Keyword-Based Buyer Detection: Find In-Market Buyers by What They Are Talking About

Keyword-based buyer detection finds companies and individuals who are actively discussing topics your product solves in public conversations — before they have formally started a vendor evaluation, before they have requested demos, and before competitors have had the chance to reach them. Letterdrop automates this at scale, running hundreds of keyword-matched searches daily and using AI to surface only the conversations that represent genuine buying intent.

How Keyword-Based Buyer Detection Works

You define the keywords, phrases, and topics that indicate buying intent for your solution. These should map closely to what your ICP says when they are in-market: problem descriptions, category terms, outcome language, frustration phrases, and questions they ask before they know what vendors exist. Letterdrop searches across the public web daily for conversations matching these definitions and uses AI to assess intent quality — distinguishing genuine buying conversations from general discussion, negative sentiment, or off-topic mentions.

Building an Effective Keyword Signal Library

The quality of your keyword-based detection depends on how well your signal definitions match your ICP's actual language. Generic category terms often produce too much noise. The most effective keyword libraries include specific pain point phrases your ICP uses (not just your solution category), comparison language (like "alternatives to" or "vs"), role-specific terminology, and the types of questions buyers ask at the start of their research. Letterdrop works with customers to refine these definitions over time.

From Keyword Match to Contact-Level Lead

Letterdrop does not just flag conversations — it identifies the specific individual who posted or commented and surfaces them as a contact-level lead with their name, title, company, the conversation context, and a suggested outreach message. Your rep knows exactly who to contact, what they said, and what to say back. The research is done. The first message is already drafted.

The Difference Between Keyword Monitoring and Social Listening

Keyword-based buyer detection is one component of Letterdrop's broader social listening capability. Social listening also includes intent assessment (not just keyword matching), segmentation by buyer stage, and integration with Letterdrop's other signal types. The result is leads that are qualified by intent, not just by keyword presence.

Combining Keyword Signals With Other Letterdrop Signals

Keyword-based buyer detection works best alongside Letterdrop's competitor monitoring, champion job change, and closed/lost revival signals. When a buyer shows up in a keyword search AND is at a company evaluating your competitor, they are showing very strong intent and should be prioritized immediately. Letterdrop surfaces these high-confidence opportunities automatically.

Frequently Asked Questions

Where does Letterdrop search for keyword-matching conversations? Letterdrop searches across the public web for conversations matching your defined keywords, including forums, communities, review sites, and other publicly accessible sources where your ICP is active.

How does AI assess whether a keyword match represents genuine buying intent? Letterdrop's AI evaluates the context around a keyword match — the question being asked, the problem being described, the level of expressed urgency — to determine whether the conversation indicates someone actively looking for a solution vs. casual discussion.

How many keywords can I define? You can define as many keywords and topics as are relevant to your solution. Letterdrop handles the search volume; you focus on defining the signal criteria that matter for your ICP.

Define Your Keyword Signals and Find In-Market Buyers — Book a Demo