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Why You Should Collect Multiple Types Of Data From Multiple Sources

Every business needs and can benefit from data. Many businesses utilize it to develop predictive insights and learn more about their markets, industries and customers. It’s important to seek data from varied sources and collect it via different methods. Here are some reasons you should collect multiple types of data from multiple sources.

1. Different Types of Data Can Produce Different Insights

You can collect internal and external data. If you collect external data, you should seek out first, second and third-party data. You’ll receive first-party data from customers directly, while second-party data comes from sources such as business partners and third-party data comes from outside sources unrelated to your company or customers. Different types of data, such as a high quality survey, cold calling or consumer purchase information can provide you with varying insights and results so you can produce more cohesive and comprehensive insights.

2. You Can Improve Or Maintain Your Data’s Integrity

Ensuring your data is coming in from multiple sources and in multiple forms can help you improve or maintain its integrity and accuracy. More data means more information to analyze and utilize, which means your data analysts will be more likely to catch errors, outliers, invalid results, misleading data and other data-related issues. This means your company will have a better handle on quality control and quality assurance regarding data.

3. Combining Qualitative And Quantitative Data Is Important

Multiple data types and sources provide you with more comprehensive analytics. Mixing data types, including qualitative and quantitative data, helps your analysts reduce gaps in your knowledge. Qualitative and quantitative data can both come from the same sources but may be collected in different ways. Qualitative data is more fluid but allows you to understand more about descriptions and interpretations, such as customers’ feelings. Quantitative data provide you with numbers and measurements. Together, they increase your overall understanding.

4. You Can Catch Emerging Trends More Quickly

The more data and sources you have at your disposal, the better equipped you will be to identify existing trends and decide whether to join them. Not every trend will be apparent in every market or industry, so one data source may not provide you with any information on it. Other sources may provide large amounts of data, highly detailed information or both. When you have this information at your disposal, you’ll be more prepared for potentially useful and lucrative trends.

5. It Can Provide You With More Context for Decision-making

One of the main reasons to collect multiple data types from multiple sources is to provide as much context as possible. The more context you have, the stronger your decision-making capabilities will be and the higher your confidence in those decisions will become. For example, you need both internal and external data to make appropriate decisions regarding internal changes such as business expansions or organizational restructuring. If you only utilize internal data, you may miss important external factors, such as social media trends or changes in related industries.

6. You Can Access More Information More Easily

If you already have multiple data sources, you’re able to access more types of data via those sources. If you collect multiple data types, it will likely be easier for you to develop collection methods for other types of data and decide how to collect data from additional sources. You can also leverage your existing sources and data types to inform the tools you use to collect data. If you decide to implement an AI algorithm to collect data, for example, you can choose to apply it to your existing data sources or develop new workflows for new sources.

To successfully collect multiple types of data from multiple sources, you should first determine what types of data you need. Then you can make decisions regarding sources and collection methods. Some types of data lend themselves better to one collection method than others and you may find some sources more useful than others.

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