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Advanced Audience Search

Most B2B data platforms are catalogs with a fixed set of filters: industry, title, employee count, geography, tech stack, and a few predefined intent signals. If the right filter exists, you can build the list. If it does not, the work moves into exports, spreadsheets, stitching, and manual enrichment. In the CLI, the really powerful mode for this is advanced_dataset_creator: it lets Landbase propose custom SQL-backed audience builds, aggregations, exact filters, and output columns when the default search agent cannot express the query.Landbase is different because the filter does not have to exist before you ask. You can describe the signal you need, and Landbase can compute it over companies, people, job postings, uploaded account lists, and historical career or hiring data.

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High-value search examples

These are the kinds of searches that advanced audience search is built for:
  • Find people who were founding sales hires at a previous startup and are now sales managers or directors at B2B SaaS companies in the US or Canada.
  • Find companies where the AE-to-SDR ratio is between 1.5 and 3.0 and the Manager-to-IC ratio in Sales is less than 0.15.
  • Find companies where hiring for AI or ML titles in the last 30 days is more than 2x the prior 30 days.
  • For an uploaded list of 1,500 accounts, count software engineers in North America and Western Europe, then flag accounts with more than 5.
  • Find CISOs at companies where Security headcount is under 2 but Engineering headcount is at least 200.

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The seven capability families

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What this changes for GTM teams

Advanced audience search moves the hard part of list building into the search itself. Instead of exporting a broad list, computing the real signal elsewhere, and reshaping the output by hand, you can ask for the exact account or contact definition you need.That is especially useful when the buyer’s question is:
  • “Which accounts are showing a signal that our sales team can act on this week?”
  • “Which contacts have actually done this work before?”
  • “Which companies look under-invested in a function relative to their size?”
  • “Which accounts from our own list match this custom profile?”
  • “Which outputs should go directly into our CRM, warehouse, or outbound workflow?”

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Why this works

These searches are possible because Landbase treats the underlying data as something you can compute over, not just something you can filter with a fixed menu.
  • Uploaded customer data is treated as a queryable table, not only an enrichment target.
  • Career history is structured across roles, dates, descriptions, skills, and headlines.
  • Job postings and career timelines are preserved historically instead of flattened to today’s snapshot.
  • Output columns can be defined by the customer at search time, including counts, ratios, booleans, and labels.

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Use it with the CLI

The Landbase CLI gives agents, scripts, and operators a direct way to run these searches and save structured output. Use --agent=advanced_dataset_creator when you need precise logic, custom SQL, aggregations, or output columns beyond the default search agent.Advanced Dataset Creator runs in two steps. First, ask for the audience and reuse a session label:
Then confirm the proposed query in the same session:
You can also ask for custom output columns in the prompt:

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