Intent Data vs. Buying Propensity — What’s the Difference?

Lainey Mebust
June 23, 2020

When it comes to marketing, data should always guide your next steps. Today, predictive analytics (like intent data and propensity to buy) use historical data to drive marketing success. While similar, intent data and buying propensity shouldn’t be used interchangeably. So, what’s the difference? Explore the key differentiators between these data-driven marketing tactics below.

What is Intent Data?

Intent data is behavioral information based on a prospect’s online activities. It combines both topic data (their search history) and context data (why they’re searching) to determine if, what, and when a prospect will purchase your product or solution. 

Topic Data and Context Data 

Topic data assumes that by searching for something online or by visiting an online store, a prospect is expressing an active interest but always not an intent to buy. 

Context data is all about gaining insight into why a prospect is searching. For example, if a marketing professional visits a blog about using AI for marketing, it’s likely they are in the process of evaluating a tool that leverages AI. But, if that visitor is a data scientist, they could simply be looking for more information on the subject.

Both topic and context data provide insight into a web user’s intent — allowing marketers to pinpoint if and when a prospect is actively considering or looking to buy their solution. 

What is the Significance of Intent Data?

87% of buyers begin their product search online, meaning prospects are researching products far before they contact your sales team — on sites that aren’t yours. B2B intent data captures that activity to provide insight into a prospect’s buying intent. While nearly all of customers are actively researching products online, only 25% of B2B companies currently use intent data

87% of buyers begin their product search online. While only 25% of B2B companies use intent data.

Companies that don’t use predictive intelligence data limit their customer insight to what they can capture on their own website. B2B intent data captures prospect activity across multiple websites, to help identify early buyer interest and pinpoint which companies are actively researching for solutions like yours.

What is Buying Propensity? 

Buying propensity uses artificial intelligence to predict who is likely to buy your product or service. This is done by using AI to learn about your current best customers and finding companies in the market that look like them. Instead of evaluating the online behaviors of a prospect, buying propensity analyzes the structure of an organization, to see how closely it fits your existing best customers and evaluates how likely they are to need or purchase your product or solution. Buying propensity help teams scale lead quality and volume at scale by further refine their target market. 

How Does Buying Propensity Work?

B2B buying propensity uses AI to deeply analyze companies. An AI engine is used to determine concepts through Natural Language Processing (NLP) from a company’s website and its internal functional makeup using deep learning (a type of AI). This creates a vector of topics that unlock the true, multi-dimensional nature of what a company does, what it needs, what it’s likely to buy, and how it might be similar or different from your best customers.

Looking at this framework for one company is just the beginning. The more valuable part of the story is that this data exists for millions of companies. When you look at large groups of companies using an AI engine, you get the whole picture. Buying propensity allows teams to accurately target and identify thousands of companies that fit their ideal customer profile. 

 

 

Want to learn how to leverage buying propensity in your marketing strategy? Join us July 8th for our live event as we debut our hyper-targeting tool, Buying Signals, and learn how AI can enhance your ABM and demand gen campaigns.

Further Reading

Lainey Mebust