Intent topics vs. Intent keywords?
Understanding buyer behavior has never been more critical for B2B marketers and revenue teams. Yet, many organizations still rely on keyword-based approaches that reveal only a surface-level view of business research. Bombora’s Intent topics solve this problem by offering a deeper, more contextual understanding of online content consumption.
Unlike keywords—which simply indicate whether a word or phrase appears on a web page—Intent topics use Artificial Intelligence technologies including deep learning and natural language processing (NLP) to understand what the content’s actually about. They empower GTM teams to discover real research behavior to build effective strategies.
What are Bombora Intent topics?
A Bombora Intent topic represents the underlying concept or subject matter of online content. These topics are generated using advanced NLP and machine learning models that interpret context, linguistic structure, semantic relationships, and industry terminology. The goal is to identify meaning, not just match to simple words.
For example:
- A keyword system may register the word “cloud” on a page several times.
- Bombora’s topic models determine whether the page is about cloud infrastructure, cloud data management, meteorology, or something else.
Using contextual intelligence, Intent topics deliver genuine insights that mirror how humans interpret information—beyond counting repeated words or phrases.
Today, Bombora’s taxonomy includes tens of thousands of unique B2B Intent topics, spanning industries, brands, solutions, technologies, capabilities, challenges, and market segments.
How Intent topics are created
Bombora’s Intent topics are powered by a multi-layered AI and content-classification process that ensures precision and relevance.
1. Curated training inputs
Bombora’s domain experts identify seed URLs and content collections representing real-world writing about each topic. These serve as the foundation for accurate model training.
2. Deep learning classification models
Bombora applies NLP models built to understand language the way humans do—through context, sentiment, structure, and semantic meaning. These models evaluate text across more than 5 million websites across the Bombora Data Co-op.
3. Topic assignment
As content is consumed across the web, Bombora’s systems classify each piece according to the topic(s) it’s most relevant to. This means a single page may correspond to multiple Intent topics if the content covers several ideas.
4. Continuous Optimization
Bombora’s taxonomy expands regularly to reflect emerging technologies, evolving buyer needs, and industry changes. Models are retrained and validated each cycle to maintain consistency and accuracy.
Why Intent topics are more meaningful than keywords
Keywords are words or strings of text that provide no context for whether a word reflects genuine interest or simply appears on a page. Intent topics capture actual research behavior, meaning companies are actively consuming them to learn, compare solutions, evaluate vendors, and more.
Key differences between keywords and Intent topics
| Keywords | Intent Topics |
|---|---|
| Literal word or phrase match | Concept-level classification |
| No context or semantic interpretation | Understands context, meaning, and relevance |
| Can’t differentiate multiple meanings | Disambiguates terms with many definitions (“cloud,” “automation,” “security”) |
| High noise and low precision | High intent and reduced false positives |
| Not inherently tied to user intent behavior | Based on real content consumption by companies |
How Intent topics power Intent data
Intent topics are at the core of Bombora’s Company Surge® measurement. By analyzing changes in research behavior over time, Bombora identifies when B2B companies – and the personas within those companies– show heightened interest in specific topics.
Where Intent Topics Are Used in GTM Motion
Intent topics are a foundational component across revenue workflows:
1. Account Prioritization
Identify which companies are researching specific pain points, technologies, or industries so sales and marketing can focus energy where demand already exists.
2. Audience Building & Segmentation
Create hyper-relevant segments for your target audience across ABM, advertising, or lead generation based on real intent signals, not assumed interest.
3. Personalization at Scale
Use Intent topics to craft messaging aligned to what prospects are actively researching to boost engagement and response rates across your outreach.
4. Product, Category, and Market Intelligence
Track which topics are gaining traction over time to understand category emergence, competitive shifts, or changes in buyer behavior.
Why context matters in B2B Intent
B2B buying journeys are complex. Multiple personas within buying groups may research dozens of topics across months before making a purchase.
A keyword-only approach can generate noise, surfacing the wrong signals. Bombora’s contextual classification—combined with scaled behavioral observation—solves this. The result? A far richer, more accurate picture of buying intent.
Summary
Intent topics represent a major evolution from keyword-based models. By interpreting content at the conceptual level and analyzing real B2B research behavior, Bombora provides the industry’s most trusted and actionable Intent signals.
FAQs about Intent topics versus keywords
How do Intent topics differ from keywords?
Keywords are literal word matches, while Intent topics interpret the meaning behind online content. Bombora’s topics use NLP and machine learning to understand context, eliminating noise and providing more accurate insights into what businesses are researching.
How many Intent topics does Bombora support?
Bombora’s taxonomy includes tens of thousands of unique B2B Intent topics, spanning industries, technologies, challenges, and go-to-market categories. The taxonomy is updated multiple times each year.
Can a web page map to multiple Intent topics?
Yes. If a piece of content legitimately covers multiple concepts—such as “cloud security,” “data governance,” and “identity management”—it will be classified under each appropriate topic.
How do Intent topics improve sales and marketing performance?
Intent topics help GTM teams prioritize in-market accounts, create more relevant segmentation, personalize outreach, and improve conversion rates by focusing on accounts and roles within those accounts that are already showing active research signals.