Apollo alternatives in 2026, sorted by the job you use Apollo for

Apollo is the default prospecting database for a large share of B2B sales teams, and most pages ranking for this search are written by a company selling the database that would replace it. Tulina is not a contact database, but it does sell a way of using several of them together, so it has an interest here too, and that is declared before anything else. This page quotes Apollo's prices from Apollo's own pages, read on 27 October 2026, says what Apollo does better than its rivals and who should stay on it, then shows how to leave it partly or wholly. It is about Apollo.io the sales platform; if you searched for Apollo Global Management, the asset manager, this is not your page.

What can I use instead of Apollo?

You can replace Apollo with a database, an email finder, a sequencer, or a combination of them, and which one you need depends on the Apollo job you are actually unhappy with. Apollo bundles three products in one seat: a contact database of 240M+ people and 30M+ companies (Apollo's figure), an email and phone finder, and a sequencer that sends from your mailbox. The listicles for this search mix all three into one ranked list. Sorted by job, the field looks like this:

Most teams that leave Apollo replace one of these rows, not all six. If the sequencer works and the data does not, keep the sequencer and fix the data. If the data is fine and you outgrew the sending, keep the data and move the sending. The Apollo connector page lists what Apollo can do from Claude or ChatGPT, which is a useful check of what you would be giving up. The AI tools that now sell parts of the same job, from Clay's research agents to autonomous AI SDRs, are compared with their prices in AI prospecting tools, sorted by the job they do.

Who is Apollo's biggest competitor?

ZoomInfo is Apollo's most cited competitor on the comparison pages: it is on every one of the five top-ranking articles for this search read on 27 October 2026 (Cognism, RB2B, Salesgenie, Saleshandy, Explorium), and on Gartner's alternatives list for Apollo. Lusha is on all five too, and Cognism on at least four. Clay appears on two (Saleshandy, Explorium), though it is less a competitor than a layer that buys from Apollo: Clay lists Apollo as one of its data providers.

The pages differ in who wrote them. Cognism ranks Cognism first, Saleshandy ranks Saleshandy first, RB2B ranks RB2B first, Salesgenie ranks Salesgenie first. That does not make them wrong, but read the criteria column before the order. This page ranks no one, and the table above is sorted by job instead.

What does Apollo cost in October 2026?

Apollo has four tiers. On annual billing, which Apollo says saves 20% against monthly, the figures are these, from Apollo's own articles of 18 August and 17 September 2026 and the snippet of apollo.io/pricing, read on 27 October 2026:

Apollo's credit rules, in its own words: an email costs 1 credit, a phone number 8, enrichment 1 to 8 depending on depth, an AI research run 1. Credits are pooled across the team, granted at the start of each cycle, and do not roll over, including add-on credits, which renew automatically until you remove them. Every seat on an account must be on the same plan, and API access is listed on Custom plans. Apollo's pricing page FAQ calls its top tier "Custom" while its articles say "Organization"; the price above is the one the articles give.

Two things follow for anyone comparing. A phone number at 8 credits means Basic's 30,000 credits buy at most 3,750 phone reveals a year per seat, against 30,000 emails for a team that reveals emails only. And since credits expire each cycle, the unused part of a quiet quarter is not carried into a busy one.

What does Apollo do well, and who should stay on it?

Apollo does three things better than most of the tools that rank against it, and this comparison would be dishonest without them.

• One seat, the whole loop. Database, email and phone finder, sequencer, Chrome extension and CRM sync from $49 a user a month, the dialer from $79. Every alternative in the first table replaces one row of that and needs another tool for the rest.
• A real free tier. 900 credits a year and two sequences, no card. That is enough for a founder to send the first campaigns and learn what a target list should look like.
• Reach from AI tools. Apollo runs its own MCP server, and says that more than 11,000 teams use Apollo from inside Claude, ChatGPT or Perplexity. It also sells its own waterfall enrichment across providers.

Stay on Apollo if one database covers your market well enough, if your reps work from one screen and would not adopt three, if you need the dialer, or if your volume fits inside a Basic or Professional seat. The switch costs more than a seat price: sequences, templates, signatures and CRM mappings all have to be rebuilt.

Is there anything better than Apollo?

Better at one job, yes; better at all of them for the price, rarely. The complaint at the top of this search is about data: the first result, a thread on r/LeadGeneration, opens with a user who found Apollo's records "outdated", people who changed companies months before still listed at the old one. Every database has that problem at some rate, because people change jobs faster than any vendor re-verifies them. What differs is how a team catches it.

What we measured, with the denominator. On 27 October 2026 we ran two people searches on Apollo through Tulina's Apollo connector, for one company domain, franke.com, a group with offices in many countries. By domain alone, Apollo returned 1,913 profiles. With the person's location set to France, it returned 56, or 2.9% of them. The two records shown were refreshed on 20 and 23 October 2026, a week before the search, so on this one domain the data was recent; what was wrong was the question. Revealing contacts by domain alone would have spent a credit on someone in the wrong country 97 times out of 100. That is one domain on one day, not a measure of Apollo's accuracy, and it is the kind of loss no alternative database fixes either.

How do you replace Apollo without switching to another single database?

You keep the parts of Apollo that work and put a second source behind it where it misses, with a table in the middle. This is honest enough to follow without Tulina.

1. Name the job you are unhappy with. Bounces, missing phone numbers, wrong country, credits running out, or the sequencer. Apollo's Settings → Credit usage breaks spend down by user and credit type, which tells you where the money goes before you move any of it.
2. Search wide, reveal narrow. People search in Apollo returns identities without emails; the reveal is what costs a credit. Filter on the person's location, title and seniority first, and reveal only what passes. On a multinational's domain, the location filter is the difference between 56 rows and 1,913.
3. Check the CRM before you buy anything. Match every candidate against the CRM by email or company domain and drop customers, open deals and anyone in a colleague's sequence. That check is free; a reveal of someone you already sell to is not.
4. Run a cascade, first hit wins. Apollo first if you already pay for it, then one or two providers that cover what it misses (Hunter for name plus domain, FullEnrich or Dropcontact as a later step). Stop at the first email found.
5. Keep the source and the date on every value. Write which provider found the email and when, next to the email. A bounce then tells you which source to trust less, instead of telling you nothing.
6. Verify, then send, as separate steps. Verification is its own call and its own cost. Loading the sequence is a deliberate step after the table is clean, in Apollo or in another sequencer, never a side effect of enrichment.

What this costs instead of money: three invoices where there was one, three sets of credits that expire on different days, and someone who keeps the table and the order of providers up to date. At a few hundred contacts a month that is light. At thousands across several segments it is a job, and the job is what Apollo's one seat was saving you.

How do you build an Apollo-style list with Claude or ChatGPT?

With Tulina, Claude or ChatGPT runs the steps above as an agent: Apollo as the database, your CRM as the check, a signal source for the reason to write, an email cascade across the providers you hold keys for, and your sequencer as the last step, staged as a draft. A person still writes the sentence, approves the filters, and launches the campaign. Tulina is an agentic RevOps workflow builder, AI agents that run sales and GTM processes on a schedule or a webhook across the tools a team already uses, with every step and its cost visible; building a target list is one of those processes.

Paste this into Claude or ChatGPT once Apollo, your CRM and your sequencer are connected:

Build a target list from this sentence: "Logistics companies in
France, 250 to 1,000 employees, hiring supply chain roles. 40 accounts,
two or three people each, operations and supply chain directors."

1. Print the filters you read from the sentence (headcount band,
   country, sectors, titles, seniority) and wait for my go before
   searching anything.
2. Search companies in Apollo with those filters. Give me the count
   first. Score each company on what the search returned and keep the
   top two tiers only.
3. Search people at the companies you kept, with the person's location
   set to the country I asked for, two or three per company. Do not
   reveal anyone yet.
4. Check every person against my CRM by email or company domain. Drop
   customers, open deals and anyone in a colleague's sequence.
5. For the companies left, find one dated reason to write: an open
   role or a technology from job postings, or news with its URL.
6. Find a work email for each person with the email waterfall: my
   connected providers in order, first hit wins, at most two paid
   steps per person. Show me the plan and its cost for one person as a
   dry run before running the rest. Write the provider that found each
   email next to it.
7. Load the people into my lemlist campaign as leads with their opener
   as a variable. Do not launch anything.
8. Report: filters used, companies found and kept, people found,
   dropped as already in the CRM, emails found by provider, not found,
   and what each step cost.

The process behind that prompt, with every step and the tools it uses:

The process in Tulina

Build a target list from a sentence

Logistics companies in France, 250 to 1,000 employees, hiring supply chain roles. Source 40 accounts.

One-sentence brief in chat

See it in a demo

Claude runs the rest autonomously

1. 1

   AI shortlists accounts and their people.

   Apollo.io

   Apollo.io

   Matching companies are scored on what the search already returned, and each one kept gets two or three people fitting the persona described.

2. 2

   AI drops contacts the CRM already has.

   HubSpot

   HubSpot

   Anyone the CRM shows as a customer, an open deal or in a colleague's sequence is dropped, matched by email or else by company domain.

3. 3

   AI gathers signals for what survived.

   TheirStack

   TheirStack

   Each remaining company gets its open roles and technology, recent funding, moves and expansions, and details from its own pages, each with its source URL.

   Serper

   Serper

   Apify

   Apify

4. 4

   AI finds verified emails and numbers.

   Apollo.io

   Apollo.io

   Each contact gets a verified address and direct number, a second source fills what the first missed, and anyone still unfound is marked unreachable, not guessed.

   FullEnrich

   FullEnrich

5. 5

   AI writes each opener from a signal.

   Each opener names one dated finding about that company and cites its URL, and a company with nothing found gets a plainer version, never an invented hook.

6. 6

   AI stages the campaign, updates the CRM.

   Lemlist

   Lemlist

   The sequence sits as a draft with each contact's own opener, the qualified list is in the CRM with its signals as a note, and the launch is left to a person.

   HubSpot

   HubSpot

See the full process

The email step in the prompt is the cascade from the previous section, run on Tulina's email waterfall. It knows nine providers (Hunter, AI Ark, Apollo, Kaspr, Lusha, Forager, Dropcontact, lemlist and FullEnrich), calls only the ones your team holds a key for, runs your own keys first, and adds no cost of its own: each step is billed by its provider as a direct call would be. On 27 October 2026 we ran one email lookup as a dry run in our own workspace, with a name and a company domain and no LinkedIn URL. Of the nine providers, three were planned with their cost named before anything was spent (lemlist on our own key, Apollo at 1 credit, FullEnrich), three were skipped for lack of a connected key, and three because they need a LinkedIn URL the row did not have. Nothing was charged. That is a claim about seeing the plan, not about find rates, which this page did not measure.

For the version that starts from a signal instead of a sentence, Outbound from buying signals scores new hiring and stack signals each morning and fills a paused campaign. For enrichment alone on a list you already have, see Enrich contacts with email and phone.

Apollo vs a cascade of providers

The two are paid for on different things. Apollo is a seat with a credit allowance that covers its own database. A cascade is the providers' own prices, each on its own key, plus whatever runs the order. Tulina does not publish its plan prices, so the column says so instead of inventing one.

The cascade is not cheaper by default. A team with one seat and one market will spend less on Apollo Basic than on three providers. The cascade pays off when Apollo's coverage is the problem, or when the same list has to go through the CRM, a signal source and a sequencer every week and someone is doing that by hand.

Free and cheaper Apollo alternatives

The cheapest alternative to Apollo is usually Apollo's own Free plan used narrowly, then a pay-per-find email tool for the gaps. The "free" entries on the listicles are free plans or trials of paid tools, each with a small number of finds or sends, and LinkedIn's own search is free but gives no emails. None of them replaces Apollo's free database search at its size. If cost is the reason for leaving, attribute the bill first (step 1 above), starting with phone reveals, which cost eight times an email.

What this comparison cannot tell you

• Which database is most accurate in your market. We measured no find rates or bounce rates for this page. The figures above are one domain on one day and one dry run, which prices a plan and finds nothing.
• What Apollo will cost next quarter. Every price here is dated 27 October 2026 and read from Apollo's own pages, whose pricing cards load in the browser only; the top tier's name differs between Apollo's pricing FAQ and its articles.
• Tulina's plan price. It is quoted on a call, not published, so the last table cannot do the arithmetic Apollo's allows. Ask for the number before you compare totals.
• The rival tools' details. The first table sorts tools by the job the comparison pages assign them; we have not tested ZoomInfo, Cognism, Lusha or the sequencers named there.
• Whether an agent spends less by itself. It does not. An agent with your keys tries every provider you allow, which is why the prompt caps paid steps per person and asks for a dry run first.

For what Apollo itself reads and writes from Claude or ChatGPT, and how its own MCP server compares with Tulina's, see Apollo for Claude and ChatGPT. How Apollo differs from Clay, which buys from Apollo among others, is in Clay vs Apollo, with both pricing models and both waterfalls side by side; what Clay charges per enriched contact is in Clay pricing explained, and a Clay alternative.