Assuming that when two things are related
Posted: Thu May 22, 2025 9:35 am
One of them is the cause is called false causation, and it is one of the most common mistakes in data analysis. Often, there is another factor that is causing the trend you are finding. So take the time to gather enough information to make sure your conclusions are accurate.
Compare current data with the previous period
If you have trouble spotting trends and patterns, it may be because you are looking at the data in isolation. You are failing to spot trends because everything you see is just a part of something bigger. You are missing the connection to the previous period’s data.
To find this connection, compare your current data to historical data. If that’s not possible—for example, you’re looking at usage data for a brand-new product feature, or this is your first analysis—then look at your industry’s benchmarks.
A Google search for “[department] performance kazakhstan phone number list statistics” or “[department] [industry] statistics” will provide useful benchmarks for different companies, departments, and industries. Journals on the subject, as well as research presented at conferences, are also good sources of benchmark data.
For example, Zendesk Benchmark allows companies to compare customer support data to industry averages:
How to Analyze Data: A Basic GuideZendesk Benchmark is a way to compare your data to a benchmark, helping you assess the effectiveness of your support team within your industry.
Zendesk Benchmark is a way to compare your data to a benchmark, helping you measure the effectiveness of your support team within your industry.
Tip: If you use benchmark data, it may be difficult to find companies of similar size or maturity. So use the numbers as a guide, but do not directly compare the results.
Compare current data with the previous period
If you have trouble spotting trends and patterns, it may be because you are looking at the data in isolation. You are failing to spot trends because everything you see is just a part of something bigger. You are missing the connection to the previous period’s data.
To find this connection, compare your current data to historical data. If that’s not possible—for example, you’re looking at usage data for a brand-new product feature, or this is your first analysis—then look at your industry’s benchmarks.
A Google search for “[department] performance kazakhstan phone number list statistics” or “[department] [industry] statistics” will provide useful benchmarks for different companies, departments, and industries. Journals on the subject, as well as research presented at conferences, are also good sources of benchmark data.
For example, Zendesk Benchmark allows companies to compare customer support data to industry averages:
How to Analyze Data: A Basic GuideZendesk Benchmark is a way to compare your data to a benchmark, helping you assess the effectiveness of your support team within your industry.
Zendesk Benchmark is a way to compare your data to a benchmark, helping you measure the effectiveness of your support team within your industry.
Tip: If you use benchmark data, it may be difficult to find companies of similar size or maturity. So use the numbers as a guide, but do not directly compare the results.