When it Comes to Predicting the Buyer Journey, How Reliable is Intent Data for Marketers? 

Have you ever wished you could read your potential customers’ minds? Well, with the rise of intent data in the world of marketing, that dream might not be too far off. Intent data promises to predict a buyer’s journey before it even begins, but how reliable is this data for marketers? In this blog post, we delve into the world of intent data and explore its benefits and limitations to help you understand if it truly lives up to the hype. So, get ready to dive in as we uncover whether or not intent data is a marketer’s secret weapon! 

What is Intent Data? 

Intent data is a record of what someone is trying to do online. It’s generated when people search for things, click on links, or visit websites. Marketers can use intent data to try and predict what someone is looking to buy, and then show them relevant ads. 

However, there are some limitations to using intent data. First, it’s not always accurate. People’s search terms don’t always reflect their true intentions, and even if they do, their plans can change. Second, intent data only tells you what someone is interested in right now. It doesn’t give you any insights into their past behavior or plans. 

Despite these limitations, intent data can be a valuable tool for marketers. When used correctly, it can help you reach your target audience with the right message at the right time. 

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How Does Intent Data Help Marketers? 

Intent data has become an increasingly popular topic in the marketing world as it is seen to accurately predict the buyer’s journey. However, there is still some debate as to how reliable intent data actually is. 

There are three main types of intent data: search engine queries, online behaviors, and purchase history. Search engine queries are the most common type of intent data and are often used to target ads. Online behaviours can be harder to track but can include things like website visits or social media interactions. Purchase history is the least common type of intent data but can be very useful for marketers trying to reach high-value customers. 

So, how does all this help marketers? By understanding what someone is searching for or doing online, marketers can better tailor their messaging and offers to match the individual’s needs. This can result in more leads and sales as well as higher customer satisfaction rates. 

Of course, no data is perfect and there are always risks when relying on it too heavily. Intent data can change quickly and be difficult to interpret correctly. Additionally, not everyone who shows interest in a product will actually buy it. Nevertheless, when used correctly, intent data can be a powerful tool for marketers trying to understand their customers’ journeys. 

What Role does Intent Data Play in the Buyer Journey? 

When it comes to predicting the buyer journey, marketers have long relied on intent data to give them insights into what their target audience is interested in. However, recent studies have called into question the reliability of intent data, particularly when it comes to predicting the final stages of the buyer journey. 

So, what role does intent data play in the buyer journey? While it can be useful for marketers to understand what their target audience is interested in at each stage of the journey, they should not rely on it exclusively to predict the outcome. Instead, they should use a combination of methods, including other forms of customer data, to get a more complete picture of their target audience and how they are likely to behave. 

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Challenges of Using Intent Data to Predict the Buyer Journey 

When it comes to predicting the buyer journey, marketers must consider the reliability of intent data. Intent data is collected from a variety of sources, including search engines, social media, and website visits. This data can be used to infer the stage of the buyer journey that a customer is in and what marketing content will be most relevant to them. However, there are several challenges that must be considered when using intent data to predict the buyer journey: 

1. Intent data is often inaccurate or incomplete. 

2. The same user may exhibit different behavior at different stages of the buyer journey. 

3. The buyer’s journey is not always linear, making it difficult to accurately predict what stage a customer is in. 

4. Some customers may never reach the purchase stage, making it impossible to use intent data to predict their behavior. 

Despite these challenges, intent data can still be a valuable tool for marketers who are looking to understand their customers’ needs and provide them with relevant content throughout their journey. 

Strategies for Improving Accuracy when Using Intent Data 

As the world of marketing becomes increasingly data-driven, the use of intent data has become a hot topic. Intent data is defined as “data that captures an individual’s research and buying behavior leading up to a purchase.” In other words, it’s the digital breadcrumbs that people leave behind as they research products and services online. 

There are a number of ways that marketers can use intent data to improve their accuracy when predicting the buyer journey. Here are four strategies: 

1. Use multiple sources of intent data: Don’t rely on just one source of intent data when making decisions about the buyer journey. Instead, use multiple sources (e.g., Google AdWords, web analytics, CRM data) to get a more complete picture. 

2. Look for patterns and trends: When analysing intent data, look for patterns and trends that can help you predict what prospects are likely to do next in their buyer journey. 

3. Test and refine your hypotheses: As with any predictive model, it’s important to test your hypotheses about the buyer journey against real-world data. Iterate and refine your models based on what you learn from testing. 

4. Use other types of data to supplement your understanding of the buyer journey: In addition to intent data, consider using demographic data, firmographic data, psychographic data, and other types of marketing intelligence to get a more complete picture of the buyer journey. 

Alternatives to Intent Data for Marketers 

One question we often get asked is whether there are alternatives to intent data for marketers. The answer is yes! There are a few different ways that you can go about predicting the buyer journey, and each has its own set of pros and cons. Here’s a rundown of a few alternatives to intent data: 

Social Media Listening

This involves monitoring social media platforms for mentions of your brand, product, or keywords related to your industry. You can then use this information to infer customer sentiment and understand what people are saying about your brand.


Social media listening is a great way to get real-time insights into customer sentiment. It’s also relatively easy to set up and doesn’t require any special software or tools.


Social media listening can be time-consuming, and it can be difficult to filter out noise from relevant signals. In addition, social media platforms are not always representative of the general population. 

Market Research Surveys

Surveys are another popular method for understanding customer sentiment and predicting the buyer’s journey. They allow you to ask questions directly to your target market, which can yield valuable insights into their thought process and decision-making criteria.


Surveys provide direct access to customers’ thoughts and opinions. They are also relatively easy to administer and don’t require any special software or tools.


Surveys can be time-consuming to create and administer, and they typically have low response rates. 


Intent data is a powerful tool for marketers to use when predicting buyer journeys. It provides an insight into customer behaviour that can be used to inform marketing decisions and tactics, helping you better understand your target audience and tailor campaigns accordingly. However, while intent data should form the basis of any marketer’s strategy, it cannot be relied upon in isolation; other sources of information such as surveys, interviews or monitoring reviews should also be considered when making decisions about how to best engage with customers. 

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