Why Data Analysis is Important for your Business
By Natalie Garrett
April 9, 2023
From proving ROI to developing a growth strategy, data analysis will continue to be critical for driving the future of businesses.
For some, the challenge of data analysis is easy to overcome with just a few clicks in Excel. To others, it is an overwhelming task that takes hours of mental energy to complete. Recent market research done by Forrester showed that insight-driven firms were 69% more likely to report year-over-year revenue growth by 15% or more.
This suggests that the days of number crunching are far from over. But don’t let this worry you! We’re going to take the pain out of data analysis by showing you three process-oriented steps.
What is data analysis?
The data analysis process works to transform raw data into information that is foundational for future business growth. Before performing data analysis, ask yourself, “What question does our data need to answer?” Starting with this question is the first step before you gather any data or work on building a report.
More times than not, questions present themselves in the form of a problem that your business is currently facing. It could also spark thoughts of an opportunity that may lie ahead. A problem, for example, could be that last month your marketing team did not generate enough qualified leads for your sales team.
To solve this problem, ask the question, “Did our campaign strategy negatively impact our marketing funnel?” Once you have identified a question for the data, you’re ready to move on to the next step:
Planning
Planning your data analysis is just as important as actually conducting it. Create a plan to how you will actually conduct your data analysis.
You’ll need to answer these questions while creating your plan:
- What data do you need in order to answer your overall question?
- Does this data already exist somewhere?
- What metrics should you analyze or report on?
An example of some key metrics might include: The number of visits to your blog, visits-to-customer conversion rate, market qualified leads to sales qualified leads and revenue.
The final step is to actually collect your data to analyze
Collecting data
Often times, businesses begin their data analysis by collecting data without having a plan or questions in mind. As a result, they find that they need more recent information or maybe even a new type of data they hadn’t considered before.
When collecting your data, it’s important to have a plan and consider the source of where it’s coming from.
There are two types of data: Internal and External.
Internal is the most common type of data that is used for analysis, and refers to data that comes from within your business. This type of data allows companies to best understand their results and identity insights that could lead to future growth. Examples of Internal data include: customer data, revenue data and conversion metrics.
On the other hand, collecting external data can also be beneficial for your overall analysis. This refers to data that is gathered from sources outside of the company, such as industry publications or census data.
Once you have collected and compiled your data, you’re ready to move on to the final step of the data analysis process: analyze and communicate.
Analyze and Communicate
As you analyze the data you have found, it’s likely you will need to revise your original question or collect even more data. After analyzing and collecting more data if needed, interpret your results.
As you are looking at your results, ask yourself these questions:
- Does the data answer your original question?
- Does the data help you defend against any objections?
- Are there any limitations on your conclusions or any angles you haven’t considered?
Once you have successfully found a way to answer these questions, sit down with your team and communicate the best course of action. By following these data analysis steps, you are making better decisions for your business because your choices and plan of action are backed by data you have collected and analyzed.
This may seem tedious, but with practice, your analysis process will get faster and more accurate, meaning that you will be making better, more informed decisions to effectively run your business.