How Web Scraping Needs Differ Between Enterprise and Startup Clients

When you’ve been in web scraping as long as I have, one thing becomes clear: no two clients are alike. But there’s a predictable divide between how enterprises and smaller businesses approach their data extraction projects. Over the years at Ficstar, I’ve worked with both Fortune 500s and startups still proving their business model, and the contrast in needs, expectations, and processes is stark.

This article takes a closer look at those differences. I’ll walk through how enterprises and startups differ in decision-making, scale, compliance, project management, and support expectations, and why those differences matter for anyone considering a web scraping partner.

Enterprise vs. Startup Web Scraping Differences

Enterprises and startups approach web scraping in very different ways. From decision-making to data scale and support. To make the differences clearer, here’s a side-by-side look at how enterprise clients and startups or smaller companies typically approach web scraping projects:

Category	Enterprise Clients	Startup / SMB Clients
Decision-Making	i) Technical team discussion on data structure and ingestion ii) Often request a website where previous vendor is blocked or data was incomplete	i) Quick decisions, smaller scope ii) Automating manual tasks iii) Exploring if web scraping is viable
Data Needs	i) Large datasets across many websites ii) Pricing data across multiple zip codes iii) Strict formats for proprietary systems iv) Typically market leaders monitoring competition	i) Usually only a couple websites ii) Under 500,000 rows iii) Build reporting tools around the data instead of integrating into systems
Compliance & Risk	i) NDA required ii) Contracts prepared by legal team iii) Formal legal reviews iv) Cyber Liability Insurance v) Specific forms or payment setups vi) Budgetary constraints	i) Contract + agreed price ii) Rarely any legal involvement iii) Fewer budget constraints but smaller project sizes
Project Management & Communication	i) Meetings with many stakeholders at different responsibility levels ii) Meetings scheduled in advance iii) Project owner communicates with top executives	i) Usually one technical person and one project owner ii) Impromptu meetings and decisions
Support & Partnership	i) Data ingested into multiple big data systems ii) Feeds pass through staging pipelines before production iii) Strict ingestion times required iv) Collaboration with multiple teams and replacements over time	i) Data use isolated within a small team ii) Changes quickly applied iii) Usually just one contact for requirements

1. How decisions get made

Enterprises When I work with a large enterprise, the process almost always begins with paperwork. The very first step is usually a signed NDA, sometimes before we’ve even discussed project details. From there, their technical team jumps in to explore how the data will be structured, how it needs to be ingested into existing systems, and whether it can fill a gap left by a current vendor.

In fact, it’s common for enterprises to approach us after being let down by another provider, maybe their vendor got blocked on a key website, or the data feeds were inaccurate and incomplete. Enterprises have little tolerance for bad data, because a mistake at their scale can translate to millions of dollars in lost revenue or poor strategic decisions.

Startups and SMBs Smaller companies are the opposite. They want to move fast, test ideas, and minimize upfront risk. Often, they’ll ask for free samples before committing. They make quick decisions and typically start with a narrow scope, like scraping just one or two sites to automate a manual task. Many times, they’re still exploring whether web scraping can help at all.

At Ficstar, we’ve supported both sides of this spectrum, and we’ve learned to adapt. For startups, flexibility and responsiveness matter most. For enterprises, it’s compliance, reliability, and proven scalability.

2. The scale and type of data

Enterprises Scale is the defining characteristic of enterprise web scraping. These clients often need massive datasets across dozens or even hundreds of websites. A retailer might want competitive pricing across every zip code in North America. A travel company might need flight and hotel data across multiple countries in real-time.

Enterprises also require data delivered in very specific formats. We’ve seen everything from JSON feeds mapped directly to proprietary APIs, to CSV outputs designed for ingestion into legacy ERP systems. They want the data to “drop in” seamlessly, with no friction for their internal teams.

And more often than not, the enterprise is the largest player in its market. That means they’re monitoring competitors at scale, not the other way around.

Startups and SMBs Startups rarely need that kind of volume. Their projects often involve a handful of websites and data volumes under 500,000 rows. Many will build their own reporting tools around the scraped data, instead of integrating into complex systems.

This isn’t a bad thing, it’s the natural stage they’re at. A founder might be trying to validate a pricing strategy or automate lead generation. For them, web scraping is about speed to insight, not massive operational integration.

3. Compliance, risk, and accuracy

Enterprises Compliance and risk management are non-negotiables for enterprises. At Ficstar, we’ve had clients who wouldn’t move forward until they confirmed we carried Cyber Liability Insurance. Contracts are prepared by their legal teams, and projects undergo formal legal review.

Payment processes can be equally complex, involving specific forms or supplier onboarding systems. And of course, there are budgetary constraints, enterprises have budgets, but those budgets are scrutinized by multiple stakeholders.

Startups and SMBs Smaller clients usually want something simpler. A contract and a clear price point is enough. They rarely involve lawyers, and while their budgets may be smaller, they’re often more flexible with scope and terms. The focus is less on compliance and more on “Does this solve my problem?”

One of our clients at LexisNexis summed this up well:

“I have worked with Ficstar over the past 5 years. They are always very responsive, flexible and can be trusted to deliver what they promise. Their service offers great value, and their staff are very responsible and present.” —Andrew Ryan, Marketing Manager, LexisNexis

That mix of responsiveness and reliability is what enterprises need, but it’s also what small businesses value—they just don’t require the same legal scaffolding.

4. Project management and communication

Enterprises Enterprise project management tends to involve large groups of people. I’ve been on calls where a dozen team members are present, data engineers, product managers, compliance officers, and executives. Meetings are scheduled weeks in advance, and there’s usually a project owner who serves as the main point of contact while reporting progress to senior leadership.

The upside? Clarity and structure. The downside? Slower timelines. Every decision can require multiple approvals.

Startups and SMBs For smaller clients, communication is lightweight. I might be talking to just one technical person and one project owner. Meetings are often impromptu and decisions happen on the spot.

That speed can be refreshing, but it can also mean requirements shift suddenly as the client pivots their business. Our job is to stay flexible and support them through those shifts.

5. Expectations around support and partnership

Enterprises For enterprises, data is mission-critical. That means:

• Multiple ingestion points across big data systems.

• Staging pipelines before production use.

• Specific ingestion times aligned with business workflows.

• Collaboration with multiple teams, sometimes across continents.

It’s also common for us to have to reintroduce a project when new team members replace old ones. Continuity is essential, and enterprises expect us to provide that.

Startups and SMBs Smaller clients keep things simple. Data use is often isolated to one person or one team. If they need a change, it can often be applied quickly. Communication usually flows through a single contact.

This makes the partnership more personal—we’re not just a vendor, but often an advisor helping them shape how data fits into their business.

Why these differences matter

These differences aren’t just about client size, they reflect fundamentally different goals, risks, and resources.

• Enterprises need scale, compliance, and integration.

• Startups need speed, flexibility, and validation.

The key to success is recognizing these needs and adapting our service accordingly. At Ficstar, we’ve built processes to handle both ends of the spectrum.

Closing thoughts

At the end of the day, web scraping is about delivering clean, reliable, and usable data. But the journey to get there depends entirely on who you’re working with.

Enterprises bring scale and complexity, they need rigorous compliance, structured project management, and data that plugs seamlessly into massive systems. Startups bring speed and experimentation, they want to see value quickly and adapt as they go.

Both approaches are valid. And for us at Ficstar, the challenge, and the privilege, is tailoring our solutions to meet clients where they are.

As Andrew Ryan of LexisNexis put it, we succeed when we’re both “responsive and flexible” while still being “trusted to deliver what we promise.” That balance is what sets apart a true enterprise web scraping partner.