Behavioral intent data refers to data generated when users interact with digital assets and touchpoints of a company, including the actions they take within a particular app or website and what content they consume.
Organizations in all industries are increasingly using behavioral intent data to enhance their digital products as the digital economy continues to grow.
What are the Main Sources of Behavioral Intent Data?
There are many sources of first-party, second-party, and third-party behavioral intent data.
Some of the most common places for companies to harvest this type of data include (but not limited to):
- Intent data providers
- Bidstream data
- Website behavior (Google Analytics, Semrush, Clickly, etc.)
- User session recordings (Hotjar, LogRocket, Mouseflow, etc.)
- A/B testing
- Qualitative user research
- User surveys
- Social media data
How Do Companies Use Behavioral Intent Data?
With 89% of B2B customers using the Web to make purchasing decisions, companies use behavioral intent data to better understand their customers and target ads and product offerings more effectively.
By tracking what users do online, companies can glean valuable insights into their interests, desires, and intentions, reaping a host of unique benefits:
- Improved customer understanding: behavioral data can help organizations understand their customers better and develop more targeted marketing strategies.
- Optimized user and customer experience: by understanding how users interact with digital products, companies can make changes to improve the overall user experience.
- Increased conversions and sales: behavioral data can be used to identify areas where target accounts are struggling to convert, so that changes can be made to increase conversion rates.
- Better decision-making: behavioral data provides insights that can help organizations to make more informed decisions about their product development and marketing strategies.
- Enhanced customer loyalty: by providing a better user experience, behavioral data can help to increase customer satisfaction and loyalty.
- User segmentation: this type of intent data can be used to segment users into groups for targeted marketing purposes.
What Are The Most Common Behavioral Intent Data Attributes?
There are a number of different types of data that can be used by marketing and sales teams to understand and predict consumer behavior, but some of the most common and helpful data attributes related to behavioral intent are purchase history, search history, and click-through data.
- Purchase history data can give insight into what types of products or services consumers are interested in and likely to buy in the future.
- Search history data can reveal what consumers are looking for and thinking about to predict future purchases or intent.
- Click-through data can show what consumers are interested in on a specific website or landing page, and can help businesses better understand which ads or offers are most likely to result in a purchase.
Depending on the type of intent data you’re working with, you can additionally gain access to demographic data, firmographic data, and other types of B2B or B2C customer data.
By understanding which data attributes are most helpful in predicting behavior, businesses can more effectively target their marketing efforts and improve their bottom line.
What Are the Pros of Behavioral Intent Data?
Behavioral intent data provides insights into customers’ and employees’ true goals and motivations, rather than their self-reported preferences or intentions.
It’s more accurate than traditional market research techniques, such as surveys and focus groups. This is because people are often not aware of their own motives and may not be able to accurately explain them.
What Are the Cons & Challenges of Behavioral Intent Data?
Here are the most common challenges related to collecting and using behavioral intent data:
- Big data management: behavioral data can be generated in large volumes, making it a challenge for companies to manage and analyze it effectively.
- Data interpretation: behavioral data can be complex and challenging to interpret, particularly for organizations that do not have prior big data analysis experience.
- Privacy concerns: behavioral data can contain sensitive information about users, which raises privacy concerns and may require companies to take extra steps to protect user data and comply with regulations such as GDPR, HIPAA, and CCPA.
- Implementation costs: tracking and analyzing behavioral data can require significant investment in terms of time and resources, which may not be feasible for all organizations.
Despite these challenges, behavioral intent data provides a wealth of benefits that can help companies to improve their digital products and enhance their understanding of customer behavior.
When used correctly, this data can be a powerful tool for driving business success.
4 Tips to Get the Most out of Behavioral Intent Data
Here are a few tips to help you get the most out of behavioral intent data:
- Partner with intent data providers: Since internally collected buyer intent data is nowhere near enough, it’s vital to seek out third-party data vendors to enhance internal records with high-quality, real-time data to create a holistic view of your target customers.
- Use multiple data sources: this background information on prospective high-value accounts is available from a variety of sources, including social media platforms, search engines, and website analytics. To get the most accurate picture of customer behavior, it’s important to use data from as many sources as possible.
- Look for patterns: behavioral intent data can be complex and difficult to interpret. To make it more manageable, zero in on patterns and trends in the data. This will help you better understand what the data is telling you about customer behavior.
- Use segmentation: behavioral intent data can be used to segment customers into groups based on their interests and desires. This will allow you to target your marketing efforts more effectively and improve your bottom line.
- Consider data privacy risks: as buyer data is often collected without the individual’s knowledge or consent, it’s important to be aware of potential privacy concerns. Make sure you are transparent about how you are collecting and using this data.
- Get data scientists on board: When it comes to behavioral intent data, it’s important to have a team of experienced data scientists who can help you understand and interpret the findings.
- Implement AI, machine learning, and predictive analytics: Using advanced technologies and data analysis methods, you can uncover hidden patterns to boost the ROI of your intent data even further.
Behavioral intent data can be incredibly useful for businesses that want to understand their customers and cater to their needs more effectively.
While there are some potential drawbacks to consider, such as privacy concerns, these can be mitigated by following best practices and using behavioral intent data responsibly.