Topic intent
In short
Topic intent is evidence that an account is actively researching a defined subject, for example "sales engagement software" or "data warehouse migration". It is built by grouping content views and searches into topics and noting which accounts show unusual interest in each.
Topic intent tells you what an account cares about, not who they will buy from. It is the unit that most intent data products are organized around, and the choice of topics largely decides whether the signal is useful.
How topic intent works
Content is tagged with topics. When people at an account read, search, or download content tagged with a topic, those actions are added up and compared with that account's normal level of activity. A noticeable rise is reported as interest in the topic.
- Topic: A subject or keyword cluster, such as "customer data platform".
- Account match: The activity is tied to a company, usually from a business network or a resolved device.
- Strength: How far current activity sits above the account's own baseline.
How to choose topics
Start with the problem, not your product name
Buyers research the problem and the category before they know your brand. Include problem topics, category topics, and a few adjacent ones.
Keep the list short and specific
Broad topics like "marketing" match almost every company and produce noise. Ten to twenty tight topics are easier to act on than a hundred loose ones.
Separate competitor and category topics
Interest in an alternative product suggests an active evaluation. Interest in the general category suggests earlier research. Route them to different plays.
Example of acting on topic intent
Say a team sells security awareness training. It tracks the topics "phishing simulation" and "security compliance training". Three accounts in its target list spike on both topics in the same week. The SDR checks fit, confirms the accounts match the ICP, and sends a message about phishing results to the security lead. The two accounts that spiked on only one broad topic go into a nurture sequence instead.
Common mistakes
- Treating a spike as a purchase decision: A topic spike can come from a student, an analyst, or a single curious employee.
- Ignoring fit: Topic interest from an account that does not match your ICP is rarely worth a rep's time.
- Never pruning topics: Review which topics led to meetings and drop the ones that did not.
Topic intent vs. related terms
Intent data is the broad category of buying-interest signals. Topic intent is the research-subject layer inside it, and it is usually third-party.
Topic intent FAQs
What is topic intent in B2B sales?
Topic intent is a signal that an account is researching a specific subject, such as a product category or a business problem. It is measured by grouping content views and searches into topics and flagging accounts whose interest rises above their normal level.
How is topic intent different from keyword intent?
Keyword intent looks at individual search terms, usually on one search engine. Topic intent groups many related keywords and content views into a subject and measures account-level interest across many sources, so it is less tied to exact wording.
How many topics should you track for topic intent?
Start with a small, specific set, often ten to twenty, covering your problem space, your category, and a few adjacent subjects. Too many broad topics create noise. Review results regularly and remove topics that never lead to conversations.
Is topic intent a reliable buying signal on its own?
No. Topic intent shows research interest, not a decision or budget. It works best combined with ICP fit and other signals, such as hiring or funding news, before a rep spends time on outreach.
