RadarLeads vs Lusha: person-level enrichment or local-business lead lists?

Lusha is a sales-intelligence platform known for its Chrome extension: visit a LinkedIn profile or company website, and Lusha reveals contact details for the people behind it, consuming credits per reveal. It also offers bulk enrichment, API access and filters across its person-level database, making it a common choice for SDR teams that live inside LinkedIn.

RadarLeads needs no extension and no LinkedIn seat. You search a business type in a city across 23 countries and receive deduplicated business records: phone, website, Google rating, review count and a verified contact email harvested from the business website with LLM fallback. Everything exports to Excel or CSV in one click. Where Lusha reveals a person, RadarLeads delivers a complete, callable business row with the context to prioritize it.

Lusha answers questions like "who is the operations director at this logistics group, and what is her mobile?" When your playbook depends on reaching specific roles inside mid-size and large companies, that is exactly the data you need, and Lusha delivers it with fewer clicks than most rivals. Its filter builder also supports bulk projects, pulling hundreds of matching contacts at once.

RadarLeads answers a different question: "which businesses in this city should I call this week?" A dental supplier does not need the mobile of a practice manager found on LinkedIn; it needs the full list of clinics in ten cities with phones that answer and emails the practice actually reads. That is business-level data, sourced live from public local-business records, and it is the gap Lusha leaves open because its unit is a person, not an establishment.

Think about how each dataset behaves at the edges, because edges decide deals. A Lusha reveal is excellent for a sales director at a 300-person logistics firm and useless for the four-person customs brokerage that would actually answer the phone. A RadarLeads row is excellent for that brokerage and silent about who runs it day to day. Teams that map their pipeline honestly discover both facts matter at different stages: business-level data to build the market, person-level data to penetrate the few accounts big enough to matter. The expensive mistake is buying one subscription and pretending it covers both jobs, then compensating with manual Google searches and spreadsheet gymnastics that erase the hours the tools were supposed to save. Match the tool to the layer, and if budget forces one choice, match it to the layer where most of your revenue actually originates. For most teams selling to local businesses, that layer is the business itself.

RadarLeads verifies the contact email of every single lead by scraping the business website, with an LLM fallback, and every record carries its public source link, so verification is something you can see, not something you are promised. Phones come from the business public listings, which is why connect rates on fresh searches run high.

Lusha accuracy is respectable for person-level data and improves constantly through community feedback, but credit-based reveals mean every check costs something, and direct dials in some regions skew stale between refreshes. The honest framing: for reaching named professionals, Lusha is competitive and convenient. For auditable, row-level verifiability on business contacts, RadarLeads design makes accuracy a property of the list you export.

Direct answer: Lusha has a free plan near 40 credits per month and paid plans from roughly $37 per user monthly billed annually, with credits consumed per reveal, while RadarLeads starts at $29 flat for 300 verified leads, so teams doing volume usually pay less overall with RadarLeads and never budget credits.

Lusha tiers climb through Pro near $52 per user monthly and Premium beyond, and multi-seat teams multiply those numbers; running out of credits mid-month is the classic Lusha complaint. RadarLeads prices are fixed: Starter $29 for 300 leads and 15 searches, Growth $79 for 1,000 leads and 50 searches, Agency $199 for 5,000 leads with unlimited searches, trial included with no card. For a two-person agency doing daily prospecting, flat pricing plus unlimited-seats-per-plan economics typically lands far below per-user credit bills.

Lusha embeds in a LinkedIn-centered routine: find profiles, reveal contacts, push to CRM, sequence. That is a strength if your team already works there and targets roles at companies; the extension keeps context switching low. Bulk enrichment supports cleaning an existing CRM in place.

RadarLeads replaces the routine rather than decorating it. There is nothing to install; the search box and the export button are the product. Virtual assistants and agencies hand the exported file straight to dialers, and the rating and review-count columns make prioritization obvious without opening another tab. If your motion is maps-and-phones rather than profiles-and-InMails, the list-first workflow is simply faster.

Lusha is worth it when named people are the product of your prospecting: recruiters, SDR teams and partnership hunters working LinkedIn get solid value from its free tier and reasonable value from paid seats. For selling to establishments, the credit model caps its usefulness, because the contacts you need are businesses, not profiles.

The budget test is simple. Count monthly reveals your team actually performs, multiply by the effective per-credit cost on your plan, and compare against a flat RadarLeads plan that returns complete business rows without metering. Small teams often discover that only a fraction of credits produce usable local-business data, the rest go to corporate profiles outside the ICP. That wasted share is precisely what a focused tool eliminates, and it is why agencies serving SMB verticals drift toward flat-priced sourcing.

Migration is procedural, not technical. Export the business-relevant rows Lusha gave you, then rebuild sourcing in RadarLeads as searches by business type and city; exports arrive deduplicated with phones, ratings and verified emails, and drop into the CRM and dialer you already run. Any CRM enrichment Lusha performed stays in your records, so nothing historical breaks when you change sourcing tools.

Plan a two-week parallel run rather than a hard cutover: week one, produce lists in both tools for the same territory and log connect rates and valid emails; week two, route all new sourcing through RadarLeads and keep Lusha only for revealing individuals inside larger accounts, if you still need that. Cancel Lusha at the seat-renewal date to avoid paying for idle seats, brief your assistants on the three-step workflow, and the switch is complete without an IT project.

Lusha onboarding is polished for the extension workflow, and its support reputation is generally decent on paid plans. Operationally, the habits to manage are credit balances across users and periodic refreshes that can change whether a saved contact still resolves, which is inherent to person-level community data.

RadarLeads onboarding is the trial itself, and daily operation has nothing to balance: no credits, no seats, no reveals to ration. Reliability comes from sourcing live public records at search time, so a fresh list reflects businesses operating this month, and every row keeps a source link you can audit before dialing. Support runs over email with human replies, and the shape of each export stays constant, which keeps assistants and call centers fast week after week.

Choose RadarLeads if you sell to local businesses, need phones and verified emails on flat pricing, prospect across Latin America or Spain, or hand lists to assistants and agencies who should not need training. It is the shortest path from "we need more SMB pipeline" to a callable file.

Choose Lusha if your ICP is a person with a job title, your team lives on LinkedIn, and per-seat credit pricing fits how you buy. Recruiters, SDR teams targeting mid-market roles and CRM-enrichment projects are Lusha sweet spots. Some teams pair both: Lusha for named decision-makers inside larger accounts, RadarLeads for the long tail of local businesses no person database covers.