At fullthrottle.ai, we've pioneered a unique methodology for interpreting user behavior via URL analysis. Similar to how AI Language Learning Models use tokenization, we break down URLs into tokens — units that represent the year, make, model, intent signals, and keywords related to automobiles, including terms like 'new', 'pre-owned', 'electric', 'EV', and 'hybrid'. By employing this approach, we decode over 1000 combinations of tokens, providing rich insights into each user's interests.
This detailed analysis enables us to categorize users into the distinct groups you see in the platform.
Most are straightforward, but here is some additional context for EV and EV+:
'EV' represents households shopping for pure electric vehicles, while 'EV+' encompasses a wider audience, including those interested in hybrids and plug-in hybrids in addition to full EVs.
The rationale for these categories is to offer automotive brands nuanced understanding of their audience. 'EV' targets committed EV buyers, while 'EV+' caters to a broader audience interested in diverse eco-friendly vehicle options. By implementing such a tech-savvy yet understandable methodology, we empower clients to strategically connect with their prospective customers, better meeting their evolving preferences in the automotive market.
Learn more about our these segments in our article on Pre-Built Journey Segments
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