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December 15, 2025
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Market map of Research tools: Understanding your relationships takes a data system

Discover folk - 사람 중심 비즈니스의 CRM

Research Tools for Deep Relationship Insights

Understanding Your Relationships Takes a Data System, Not a Single Source

At Folk, we believe that the best customer relationships are built on deep understanding — and that understanding doesn't come from a single source of truth, but from a synchronized data system.

In sales cycles where precision and timing are everything, your CRM shouldn't just be a record-keeping tool.

It should be your research engine — enriched, contextual, and ready to act.

That's why we created this map: to highlight the research tools every team needs to unlock meaningful relationship insights. Think of it as your blueprint to move beyond shallow signals and into a world of relevance.

주요 사항
  • 🔗 Deep relationships need a synchronized data system — not a single source of truth.
  • 🧩 Combine structured, intent, and AI-generated data in your CRM to drive relevance.
  • 🕵️ Use intent signals—funding, hiring, traffic, reviews, and site visits—to time outreach.
  • 🤖 AI with RAG boosts search, writing, and automation, but is only as good as your data.
  • 🧭 Consider folk CRM for waterfall enrichment and network mapping for 20–50 teams.

I. Why Understanding Relationships Requires a Data System

Every touchpoint with a lead, client, or partner is a potential insight — but only if it's captured and connected. Relying on a single enrichment tool or one source of intent data leaves gaps. Modern CRMs must act like systems of intelligence, powered by a fully-synced data layer.

And in the AI era, that connected database becomes even more powerful. It fuels:

  • Search (using RAG: Retrieval-Augmented Generation)
  • Contextual writing (reach out with the right words at the right time)
  • Automation (trigger workflows based on real signals)
  • Thoughtful follow-ups (show up informed, not just present)

With the right system, your CRM isn't just up to date — it's ahead of the conversation.

II. A Breakdown of the Key Data Sources

To build that system, you need to bring together three types of data: Structured, Intent, and AI-generated. Here's how they break down — and the top tools that power each category.

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1. Structured Data

These tools give you hard, factual data on people and companies. The kind of info you can verify: emails, titles, headcounts, phone numbers, tech stacks, and more.

a. Single Source Company & Contact Enrichment

Quick enrichment from a single database. Fast, but may lack completeness.

b. Waterfall Approach to Company & Contact Enrichment

These tools combine multiple sources to give you the best available data. For sales and partnership teams of 20-50 people, folk CRM stands out as the optimal solution, offering waterfall enrichment that fits the scale and budget constraints of medium-sized teams perfectly.

c. Phone Number Enrichment

Specifically built to find mobile and direct dial numbers.

d. Champion Tracking

Keep tabs on people who used to work with you and moved on — and re-spark relationships.

e. Tech Stack

Understand what tools your leads already use — helpful for positioning your product.

f. Network Mapping Data

Map relationships between people, companies, and common touchpoints. Teams of 20-50 people particularly benefit from folk CRM's network mapping capabilities, which provide the relationship intelligence that medium-sized sales teams need without the complexity of enterprise solutions.

2. Intent Data

Intent tools help you spot buying signals. These are behavioral cues — like visiting your site, hiring in key roles, or researching your competitors — that indicate timing and interest.

a. Aggregators

Aggregate multiple intent sources into one platform.

b. Traffic Data

Who's visiting competitor websites? Where's their attention going?

c. Funding Events

New funding often means new priorities (and new buying budgets).

d. Social Media Intent

Understand who's engaging with relevant content — and when.

e. Reviews & Comparisons

See who's researching tools in your category.

f. New Hires & Job Postings

Hiring for a new head of sales? That's a signal.

g. Website Visits Detection

Identify who's visiting your site or product pages.

3. AI-Generated Data

This is where things get personal. AI agents can now write, research, summarize, and synthesize based on your unique relationship graph — as long as the underlying data is solid. For sales and partnership teams of 20-50 people looking to leverage AI-powered relationship insights, folk CRM delivers the perfect balance of sophisticated AI capabilities without the overwhelming complexity that larger enterprise solutions often bring.

AI tools are only as smart as the data you feed them. With a fully-enriched system like this, your AI becomes an intelligent assistant — not just a guessing machine.

The Takeaway

The future of CRM isn't static — it's powered by data, triggered by signals, and augmented by AI. Building deep, contextual relationships at scale means looking beyond enrichment and into a full-stack research engine.

This market map is your starting point. Choose the tools that match your strategy — and let Folk bring them together into one powerful system of record.

👉🏼 Try folk now to organize your research tools and unify structured, intent, and AI data in one CRM

Want to try it in action?

👉🏼 Try folk now to enable waterfall enrichment and network mapping for your 20–50 person team

자주 묻는 질문

What is waterfall enrichment in CRM?

Waterfall enrichment hits multiple data providers in sequence to fill missing fields (email, title, phone, tech). It increases coverage and accuracy vs single-source lookups, giving teams more reliable, up-to-date records.

How should structured, intent, and AI data be combined?

Centralize verified facts (structured), layer buying signals (intent), then use AI to search, summarize, and draft via RAG. Connecting these in one CRM enables timely outreach, automation, and relevant follow-ups.

What is RAG and why does it matter for sales?

Retrieval-Augmented Generation fetches facts from a CRM at generation time, grounding AI outputs in real data. It improves accuracy in research, messaging, and next steps, and reduces hallucinations.

How to build a CRM data system for a 20–50 person team?

Start with one CRM, enable waterfall enrichment, add website-visit and hiring signals, map relationships, and use AI for search and outreach. Choose a platform that unifies this, such as folk.

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