For many businesses, web data is the bedrock of operational strategy. Online shops need data to assess their competitors, marketing agencies to analyse search engine results pages, and travel aggregators to collate pricing information from airlines and hotels.
Much of this data can be acquired through third parties. Some of it can be gained manually. At some point, however, most businesses will need to bring data collection in-house and automate it—this is where problems can start.
It’s not true that spending more money leads to better quality data collection. On the contrary, good data collection can be affordable – with the right resources.
Here are five reasons why you might be spending too much on data collection.
Lack of Clear Objectives
Many businesses fail to set clear objectives when it comes to data collection, leading to more or less data being gathered than necessary.
For example, an e-commerce website might want to keep an eye on a competitors’ SEO strategy. To this end, they track their competitors’ blog pages and product descriptions to assess which keywords they’re focusing on.
But what about their competitors’ organic social media profiles, search engine results pages, and local SEO strategy? Without these data metrics, they lose a complete picture, and all other data gathered becomes less valuable, clear and relevant.
On the other hand, companies often gather too much information. Let’s say, instead, the e-commerce website was more concerned with its competitors’ pricing strategy rather than SEO; it might be redundant to scrape blog pages and product descriptions — only the item pricing itself.
It’s important to be conscious of your resources and scrape only what you need.
Not Automating Data Collection
These days, you probably wouldn’t keep your company’s accounts in a notepad or use an abacus to run calculations. It’s no different when it comes to data collection.
The fastest and easiest way to collect data is to automate it. Of course, you could regularly check every website and search engine result page manually, but it’s an enormous time-sink (especially when there are alternatives).
Manually collecting data also raises big risks when it comes to human error. Naturally, mistakes happen, but it’s your company’s reputation and operational integrity that are on the line.
It’s far better to automate the data collection process to save on labour costs. Not only is it quicker, but software tends to make fewer mistakes than humans. They also more easily integrate within wider systems.
To automate, however, you will need to use proxies to bypass IP bans and rate limits. Ideally, you’d opt for proxy solutions that self-heal and cycle IP addresses, meaning that if the server is blocked by websites or search engines, it will switch to a working one. It’s essential to keep the data flow running.
Using Outdated or Inappropriate Tools
Once you’ve decided to automate, you’ll need to choose the right infrastructure to do so. It’s worth restating point one: set clear objectives. This way, you don’t spend too much money on software with features that you won’t need or use.
In any case, there are three other costs to consider when choosing the right tool to collect data. The first is maintenance costs. Outdated software can have high maintenance costs in terms of lost productivity, as well as paying someone to fix it if it crashes. This can be up to 20% of a software’s annual licensing cost.
The second is a high relative cost. In simple terms, this means overspending when there are more affordable alternatives that do the same thing – maybe even better.
The final cost that’s not often considered is the cybersecurity risk of using outdated software. Data is valuable, meaning that any kind of web scraping operation you run is a decent target for malicious actors.
Often, custom software is ideal for many businesses. It’s secure, affordable, and reliable. If you go down this road, you’ll need to make sure you use the right proxy solutions to support it.
Overlooking Data Quality
Once your automated data collection operations begin, you’ll need to consider the quality of the data you collect. Think of this as an invisible cost: bad quality data leads to misinformed operational decisions and subsequent revenue loss.
Bad-quality data can take many forms, such as:
Outdated information.
Duplicate entries.
Inaccurate details.
Incomplete records.
Misclassified information.
Much of this can come from the websites being scraped, and there’s not much you can do, even if you’ve got the right software infrastructure. However, small changes can improve data quality.
For example, you should consider implementing a proxy solution with constant uptime. This means that there are never any gaps in your data. Likewise, a proxy solution with international server locations can give you access to geo-specific data scraping, further improving the depth and quality of your data.
Not Using The Right Proxy Solution
Not using the right proxy solution can massively inflate your costs. Proxies are essential to data scraping, as they allow you to bypass IP bans and rate limits.
However, not all proxies are created equal. Good proxy solutions rotate IP addresses automatically, saving you the hassle. Likewise, they provide sufficient geographic coverage, thereby increasing access to region-specific content and decreasing the risk of detection. They’re also more secure and encrypted, protecting users from malicious actors.
Without these features, companies might end up spending more on additional proxies or sophisticated software to overcome these hurdles rather than optimising what they already have.
If you’re looking for a reliable and trusted proxy solution to supercharge your data collection efforts, please contact us at claudiu@appstractor.com
