and “Identifying Target Contacts” are the top two tactics used by marketers within an ABM model. ()

Intent data statistics

Intent data allows marketers to capture important insights into the buying patterns of their prospects. Here’s a few stats on intent data’s effectiveness:

24. Compared to the control group campaigns, intent-based ads were 2.5x more efficient. (Foundry)
25. Compared to the control group campaigns, intent-based ads had a 220% higher click-through rate. (Foundry)
26. 95% of marketers use more than one intent data source. ()
27. Almost 70% of marketers plan on increasing spend on intent data next year ()

Importance of ABM + intent

ABM combined with intent data is a fantastic tool for businesses to run highly targeted campaigns to their most important accounts. Here’s a few stats on the benefits of combining the two:

28. The importance of engaging target accounts early in the buying journey is increasing. 87% of buyers want to self-serve part, or all of their buying journey. (
29. Competitive intent signals peaked approximately 80% of the way through the buying cycle. ()
30. Intent data works best with a process or ABM platform in place. 71% of B2B organizations are collecting buyer signals, but more than half of those organizations are not operationalizing the data. ()

ABM results

Since real results are just as compelling as these 19 stats, we thought we’d throw in a few ABM success stories.  

• SugarCRM saw  by implementing an ABM and intent data strategy.
• ����𲹰��ɲ������� with intent-based personalization.
• Dynatrace met internal growth demands and during a pandemic year by utilizing intent signals.

TL;DR: Combine intent data and ABM for a powerful B2B marketing and sales solution that allows you to run highly targeted and successful campaigns. Learn more about the power of ABM and intent data in our latest .