What is Buyer Intent?
Buying intent is defined as a measure of how likely it is that a customer will buy something within the next 30 days. This metric is used to predict whether customers are ready to make a purchase or not.
It is essential because it helps marketers understand the level of interest in a certain product or service [1].
Buyer intent is usually measured by analyzing data collected from previous purchases, browsing history, social media posts, etc. You can always check this data in various analytics tools: Google Analytics, social media insights, and Reports, Stats, and Analytics in your site search.
Predictive analytics uses algorithms to analyze historical data and determine future trends based on current behavior [2].
What is Intent Data?
Intent data gives marketers insight into customer behavior. Marketers use it to figure out which customers are most likely – and least likely – to buy products or make purchases. They can target those customers with personalized messages and offers [3].
Marketers collect this data through cookies and other tracking tools. It can help you identify potential leads, find new ways to sell products, and increase conversion rates 4].
When people talk about intent data, they’re referring to how companies should approach their advertising campaigns. You might see ads for a product that seems like it could be useful but isn’t relevant to your audience. Or you might see an ad for something that doesn’t seem like it’s related to your brand at all.
Companies can prioritize accounts based on the things they’re searching for.
For example, if someone searches for “coupons,” you know they’re probably shopping for discounts. If they’re looking for “batteries,” you know they’re more interested in electronics [5].
This information helps marketers better understand what customers want before asking for anything. It lets them know whether they should focus on one part of their site or another.
How is Buyer Intent Data Collected?
There are six main ways to gather buyer intent data:
Search queries - The search terms users enter can provide insights into their purchase intentions [6]. Check this data in Reports, Stats, and Analytics on your site search.
Social media posts - Analyzing posts can reveal user interests and potential buying signals [7].
Email marketing - Tracking interactions with emails can indicate purchase readiness. Mobile app usage - App behavior can provide insights into user preferences and intentions 8].
Website traffic - Analyzing page views, clicks, and time spent on the site can highlight buying intent [5].
Customer reviews - Reviews can provide insights into customer satisfaction and potential repeat purchases [9].
How Does Intent Data Differ?
First-Party Data
You probably use web tracking data to understand what happens on your site. But do you know how much traffic you’re getting, where it came from, and why people are clicking on certain buttons?
Intent data gives you insight into each visitor’s actions once he/she lands on your site. This information helps you better understand what visitors want and whether or not they converted [10].
Third-Party Intent Data
Third-party intent data helps marketers understand what people are doing online. In addition to helping you understand how people interact with your product or service, it allows you to see where people go after interacting with your brand. You can use this information to improve your marketing strategy [11].
There are five main ways to gather this type of data:
Conversions - If someone visits your site and makes a purchase, this is called a conversion.
Interactions - If someone interacts with your brand on social media, this is called an interaction [12].
Events - If someone signs up for your newsletter, subscribes to your blog, or downloads a whitepaper, this is called an event.
Website Behavior - If someone spends 10 minutes looking around your website without making a purchase, this is considered website behavior [5].
Search Terms - If someone searches for something related to your brand, this is called a search term.
Conclusion
The world of ecommerce is changing rapidly. New technologies like artificial intelligence and machine learning automate tasks and make customer interactions easier. This trend is already impacting how businesses and people buy products online [13].
As we move forward, there will only be more opportunities to collect valuable insights about our customers.
The key is understanding how to best leverage these insights to grow your business.
References
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Tagliabue, J., Greco, C., Roy, J.-F., Yu, B., Chia, P., Bianchi, F., & Cassani, G. (2021). SIGIR 2021 E-Commerce Workshop Data Challenge. ArXiv.
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Kumar, A., M., D., Jiménez Macedo, V. D., Mohan, B., & N., A. (2023). Machine Learning Approach for Prediction of the Online User Intention for a Product Purchase. International Journal on Recent and Innovation Trends in Computing and Communication.