Apollo alternatives, matched to the job you're replacing

This page is for sales leaders, founders and RevOps people who use Apollo, or nearly bought it, and want to know whether another tool would do one job better. Know three numbers before you start: how many reps you have, how many new contacts each needs a month, and how many of those need a phone number. Every comparison below turns on them.

How we compared

Bebop, made by Blackpearl Group, wrote this page and is one of the options in it. It only partly replaces Apollo: it finds and researches accounts and contacts, but it doesn't send email sequences or dial. We set these rules before writing:

• Selection. Each option replaces at least one Apollo job and was named in the Apollo alternatives lists we reviewed from the top search results on 25 October 2026. We left out enterprise intent and ABM suites, which are a different purchase (see sales intelligence platforms), and tools whose pricing pages we couldn't read on the day.
• Facts. Every price, plan name and credit rule comes from the vendor's own pricing page or help docs, read on 25 October 2026 and listed in the sources. Where a vendor doesn't publish prices, we say "quote only" and what its page says is included. Prices are list prices before tax and discounts.
• No hands-on scores. We haven't run head-to-head tests of these products, so there are no ratings here. The test protocol below is the one we'd want you to run on your own accounts.
• Fairness. For each tool, we say when Apollo is still the better fit.

Which Apollo job are you replacing?

Apollo bundles five jobs into one subscription. Most teams looking for an alternative are unhappy with one of them, and replacing the whole bundle to fix one job usually costs more.

If the complaint is simply price, check Apollo's own options first. Annual billing on Basic is $49 per seat a month against $65 monthly, which Apollo advertises as a 24% saving.

Apollo's plans and credits on 25 October 2026

How the credits work, from Apollo's pricing page and API documentation:

• Credits are pooled across the team, granted upfront each billing cycle, and reset at the start of the next one. Unused credits don't roll over.
• An email (or person data) costs 1 credit. A mobile number costs 8 more. If no credit-consuming data comes back, nothing is charged.
• The same pool pays for other things: US dialer minutes (the pricing page calculator uses 2 credits a minute, charged in 30-second increments) and warmup for each mailbox after the first (200 credits a month).
• Extra credits start at $0.025 each and fall to $0.015 at high volume.

The alternatives at a glance

Published plans as listed on each vendor's pricing page on 25 October 2026. Annual figures are the monthly equivalent when billed annually.

What one credit actually buys

This is where headline prices mislead. "400 credits" and "2,500 credits" can't be compared until you convert them into the mix of emails and phone numbers you need.

Three things follow from this table:

• Convert allowances into your mix. Lusha Starter's 400 credits are 400 emails or 80 phone numbers. Apollo Basic's 2,500 credits per seat are 2,500 emails or about 312 mobile numbers (2,500 ÷ 8). UpLead Essentials' 170 credits are 170 contacts with both.
• Below your allowance, you're paying for seats. If a team uses a fifth of its credits, the real price is the bill divided by contacts used, not the price per credit.
• Misses and mistakes are charged differently. Apollo charges nothing when no data comes back, and Lusha charges waterfall enrichment only on a confirmed match. But a wrong number you did pay for costs you twice: the credit and the rep's time.

Worked example: three reps, one month

Illustrative example. The company and volumes are invented. Prices are the list prices published on 25 October 2026, before tax or discounts.

The team: Tallyfold (tallyfold.example) sells payroll compliance software to multi-site restaurant groups. Three SDRs each need 120 new contacts a month with a verified email, and 40 of each rep's contacts also need a mobile number for call blocks. That's 360 contacts a month, 120 of them with mobiles. Tallyfold already runs its sequences in Apollo.

Credits needed each month:

• Apollo: 360 emails × 1 + 120 mobiles × 8 = 360 + 960 = 1,320 credits
• Lusha: 360 × 1 + 120 × 5 = 360 + 600 = 960 credits
• UpLead: 360 contacts × 1 = 360 credits (email and mobile in the same credit)
• Hunter: 360 emails × 1 = 360 credits, and no mobiles

Cost per contact is the bill divided by 360: for example, $195 ÷ 360 = $0.54.

What changes the answer:

• Volume. At 400 contacts per rep (1,200 a month, 400 with mobiles), Apollo needs 1,200 + 3,200 = 4,400 credits, still inside 7,500. Lusha needs 1,200 + 2,000 = 3,200, just inside Premium's 3,400. UpLead needs 1,200 credits, so three Essentials accounts (510) no longer fit and three Plus accounts cost $597 a month ($447 annually). Hunter's 1,200 emails still fit Starter.
• Phone mix. If every contact needs a mobile, each one costs 9 Apollo credits and 6 Lusha credits, but still 1 UpLead credit. Phone-heavy teams should look hard at how a vendor defines a credit, then test whether its numbers actually connect.
• Accuracy. Suppose one tool returns 10 percentage points more wrong records than another. At 360 contacts, that's 36 extra bad records. If each costs a rep three touches at four minutes each, that's 36 × 12 = 432 minutes, or 7.2 hours. At an illustrative loaded cost of $45 an hour, that's $324 a month, more than the list-price gap between most options above.
• Workflow. Tallyfold sequences in Apollo. Replacing only the data means paying for a sequencer as well (Apollo Basic itself, or lemlist's Email plan at $55 to $69 a month) and moving contacts between tools.

What makes this comparison fair: it starts from the team's own volumes, converts each vendor's credits into that mix, counts the seats three reps need, and treats wrong records as a cost.

Run your own test on 20 to 50 accounts you know

Vendor accuracy figures describe someone else's market. This protocol measures yours in about a day per tool.

1. Build a truth set. Pick 20 to 50 accounts you know well: customers, recent lost deals and researched targets. For each, write down the buyer you'd want and the email and phone you know are right because that person replied or answered in the last six months.
2. Set pass marks first. Decide what's good enough before testing: for example, at least 70% of your buyers found, under 3% hard bounces and a maximum cost per usable contact.
3. Check what the free tier covers. Most free tiers won't stretch to 50 accounts with phone numbers (see the table below), so budget for one paid month on monthly billing.
4. Run the same lookups in every tool on the same day. Same accounts, same roles, no names supplied. You're testing whether the tool finds the right person.
5. Score every record. Give +1 for the right person in their current role with a working email or number, 0 for a plausible record you can't confirm, and -1 for a wrong person, someone who has left, a bounced email or a wrong number. This mirrors the scoring in GTM-Bench, Blackpearl Group's June 2026 benchmark of AI prospecting systems, where records below its quality bar score -1 so volume can't hide weak results. Several general-purpose AI agents in that benchmark finished with negative net scores.
6. Test the research, not just the data. For ten accounts, ask each tool what has changed in the last 90 days and who you should contact. Check every claim against the company's own site or news. An unsupported claim scores -1, the same as a wrong email.
7. Test the hand-off. Push ten scored contacts into your CRM and sequencer, and note duplicates and anything a rep must fix by hand.
8. Work out cost per usable contact. Divide the monthly price at your real volume by the contacts you'd expect to score +1. For example, if 80% of Apollo's records scored +1 for Tallyfold: $195 ÷ (360 × 0.80) = $195 ÷ 288 = $0.68.

Keep one log per tool so the results are comparable:

Tool and plan tested:                 Date:
Job being replaced: [database / email finding / sequencing / dialer / enrichment / research]

PASS MARKS (set before testing)
Buyers found: at least ___%
Hard bounces: under ___%
Cost per usable contact: under $___

RESULTS (truth set of ___ accounts, ___ contacts requested)
Contacts returned: ___ of ___ (___%)
Scored +1 (right person, current role, reachable): ___
Scored 0 (plausible, can't confirm): ___
Scored -1 (wrong person, left, bounced, wrong number): ___
Net score (+1s minus -1s): ___

Research check (10 accounts): claims checked ___, supported ___, unsupported ___
CRM and sequencer hand-off: [what broke, what needed fixing by hand]

Monthly price at our volume: $___
Cost per usable contact: $___ ÷ (___ contacts × ___% scored +1) = $___

Decision and why:

Best fit and limitations for each option

ZoomInfo. Best for: larger teams that want broad contact and company data, buyer intent signals (on Copilot Advanced and Copilot Enterprise) and marketing products under one contract. Limitations: quote only, priced on features, licenses and credit usage, and each export costs a credit. Intent isn't listed on the Professional tier. Apollo is the better fit if: you want self-serve prices with sequencing included.

Cognism. Best for: teams of five or more that care about mobile number quality. Pro adds intent data and on-demand mobile verification, and re-viewing a contact you've already revealed is free. Limitations: quote only, and both plans include five seats, which is more than a one- or two-rep team needs. Apollo is the better fit if: you're a small team or want sequencing in the same tool.

Lusha. Best for: individual reps and small teams who want quick email and phone lookups, with monthly plans that roll unused credits over (up to twice the plan limit). Limitations: a phone number costs five credits, so phone-heavy work uses credits fast, and Lusha asks teams of more than five users to contact sales. Apollo is the better fit if: you want sequences and a dialer alongside the data.

UpLead. Best for: small teams that call as much as they email, because one credit covers a contact's email and mobile direct dial. UpLead's pricing page states a 95% email accuracy rate (its own figure). Limitations: Essentials and Plus are single-user accounts, so team admin means Professional (quote, annual only), and allowances are smaller than Apollo's. Apollo is the better fit if: your work is mostly email and you want more volume per dollar.

Hunter. Best for: email-first prospecting: finding and verifying work emails from a company domain, with basic sequences and unlimited team members on every plan. Limitations: its pricing page covers email finding and verification, not phone numbers. Apollo is the better fit if: your reps call prospects.

Clay. Best for: ops-minded teams that combine many data providers in waterfalls and run AI research (Claygent) inside custom tables, with unlimited users on every plan. Limitations: someone has to build and maintain the tables, and costs depend on which providers your workflows call. Apollo is the better fit if: reps need to prospect on day one without building anything.

lemlist. Best for: replacing Apollo's sequencing, especially multichannel: the Multichannel plan adds LinkedIn steps, SMS and a built-in dialer, and every plan includes its lead database and finder. Limitations: Multichannel is priced per user, so cost scales with headcount, and extra data comes as a credit add-on. Apollo is the better fit if: your sequences already work and the data is fine.

Instantly. Best for: high-volume cold email, with unlimited sending accounts and warmup on its Outreach plans. Limitations: the lead database is a separate credit subscription, and plans cap both emails and uploaded contacts, so price both. Apollo is the better fit if: you want data, sequencing and a dialer on one bill.

Bebop (we make it). Best for: teams that already have sequencing and want better targeting and preparation. You describe the companies you want in plain language; it finds matching accounts and contacts, researches each account and builds a playbook: who to talk to, what's happening at the company, the angle to open with and the objections to expect. Limitations: it doesn't send sequences or dial, so it replaces Apollo's research job only. Bebop Starter is $149 a month for one user, with 5,000 credits a month. Apollo is the better fit if: what you're missing is cheaper data and sequencing, not research.

Where every option falls short, Apollo included

• Data decays. People change jobs and every database lags behind. Re-check records before a big campaign.
• Accuracy claims are self-reported. Vendor figures describe their own samples, usually without a published method. Your truth-set test is the number that applies to your market.
• Compliance stays with you. The UK's ICO says a named business contact's details are personal data and that your use of a bought list must comply with UK GDPR. Buying data doesn't hand that obligation to the vendor.
• More rows aren't better. In GTM-Bench, systems that returned thousands of rows repeatedly ended with negative scores, because weak records counted against them. A short list you've checked beats a long one you haven't.

Stay, switch or add?

Stay with Apollo if:

• You use its data, sequences and dialer together, and your test shows the data holds up in your market.
• Cost is the only complaint, and annual billing or a different plan fixes it for less than a second tool.

Switch the data if:

• Your test shows a clearly higher wrong-record rate than an alternative's.
• You call more than you email, and a vendor whose credit includes the mobile number tests well for you.
• You need enterprise coverage and intent under one contract (ZoomInfo, Cognism).

Switch the sequencing if you need multichannel steps or very high sending volume (lemlist, Instantly).

Add research if reps reach the right people but have nothing specific to say. That's a research gap, not a data gap, and the account research guide shows what good research covers.

Next step: before you sign with any data vendor, run the data-quality test and ask the sourcing questions in sales intelligence platforms compared.