2022-11-04 | 292 Print PDF
According to researchers from MIT, “companies in the top third of their industry in the use of data-driven decision making were, on average, 5% more productive and 6% more profitable than their competitors.”, this can only be possible with the use of data science and data analytics.
So, how does the use of data science and data analytics help to improve digital marketing, especially in the area of using data to make coherent-driven decisions to foster business growth in an age of data-driven marketing?
But before we proceed forward we need to understand the definition of data science and the use of data analytics for digital marketing.
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data, and apply knowledge from data across a broad range of application domains.
While data analytics is the systematic computational analysis of data or statistics. It is used for the discovery, interpretation, and communication of meaningful patterns in data. It also entails applying data patterns toward effective decision-making.
As qouted by Wikipedia.
With the definition of data analysis, the next question will be why is it essential in digital marketing? Analyzing data effectively allows business leaders to make concise organizational business decisions. Nowadays, data is collected by businesses constantly: through surveys, online tracking, online marketing analytics, collected subscription and registration data (think newsletters), and social media monitoring, among other methods.
These data can be divided into quantitative and qualitative data;
Quantitative data—otherwise known as structured data— may appear as a “traditional” database—that is, with rows and columns. Qualitative data—otherwise known as unstructured data—are the other types of data that don’t fit into rows and columns, which can include text, images, videos, and more. For clarity, quantitative data are measurable data that come with figures, and summation, and are quantifiable.
While qualitative data include comments left in response to a survey question, things people have said during interviews, tweets, and other social media posts, and the text included in product reviews.
Data analysts work with both quantitative and qualitative data, so it’s important to be familiar with a variety of analysis methods, you can read more on this topic at https://careerfoundry.com/en/blog/data-analytics/data-analysis-techniques/
There are several reasons why digital marketers will like to apply data analysis in their marketing, but these are our personal take on the need to use data analysis in digital marketing.
As emphasized earlier the major caveat here will be what to use as your data priorities (ie goals), which are being defined by the campaign KPIs. Without those set of rules, you will be executing a campaign with no focus or target, which defiles the purpose of executing the campaign itself.
When most campaign goals are being set, one of the things that most advertisers or digital marketers look are the information of data that comes abound with it, it doesn't mean that you execute a campaign that it should equate to sales, not having data or conversion in a campaign is one that speaks volume.
It is based on this collated information data, that you as a digital marketer can finetune your campaigns on the fly, and also re-target them (re-purpose) to fit in your campaign goals, real-time data analysis can help you achieve that.
Data from new and existing customers targeted to a product or service landing page can easily provide information on what individuals think about your product or service based on page visits, You can gather valuable insights from your customer data and perform cluster analysis to check your audience is willing to buy from your current stock and at what price.
Also using location, demographic, and interest or preferences can aid you to fine-tune how your product or service deliverables are being responded to by your target audience.
As already mentioned, Data analysis can aid in identifying customer behavior, which can help you better tailor your marketing campaigns and implement them accordingly. This results in generating a high-quality consumer experience and satisfying their needs.
Moreover, collect the information to strategize a better-personalized relationship with your customers, making them feel exceptional when they are about to make a purchase.
Having a pleasing customer base is the need of the hour for any business. With Data Science, you can gather information about your audience and develop effective marketing guidelines, which you can implement keeping tomorrow in mind.
In conclusion, we can see how data science correlates with digital marketing, and how the use f big data can further aid in data analysis, which can bring about growth for a business. Without stating the obvious, most companies, especially SMEs do fail to realize the amount of information that is being given to them via their Google analytics based on website performance and Ads campaigns, it's about time we as digital marketers start utilizing the use of data science to decode and decipher data analysis information to help deliver more profound results to clients.