Market and competitive intelligence used to be slow, manual, and fragmented. Analysts would export spreadsheets from a few tools, ask local teams for screenshots, and hope nothing important changed overnight. Today, markets move faster than ever—and business decisions are only as good as the data behind them.
Proxies give market analysts a practical way to see what real customers see in different countries, on different devices, and in near real time. With the right setup, you can track prices, assortments, messaging, reviews, and macro signals across dozens of markets without leaving your desk.
This article explains how proxies fit into business and competitive intelligence workflows, what types of proxies make sense for analysts, and how to design reliable, compliant data collection pipelines that your team can trust.
For business intelligence teams, proxies are less about “hiding” and more about getting a truthful, consistent view of global markets.
Used correctly, proxies help you:
See localized experiences
Check how prices, promotions, and product assortments differ by country, region, or even city.
Avoid personalization bias
Reduce the impact of cookies, account history, and prior browsing behavior that can distort what you see.
Collect structured data at scale
Feed dashboards and models with fresh data from retailers, marketplaces, and review platforms.
Stress-test strategies and campaigns
Monitor how competitors change their messaging, pricing, or channel mix over time.
Protect internal networks and identities
Route automated research through controlled proxy infrastructure instead of employee laptops.
When proxies are integrated into your market intelligence stack, you get a repeatable, auditable way to capture what’s happening “out there” without relying solely on vendor reports or anecdotal local feedback.
Different teams use proxies in different ways, but most applications fall into a few repeatable patterns.
Analysts use proxies to monitor:
By routing requests through datacenter proxies in target markets, you can build time series of price and promo data that support:
For assortment and supply-side analysis, proxies help answer questions like:
Scraping category and product listing pages via proxies allows your team to map who sells what, where, and how often it changes.
Marketing and brand teams rely on proxies to see:
Because many sites personalize content by region and IP, proxies are often the only practical way to see what a first-time visitor in a given country would encounter.
Customer feedback is a rich source of insight but often spread across multiple platforms and regions.
Proxies enable you to:
This kind of review intelligence is especially powerful when combined with text analytics and topic modeling.
Beyond product-level detail, proxies support macro-level questions such as:
By sampling category and search pages regularly across multiple geographies, analysts can build early-warning signals for change and opportunity.
Not every project needs the same proxy setup. For most analysts, the goal is reliability and representativeness, not maximum stealth.
For many price, assortment, and messaging projects, dedicated datacenter proxies are ideal:
Pros
Typical use
In some cases, you may need IPs that look more like consumer traffic:
ISP or residential proxies cost more and require stricter governance. Many BI teams reserve them for niche, higher-friction targets, while running the majority of workloads on datacenter infrastructure.
Static IPs
Rotating IPs
Most teams use a mix: static IPs for “sensitive” partners or repeated visits, and rotating IPs for wide, low-friction category and search coverage.
The best proxy setups are not one-off scripts—they are pipelines. Here’s how BI teams typically structure them.
Start from business questions, not technology:
From there, list specific target websites, endpoints, and page types.
Next, assign proxy requirements:
This mapping becomes your proxy “bill of materials” for the project.
Most BI teams use languages like Python, Node.js, or Go to gather data. Regardless of language, the patterns are similar:
If your organization already has integration and code tutorials for proxies, your development team can reuse those patterns for new BI tasks.
Raw HTML or JSON needs to be transformed into something analysts can use:
Once this foundation is in place, visualization tools and dashboards can do the heavy lifting.
Proxy-backed pipelines are never truly “finished.” Markets change, sites redesign their pages, and anti-bot rules evolve. Make quality a first-class concern:
This feedback loop keeps intelligence products trustworthy and strengthens internal confidence in proxy-powered data.
Market and competitive intelligence teams must balance ambition with responsibility. Proxies are powerful, but they come with obligations.
Proxies should never be used to:
Focus on publicly accessible content and align with your company’s legal and data ethics guidelines.
Even for public data, you should:
Compliance is not just a legal checkbox—it also protects your long-term access to critical sources.
Clusters of uncoordinated scripts can create risk. A more sustainable approach is to:
Central governance reduces duplication, improves bargaining power with vendors, and makes audits far easier.
Consider a global CPG company that wants to track how its products and competitors are positioned online.
Without proxies, analysts might:
With a proxy-backed pipeline, the same team can:
Over time, they can layer in additional sources—reviews, search results, advertising impressions—without redesigning their underlying infrastructure.
For many BI teams, the biggest obstacle is not methodology—it’s infrastructure. You need proxies that are:
Dedicated datacenter proxies are often the best fit for these requirements. They provide:
Once your developers have clear integration patterns, analysts can treat proxies as just another piece of core data infrastructure: always there, always reliable, and easy to scale as new questions arise.
Yes, proxies themselves are legal, but how you use them matters. Market and competitive intelligence teams must stick to public data, respect website terms, and comply with privacy and data protection laws in each jurisdiction.
Dedicated datacenter proxies are usually the best starting point for analysts. They offer a good balance of cost, speed, and reliability for price tracking, assortment monitoring, and competitive messaging analysis across regions.
Most BI and competitive intelligence use cases do not require residential or mobile proxies. These are more expensive and typically reserved for highly sensitive, consumer-facing targets. In many cases, carefully managed datacenter proxies are sufficient and easier to scale.
It depends on your coverage and refresh frequency. A small team might start with a handful of dedicated IPs per key region, then scale into larger pools as the number of tracked products, pages, and markets grows.
For stable categories, daily or weekly snapshots are often enough. For dynamic markets with frequent price changes or aggressive promotions, you may want multiple collections per day—but always within reasonable rate limits.
By routing traffic through IPs in different countries or regions, you can see the same pages and search results that local users see. This is crucial when prices, assortments, and marketing messages differ by market.
The biggest risks are over-aggressive crawling, ignoring site rules, and relying on untrusted proxy sources. These can lead to IP bans, poor data quality, or potential policy and compliance issues if not managed properly.
Use a reputable provider, centralize proxy governance, and monitor success rates, errors, and latency over time. Combine that with clear internal rules, documentation, and automated alerting so your market intelligence pipelines remain stable as they scale.
For market analysts and competitive intelligence teams, proxies are not a niche technical tool—they’re a way to see the world more clearly. When integrated thoughtfully into your data pipelines, they reveal how products, prices, and messages shift across regions and channels in near real time.
The key is to treat proxy infrastructure as part of your core BI stack: governed, monitored, and designed for long-term use. With the right mix of datacenter IPs, robust code integrations, and clear internal policies, your team can move beyond one-off snapshots and build a sustainable, constantly refreshed view of global markets.
Once you have that foundation, every analyst, product manager, and strategist in the organization benefits from a more accurate picture of what’s really happening outside your four walls.
Ed Smith is a technical researcher and content strategist at ProxiesThatWork, specializing in web data extraction, proxy infrastructure, and automation frameworks. With years of hands-on experience testing scraping tools, rotating proxy networks, and anti-bot bypass techniques, Ed creates clear, actionable guides that help developers build reliable, compliant, and scalable data pipelines.