6 Steps to Becoming A Data-Driven Business
Success in today’s business landscape requires the intelligent use of data. As evidenced by Dennis Kelly’s work with the direct mail software Postalyticas, collecting important information through tech tools gives businesses a clearer understanding of their customers. That enhanced understanding allows them to design more effective campaigns.
Becoming A Data-Driven Business
In today’s competitive market, becoming a data-driven business is essential. You need to find new and innovative ways to collect, process and analyze data in order to make better decisions and scale up. It might seem complicated if you’re not familiar with data collection and analysis. It’s a process that requires time, patience and trial to effectively leverage your data and make data-driven decisions.
To help you figure out how to use data in your business, we’ve outlined six steps you can follow.
Step 1: Identify the Problem
Before you can determine what kind of data you need to collect, you must first identify what problem you’re trying to solve. Let’s say you’re an e-commerce business with an active social media presence. Despite regularly releasing content on your social media accounts, you don’t seem to get much traction online. Sales could be higher if more people knew about your brand. From there, you’ve identified a vague goal: you need to increase social media engagement to attract more customers.
Step 2: Track the Right Metrics
To make the best use of data, you need to determine which pieces of information can best support your specific goal. In the example above, you’re focused on social media. That means looking at metrics relevant to your social media visibility: likes, comments, shares, and clicks. When selecting metrics to track, it’s important to understand why each matter. In this case, likes, comments, and shares tell you which pieces of content roused enough of a reaction from your followers.
Demographic data, such as age, gender, occupation, and interests, can also contribute to your goal. They give you a clearer picture of who your audience is, and how you can appeal to them.
Step 3: Define a SMART Goal
Once you’ve determined which metrics are most relevant, you can finally design a SMART goal. SMART stands for specific, measurable, assignable, realistic, and time-bound. If your problem is a lack of engagement, your goal then is to increase your post engagement by a specific number within a specific time frame. For example, you can aim for a goal of 500 likes per post within a timeframe of two months. To determine how you achieve that goal, turn to past metrics.
Step 4: Assess Past Results
The next step is to assess why you got specific metrics in the past. In the case of the social media campaign, ask yourself: why did specific posts get engagement and not others? Were there any common threads in these posts? Can your demographic data tell you anything about why certain posts were successful?
Step 5: Create An Action Plan
By assessing past metrics, you can figure out how to tweak your campaign to get better results. For example, in assessing your social media engagement, you discovered that your posts tended to gain more traction when they were posted on Sunday nights. This aligns with your knowledge of your demographic: since your followers are mostly students, they spend fewer hours on social media on school days.
From these discoveries, you can finally make a plan of action: increase engagement by creating a posting schedule that aligns with your followers’ browsing habits.
Step 6: Train Your Team
Once you have a clear understanding of how to use data to achieve business goals, you need to get the entire team on board. Data literacy is so necessary today in business that modern business administration programs include data management in their curriculums. Training in data analysis concepts helps today’s students gain a competitive edge in the business world. However, modern organizations have yet to catch up, and employees who did not study these topics as part of their education or training are falling behind.
Statistics show that only 39% of employers offer data training opportunities. As a result, 75% of workers say they feel overwhelmed when working with data. Give your employees access to data training resources, such as LinkedIn Learning, Coursera, and Udemy. If possible, you can also include data training in employee learning and development programs.
As the business world becomes more dependent on digital technologies, data plays a bigger role in business results. For any business to thrive, it needs to use accurately and efficiently collected information to guide its campaigns and business decisions.
