Unqualified leads are a problem. In fact, marketing teams identify only 44 percent of leads as good fits.
Intent data helps to solve this problem. It indicates the likelihood of a person buying your product or service. This allows you to identify good-fit leads, and drive conversions as a result.
But to know how to use intent data, you must first understand it. So, let’s break down the ten intent data terms you need to know.
1. Buyer intent data
Buyer intent data gives information about individuals’ behaviour online that provides signals of the topics they’re interested in. Depending on the data’s reliability, it can indicate the likelihood of a person buying your product or service.
Account-based marketing (ABM) focuses time and resources on targeted, individual prospects instead of the whole market. Intent data helps inform ABM strategies, giving teams insights on who is more likely to convert into a sales opportunity.
Account-based experience (ABX) is an evolution of ABM focusing on how the end user interacts with your brand. Sales and marketing teams work together to ensure messaging aligns with where the customer is in the sales funnel. Tracking keywords in the content users read is also key to this strategy.
4. Intent keywords
Sales and marketing teams can assign buying intent to a prospect by monitoring the content users read and the keywords within it. For example, if someone is engaging with content that uses the keyword ‘free’, they’re likely not ready to buy. But prospects scouring informative content with keywords such as ‘How to’ are good opportunities for lead nurturing. Then there are your high-intent keywords indicating a good chance for a sales conversion. Examples of these are ‘buy’, ‘purchase’, and ‘where can I find X near me’.
5. Topic clusters
A topic cluster consists of multiple pieces of content organised around a topic. The core pillar page provides an overview, with relevant articles interlinked to help people explore the topic in depth.
6. Intent topics
Intent topics provide more context to the content users consume. AI programs such as natural language processing (NLP) monitor the topics and identify what is more relevant to users for a better understanding of their buying intent.
Natural Language Processing (NLP) is a subset of computer science and linguistics that focuses on the interactions between computing and human language. It analyses large amounts of human language data to provide context to users’ written and spoken words.
8. Intent event
This an action that signals a user’s interest in a specific subject. Good examples of this would be when they register for a webinar or download an ebook.
An intent-qualified lead (IQL) is a contact who has demonstrated interest in your product or service and is thus worth pursuing.
An intent-qualified account (IQA) is the entire organisation that, thanks to your intent data, is worth pursuing as a sales prospect.
Understanding these ten terms will provide a good basis for your ABM efforts. But if you want to know you’re targeting the right leads, you need quality intent data.
At Intentify Demand, we use intent keywords and NLP to unearth high-intent leads with a 97 percent degree of accuracy. Then, our unique AI Pelago will assign a numerical value to each one. So you’ll know which prospects hold the most promise, and can prioritise your best-fit leads as a result.
Get in touch with our intent data specialists to learn more.