Data science is used in different fields and industries. And believe it or not, it also plays a significant role in digital marketing. In this post, that is what we’re going to be discussing.
Data science is a big field, and it is employed extensively in different industries, from healthcare and transport to education and commerce. In fact, it is the cornerstone of groundbreaking technologies such as AI-based virtual assistants and self-driving cars.
The definition of data science proffered by The Journal of Data Science is:
“By ‘Data Science’, we mean almost everything that has something to do with data.”
Looking at this definition, it’s easy to appreciate the fact that there is virtually no field or industry that does not utilize data science in some capacity. It’s everywhere, albeit in varying degrees.
And as such, it’s also utilized in digital marketing.
At a glance, it can be a little difficult to understand just how data science plays a role in digital marketing and how it benefits the same. But don’t worry. That’s what we’re going to be clearing up in this post.
What is Data Science?
We want to start off with the basics, so let’s look at what data science is. Although we did start off with a definition from The Journal of Data Science, it’s not very explanatory.
Data science can be defined as the field or study that deals with finding and extracting useful and meaningful statistics and insights from a collection of structured and unstructured data.
If we wanted to, we could go a little sophisticated and step into the shoes of some sage from the Middle Ages to define data science as “…to make ordered, that which is unordered…”. It’s a bit much, but it conveys the idea nicely.
The process involved in data science is divided into various steps, which are collectively known as the Data Science Life Cycle. There aren’t any specific steps that can be universally enumerated as being part of the Data Science life cycle but, generally, it involves the following:
- Data collection
- Data organization
- Data processing i.e., data mining, data modeling etc.
- Data analysis
- Finalization of results
If you want, you can learn more about data science by taking this course.
How Data Science is useful in digital marketing
Now that we’re done with this preamble, let’s move on to discuss how data science can be useful in digital marketing.
1. Keyword research
One of the main benefits of data science in digital marketing is providing help with keyword research. Actually, before moving on, let’s clear up how exactly keyword research is related to digital marketing.
Keyword research is a vital and necessary part of Search Engine Optimization (SEO). And SEO itself is a major branch of digital marketing. That’s basically how these two are connected.
Let’s get back to the point.
Whenever a digital marketing expert wants to work on the SEO of their website, they first have to create a keyword strategy for the content. The keyword strategy basically describes the short-tail and long-tail keywords that have to be featured in the website’s content and metadata. It also describes the number of times that the keywords have to be used and so on.
Now, there is no limit to the number of keywords that are (and can be) searched by online users. They literally run into trillions. When someone has to select a few from this vast and virtually endless trove of keywords, they have to employ data science.
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Here is how data science can work in keyword research:
- For the first phase, the digital marketer (or the SEO specialist) will narrow the keywords down to the ones related to their niche. This is, as we mentioned above, the “data collection” step.
- Then, from this collection of keywords, the ones with high search volumes will be prioritized and short-listed. This is the “data organization” step.
- After this, the specialist will have to find those long-tail and short-tail keywords that have a manageable ranking difficulty. In other words, this step will entail going through the shortlisted keywords and handpicking the most suitable ones.
- Then, the selected keywords will be refined even more until the finalized list is prepared. This can be referred to as the “data analysis” step.
- And once all the above is done, the list of keywords will be prepared in a document and given to the relevant personnel. This is the last step of the data science life cycle.
So, taking a look from the first step of the process to the last one, we can observe that from a list of infinite keywords, a selected number of them were handpicked and finalized. Again, this is basically what data science is. To find patterns and useful insights from unsorted or sorted data.
2. Analysis of website performance metrics
This is yet another instance of digital marketing where data science can be highly beneficial.
Basically, digital markers have to keep an eye on the performance of their website or online platform. They have to see how users are interacting with the various web pages and how much traffic the website(s) is/are generating.
To measure website performance, there are actually a lot of different stats and metrics. For example, some of them include:
- Dwell time
- Bounce rate
- Amount of traffic
- Requests per second
- Error rate
By employing data science strategies to gather and analyze the various metrics, digital marketers can easily understand how well their website is working and how users are interacting with it.
Similarly, by analyzing these metrics, they can also easily find out if the website (or a particular webpage) has been hit by a search engine penalty. This is actually a very useful benefit of keeping on top of website performance metrics.
There are different types of violations that can bring about a penalty from the search engine, or that can just simply reduce the traffic/popularity of a certain webpage.
For one, if a page takes a lot of time to load, it can get abandoned by a lot of users. This can be detected if there is a rise in the bounce rate and a decrease in the dwell time. Incidentally, the loading time itself is a website performance metric on its own.
To improve the loading time, methods such as code beautification and minimization can be used. Similarly, the images and effects featured on the page can be toned down etc.
Plagiarism is also a harmful factor that can get websites penalized. These types of penalties can either reduce a website’s rank or get it completely de-listed.
To avoid this, webmasters always have to check plagiarism before finalizing any content for their websites.
This is usually done with the help of plagiarism-checking tools that can scan the given content against the internet in order to find any duplication that may exist in the former.
3. Monitoring website ranking statistics
Just as monitoring website performance by analyzing statistics like the bounce rate, dwell time etc., is important, staying on top of the ranking statistics is equally necessary.
By staying up-to-date with the website ranking in the SERPs, digital marketers are able to adjust and manage their SEO strategies. If upon taking a certain step, the rank of the site drops, then it means that it (the step) should not be taken in future. On the other hand, if the rank rises after making some changes to the website, then it is a signal indicating that the changes are beneficial rather than harmful.
Data science can be employed for keeping up with this information as well.
Grow digital marketing with Data Science
There are actually a lot of other ways in which data science can be useful in digital marketing. But, since we want to stick to brevity, we’ve listed some common and main ones above.