Today, businesses are held to a higher standard than ever. As customers, we have begun to compare businesses of all shapes and sizes to the Amazons and Apples of the world. A new standard of communication has been set, and anything that falls short fails to impress us. When it comes to marketing communications, businesses can no longer provide the content they THINK potential customers want. Individually personalized content across all touch points of each unique customer’s journey has become the customer’s expectation. Unfortunately, this requires a huge investment of both time and resources. So, how do businesses provide their customers with one-to-one personalized experiences in a way that is also scalable?

The answer is AI.

While AI is without a doubt the direction marketers are headed, it too has a steep barrier of entry. AI programs require substantial amounts of data to operate effectively. Often, businesses don’t have the amount of data necessary, and those that do don’t always trust their data’s integrity. As a result, many businesses are turning to third-party data providers to fill the gaps.

What is intent data?

Bombora defines intent data as data that is collected about a person’s or company’s observed online behavior — specifically Web content consumption (articles they read, white papers they download, etc.). Intent data provides insights into their interests, and from this indicates a potential intent to take action. There are two types of intent data: first-party data is the data generated from engagements with businesses’ internal content, and third-party data is the data generated by engagements with external content across the Internet. Third parties provide the latter by monitoring and aggregating data about the content consumed by individuals across a huge network of content providers, such as The Wall Street Journal or Forbes.

Intent data provides behavioral insights on two types of people: known and anonymous. The known visitors are individuals who have provided their basic contact details like their name and email address. The most common way for a potential lead to become “known” is by filling out a Web form. Anonymous visitors are individuals who have not yet provided any information. When anonymous leads visit a site, their IP addresses are collected by third-party data providers like Bombora or The Big Willow. Through reverse IP lookup, providers can determine a visitor’s company and attribute that individual’s intent to a specific B2B account.

How is intent data used?

Many marketers are gaining a leg up on their competition by integrating intent data into their marketing strategies. Intent data helps marketers fine-tune their process so that each potential lead is receiving the exact information they are looking for, when they are looking for it. It’s helping change the narrative from “Here are all the reasons our product/service is great” to “Here is the way our product/service can help solve your specific problem.” Marketers are using intent data in a variety of ways, such as earlier content personalization and segmentation, more accurate account and lead prioritization, and to help drive content strategy.

1. Earlier Segmentation and Content Personalization

According to Google, individuals involved in the B2B buying process are already 57 percent of the way down the path before they make contact or take action on your website. The days of marketers waiting around for potential customers to make the first move are gone, and businesses that fail to adapt are finding themselves behind the curve. With third-party intent data providers, marketers now have visibility to the content interests of anonymous and known prospects, enabling us to use Web personalization to tailor their very first website experience by displaying content relevant to the interest they have demonstrated externally across the Web. When those leads engage internally and provide their email addresses, marketers are then able to drop them into the most relevant nurture path, with content specific to the topics they were researching prior to trafficking their website.

2. Lead Scoring and Account Prioritization Tactics

With the mass adoption and proven success of marketing automation, many businesses are integrating intent data to optimize their lead-scoring model. The goal of behavioral lead scoring is to assign numeric values to the purchasing likelihood of prospects. For example, if a prospect visits a services page, that person’s account may receive a score increase of 2 points, whereas an account with a visitor who views your pricing page, demonstrating a greater intent to purchase, may receive a score of 5. Eventually, when a lead’s or account’s score reaches a specific value, indicating that the prospect is sales-ready, that information is then sent to sales.

In the past, lead scoring has been limited to the actions taking place on your website. But as we know, this is far from a complete picture. Consider the scenario of a B2B digital marketing service provider who has two potential customer accounts. The first has multiple employees reading articles about the top digital marketing companies in 2018 and downloading white papers about selecting an agency. The other account does not. They both may exhibit the same behavior on your website, but the first account is clearly a better place for sales to focus their efforts. Third-party intent data is providing B2B businesses with the data necessary to better determine sales-qualified leads and more effectively prioritize sales and marketing efforts.

3. Content Strategy Insights

For years, marketers have been limited to first-party on-site activity to draw conclusions about the behavior of potential leads. Unfortunately, with 57 percent of the buying research taking place prior to any interaction on our websites, we are missing more than half of the picture. By understanding what content customers are searching for at the beginning of the buyers’ journey, businesses are able to create content that captures their attention earlier. It also helps refine key phrase strategies. Often the topics or types of content companies think prospects are interested in (e.g., white papers, videos, checklists, case studies, etc.) can be very different from reality.

Intent data has enabled marketers to both personalize and automate the delivery of targeted, more relevant content from the very first touch point. And while there is no disputing that AI and predictive machine learning programs are the future, intent data is proving to be a highly valuable addition to the successful marketer’s arsenal.