Nowadays, data is worth even more than gold, precisely because we live in the digital era. The data enables our company to adjust itself and be more precise with every step it takes. It is the process of collecting, measuring and analyzing accurate insights for research using standard validated techniques. A researcher can evaluate their explanation on the basis of collected data. It is the primary and most important step for research in any field. Success in data use lies behind a more productive and, mostly, strategic collection. Not only do we collect this information, but it is also important to know where to find it, how to organize it, and, lastly, analyze it.
The most common techniques used in Data Collection are as follows:
Surveys & Polls
- It is the process of obtaining data through certain mediums like telephone interviews, face to face interviews etc.
- This medium generally focuses on a targeted group of people about their opinions, behavior or knowledge. It is helpful in identifying customers’ requirements / preferences.
- Assessing customer or employee satisfaction such as identifying or preauthorizing problems to address. Evaluating proposed changes and also assessing whether a change was successful.
Interviews & Focus groups
- Generally, in focus groups a coordinator guides the group on a set of predetermined set of topics.
- The coordinator arranges the environment in such a way that it encourages participants to share their perceptions and point of view.
- This is a very interesting way of data collection as the information that will be collected varies from person to person.
- Also, there is another drawback to this method is whenever the group becomes large some participants try to dominate the stage while others fade into the background.
Social Media Monitoring
- One of the most important methods for data collection as the process is non-stop and plays an important role in the digital era where the data is vast and organizations have the potential to use that data to revolutionize their business and encourage people to visit their platforms on a daily basis.
- These datasets are built by acquiring these data and then feeding these data for the ML process.
Subscription / Membership
- Signing up to your email list or rewards program almost always requires providing valuable customer data.
- The main benefit of such a method is that your leads are more likely to convert. They have already shown an interest in your brand.
- We just need to remember that asking for too much can discourage people from joining your subscription, but if we’re not asking for enough your data analytics won’t be as valuable.
- This method makes the work process much easier to collect data as more customers/interested individuals subscribe, the more the organization evolves into a global giant.
Transactional Data Collection
- This process generally involves transactions that happen on a daily basis.
- It mostly includes the time of transaction, the place where it occurred, the prices of the specific items purchased, the payment method employed, discounts if any, other quantities and qualities associated with the transactions.
- Transactional data is usually captured at the point of sale. In other words, transactional data is data generated by various applications while running or supporting everyday business processes of buying and selling.
- A large and intricate web of point-of-sale servers, security software, ATM, and payment gateway data exists, originating from every possible device used to complete a financial transaction.
- Therefore, transactional data plays an important role when collection of data is involved through this medium as it is a very important function where the data that comes in is unlimited.
Data collection is the process of gathering and measuring information on variables of interest, in a recognized systematic fashion that enables one to answer stated research questions, test supposition, and evaluate outcomes. These are key elements of the scientific research process as well and data is the result collected from testing. The conclusions drawn are according to our own interpretation of the data.