How you gather data can greatly impact your business, for better or worse. However, by following best data collection practices, you can ensure that you not only get the best data possible but also put it to good use. With this in mind, here, take a look at what these best practices are and how to implement them.
Developing a Game Plan
Before you even start data gathering, you must first understand what data you want to collect and how it will affect your business. This will keep you from spending time and resources collecting data that is virtually useless to you.
For example, suppose you want to get more of your social media followers into your sales funnel. In that case, you should collect data on your own social media efforts and on the effectiveness of your sales funnel itself. Going through the data from start to finish will allow you to pinpoint weak spots that are having issues so that you can fix them.
When you know exactly what aspects of your business you want to improve, you’ll know what data you should collect. This will help you focus your efforts and rapidly improve your business.
Keep Your Data Secure
Any data you gather can be used against you under the right circumstances. This applies to data gathered through methods such as surveys, focus groups, and interviews and to any data you gathered via scraping online. It would be a bad look if the data you scraped got leaked because then your competitors would know what you’re up to and would likely install more significant anti-scraping countermeasures on their websites.
Safeguarding your data means taking several practical steps. Firstly, back it up so that if there is a system crash or wipe, you will still have access to it. Also, make sure that the data doesn’t contain personally identifiable information.
You don’t want someone hacking you and then doxing your customers after all. Lastly, make sure that your basic deterrents, such as your firewall, antivirus protection, and anti-malware software, are up-to-date. This will help you to keep your data safe from security breaches.
Understand All Regulations Concerning Data Collection
In some areas, data collection is more heavily regulated than in others. This means understanding rules that come from the government where you live, but also the TOS of any online services or software that you are using.
For example, in the US, the FCC has special regulations concerning broadband data collection. Therefore, ensuring you follow all applicable rules and regulations in your area will help ensure that there are no legal problems for you to deal with down the road.
Ensure the Quality and Accuracy of Your Data
Inaccurate data is more than just a waste of time; it can harm your business. This issue is compounded when you realize that many anti-scraping systems deliberately send fake data to your scraping software if it gets detested.
The best way to ensure the quality and accuracy of the data you collect is to have someone oversee it and manually check it. Common tasks include cross-referencing data from various sources to ensure that it matches up so that its accuracy can be verified. Examples of types of data that should be double-checked like this include social media handles, login information, mobile numbers, and IP addresses.
When to Be Transparent
There are times to be transparent with your data collecting and times not to be. When you’re scraping data online, you probably don’t want to announce it to the world. This could lead to the targets of your scraping taking greater countermeasures, as previously mentioned.
If you are performing data collection methods, such as focus groups and surveys, then you 100% want to be transparent about what you’re doing and why.
Best Practices for Better Business
When following a set of best practices for gathering data, it is important not just to think of them as a set of rules but to understand that they are methods for making your business more successful. From protecting your data and avoiding legal problems, there is always an upside to these best practices that can’t be ignored.
