Every successful digital marketing campaign has been backed by data. Successful leaders have always relied on some form of data to guide their decision-making process. Therefore, digital marketing is successful if data is utilized, interpreted, and executed correctly. To understand data-driven digital marketing, we must first understand data-driven marketing.
What is data-driven marketing?
Simply defined, data-driven marketing is the art of basing strategic marketing decisions on data. This data is generally gathered through big data analysis on customer interaction and engagement. If applied correctly, data-driven marketing leads to better predictions about future customer behavior and helps you grow your business. The same applies to digital marketing.
However, marketers generally suffer from too much information. We can track almost anything now, and not every type of collected data is useful in solving the problem at hand. Therefore, it is essential to know what type of data your business can benefit from and what data is important for your business. Your business goals will help you decide on the type of data to collect and how to utilize those data to gain a competitive advantage in your industry.
Types of data
Hard data is data based on measurable facts from reliable sources and methodologies.
Soft data is data based on qualitative observations such as ratings, surveys, and polls.
For example, a marketing study often includes last year’s purchasing history (hard data) and customers’ reviews of products purchased (soft data).
Differences between Hard Data & Soft Data
|Hard Data||Soft Data|
|Definition||Concrete quantitative information. Generally in quantitative (amount - in number format).||Information about things that are difficult to measure, generally qualitative (measured by quality, descriptions) and subjective.|
|Category||Output, Quality, Cost, Time||Behavior, Activity, Interest, Interactions|
|Credibility||Measurable, quantifiable, objective. Immediately perceived as credible by management.||Unpredictable, subjective, behavior-oriented. Often perceived as less credible by management.|
|Measurability||Easy to measure as data is objective and concrete.||Hard to measure because data is subjective and opinion-based by nature and there is room for interpretation.|
|Examples||Sales, new account, operating costs, product returns, etc.||Customer satisfaction, customer loyalty, brand awareness, brand recognition, etc.|
Table: Difference between Hard Data Vs Soft Data
After defining the two types of data and their differences, we can use them to become more efficient marketers.
Soft data is often perceived as less reliable and harder to use to validate ROI proposals. However, it can be extremely powerful. For example, Apple continuously uses soft data to drive the never-ending loyalty of their target customers. Companies like Apple pay millions of dollars to deeply understand their customers' behaviors, activities, interests, and other forms of soft data.
What type of data is important in digital marketing?
Both hard and soft data types are extremely important when making data-driven digital marketing decisions.
There are currently 2.5 quintillion bytes of data created every day. In other words, we have so much data that it’s easy to get lost in it unless we establish a clear goal for turning data into value. Therefore, it is essential to know what type of data we are collecting and its intended use.
For example, if you want to start a personalized email marketing campaign, you will need a combination of both types of data to succeed. Hard data like the person’s name and email address are required for you to create a personalized email and send it. Soft data like the person’s interests can be used to ensure that they receive a relevant offering.
What are some of the challenges of data-driven marketing?
Data can be complex, hard to analyze, and even misleading at times. Some of the biggest challenges digital marketers face today include:
- Insufficient technology
- Lack of internal experience
- Lack of first-party data
- Difficulty proving ROI
- Poor data sharing protocols
- Lack of resources
- Low quality in third-part data
- Internal and external competition
These hurdles drive companies away from executing data-driven digital marketing strategies. However, opting out is no longer an option because the market has evolved to be highly customized, digital, and exceedingly consumer-oriented. We at PTMIND are obsessed with making data easily understandable for anyone in any department in any industry.
How can we utilize, understand, and execute data more efficiently?
Today we are able to understand the customer on a personal level. In the past, marketers never knew the exact numbers for how many people viewed their TV advertisement, or even how many of them fell in the targeted demographic. Now in the digital era, we can calculate and view useful data for extremely niche segments. For example, how many times a person visited your website from the same IP address, or how many people shared your post and who they are. Data is increasingly useful in guiding your customers' journeys.
Addressing ethical dilemmas in data-driven digital marketing
For more than a decade, big data has been revolutionizing the way products/services are offered and public opinion is influenced. Influencing the United States election is a prime example. Former US President Barack Obama’s 2008’s race for the presidency utilized data-driven digital marketing and changed the election game in the United States forever.
Afterward, President Donald Trump’s election was no exception. The campaign's data-driven targeted digital marketing victory set a new precedence in the data-driven digital world. The election sparked a number of controversies and lawsuits against data giants like Facebook, Google, and others relating to data privacy. Despite the fact that data was being compromised every day, this digital era will only continue to grow and strengthen.
Data is integral not only for understanding your customers but also for making the customer's experience amazing (and thus increasing sales through customer loyalty). However, we can’t succeed without using customer data ethically and effectively. To gain the trust of your customer you should prioritize securing your customers' data and privacy. You must take extra caution while handling the personal data of your customers. Always remember to make your terms of usage as transparent and as clear as you can.
How can we use data to improve the customer experience and customer journey? The answer leads us to a better marketing strategy.