Apollo.io vs Lusha vs Custom Scraping: Which Wins?

The B2B Data Challenge

Sales and marketing teams face a fundamental choice when building prospect databases: subscribe to a B2B data platform like Apollo.io or Lusha, or build custom scraping capabilities to gather data directly from sources. Each approach involves different tradeoffs around cost, data quality, compliance, and flexibility.

The stakes are significant. Apollo.io email accuracy is cited at 80-85% with up to 35% bounce rates reported by some users. ZoomInfo claims 95%+ verified accuracy but at enterprise pricing that many organizations cannot justify. Lusha offers accessibility but with a smaller database than competitors. Meanwhile, custom scraping promises flexibility but demands ongoing technical investment.

Understanding the real-world performance, costs, and limitations of each approach enables informed decisions about how to build your B2B data infrastructure.

This comparison examines Apollo.io, Lusha, and custom scraping approaches based on actual user experiences, published metrics, and practical implementation considerations.

Apollo.io: The All-in-One Platform

Apollo.io positions itself as an end-to-end B2B sales platform combining contact database access with email sequencing, automated dialing, and CRM integration. It has become a popular choice for startups and growth-stage companies seeking an affordable alternative to enterprise platforms like ZoomInfo.

Database and Coverage

Apollo claims access to a large global B2B contact database with basic contact information including emails, phone numbers, and company data. The platform validates data in real-time according to Apollo, though user experiences vary significantly. Multiple sales professionals have reported issues with outdated contacts and missing mobile numbers compared to premium alternatives.

Pricing Structure

Apollo offers a genuine free tier with basic prospecting capabilities, making it accessible for individual sales reps and small startups. Paid plans scale based on user count and features. The transparent, seat-based pricing contrasts with enterprise platforms that require sales conversations. However, some users note that credit allocations run out quickly with high-volume prospecting.

Key Strengths

Integrated outreach capabilities set Apollo apart from pure data providers. Email sequences, task automation, and CRM syncing are built into the platform. The Chrome extension enables LinkedIn prospecting directly in the browser. For teams wanting a unified workflow from prospecting to outreach, Apollo reduces tool fragmentation.

Limitations

User reviews consistently cite data accuracy concerns. Email bounce rates significantly higher than enterprise alternatives have been reported by users, with some citing rates up to 35% compared to ZoomInfo's claimed <5%. Mobile phone accuracy reportedly drops to around 40% due to automated verification without human validation layers. The platform also experienced LinkedIn integration issues in early 2025 when its company page was delisted for platform policy violations.

Lusha: The Accessible Alternative

Lusha targets SMBs and sales reps who need quick access to contact data without enterprise complexity. The platform emphasizes ease of use and transparent monthly pricing over comprehensive feature sets.

Database and Coverage

Lusha delivers B2B data for sales, marketing, and recruiting teams through its prospecting platform, browser extension, and API. The LinkedIn Chrome extension is a core product, enabling profile enrichment directly from LinkedIn pages. Database size is smaller than Apollo or ZoomInfo, which can limit coverage for certain industries or geographies.

Pricing Structure

Lusha uses a credit-based system: 1 credit for an email, 5 credits for a phone number. This model works well for low-volume prospecting but becomes expensive at scale. A free plan provides limited monthly credits for trial users. Paid monthly plans offer additional credits per user, with custom enterprise packages available.

Key Strengths

Browser-based contact capture is Lusha's core strength. The Chrome extension pulls data directly from LinkedIn profiles and company websites with minimal friction. Monthly subscription plans without annual commitments provide flexibility for smaller teams testing the platform.

Limitations

Lusha lacks advanced features required by sales operations managing large teams. The platform does not provide bulk enrichment APIs, automated CRM sync at scale, or sophisticated reporting. Data accuracy hovers around 82-85% for emails with higher variance for phone numbers. Some users report that integrations could be improved. Organizations scaling beyond 50 reps typically outgrow Lusha's capabilities.

Custom Scraping: Build Your Own

Rather than relying on third-party databases, some organizations build custom scraping capabilities to collect contact data directly from sources like company websites, directories, and professional networks.

How It Works

Custom scraping typically involves developing scrapers using Python frameworks like Scrapy or Beautiful Soup, or browser automation tools like Playwright and Puppeteer. Scrapers extract contact information from target websites, directories, event attendee lists, and other public sources. The data is then processed, validated, and loaded into CRM or sales engagement platforms.

Potential Benefits

Custom scraping offers unique advantages in specific scenarios. You control exactly which sources to target, enabling focus on niche industries or specific company types that database platforms may underserve. Data freshness depends on your scraping schedule rather than vendor update cycles. For very specific use cases, custom scrapers can collect data points that standard platforms do not provide.

Real Costs

The hidden costs of custom scraping often exceed initial estimates. Development requires specialized engineering talent - web scraping freelancers on Upwork charge $20-40 per hour median, with specialized projects commanding higher rates. Ongoing maintenance is essential as websites change layouts and implement anti-bot measures. Infrastructure costs include proxies, captcha solving services, and cloud hosting. Compliance review adds legal overhead.

Technical Challenges

Anti-bot detection systems block automated access across major platforms. LinkedIn aggressively restricts scraping and terminates accounts. Company websites implement rate limiting and IP blocking. Maintaining scrapers against constantly changing website structures demands continuous engineering investment. Data quality issues including duplicates, outdated information, and incorrect parsing require ongoing cleanup.

Side-by-Side Comparison

Which Approach Wins?

The right choice depends on your specific context, resources, and requirements.

Choose Apollo.io When

Your team needs an integrated workflow from prospecting through outreach. Budget constraints rule out enterprise platforms. Volume requirements are moderate and email-focused rather than phone-heavy. You can tolerate some data quality variance and build verification into your workflow.

Choose Lusha When

LinkedIn is your primary prospecting channel. You need quick access to contact data without complex setup. Monthly flexibility matters more than volume discounts. Your team is small (under 50 reps) and does not require enterprise reporting.

Choose Custom Scraping When

You need data from specific sources that platforms do not cover. Your use case requires unique data points beyond standard contact information. You have engineering resources to build and maintain scrapers. Compliance requirements demand complete control over data sourcing.

The Fourth Option: Managed Scraping Services

Each approach above involves significant tradeoffs. Platform databases offer convenience but limited customization and variable accuracy. Custom scraping provides flexibility but demands ongoing technical investment and quality management.

Tendem's AI + Human scraping service offers an alternative that combines custom scraping flexibility with verified data quality - without the engineering overhead.

Rather than relying on pre-built databases or managing your own scrapers, Tendem builds custom data collection workflows for your specific requirements. AI handles scale and automation. Human experts verify accuracy, resolve edge cases, and ensure data quality meets your standards.

This hybrid approach addresses the core limitations of each alternative. You get the customization of custom scraping without engineering burden. You get accuracy that exceeds automated platforms through human verification. You get data from the specific sources that matter for your business.

Ready to explore how managed scraping can improve your B2B data quality? Check how Tendem handles web scraping.

Related Resources

- ZoomInfo Alternatives: Cheaper B2B Data Options

- B2B Lead Scraping: How to Build Targeted Prospect Lists

- Contact Scraping Services: Finding Emails & Phone Numbers at Scale

- Tendem Data Scraping Services