Do you think it would be wise to spend $13.7 billion on buying a business just so you could get your hands on their data? Well, Amazon seemed to have thought so when they acquired Whole Foods in 2017.
There’s a clear correlation between data and growth in the modern world. But not just any data, you want relevant actionable data that can propel your business towards a downpour of revenue.
So what makes data relevant and actionable? Two simple words — buying intent.
What is Buying Intent?
Just as simple as the two words connote, buying intent is nothing but the intention to buy. Behind any interaction, there exists a certain intention, however small or big, that is transactional in nature. These are not necessarily monetary transactions but also informational and exploratory ones.
In the business world, buyer intent data simply stands for the data that helps you identify a buyer’s readiness to purchase your product at any given instant of time.
Now intent data providers tend to often portray buyer intent as a bubble. However buyer intent data generally constitutes multiple intent signals, some more actionable and valuable than others — we at Slintel call it a spectrum.
In this post we’ll run you through the different types of buyer intent data signals on the basis of how well they perform in the real world. All this through an interactive simulation. So lo and behold:
What Are the Different Types of Buyer Intent Data Signals?
Now that we’ve gone through the different types of buyer intent data signals, it may come as a surprise, but buying intent data can be further segregated.
How Do We Segment Prospects Using Buyer Intent Data
All the prospects in your pipe can be categorized into two kinds on the basis of their appetite to make a purchase.
Active Buying Intent
When a user emits active buying intent signals, they’re outwardly searching for a product or service. They are on the journey to becoming a customer of the product. This could either happen immediately or take place sometime in the near future depending on the type of signal they emit.
Active buying intent can further be divided into three types based on this level of immediacy.
Informational Buying Intent
The earliest stage of active buying intent is when a buyer is trying to familiarize themselves with your product. In the process they may consume content that helps educate themselves about the product and its uses.
For example, a user exhibits informational buying intent when they go through yours or your competitors’ blog, or any other content that may help them learn more about your product. Here, these informational interactions will help propel the user towards a more transactional one.
Once a user has familiarized themselves with the product, they need help navigating towards a particular brand to make their choice.
When users consume product collateral such as competitor comparison pages, or take a trial to finalize their choice, this can be considered navigational intent.
Once a choice has been made the user now becomes a buyer and is ready to make the purchase.
When a buyer visits pricing pages or gets on a demo, they are said to be in the final stages of making their decision and parting with their monies.
But what happens to those people that clearly have a use or need for your product but have little to no knowledge about it? For that we must turn our attention to passive intent.
Passive Buying Intent
Passive buying intent indicators help you identify prospects that clearly have a use for your product, but have little to no idea about it. These prospects need to be educated and nurtured before they can turn into buyers.
For example, someone that uses a go-to-market solution like Slintel to find high-intent active and passive buyers will also inherently have a need for an outreach tool to use Slintel’s data to automate custom personalized messages to them.
Prospects with expiring contracts, or those that use integrating/complementary tools can be great places to start looking out for passive buyers.
And that, as they say, is that
Having seen what different buying intent data types have to offer, we hope it has helped you gain a better understanding of your buying intent needs and where you stand currently.
The human mind can only go so far in a world that’s drowning in an infinite ocean of data. So why try to be a superhero when there’s a proven buying intent framework that can help propel you into the hypergrowth stratosphere.