Data Basics

Digital Marketing - Study Notes:

What is data?

To work with data effectively, you must first understand what data actually is. Essentially, data is information in a raw, unorganized form – such as letters, numbers, or symbols – that refer to or represent conditions, ideas, or objects. 

Raw data is the starting point. An analyst’s or digital strategist’s job is to structure the raw data in a way that enables them to derive meaning from it. Data helps you to make informed decisions and to develop your digital strategy. It also helps to mitigate the risk of taking uninformed actions that are of little value to your strategic planning. So, rather than guessing what to do, or relying on a gut feeling, familiarity with data and data trends can guide you in making better decisions. 

Data-driven marketing

Once it’s collated and analyzed correctly, digital marketing data can help you understand your customers and help optimize how you can engage with them. Data analysis can also enable you to identify success. It can provide insights into how and why your audience interacted with a campaign message, creative, or promotions, and provide valuable information when planning future campaigns. This is known as data-driven marketing. It is marketing that is built on data analysis, rather than guess work. 

Furthermore, the use of data for decision making can facilitate faster stakeholder buy-in for your strategies. Ideally you should be basing your decisions and strategy on metrics and trends that are free from bias, and not being swayed by your own emotions, opinions, or pre-conceived ideas. As a result, it’s easier to convince others of the value of your plan and achieve a positive outcome, because the data provides validity. So, when you say things like: “The data indicates that this is a good course of action to grow the business” or “The data shows the risks associated with this digital strategy”, you can manage resistance or any potential interpersonal conflicts in relation to your digital strategy. 

In most cases, people who might disagree with you tend to find it hard to disagree with what the data says. Similarly, if you are trying to convince colleagues against taking a course of action, using data to highlight the risks or problems with their plan is a more effective means than disagreeing with them from a personal perspective. Familiarity with data and trends assists in all business situations and helps provide a guide to optimize your digital strategy. 

Benefits of data-driven marketing

Data-driven marketing has several benefits. 

•      Optimize campaigns: Data can provide you with information such as what your target demographic typically buys and how they buy it. It can also reveal the time of day, week, month of the year when they are likely to make the most purchases. Data analysis can also help reveal how your competitors are reaching the target market. With real-time data, you can optimize a marketing campaign by adjusting it according to your latest data.
•      Improve product quality: Data can highlight your target audience’s needs and pain points. This, in turn, can help you strategically improve a product or service. 
•      Drive performance: Data provides digital marketers with information to back strategic decisions and help to keep up with changes in the business environment, again, rather than relying on gut feelings and emotions or simply hoping for the best. 

Challenges facing digital marketing strategists and data analysts

Although data can bring several benefits, working with data can also be challenging at times. There are several reasons for this:

•      Limitless: Data is potentially limitless, so the first challenge is that the sheer amount of data available can be overwhelming. 
•      Interpretation: With the abundance of data, you might try to manipulate it to tell the story that you want to tell. Be mindful of your own confirmation bias when using data. This is when people favor information that confirms or strengthens their beliefs or values. With any analysis, it’s important to challenge yourself and your biases too when using data. Otherwise, this can lead to falsehoods, which is one of the big issues with analyzing data.
•      Security: This is becoming a fundamental issue in terms of privacy. There have been many examples where data has been compromised, and has been leaked on to the internet. It is crucial to think about how you store and secure your data.
•      Relevance: Data is time-dependent. That means that it can quickly become outdated or irrelevant. Today, customers expect companies to use real-time data to react to evolving trends or situations.
•      Time-bound: It is important that you use the data quickly and if possible, in real time. Organizational systems often make it difficult to do that, so it’s important to know what can be achieved within the limits of your systems.
•      Accuracy: How accurate is your data? And is it capturing all the factors and variables that you need to really make an impact with your digital strategy? If there are gaps, you should think about where you can find the information to complete your analysis or restrict your conclusions to the available data. So it’s essential to have a good understanding of the accuracy of your data at all times.