How to Become a Data-Driven Business

Data is one of the most important by-products of any business. It can help you make better decisions, improve your processes, and even increase your profits. However, many businesses don't take advantage of data because they don't know how to become data-oriented. In this blog post, we will discuss how to integrate data into your daily business decisions. We'll start by defining what type of data will be most helpful to you, then move on to how best to collect and clean that data. Finally, we'll look at how to organize the data so you can discover the insights most useful to your business. Once you have applied these insights, you will become one step closer to becoming a data-driven business!

What Data Should I Be Collecting?

When it comes to collecting data, you first need to determine what type of data will be most helpful to your business. Here are some questions to ask:

• What are my goals?
• What are my current pain points?
• What areas of my business could I improve?
• What do I want to track over time?
• Who are my customers?
• What do my customers want?

Once you have answered these questions, you will have a better idea of what type of data to collect. This is a great exercise for any business to undergo. You may be surprised at what you discover!

How Do I Collect & Clean My Data?

The next step is to actually collect the data. This can be done in several ways, including surveys, web scraping, transaction data, and more. The easiest win here is to make use of the existing data you have. Depending on the business, this data could be found in software such as QuickBooks, ADP, Salesforce, etc. If you do not have the data you need and must go collect that data, a common method is to use surveys. Surveys are a great way to collect data from a large number of people in a short amount of time. You can use surveys to collect data on anything from customer satisfaction to product feedback. You may also need to look into integrating new systems and software to capture the desired data. Transitiv’s FIT has 200+ integrations to easily connect your data into 1 organized interface.

Once you have collected your data, you will need to clean it. This is an important step because it ensures that the data is accurate and ready to be analyzed. Data cleaning involves removing any invalid or duplicate data, as well as formatting the data so it can be easily read and understood. This step can be time-consuming, but it is important to do it right so you don't waste time later on analyzing bad data.

How Do I Organize My Data?

The next step is to organize your data. This can be done in several ways, but the most important thing is to make sure the data is easy to understand and use. One way to do this is to create a data dictionary, which is a document that defines all of the variables in your data set. This is especially helpful if you have a lot of data or if you plan on sharing your data with others. Another way to organize your data is to create visualizations. This can be done using software such as Tableau, Microsoft Excel, or Google Sheets. Visualizations help you to see the data differently and can sometimes reveal patterns that you wouldn't have seen otherwise. Oftentimes, this step may require a technically-skilled individual with a background in big data, utilizing coding languages such as python. Luckily, there are companies, such as Transitiv that handle the data organization & presentation for you to help expedite the entire process.

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What is the Data Telling Us? How do We Apply it to the Business?

The final step is to look at the data and discover the insights most useful to your business. This step can be done in several ways, but the most important thing is to make sure you are looking at the right data, and that it is statistically significant. Understanding statistical significance will allow you to know which data are more reliable vs others. There are tools built into many software, including Excel that calculate statistical significance. Here is a quick refresher on statistical significance.  

Once you understand what the data is telling you, it's time to look at how the data applies to the business. For example:

• Do you need to change your marketing strategy?
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  Example: You've discovered that although LinkedIn advertisements are driving fewer leads overall, the quality and average lifetime value of those leads are 32% higher than other marketing channels.

• Do you need to improve your product?
  
  Example: Customers between 3-6 mos old are demonstrating 50% less utilization of a key product feature vs customers 1-2 years old and this is resulting in a 30% greater churn in newer customers.

• Do you need to better understand your customers?
  
  Example: New customer sales to individuals 24-35 have decreased by 25% over the past year, however, retention & activation for existing customers in this age group remains static.
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By becoming a data-driven business, you’re able to harness the following benefits:

• Data-driven businesses tend to be more profitable.
• Data-driven businesses are better at making predictions.
• Data-driven businesses make better decisions when armed with the right data.
• Data-driven businesses are in a better position to serve their customers more adequately.
• Data-driven businesses have a competitive advantage over those that do not utilize data.

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As you can see, data can be extremely helpful in making business decisions. By becoming a data-driven business, you will be able to make better decisions that are based on evidence and facts, rather than guesswork. If you're not sure where to start, there are many resources available online, including blogs (like this one!), books, and courses. And, of course, there are businesses such as Transitiv that are optimizing the entire data collection, cleaning, and presentation process for customers so they can focus on allocating resources elsewhere. So what are you waiting for? Get started today!

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