在本文中，我们将讨论一些常见的数据收集用例，以及它们在有无代理情况下的结果：

• 电子商务
• 金融
• 人力资源

电子商务

涉及电子商务前端和后端行业的公司通常会收集以下常见的数据集：

• 竞争对手的产品定价
• 消费者的评论（包括本地评论和跨平台评论）
• 销售量和销售点（PoS）数据

当公司手动收集这些数据时，过程非常缓慢且乏味。网站结构经常变化，数据集实时更新。这可能导致一些负面的货币/业务结果风险，例如：

• 当你获取到错误的竞争对手定价（因为价格变动比你收集的速度快）时，你的动态定价策略会受到影响。不仅会在这个特定销售中损失大量销售量，而且在长期内，消费者不会回到被认为“价格过高”的数字零售商。
• 评论帮助你了解竞争对手消费者的痛点。例如，如果他们的产品难以组装，你可以提供免费组装服务，从而提高销售量。但是，如果你的竞争对手已经解决了这个问题，而现在有另一种吸引消费者兴趣的方法（例如隔夜运输），你可能无法及时发现这些过时的信息，浪费了时间和资源。
• 销售量帮助你了解当前流行的产品，PoS数据揭示了客户偏好的购买地点和方式。这可以是非常有价值的信息，例如，如果粉红色的星形太阳镜在使用PayPal时流行，你可以利用这些信息增加订单数量/生产水平/营销活动，并为那些使用PayPal完成订单的人提供特别折扣/优惠券。

金融

涉及金融行业的公司通常会收集以下常见的数据集：

• 证券流动
• 与特定股票或行业相关的新闻报道
• 关于股票（例如AMC娱乐控股公司）或商品（例如黄金或白银）的社交媒体情绪

不使用代理收集这些数据的风险包括：

• 流动性或“股票交易量”对一些股票交易员、基金经理，尤其是日间交易员来说是一个非常重要的指标。它表示对股票的兴趣、买卖意愿以及当前价格的稳定性和流动性。当你根据不准确的股票交易量进行交易时，你的决策可能会被负面或正面影响，导致你在自己的或客户的投资组合上做出错误的决策。
• 证券对新闻报道非常敏感，例如，如果FDA批准了一种药物并且该新闻传播开来，会影响价格。如果CEO因欺诈被起诉，该新闻发布后会有实际的财务后果。当你根据旧新闻进行交易时，你会失去动量以及具体的情报优势。
• 社交情绪，如Reddit的Wall Street Bets（WSB）组，对股票流动有重大影响。当“大空头挤压”的策划者上传帖子表示“持有AMC股票，因为它将‘上月球！’”时，就股票估值而言，这意味着实际意义。

人力资源

涉及人力资源/人才招聘相关行业的公司通常会收集以下常见的数据集：

• 来自社交媒体/商业网络的人员数据（包括特殊人才、非凡的工作/培训经验、语言技能、特定计算机程序的熟练程度）
• 公司数据（员工人数、增长率、在其行业中的独特销售主张等）

不使用代理收集这些数据的风险包括：

• 由于各种原因，收集到的不准确人员数据。例如，相关人员可能已经被雇佣，其技能可能发生了变化，使其对潜在雇主的吸引力更大或更小。
• 公司数据也有快速变化的风险。例如，如果相关公司在你首次记录时是一个小型初创公司，并且在过去6个月中经历了爆炸性增长，它可能对某些潜在员工的吸引力较小。这是因为一些非常有才华的人实际上更喜欢在较小的公司工作，他们在这些公司中的影响力比在大型公司中更大。

结论

手动进行数据收集而不使用代理不仅速度慢且乏味。更重要的是，它会扭曲你基于准确实时数据做出明智商业决策的能力。使用代理速度更快、更高效，并且会为你提供准确的竞争对手和目标受众的实时行业信息。

In this article, we will discuss some common data collection use cases and how they would end with, and without proxies:

• eCommerce 
• Finance 
• Manpower 

eCommerce 

Common industry datasets for companies involved both in the front, and back-end of eCommerce-related industries include:

• Product pricing among competitors
• Consumer reviews both natively, and across different platforms 
• Sales volume, and Point of Sale (PoS) data

When a company seeks to collect these data points manually, it is a very slow, and tedious process. Site structures change frequently, and datasets change in real-time. This can lead to some risks with negative monetary/business outcomes, for example: 

• When you are obtaining competitor pricing that is wrong (as it is being changed quicker than you can collect it) then you are putting your dynamic pricing strategy at risk. You risk losing a lot of sales volume, not only on this specific sale but in the long term, as consumers won’t return to a digital retailer who is perceived as ‘overpriced’. 

• Reviews help you gain insight into your competitor’s consumer pain points. For example, if their products are hard to assemble, you may offer free assembly with every purchase, thereby boosting sales. But if your competitor has already addressed this issue, and now there’s a different way to attract consumer interest (say overnight shipping), you may not find this out in time with your outdated information, wasting time and resources on an out of date value proposition. 
• Sales volume helps you understand which products are currently popular and PoS data sheds light on where/how customers prefer to carry out their purchases. This can be very valuable information, for example if pink, star-shaped sunglasses are trending using PayPal, you can use this information to ramp up your order quantities / production levels / marketing campaigns, and special discounts/coupons for those who complete orders using PayPal. 

Finance 

Common industry data sets for companies involved in the financial industry include:

• Securities movement 
• News stories pertaining to a specific stock or industry 
• Social media sentiment about a stock (e.g. AMC Entertainment Holdings) or a commodity (such as gold or silver)

The risks of collecting this data without proxies include:

• Movement or ‘stock volume’, as it is commonly known as, is a very important metric for some stock traders, fund managers, and especially day traders. It is indicative of interest in the stock, willingness to buy/sell as well as current price stability, and mobility. When you are trading based on inaccurate stock volumes your decisions can be negatively or positively skewed, leading you to make bad decisions regarding your or your customer’s portfolio. 
• Securities are very sensitive to news stories, for example if the FDA approves a drug and that story goes viral it impacts prices. If the CEO is indicted for fraud, and that story comes out, it has real financial consequences. When you trade based on old news, you lose momentum, as well as your concrete informational advantage. 
• Social sentiment, as was the case with the Reddit-based Wall Street Bets (WSB) group, had a major impact on stock movement. When the masterminds behind ‘The Big Short Squeeze’ uploaded posts to ‘hold AMC stock’, as it was ‘going to the MOON!’ that meant something in real terms as far as the stock’s valuation. 

Manpower 

Common industry data sets for companies involved both in manpower / talent-sourcing related industries include:

• People data from social media /business networks (including special talents, out of the ordinary work/training experience, language skills, proficiency in specific computer programs)
• Company data (number of employees, rate of growth, Uniques Sales Proposition in their industry etc)

The risks of collecting this data without proxies include:

• Collecting people data that is inaccurate for a variety of reasons. For example the person in question could already be employed, and their skills may have changed in a way that makes them more /less attractive to potential employers.
• Company data also runs the risk of changing at a fast pace. So for example, if the company in question was a tiny startup when you first logged it into your systems, and has experienced explosive growth over the past 6 months, it may be less attractive to certain potential employees. This is because some very talented people actually prefer working for smaller companies where their ability to have a real impact is much greater than at a larger corporation.

The bottom line

Performing data manually, without the help of a proxy can not only be slow, and tedious. But more importantly, it can distort your ability to make smart business decisions based on accurate real-time data. Using proxies is quicker, more efficient, and will provide you with an accurate live industry of your competitors and target audiences.