Every Clay Feature Ranked: The Definitive Tier List for B2B Sales Teams

Clay has more features than any other GTM platform on the market. The problem is that nobody tells you which ones are worth learning first and which ones you can ignore.

We have run Clay across 70+ client accounts and built more enrichment workflows than any other agency on the platform. Some features we use daily. Others we have never touched after the first test. The gap between the best and worst features inside Clay is massive.

We sat down and ranked every single Clay feature into S, A, B, C, and D tiers based on how much value they deliver in real campaigns. This is not theory. This is what we see working across live accounts spending real money on outbound.

Here is the full breakdown.

1. S Tier: The Features That Make Clay Irreplaceable

These are the features that justify the entire Clay subscription. If you are not using them, you are paying for a spreadsheet with extra steps.

Using AI Models in a Spreadsheet

This is the single most powerful thing about Clay. You can run GPT, Claude, Gemini, and Perplexity directly inside your enrichment table. No code. No API wrangling. Just select a model, write a prompt, and run it across thousands of rows.

The practical value here is hard to overstate. You can classify companies by ICP fit, summarize websites, extract specific data points from messy inputs, and generate custom variables. All inside the same table where your lead data lives.

Every other spreadsheet tool requires you to export data, run it through a separate AI workflow, and import it back. Clay does it in one column.

Claygent

Claygent is Clay's AI agent for web research at scale. Give it a task like "find the pricing page for this company" or "pull the CEO name from this website" and it browses the web, reads pages, and returns structured data.

We use Claygent for tasks that no static database can handle. Finding whether a company has a specific product feature. Pulling data from 10-K reports. Checking if a prospect recently spoke at a conference. These are research tasks that would take a human 5 minutes per company. Claygent does them in seconds across 10,000 rows.

The key is pairing it with the right model. Use a cheap model like GPT-4o-mini for the web browsing step, then pass the raw output to a smarter model for analysis. This keeps costs low and quality high.

TAM Sourcing

Clay is not just an enrichment tool. It is one of the best list building platforms available. You can source companies and contacts at scale using dozens of built-in data providers, filters, and integrations.

The sourcing capabilities are what separate Clay from tools that only enrich existing lists. You can start from zero. No CSV required. Pull companies by industry, headcount, technology, funding stage, location, and dozens of other criteria. Then find the right contacts at those companies without leaving the platform.

For teams that need to build targeted prospect lists from scratch, this alone justifies the subscription.

If you want to find verified contact details for prospects you have already identified, try our free tool:

People Finder

AI Formulas

This feature is free. Zero credits. And it is one of the most underused tools in Clay.

AI formulas let you write complex conditional logic without knowing how to code. Tell the AI what you want in plain English and it generates the formula. Want to extract the domain from a URL, normalize company names, or route leads based on multiple conditions? The formula writer handles it.

The reason this is S tier is not just because it is free. It is because it replaces work that would otherwise cost credits or require manual effort. Every formula you write is one less enrichment you need to pay for.

2. A Tier: Extremely Valuable, With Some Caveats

A tier features are powerful and we use them regularly. They are not quite S tier because they have a learning curve, a cost consideration, or a specific use case that does not apply to everyone.

GTM Workflow Orchestration

This is Clay at its best as an operating system. You can combine enrichment, qualification, scoring, email finding, and campaign upload into a single automated workflow. Data flows from one step to the next with conditional logic at every junction.

The value compounds the more steps you chain together. A workflow that sources companies, enriches them, scores ICP fit, finds contacts, validates emails, and pushes qualified leads to Instantly replaces what used to take 5 separate tools and 3 hours of manual work.

The caveat is complexity. Building these workflows requires understanding how Clay's table logic works. New users should master individual features before attempting full orchestration.

HTTP API Integration

For technical users, this is where Clay becomes limitless. The HTTP API lets you connect any external tool, any database, any service that has an API endpoint. If a tool exists and has an API, you can use it inside Clay.

We use this for pulling data from Rapid API marketplaces, connecting niche data providers, and integrating tools that do not have native Clay integrations. The cost savings are enormous because you bypass Clay credits entirely and pay the external provider directly.

The reason it is A tier and not S tier is accessibility. Non-technical users will struggle with API authentication, headers, and JSON parsing. If you can handle it, this feature alone saves thousands in credits per month.

AI-Powered Lead Scoring and Qualification

Using GPT or Claude to score and qualify leads inside Clay is transformative. Instead of rigid point-based scoring, you get contextual evaluation that considers multiple factors simultaneously.

Give the AI your ICP criteria and it reads through company descriptions, job titles, tech stacks, and growth signals to assign a tier. The output is more nuanced than any formula-based scoring system because the model understands context.

We use this on every client campaign to separate high-priority accounts from the rest. The top-tier prospects get more personalization investment. The lower tiers get simpler sequences. This single workflow step improves reply rates across the board.

Email and Phone Number Finding (Waterfall Enrichment)

Clay's waterfall approach to finding contact information is the industry standard. Run multiple providers in sequence. If the first one misses, try the next. Keep going until you find a verified email or phone number.

The waterfall setup inside Clay is cleaner than doing it manually across separate tools. Conditional logic ensures each provider only runs when the previous one came up empty. This saves credits and reduces duplicate lookups.

The caveat is cost. If you are using Clay-managed providers, the credits add up fast. Connect your own API keys from Prospeo, FullEnrich, or Wiza to bring the per-contact cost down dramatically.

You can find verified email addresses for any prospect using the same waterfall logic we use at ColdIQ:

Email Finder

3. B Tier: Solid Features That Serve Specific Purposes

B tier features are useful. We would not want to lose them. But they are not the reason anyone buys Clay.

Credit-Based Pricing

Clay's outcome-based pricing model is smart in concept. You pay per enrichment result, not per seat or per month. This aligns the cost with the value you receive.

The downside is that small teams with limited budgets feel the squeeze quickly. Credits disappear faster than expected, especially if you do not connect your own API keys and set conditional formulas. The pricing model rewards power users who optimize their workflows. It punishes beginners who click "run all" without understanding the cost.

CSV Import and Export to Campaigns

Simple but essential. You can import any CSV into Clay, enrich it, and export the results into your sending platform. This is the basic workflow for teams that do not use Clay's native integrations with Instantly or lemlist.

It works. It is not exciting. It is table stakes for any data tool.

Filtered Views

Filtered views let you create different perspectives on the same dataset. Filter by ICP tier, email status, enrichment completion, or any custom variable. Then run enrichments only on the filtered subset.

We use filtered views constantly for conditional running. Instead of enriching the entire table, filter to the 200 rows that need email finding and run only on those. This prevents wasted credits and gives you cold calling lists, qualified segments, and campaign-ready exports from a single table.

Share as Template

When you build a workflow that works, you can share it as a template for your team or community. This is useful for agencies managing multiple client accounts. Build the workflow once, share it, and replicate across accounts without rebuilding from scratch.

Recipes

Pre-made enrichment templates that handle common use cases like "find email from LinkedIn URL" or "enrich company from domain." They reduce setup time for standard tasks.

Recipes are a good starting point for new users who do not want to build everything from scratch. For experienced users, they are often too generic. You end up customizing them so heavily that you might as well have built from scratch.

4. C Tier: Useful in Theory, Mixed in Practice

C tier features have genuine value but come with significant limitations that keep them out of the higher tiers.

AI Personalization for Emails

This is the feature that gets the most hype and delivers the most inconsistent results. Using AI to write personalized opening lines or email body copy sounds perfect in theory. In practice, the quality varies wildly.

The problem is that AI-generated personalization often sounds like AI-generated personalization. "I noticed your company recently..." followed by a generic observation pulled from a website. Recipients recognize the pattern. When every email in their inbox uses the same AI personalization approach, nobody stands out.

We use AI personalization selectively. For highly specific triggers like funding rounds, new hires, or job postings, the AI does well because the data is concrete. For vague personalization like "I saw your company values innovation," skip it. A well-written static email with a strong offer outperforms a badly personalized one every time.

If you want to check whether your current outreach is landing in the inbox or getting flagged as spam, test it for free:

Spam Checker

Enrich Person and Company Data

Clay's built-in enrichment providers pull data like job title, company size, revenue estimates, industry classification, and social profiles. This data is useful for segmentation and qualification.

The limitation is accuracy. Revenue estimates are notoriously unreliable across all data providers, not just Clay. Employee counts can be months out of date. Industry classifications vary by provider. Use enrichment data for directional guidance, not precise targeting. Cross-reference when the decision matters.

Score Row

Score Row lets you set parameterized scoring rules and assign points based on conditions. If the company has more than 50 employees, add 10 points. If they use Salesforce, add 5 points. If they are in SaaS, add 15 points.

It works for simple scoring. But AI-based scoring (A tier) is more nuanced because it weighs context, not just individual data points. A company with 30 employees that just raised $5M and is hiring aggressively should outscore a stagnant 200-person company. Score Row cannot make that judgment. AI can.

Intent Signals and Job Openings

Hiring signals, funding events, and technology changes are legitimate buying triggers. Clay surfaces these through its data providers, and they can be powerful for timing your outreach.

The problem is oversaturation. Every outbound team now uses the same intent signals. If a company just raised a Series B, they are getting 50 cold emails referencing the raise. The signal is real, but the approach needs to be differentiated. Use intent data to prioritize who to contact, not as your opening line.

You can monitor buying signals in your target market for free with our intent signal tracker:

Intent Signals

Claybooks

Claybooks are Clay's attempt at end-to-end workflow templates. The concept is excellent. Pre-built playbooks that handle entire use cases like "find competitors of my customers" or "build a lookalike list from my best accounts."

The execution needs work. The UI is clunky. The workflows are rigid. Customization is limited. When a Claybook works for your exact use case, it saves hours. When it does not fit perfectly, you spend more time fighting the template than you would have spent building from scratch.

Great idea. Needs a UI overhaul before it earns a higher tier.

5. D Tier: Skip These (For Now)

D tier features are not broken. They are just not worth your time relative to everything else Clay offers.

LinkedIn Likes for Lead Generation

The concept: scrape people who liked a specific LinkedIn post and reach out to them. They showed interest in a topic, so they are warm leads.

This worked well when fewer teams were doing it. Now it is overused. The people who like popular LinkedIn posts are getting contacted by dozens of teams running the same playbook. The signal-to-noise ratio has dropped to the point where the response rates do not justify the effort.

If you want to use LinkedIn engagement data, focus on comments rather than likes. Commenters show higher intent and are less targeted by automated outreach.

Graph View

Graph View visualizes relationships between companies, contacts, and data points in a network diagram. It looks impressive in demos.

In practice, we have never used it to make a decision that the standard table view could not support. The visualization is interesting but not actionable. Your time is better spent learning the features in the tiers above.

6. How to Prioritize Your Clay Learning Path

If you are new to Clay, do not try to learn everything at once. Start with the S tier features and build from there.

Week 1 to 2: Foundations

→ Learn AI formulas (free, zero risk)

→ Practice TAM sourcing with built-in data providers

→ Run your first AI model enrichment on a small batch

Week 3 to 4: Core Workflows

→ Set up Claygent for web research tasks

→ Build your first email waterfall with conditional logic

→ Connect your own API keys for AI and email finding

Month 2: Orchestration

→ Chain enrichment steps into full GTM workflows

→ Experiment with AI lead scoring

→ Learn HTTP API integration if you are technical

Month 3 and Beyond: Optimization

→ Audit credit spend and optimize waterfalls

→ Test filtered views for segmented campaigns

→ Build reusable templates for your team

This progression matches how our most successful clients adopt Clay. They master the high-impact features first and layer in the rest as their workflows mature.

7. The Features We Use Every Day at ColdIQ

Across our 70+ client accounts and our own $7M ARR operation, here are the features we touch daily:

→ AI models in spreadsheet: every single campaign

→ Claygent: every research-heavy enrichment

→ TAM sourcing: every new list build

→ AI formulas: every table setup

→ Waterfall enrichment: every campaign launch

→ Filtered views: every time we run selective enrichments

→ HTTP API: every time we connect a non-native tool

The S tier features are not aspirational. They are operational. If you build your Clay workflows around these seven capabilities, you are covering 90% of what the platform can do for your pipeline.

Conclusion

Clay is the most capable GTM platform available today. But capability without prioritization leads to wasted credits, wasted time, and underwhelming results.

The S tier features, AI models in a spreadsheet, Claygent, TAM sourcing, and AI formulas, are where the overwhelming majority of Clay's value lives. Master those four and you are ahead of 95% of Clay users.

The A tier features unlock scale. The B tier features support your workflows. The C tier features have niche value when applied correctly. The D tier features are not worth your attention right now.

Stop trying to use everything. Start with what works. Build from there.