How Visualizing Intent Data Can Improve Win-Rate Percentages

There are plenty of reasons to invest in third-party intent data—to improve content marketing strategy, maximize sales enablement, support personalized marketing, or even optimize ABM efforts.

But no matter which use case is right for you, the ultimate goal is to improve your organization’s win-rate percentage.

One of the biggest advantages of using intent data to improve win-rate percentage is that you get visibility into individual buyer journeys. Understanding the activity of target accounts and contacts at each step of the buyer’s journey will help you send the right marketing/sales messages at the right time.

But buyer journeys can become extremely complicated. Staring at a massive dataset might not make insights obvious enough, which is why data visualization is so important to drawing winning connections between your marketing and buyer needs.

What a Marvel Data Visualization Teaches Us About Intent Mapping

If you’ve followed pop culture even remotely over the last decade, you know that the Marvel Cinematic Universe (MCU) has essentially dominated consumer attention. When the billion-dollar-blockbuster Avengers: Endgame premiered in April 2019, it was the 22^nd movie in a complex series that started all the way back in 2008.

The result is a web of character relationships and plot points that looks something like this:

This data visualization put together by The Straits Times contains detailed descriptions about the roles of every character throughout the MCU. But it’s not just a wiki with a paragraph or two about the movies characters appeared in—it lets you sort by various relationships and activities that connect individual characters and movies on the larger scale.

Unless you’re a serious MCU fanatic or were somehow involved in creating the movies, it’s understandable if you lose track of how events in 2008’s Iron Man were later referenced in 2019’s Avengers: Endgame. Or, how Tony Stark’s father is connected to the man who created the Ant-Man suit.

With a data visualization, you can quickly identify valuable insights much faster than if you were just looking at a spreadsheet. This is as true for the MCU as it is for mapping intent in a buyer’s journey.

We like to think that the buyer’s journey is linear. But you know that it’s often more complicated than that. A target account could view middle-of-the-funnel content one day and fall back to the research phase the next. Or, you could lose a deal to a competitor only to find that the account is back to actively looking for a solution soon after.

Being able to cut through all that noise and truly understand real-time intent signals is the key to improving your win-rate percentage. This is where a third-party intent data provider can help.

Visualizing Intent with Machine Learning

Using data visualization to wrap your head around the MCU before a new movie comes out might be fun, but it won’t exactly help you improve business results.

The missing link between something entertaining like the MCU data visualization and a model designed to improve win-rate percentage is the presence of causal links. You don’t just want to see the individual points of activity on a specific buyer’s journey—you want visibility into what leads to won opportunities and what leads to losses.

When evaluating third-party intent providers, make sure that they use machine learning to maximize their results. Machine learning algorithms can take all of the different intent signals of your target accounts, determine levels of active research ahead of sales opportunity creation, and predict win-rate variances.

By weaving machine learning into our B2B purchase intent analysis, we can help you identify the causes and effects of your closed deals and determine how to apply those insights to new opportunities. If someone can simplify all the interwoven characters in the MCU, we can help you find the valuable insights in all that buyer’s journey data.