Coresignal vs Crustdata 2026: Pricing, Freshness & Fit

Coresignal vs Crustdata is a question about meters, not features. Both aggregate public professional data from 15+ sources into one schema, and both sell it to teams building sales, recruiting and investment products. They charge for it in two different ways, and that difference decides your bill.

One sells datasets first and meters the records you collect. The other sells an API first, meters cached reads cheaply, then gates the live and contact endpoints behind higher plans.

This page puts the two side by side on published numbers. It then adds a third option for teams whose agent queries per request.

Key Takeaways#

• Coresignal meters collected records at 10 to 20 credits each, on self-serve plans from $49 to $5,000 a month. Contact enrichment unlocks at the $499 Pro plan.
• Crustdata meters search at 0.03 credits per result and cached enrichment at 1 to 7 credits. Live and contact endpoints sit on gated plans, and named plan prices are not published.
• One full profile with a work email costs 30 to 40 credits on Coresignal, up to 12 on Crustdata enterprise endpoints, and one record (about $0.0005 on a $99 plan) on a record-priced API refreshed every 30 days.
• Bulk ingestion favours Coresignal. Cheap cached discovery favours Crustdata. Per-request agent workloads on a self-serve budget favour a hosted, record-priced model.

Coresignal vs Crustdata at a Glance#

Coresignal is a dataset vendor with credit-based APIs on top. Crustdata is an API-first provider with a cached tier and gated live endpoints. The table below normalises both to published credits and dollars, with a record-priced API in the third column as the reference point for agent workloads.

Two numbers in that table carry most of the weight. Crustdata's 0.03 credits per search result is the cheapest discovery in the category. Coresignal's 20-credit contact enrichment, behind a $499 plan, is the most expensive path to a work email.

What Does Each One Cost for 1,000 Profiles With a Work Email?#

A month of 1,000 profiles with a work email lands on the $499 Pro plan at Coresignal, on an enterprise quote at Crustdata, and inside the $99 Start plan on a record-priced model. The record is the same. The meter is not.

Run the math on Coresignal first. A base record is 10 credits and a contact enrichment is 20, so each profile is 30 credits. One thousand of them is 30,000 credits, which fits Pro at 35,000. Choose the multi-source record instead and it is 40,000 credits, which pushes you to Growth at $1,000.

On Crustdata the cheap path is cached: base profile 1 credit, business email 1 more. Two thousand credits for the batch. The catch is age. A cached record is as fresh as the last crawl, and the live path is 7 credits plus 1 to 5 for contact data, up to 12 per profile, on plans that start with a sales conversation.

On records, a full profile (refreshed every 30 days) with its verified work email is one record. That is 1,000 records for the batch, half a percent of the Start plan's 200,000, with a published refresh cycle and emails that are not gated on any tier.

The mistake most teams make is comparing entry prices. $49 against $95 says nothing. Compare what one month of your real workflow consumes on each meter, and check which plan that volume forces you onto.

Which One Is Fresher?#

Freshness depends on which endpoint you can afford, not on which vendor you pick. Coresignal's API returns the latest record it holds, while its datasets age between scheduled refreshes. Crustdata's live endpoints query at request time, but they sit on gated plans, and its self-serve tier reads a cache.

A public vendor test makes this concrete. The agency 42agency checked one verified job change against twelve data sources two weeks after the move. The cached answers, Crustdata's among them, still returned the old employer. Sources that query live at the moment of the call got it right.

Builders say the same thing in their own words. One founder who compared six enrichment APIs on the same 349 resolved domains described the exercise as the only way to see real freshness, because every vendor claims it. Another chose Coresignal for the depth of its records, then noted that depth and recency are different fields.

What surprised us was how often the cheap tier is the stale tier. That is not a trick. Caching is what makes 0.03 credits per result possible. It just means the price you compare on is not the price of the answer your agent needs.

Who Should Pick Coresignal?#

Pick Coresignal when the job is bulk. Warehouse-scale ingestion, market mapping across millions of companies, training data, and headcount analytics over time all want a dataset you own and join locally. The multi-source aggregation and the flat-file delivery are built for exactly that.

The high tiers reward it. At Premium, $1,500 for a million credits, a credit costs about a fifth of what it costs on Mini. Collecting records at scale stops being a line-item decision. Jobs data is strong too, at one credit per posting record.

One RevOps team wrote publicly about running Coresignal's MCP server with Claude Code for enrichment and called it one of the cleaner integrations they had tried. Add the most visible data-ethics program in the category, and a compliance review goes faster.

Not for you if your agent needs a work email on a $49 budget. That field opens at $499.

Who Should Pick Crustdata?#

Pick Crustdata when cheap cached discovery is your core loop. Nothing in the category beats 0.03 credits per search result for building large filtered lists, and the free company identify endpoint is useful plumbing before you spend anything.

Stay for the depth it goes into: technographics on company records, developer-platform signals, employee reviews, and a monthly S3 flat file next to the API. The documentation is genuinely good, and one builder called its real-time search option something they had not seen at other providers.

The honest trade-off, in the words of another user: the data was decent but it got pricey fast once bulk needs appeared. That is the gate talking. Live people endpoints, contact enrichment and social posts all sit on plans most self-serve builders do not have, and credits expire six months after purchase.

Not for you if you need those gated capabilities daily on a self-serve budget. Then the gate is the price.

Is There a Third Option for Agent Builders?#

Yes. A record-priced API serves every query from a hosted database, counts each profile or company returned as one record, and includes verified work emails on every plan. DataForB2B is built on that model: 850M+ profiles and 75M+ companies refreshed every 30 days, 60+ people filters and 40+ company filters, over REST and MCP. No dataset to host, no refresh pipeline to run.

Take a three-person team building a deal-sourcing agent. It tracks 1,200 founders who left a top-50 tech company in the last twelve months. Each week it checks current role and pulls a work email only for the 60 who started something new. Checking 1,200 roles a week is about 5,200 records a month, with the 60 emails included, well inside the $99 Start plan's 200,000.

One call shows the shape:

curl -X POST 'https://api.dataforb2b.ai/enrich/profile' \
  -H 'api_key: YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
    "profile_identifier": "https://www.linkedin.com/in/the-founder-you-track",
    "enrich_profile": true,
    "enrich_work_email": true
  }'

The signal surface is wider than profiles. Posts search covers LinkedIn, X and Reddit by keyword and returns who engaged, so a thread where buyers ask for a tool becomes a lead list. Jobs search reads LinkedIn and Indeed on one schema.

The trade-off is structural and worth saying plainly. There are no flat-file datasets here. If you need 50 million records in Snowflake by Friday, Coresignal is the right counter. Plans run $99, $499 and $999 a month (200,000, 5 million and 15 million records), with a free trial of 100 credits. Grab an API key on the pricing page.

You are probably wondering about integration time. A search is one POST request. The MCP path skips even that, because the agent calls the tool natively.

How Do You Run a Side-by-Side Test?#

You run a side-by-side test by taking one list you already trust, sending the same 100 profiles through each provider on the same day, and scoring three things: how many current employers were right, how many work emails came back, and what the batch cost on the plan it forced you onto.

1. Create an account on app.dataforb2b.ai/signup, start the free trial (100 credits) and pull an API key. Do the same on the Coresignal trial and the Crustdata self-serve tier.
2. Connect the MCP server in Claude under Settings, then Connectors, at https://mcp.dataforb2b.ai/mcp. The same server works with Cursor, VS Code, ChatGPT and any MCP-compatible agent.
3. Paste a prompt that runs the test: "Take these 100 LinkedIn profiles of RevOps leads, look up each one's current company and title, add a verified work email where one exists, and flag every profile whose employer changed since the CSV date."
4. Turn the conversation into a scheduled routine, weekly, so the freshness score is measured over a month rather than one afternoon.

Keep the list identical across providers. The only variable should be the meter and the freshness, and the numbers will tell you which one you were really paying for. Our Coresignal comparison and Crustdata comparison go deeper on each vendor alone.

Both vendors are good at the job they were built for. The question is whether your workload looks like a warehouse, a list, or a conversation happening right now. See the current grid on the pricing page and run the 100-profile test this week.