Clay vs Apollo: a data workbench or an all-in-one sales platform?

Clay or Apollo: who should pick which?

Clay and Apollo land on the same shortlists, but they solve different problems. Apollo is a sales platform: a searchable B2B contact database with email sequences, a dialer and a task queue on top. Clay is a data workbench: a spreadsheet-like table where each column can call a data provider, run an AI research step or apply your own logic, so you can build lists that no single database would give you.

The rest of this page goes past the feature list: where the data comes from, the same target list built in each tool, who ends up owning the work, how to count the real monthly cost, and a short test you can run on your own accounts before you sign anything.

• Pick Apollo if you are a founder or a small sales team that wants to search for contacts, write a sequence and start sending this week, without stitching tools together.
• Pick Clay if you have a growth engineer or RevOps person and a targeting idea that needs several sources combined, such as agencies that list a given tool on their site and posted a developer job this month.
• Use both if you like Apollo as a contact source but want to enrich, research and score records before they go out.
• Skip both if you would rather not run a database or a data workbench at all and want qualified leads delivered with a reason to reach out. We cover that option at the end, and our lists of Clay alternatives and Apollo alternatives go wider.

How do Clay and Apollo compare side by side?

Where does each tool get its contact data?

This is the difference that matters most. Apollo maintains its own database, so a search returns records Apollo already holds: names, titles, company details, emails and, depending on your plan, phone numbers. You get speed and a single bill. The trade-off is sameness: anyone with an Apollo seat can build a similar list, so the most obvious prospects in your category hear from several vendors a week. Apollo's database search shows what the filters cover.

Apollo has also moved into Clay's territory. Its waterfall enrichment can ask third-party providers for an email or phone number when its own record comes up empty, and its buying intent data flags companies researching topics you choose. So the old shorthand, one database against many providers, is blurrier than it was. The real difference now is control: Apollo runs those steps inside its product, while Clay lets you pick each provider, its order and what happens when it fails.

Clay does not try to be the database. It sends each row to a series of providers and stops when one returns an answer, which Clay calls waterfall enrichment. Providers have different gaps, so trying several in order tends to find contacts that any single one misses. Clay adds Claygent, an AI agent that visits a website or searches the web to answer a question you write, such as 'Does this company sell to hospitals?' or 'Which CRM do they mention on their careers page?'. It also runs Clay signals, such as a past champion changing jobs, which add rows to a table when something happens.

So the practical question is how specific your targeting is. If 'VP Sales at US software companies with 50 to 200 employees' describes your buyer, Apollo's filters get you there in minutes. If your best buyers are defined by something they did or published, you are in Clay territory, or you need a signal-based approach that starts from those events. Our explainer on what intent data is covers the difference between topic intent, like Apollo's, and first-hand events such as a post or a job listing.

One target list, built twice: a worked example

Here is an example we built to show the difference; the targeting is ours, not a customer's. You sell HubSpot implementation and sales operations work. Your best buyers are US B2B software companies with 20 to 150 employees that already use HubSpot and have just posted a job for their first RevOps or sales operations hire, one of the clearer hiring signals in your market. The person to email is the VP Sales, or the founder when there is no sales leader yet.

Building it in Apollo

You open people search and set the firmographic filters: United States, software, 20 to 150 employees, titles such as VP Sales, Head of Sales or Founder. Then you add the technology and hiring conditions. Apollo's company filters cover a lot of technographic and hiring data, so check on your own plan how precisely you can express 'uses HubSpot' and 'posted a RevOps job in the last 30 days'. Save the search, review a sample by hand, then add the contacts to a sequence.

Time to a first list: often under an hour. What you get: a list that matches on paper, with emails for many of the records. What you do not get: proof, row by row, of why each company is on it. If the hiring condition is coarse, part of the list will be companies that hired for RevOps a year ago and no longer need you.

Building it in Clay

Each step below is a column in one table. Rows move to the right only when they pass.

• Source: a broad company list, imported as a CSV or pulled from a company search. Breadth is fine at this stage; the next columns do the filtering.
• Hiring check: a Claygent column asks 'Does this company's careers page list an open RevOps, revenue operations or sales operations role? Return the job title and the URL.' Rows without a URL drop out.
• Stack check: a second AI column asks whether the website or the job post mentions HubSpot, and quotes the sentence it found.
• Decision-maker: a people lookup for the VP Sales, with the founder as the fallback.
• Email: a waterfall that tries several providers in order, then a verification step, so only deliverable addresses move on.
• Score and route: a formula column keeps rows that passed both checks and sends them to your sequencer or CRM, with the job URL and the quote attached.

What the example shows

In Clay, the first build takes a day or two; later runs take minutes. You get fewer rows, each with a quoted reason your first email can reference: 'Saw you are hiring your first RevOps lead; the first 90 days of that role are usually spent cleaning up HubSpot.' The cost is that every column that calls a provider or an AI step uses your allowance on every row it touches, including rows that fail later.

Apollo wins on speed and breadth when its filters express your idea well enough. Clay wins when the reason to buy is something a filter cannot see, and when you want that reason written next to each lead. If you want the second result without building it or paying per row, that is the problem AI lead generation from buying signals is meant to solve, and our guide on how to find B2B leads compares the manual routes.

Can you run outreach from Clay or Apollo?

Apollo, yes. You build a sequence of emails, call steps and manual tasks, connect your mailboxes, and Apollo sends and tracks. Its dialer lets reps call from the same screen. For a small team, keeping list, sequence and calls in one place removes a lot of copy-pasting between tools.

Clay's core job is building the list, but it now documents its own email sequencer, so simple campaigns can go out without leaving the table. Many Clay users still push enriched rows into a dedicated cold email tool such as Instantly, Smartlead or lemlist, or into their CRM, because those tools were built around inbox rotation, warmup and a shared reply inbox. Before you rely on any sequencer for volume, check how it handles those three things. If you are choosing a dedicated one, our Instantly vs Smartlead comparison covers the two most common picks.

Whichever path you take, the sending setup decides whether your emails land. Send from domains separate from your main one, warm up new inboxes, cap daily volume per inbox and verify every address before it enters a sequence. Our cold email deliverability guide walks through the setup in order.

Who will own the tool, and what changes for each role?

Apollo has the gentler start. The interface is search, lists, sequences and a task queue, which most salespeople understand in an afternoon. Clay rewards people who think in workflows: a good table can replace hours of manual research, but someone has to design it, watch how much each row uses and fix it when a provider's output changes. Teams that do well with Clay usually have a named owner, which is also why many agencies sell Clay builds as a service.

The founder doing outbound alone

Apollo fits the time you have. You can build a list on Monday morning and have a sequence running by lunch. Clay is worth it only if you enjoy building, or if your niche is so narrow that no filter finds it. A table nobody maintains goes stale within weeks, as job posts close and providers change their output.

The SDR or account executive

In Apollo, reps live in the task queue: emails to review, calls to make, follow-ups due. In a Clay setup, reps rarely open Clay at all. They receive researched leads in the sequencer or CRM, with notes they can use on a call. That is a better handoff, but it depends on someone upstream keeping the table healthy.

The RevOps lead or growth engineer

Clay is their tool. They design tables, choose providers, set up syncs to the CRM and keep usage in check. In an Apollo shop, their work shifts to list hygiene, deduplication against the CRM, and reporting on which sequences produce meetings.

The agency running outbound for clients

Agencies often use Clay to build a distinct list per client, with research columns that justify the angle, and send from a dedicated sequencer with separate domains per client. Apollo works for agencies too, but every client's list comes from the same database their competitors can search, so the angle has to do more of the work.

How are Clay and Apollo priced, and what will you really pay?

The two pricing models reward different habits, so compare them on your expected monthly volume rather than on the entry price.

• Clay sells usage-based plans. Its current model meters two things: data credits for data from providers, and actions for the work your tables run. The cost of a row depends on how many steps it runs and which providers it calls. Clay has reworked its plans more than once, so read the Clay pricing page and its pricing announcement before you model anything.
• Apollo has a free plan and paid plans billed per user. Each plan includes credits for actions such as exporting contacts or revealing phone numbers. Current plans are on Apollo's pricing page.
• The line item people forget: with Clay you may also pay for a dedicated sequencer and sending inboxes; with Apollo you still need separate sending domains and inboxes if you follow deliverability best practice.

Worked example: counting a month of usage

Assumptions, not Clay's or Apollo's figures: you want 1,000 new contacts a month that are ready to email, using the six-column table from the example above. Half the companies pass the hiring check, and two in three of those pass the stack check, so you start from about 3,000 companies.

• Company data and the hiring check run on all 3,000 rows: 6,000 step runs.
• The stack check runs on the 1,500 rows that pass hiring: 1,500 runs.
• The people lookup, the email waterfall and verification run on the 1,000 rows that pass both: 3,000 runs, more when the waterfall has to try several providers.
• Total: about 10,500 step runs a month before a single email goes out. In Apollo, the same 1,000 contacts mean about 1,000 exports or reveals against your seats' credits, but no evidence of the hiring signal unless a filter supplies it.

How do you test Clay and Apollo before you commit?

Feature lists will not settle this; your own accounts will. Run a short test on both tools with the same inputs, and score the outputs the same way.

1. 1

   Pick 100 accounts you already know

   Take 50 recent customers or closed deals and 50 accounts you lost or never reached. You know what the right contact looks like at each one, so you can judge the results instead of trusting them.

2. 2

   Run the same brief in both

   Ask each tool for the decision-maker and a business email at all 100 accounts. In Clay, use a simple waterfall and one research column. In Apollo, use search and enrichment as they come on your plan.

3. 3

   Score coverage and accuracy

   For each tool, count three numbers: accounts where it found the right person, accounts with an email, and emails a separate verifier marks deliverable. A wrong person counts as a miss, not a hit.

4. 4

   Measure the hours

   Time how long it took to reach a usable list, including setup. Clay's first build is slow and later runs are fast, so record both figures.

5. 5

   Compute the cost per usable contact

   Divide what the test used (credits, actions, or your share of a seat) by the number of correct, deliverable contacts. That figure, not the plan price, is what you compare.

6. 6

   Check the handoff

   Push ten records into the place you send from and confirm that fields, research notes and unsubscribes land where they should.

Is there a third option besides Clay and Apollo?

Both tools assume you start from a list and work out later who might care. Startories starts from the moment a company shows a reason to buy: a Reddit post asking for a tool, a complaint about a competitor, a Product Hunt launch, a hiring or funding announcement. It matches the signal to a real company, scores it against your ideal customer profile with the reasons written out, finds and verifies the decision-maker, writes an email about that event and sends it from warmed-up inboxes on separate domains. Replies come back classified, with a suggested answer.

Data, verification, sending and reply handling are in the plan, so there is no database seat or credits plan on top. It is not a replacement for everything: if you want to design your own enrichment logic, Clay is more flexible, and if your team lives on the phone, Apollo's dialer does something Startories does not. See how signal-based outbound works in practice, or how it ranks among the best AI SDR tools. Plans start at $99 a month, and your first Starter project starts with a 3-day full-access trial for $1: see pricing.

Frequently asked questions

Sources

• Clay: Pricing
• Clay: Introducing Clay's new pricing
• Clay: Waterfall enrichment
• Clay University: Enriching with Claygent
• Clay: Signals
• Clay University: Email sequencer
• Apollo: Pricing
• Apollo: B2B contact database
• Apollo: Dialer
• Apollo Knowledge Base: Waterfall enrichment overview
• Apollo Knowledge Base: Buying intent overview