Online Marketing Strategies

How To Use Data Science in Digital Marketing .

2022-11-04 | 292 Print Friendly Version of this pagePrint Get a PDF version of this webpagePDF


How To Use Data Analytics in Digital Marketing.

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.

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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/

 

How Data Analysis Can Be Used In Marketing:

5 Major Benefits of Data Science and Data Analysis in DigitalMarketing.

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.

1.) Campaign Optimization


With the vast use of different channels and mediums to generate traffic to websites or landing pages, one tends to have voluminous use of data viewable on Google analytics or any other website performance site.
You are showcased with various data from bounce rate to acquisition, and so much more.

Focusing on the main criteria for your campaign KPIs (Key Performance Index), you as a digital marketer will be able to deduce a lot of performance laps or gain insight into our your campaigns are performing.


The use of Google Analytics to execute data analysis on your campaign ads is beyond a doubt, the most useful means of data collation on website performance in response to an executed campaign set.

With the set of tools provided to you by Google analytics you can improve your campaign audience by interpreting the large amount of data being provided to you, eg it could be by location, by page (exit, visit behavior, etc), or by goal setting, etc.

 

2.) Real-Time Data


The use of Google Analytics for data collation is very important as it presents real-time visits and data for live monitoring and studying. Normally data collation is basically done after a campaign has been executed but in real-time, data can be based on the current market trend or performance and real-time data collected can also be used to optimize and plan current and future marketing strategies, which can be applied on the go as the current campaign is still in progress.

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.

3.) Improve Product or Service Delivery


With the explanation above we can deduce the benefit of real-time data, and one of the cogent points will be that it helps the digital marketer to easily spot issues with their product or service deliveries, in as much as a campaign can be well planned and executed, in most cases, poor performance can likely be that of the product itself and less of the method or channel being used for the campaign execution.

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.

4.) Budget Optimization


With a good data analysis for your campaign you can easily correlate your campaign performance with the days you are getting optimum results, hence as a digital marketer, you spend less on days with minimal performance and spend more on the days with higher performance.


This will increase both your campaign quality score and reduce your overall cost per conversion on clicks, with this practice we have been able to deliver more than expected in terms of overall data, campaign impression, and conversion through rate, whilst reducing the cost per click.

5.) Improve Customer Experience

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.

 

Conclusion:

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.


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Olatunji Adetunji

I am a seo web analyst and have a love for anything online marketing. Have been able to perform researches using the built up internet marketing tool; seo web analyst as a case study and will be using the web marketing tool (platform).

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