Let me save you some time. All website finder tools work the same way: they either query a database or search Google if their database doesn't have the company yet.
The real difference is how Google results are analyzed and scored.
At Datablist, we offer two methods:
- A cheap and deterministic one without intelligence
- And an AI Agent for complex name to domain searches
When you compare Datablist and CU Finder on pricing, usefulness, and AI capabilities., the winner becomes obvious pretty quickly.
📌 Summary For Those In a Rush
This article compares Datablist and CU Finder for finding company websites from company names, focusing on the metrics that actually matter for your lead list building workflow.
- Pricing: Datablist offers significantly lower cost per website lookup ($0.005 vs. $0.049) and a lower entry point ($25/month vs. $49/month).
- Usefulness: Datablist has 60+ tools for data enrichment compared to CU Finder's 15 enrichments.
- AI Capabilities: Datablist includes 3 AI agents and 2 AI editing assistants. CU Finder has no AI features.
The Verdict: Datablist wins by a landslide in all three categories; not exaggerated
Datablist vs. CU Finder: The Quick Verdict
Before we dive into the details, here's how both tools score across our three comparison factors.
| Factor | Weight | Datablist | CU Finder |
|---|---|---|---|
| Pricing | 5 points | 🟢🟢🟢🟢🟢 (5/5) | 🟠🟠🟠 (3/5) |
| Usefulness | 3 points | 🟢🟢🟢 (3/3) | 🟠🟠 (2/3) |
| AI Capabilities | 2 points | 🟢🟢 (2/2) | 🔴 (0/2) |
| Total Score | / | 10/10 | 5/10 |
Datablist scores twice as high as CU Finder. But don't just take the table at face value. Let me break down exactly how we arrived at these scores.
How We Compared These Website Finder Tools
Comparing website finder tools without a framework is like comparing apples to oranges. That's why we created a scoring system that lets you identify what actually matters when finding company websites from company names.
| Factor | What We Look For | Weight | Why It Matters |
|---|---|---|---|
| Pricing | Low entry subscription, low price per website | 5 points | Since accuracy is nearly identical across website finder tools, pricing becomes the biggest differentiator |
| Usefulness | Data enrichment features, lead list building tools, CRM enrichment capabilities | 3 points | Finding websites from company names is just step one. What you can do with that data determines your true ROI |
| AI Capabilities | AI agents, AI assistants, contextual search | 2 points | AI features help with complex company names and automate workflows others can't touch |
Why pricing gets the most weight: All website finder tools have almost the same accuracy (within 1-3% of each other). They're all pulling from similar data sources and using comparable matching algorithms. When the output is basically the same, the tool that costs less wins.
Pricing: Datablist vs. CU Finder
Let's start with the factor that carries the most weight: Pricing. Here's how both tools stack up.
Datablist Pricing
Entry Point
Datablist starts at $25/month with 5,000 free add-on credits[3] included. This gives you access to the website finder plus all 60+ data enrichment tools on the platform.
Cost Per Website
Using the basic database search, each website lookup costs 1 credit ($0.005 per website). If you need Google verification for harder-to-find companies, it costs 2.5 credits ($0.0125 per website).
For complex use cases, please use our AI Agent to find websites from company names. This method is designed for companies with little online presence or ambiguous names, and when you want to use extra context to improve scoring. Pricing is usage based. On average, expect around 15 credits per company name.
What This Means in Practice
With the Starter plan at $25/month, you can find up to 5,000 company websites without spending a single extra dollar beyond your subscription.
CU Finder Pricing
Entry Point
CU Finder's Growth plan starts at $49/month for 1,000 credits[1]. That's almost double Datablist's entry price for significantly fewer lookups.
Cost Per Website
Each website lookup costs 1 credit ($0.049 per website). That's roughly 10x more expensive than Datablist's basic search.
What This Means in Practice
With CU Finder's Growth plan, you can find 1,000 company websites per month. To match Datablist's 5,000 lookups, you'd need to upgrade to a higher tier ($299/month)
The Verdict on Pricing
Datablist is nearly 10x more affordable per website lookup and offers a lower entry point with more included credits, making it especially attractive for individual users and small teams.
| Metric | Datablist | CU Finder |
|---|---|---|
| Starting Price | $25/month | $49/month |
| Included Lookups | 5,000 | 1,000 |
| Cost Per Website | $0.005 | $0.049 |
Datablist: 5/5
CU Finder: 3/5
Usefulness: Datablist vs. CU Finder
Finding company websites is rarely the end goal. Most people need websites to build lead lists, enrich their CRM, or start outbound campaigns, so the question we base this section on is: what can you do after you find the website?
Datablist's Data Enrichment Ecosystem
Datablist offers 60+ tools for lead list building and data enrichment. Here's what you get beyond the website finder:
Lead Generation Tools
- Waterfall Email Finder (aggregates multiple data vendors)
- Waterfall Phone Number Finder
- Waterfall People Search
- LinkedIn Sales Navigator Scraper
Data Enrichment Tools
- Technology Finder (find companies using specific tech stacks)
- Company Information Enrichment
- Job Posting Scraper (scrapes 19 job boards simultaneously)
Data Cleaning Tools
Automation Features
- “If that, then this” automations / conditional automations
- Scheduled workflows
- CSV/Excel import and export
- REST API access (upload/download/edit)
- Custom HTTP calls from your sheets (to connect to other tools)
CU Finder's Data Enrichment Features
CU Finder offers 15 data enrichments[2] focused primarily on contact and company information:
Contact Data
- Email Finder
- Phone Number Finder
- Contact Search
Company Data
- Company Domain Finder
- Company Information Lookup
- Account Search
Integrations
- Multiple API integrations available
- CRM connections
The Verdict on Usefulness
Datablist offers 4x more tools and covers the entire lead list building workflow from finding websites to cleaning data to finding contacts. CU Finder focuses primarily on accounts, contact lookup, and a few simple enrichments
| Capability | Datablist | CU Finder |
|---|---|---|
| Total Enrichment Tools | 60+ | 15 |
| Email Finding | ✅ Waterfall (multiple vendors) | ✅ Single source |
| Phone Finding | ✅ Waterfall (mobile only) | ✅ Available |
| Technology Finder | ✅ | ❌ |
| Data Cleaning | ✅ Comprehensive | ❌ |
| Workflow Automation | ✅ | ❌ |
| Web Scraping | ✅ AI-powered | ❌ |
Datablist: 3/3
CU Finder: 2/3
AI Capabilities: Datablist vs. CU Finder
Here's where the comparison gets interesting. AI capabilities determine whether you:
- Can handle complex company names
- Automate workflows that would otherwise require manual work.
- Keep up with the rest of your competitors who use AI daily to work more efficiently
Datablist's AI Features
Datablist includes several AI-powered features that set it apart:
AI Agents (2 Available)
- AI Research Agent: Performs contextual searches for complex company names. When "United" or "Pioneer" could match hundreds of companies, the AI uses additional context (location, industry, description) to find the right one. You can also use it for other use cases where you need to scale AI search across thousands of records
- AI Site Scraper: Extracts structured data from any website automatically.
Author’s Tip: Check These Guides Out to Learn More About AI Agents
AI Editing Assistants (2 Available)
- AI Processor: Runs ChatGPT-style operations on your data at scale.
- AI Editing Assistant: Manipulate and clean data with a prompt.
Why AI Matters for Website Finding
Standard website finders struggle with:
- Complex legal names (e.g., "IC. INTERNATIONAL FUND MANAGER S.À R.L")
- Common company names with multiple matches
- Companies with different trading names vs. registered names
Datablist's AI Research Agent solves this by using contextual information you provide to identify the correct company.
CU Finder's AI Features
CU Finder currently offers no AI capabilities. If you need AI-powered features for complex lookups or data processing, you'd need to subscribe to an additional tool.
The Verdict on AI Capabilities
Datablist offers 5 AI-powered features. CU Finder offers none. If everyone else is using AI and you aren't, you're at a disadvantage.
| Feature | Datablist | CU Finder |
|---|---|---|
| AI Agents | 3 | 0 |
| AI Assistants | 2 | 0 |
| Contextual Search | ✅ | ❌ |
| AI Data Processing | ✅ | ❌ |
Datablist: 2/2
CU Finder: 0/2
The Final Verdict: Datablist vs. CU Finder
TL;DR: Datablist wins, and it was not even close.
As I mentioned at the beginning, all website finder tools work the same way:
- They either do a database query
- Or search on Google if their database doesn't have the relevant data yet
This means accuracy is almost identical across all platforms. So the things you should look for are:
- Pricing
- Usefulness
- AI capabilities
And if we look at these metrics, Datablist wins by a landslide. (Ask ChatGPT, and it will tell you the same.) Let me prove it again, by doing a quick recap:
On pricing: Datablist costs $0.005 per website lookup vs. CU Finder's $0.049. That's nearly 10x more affordable. Datablist also has a lower entry point ($25 vs. $49) with 5x more included lookups (5,000 vs. 1,000).
On usefulness: Datablist offers 60+ data enrichment tools covering the entire lead generation workflow. CU Finder offers 15 enrichments focused mainly on accounts & contacts lookup, with little enrichment and automation capabilities.
On AI capabilities: Datablist has 3 AI agents and 2 AI assistants. CU Finder has none.
Click here to try Datablist for Free 👈🏽
How to find websites using company names with Datablist
Now that the feature comparison is done, here is how to find company websites.
Method 1: The "Find company domains from company names" enrichment
This enrichment searches our internal database and queries Google if it cannot find a result. It scores results using strict rules like domain patterns and company name matching.
This method is fast. Cheap. And works great for most companies with a clear online presence.
👉 Click here to learn more about our "Find company domains from company names" enrichment.
Method 2: AI agent for complex searches
The method 1 with deterministic rules struggles with:
- False positives
- Generic company names
- Legal entities vs. brand names
When things get tricky, we advise you to switch to our AI Research Agent. This agent uses reasoning. It understands context.
You can give it extra information like:
- Location
- Industry
- Description
This is crucial when a company:
- Has little online presence
- Uses a different trading name
- Is searched using a legal entity name
The AI agent evaluates Google results like a human would.
- It removes bad matches.
- It visits results to compare them with the context you provided. This reduces false positives.
That is why, for complex name to website searches, Datablist is the clear winner.
👉 Click here to learn more about the AI agent for name to domain search.
Frequently Asked Questions (FAQ) About Datablist vs. CU Finder
Is Datablist or CU Finder Better for Finding Company Websites From Company Names?
Datablist is the better choice for finding company websites from company names. It scores 10/10 in our comparison vs. CU Finder's 5/10 across pricing, usefulness, and AI capabilities. Specifically, Datablist offers 10x lower cost per lookup ($0.005 vs. $0.049), 4x more data enrichment tools (60+ vs. 15), and many AI features, while CU Finder offers 0 AI tools.
How Much Does It Cost to Find 1,000 Websites With Datablist vs. CU Finder?
When broken down into price per website, finding 1,000 company websites with Datablist costs approximately $5 using the basic database search (1 credit per lookup at $0.005 per credit). With CU Finder, the same 1,000 lookups would cost approximately $49 (the minimum monthly plan). That's nearly 10x more expensive for the same number of results.
Which Tool Has Better AI Capabilities for Finding Websites: Datablist or CU Finder?
Datablist has significantly better AI capabilities with 2 AI agents and 2 AI editing tools + all major LLMs built into the platform. These include an AI Research Agent for handling complex company names, an AI Site Scraper, and AI data processing tools. CU Finder currently offers no AI capabilities, so if you need AI-powered features for complex lookups or data processing, you'd need to subscribe to an additional tool.
What Separates Datablist and CU Finder When It Comes to Data Enrichment?
The biggest difference is scope. Datablist offers 60+ data enrichment tools covering the entire lead list building workflow: website finding, email finding (waterfall across multiple vendors), phone finding, technology lookup, data cleaning, deduplication, and AI-powered scraping. CU Finder offers 15 enrichments focused primarily on contact and company information lookup. If you need a complete data enrichment ecosystem, Datablist is the better choice.
Are There Free Tools to Find Company Websites From Company Names?
While most website finder tools require a paid subscription, Datablist is adding a free tier that lets you try the website finder tool before committing. Beyond that, you could manually search Google for each company, but this isn't scalable for lead list building at any meaningful volume. For professional data enrichment work, a paid tool like Datablist (starting at $25/month for 5,000 lookups) is the most cost-effective option.
How Do Website Finder Tools Work?
Website finder tools like Datablist and CU Finder use two primary methods to find company websites from company names:
-
Database Matching: The tool queries a pre-verified database of company names and their associated domains. This is fast and cost-effective.
-
Google Search: If the company isn't in the database, the tool performs a Google search and uses probability matching to identify the correct website from the results.
Most tools use a combination of both methods. The accuracy is nearly identical across all major website finder tools (within 1-3%) because they're all using similar data sources and matching algorithms. This is why pricing and additional features are the real differentiators.