B2B, Digital Marketing, Marketing services

Role of AI in Helping B2B companies that are Missing Out on Buyer Intent Data

Buyer intent data is part of a fast-growing Martech and Sales intelligence landscape. B2B marketers are using powerful buyer intent data tools to understand how prospects and customers are interacting with product before actually buying it. There are different levels of buyer intent data applications in the modern B2B sales journey and these are more or less linked with account-based marketing (ABM) and personalization management. AI’s role, therefore, becomes very important in understanding how different buyer intent data tools function and how these help businesses unlock the true potential of their buyer intent data management and capabilities.

What is Buyer Intent Data?

Intent data is part of the ever-growing family of B2B data, which may consist of individual contact information or database of customers specifically meant for Marketing and Sales activities. B2B data, generally, defines Ideal Customer Profile (ICP), Net Promoter Score (NCP), demand generation / lead gen, CRM, outbound sales intelligence, and so much more. Buyer intent data is a sub-set of B2B data specifically used for lead generation activities.

According to Aberdeen, Intent Data is fact-based real time information about what a customer is doing. The scope of this definition could be extended further to identify what’s the probability of a buyer actually going ahead and buying a product. How it differs from demographic data or PII or user data – this has to be understood clearly.

Buyer intent data is part of marketing analytics and sales intelligence. It leverages advanced data science and business analytics to show how leads behave over a period of time across multiple touch points in an omnichannel market. The best part about using buyer intent data in sales intelligence is its direct association to buyers in the buying journey. Buyer intent data is based on the information aggregated as first party data or third party data during the buyer’s journey. It mostly comprises of purchase intent signals which allows Marketing, Sales and Customer Experience management teams identify the behavior and attitude of various types of buyers.

Buyer intent data could be derived from website analytics, lead gen forms, comments, social media engagements and email marketing subscriptions. Webinar registrations, event participation and surveys are also very strong and reliable source of buyer intent data.

The top 3 indicators of a strong buyer intent data management strategy is:

  • High volume of content consumption by buyers and customers
  • Social media engagements growing at 5x per quarter
  • Email subscription growing at 10x per quarter

It is impossible to think of customer targeting strategies without understanding AI, predictive analytics and intent data management.

Why Do B2B Businesses Need Intent Data?

What is the top priority for a B2B marketing and sales team?

According to Hubspot, it’s lead generation that influences customer acquisition. And, 92% of the marketers use data analysis tools but almost 50% are unaware of the advanced capabilities of these tools. The future of martech platforms depend on how well these integrate with the B2B buyer intent data solutions.

According to Gartner, buyer intent data is the future of B2B lead generation. With buyer intent data, marketers and sales teams are able to predict various actions their prospects and customers might take to convert or influence sales. In the last 5 years, marketing and sales teams have been using different tools and platforms to improve their lead generation and demand generation. However, it’s never easy to directly leverage data in lead generation. While B2B lead generation is the critical driver of growth for most businesses and the first step in building a meaningful relationship with customers in every industry, in-house marketing and sales teams continue to face massive challenges in justifying investments in these operations. So, today, for any B2B marketing and sales team, getting lead generation right is one of the biggest challenges.

Why is Lead Generation so Challenging in B2B Sales and Marketing?

According to a new survey of US and UK senior marketing and sales professionals, commissioned by Leadfeeder, 82% of B2B companies continue to find lead generation a challenge. Bigger companies (with over 250 marketing and sales people in the organization) are likely to find B2B lead generation more challenging when compared to an SME.

Recommended: DeepNash and the World of Model-free Multi-agent Reinforcement Learning (RL)

The research also found 65% of B2B companies are looking to invest more in buyer intent data to overcome their lead generation challenges.

Buyer intent data is now a vital way companies can grow their leads. Intent data consists of aggregated behavioral signals that indicate interest in a service or product, helping marketers and sales teams to nurture and convert new customers.

According to the research, over three quarters (76%) of businesses now use buyer intent data to inform their marketing and sales strategy.

Of the in-house teams who use buyer intent data, frequency of visits was cited as the strongest indicator of a sales lead, followed by time spent on site, requests for more information, completing a contact form and downloading assets.

Furthermore, the most reported benefits of using buyer intent data were higher conversion rates (47%), bigger deal sizes (43%) and more deals closed (38%). Only 1% of respondents reported no performance increases, highlighting its value when used correctly.

B2B companies need a lead generation funnel for the simple reason that, in most cases, a purchase takes a long time to develop. It’s a lengthy process, with 90 percent of B2B sales taking more than one month to close, while 10 percent take more than one year.

While there are a lot of differences in the way individuals make a purchase, there’s still a process leading up to a buyer’s decision. And increasingly, B2B companies are tracking intent data signals to help them develop a smarter, more customer-focused marketing and sales strategy that’s designed around the modern buyer cycle.

But despite a growing appreciation for the value of buyer intent data, a knowledge gap remains.

The study reveals 87% of senior sales and marketing professionals still have more to learn about this method. The majority of B2B companies aren’t fully leveraging the power of buyer intent data and may need expert external support to unlock more value.

Of the B2B companies that don’t use buyer intent data, lack of internal knowledge and budget limitations were cited as the main reasons why.

Jaakko Paalanen, CRO at Leadfeeder commented on the findings:  

“Our survey provides a valuable insight into the challenges faced by B2B sales and marketing teams when it comes to lead generation but also highlights the benefits of taking a more data-led approach. It’s clear that lead generation is still a priority of B2B marketers and a major headache. But with the help of intent data, marketing teams can drive more qualified pipeline and sales teams can focus on the right prospects, creating a more efficient process that delivers revenue.”

Role of AI and Machine Learning in B2B Lead Generation

Why AI?

Well, according to a recent survey, businesses could save upto $35000 USD every year by using AI and machine learning for their processes, and this includes Marketing and Sales activities.

AI for sales and marketing has been around for some time now. AI could do many things for B2B businesses, however, its role in ABM and intent based B2B sales seldom made through the initial rounds of prospecting and predictive lead scoring. But in the last 2 years, largely thanks to the COVID-forced paradigm shift in virtual selling (yes! 86% of buyers now prefer to be sold “virtually”), B2B teams have hooked on to the AI-driven intent data. AI is the foundation of content discovery and social media intelligence for buyer intent data aggregation and analytics. For B2B companies that use third party sources for lead generation, AI can optimize the process of intelligent content discovery. It could track down the accounts that sales team is actively chasing and compare these conversations and engagements across multiple physical-digital (phygital) touchpoints. AI-based account matching, CRM automation, identification and prospect cleansing activities can be actively done using machine learning algorithms built specifically as part of B2B Martech and Sales Technology solutions. With buyer intent data using AI, account managers have a superior sense of how to influence buyer’s behavior through superlative timing, relevance and contextual targeting.

Today, ABM strategies run largely on powerful AI that makes it possible to uncover hidden patterns in user behavior and intent signals. From how prospects spend time on a webpage to what kind of content is keeping them most engaged to how effective social media posts are in influencing sales within a group of users – AI has emerged as a true game changer in improving the overall lead gen strategies. From helping account managers identify the top prospects who engage the most to triggering an automated signal using chabtots or virtual assistants, AI and intent data management solutions are a must to succeed with modern-day lead generation strategies in B2B.


This article is written by AiThority and originally published here



Flare Netharn

You might also be interested in