How has Data Science influenced Digital Marketing?
Regardless of who you are, where you live, or what you do for a living, everyone has at some point interacted with a social media platform. Whether it be from a friend or family showing you an image of an event or from your actually own social media accounts. Knowing this, many companies are trying to optimize their online presence in order to keep up with customers who are technologically inclined. They accomplish this by using more digital marketing companies that utilize data science of some sort to engage current, new, and potential customers. I will be walking you through the concept of data science to enlighten how it has become such a big part of digital marketing. In addition to why data science is vital for a great go-to-market strategy for every company in any industry. By the end of this article, you should be able to effectively and efficiently apply data science tools in your company to boost marketing strategies and campaigns.
Introduction
Considering the fact that there has not been much research on the relationships between data science and digital marketing; the aim of this article is to help you understand just how much data science has made digital marketing more applied to everyday life changes in the digital space.
Data Science (DS) is a broad ecosystem that encompasses different pattern identification strategies, models of analysis, performance indicators, statistical variables, and technicalities linked to great technological expertise. (Leeflang, Verhoef, Dahlström, & Freundt, 2014). In other words, DS simply combines programming skills and the knowledge of mathematics and statistics to extract meaningful insights from data. Hence, the use of data science has notably increased in the digital marketing industry as a tool for driving the strategies for digital campaigns.
Digital Marketing (DM) is said to be the advertising of products or services using digital technologies, primarily on the internet, mobile phones, and other digital mediums. According to Sanjay Dholakia, Former Chief Marketing Officer at Marketo, Digital is at the core of everything in marketing today—it has gone from ‘one of the things marketing does’ to ‘THE thing that marketing does. Take a minute to think about all this was just said. Let me bring the concept closer to home; we all cross the street, right? I know your answer was “yes”. When we are getting ready to go across a street the notion is that you look left, right, and left again pairing that with the traffic light for the perfect time to cross the street. Guess what? That is probability and data that we use every day without thinking about it. Similarly, digital marketing companies use that same probability and data to determine when it is the perfect time to put an ad on the billboard at that very same traffic light. It is therefore evident by now that data science is needed for the extraction of knowledge in data analysis to answer specific marketing research questions. Depending on the company goals for their digital marketing strategies, the patterns and analytical skills deployed will be different. Let’s look at a few.
· Clustering – is the segmentation in a business, clustering consists of the identification of behaviours, tastes, or habits that identify the same group of consumers among other uses.
· Outlier and anomaly - identify infrequent patterns that could be fraudulent. For example, in the financial or insurance sectors.
· Prediction Patterns - predicts a missing value of an attribute like a product and/or service
· Transactional data - information regarding sales, invoices, receipts, shipments, payments, insurance, etc.
· Non-transactional data - demographic, psychographic, behavioural, lifestyle data, etc.
· Operational data - data on strategies and actions related to logistics and business operations.
· Online data - User Generated Content (UGC), emails, photos, tweets, likes, shares, websites, web searches, videos, online purchases, music, etc.
All of the above are data science techniques that help any digital marketing company used their time and allocated resources more efficiently. In that, they can track the online traffic of users to provide more accurate and relevant posts on social mediums. Have you ever noticed how you just bought a new phone and all of a sudden there are phone cases and screen protectors following you around on social media? Well, that is because you use google. Google utilizes our data and suggests ads based on the information it gathers about us. The tables below show the information a google account gathered on a particular user.
Figure 1
Figure 2
The owner of this account will receive targeted ads about travel promotions, fitness, beauty and music. Now that you have a visual representation you can imagine that Instagram and Facebook do the exact same thing. The information to run ads that are done to target persons in a particular age range, location and interest are gathered from many software.
For instance, Facebook uses Facebook pixel to do retargeted ads. Facebook pixel is an analytics tool that allows you to measure the effectiveness of your advertising by understanding the actions people take on your website. You will be surfing the internet one day and click a link to look at shoes; then the next couple of days there are ten different shoe ads on your feed. That is called retargeting. In the same way, Artificial Intelligence (AI) uses past behaviours and interests to recommend purchases on sites like Amazon or as simple as what pages to follow on Instagram and what pages to like on Facebook.
In digital marketing it is acknowledged that all customers are individuals; meaning a one-size-fits-all approach doesn’t work as it does not provide optimum efficiency. Data science allows us to portion customers into particular criteria with their characteristics. This makes it easier for running targeted ads. According to Christopher Zita PR Director at Zaire Media data science will have grown and will continue to grow in need as data-driven decision making has become the norm. Before DS became so profound excel was the go too for data analysing. Now, use Google Analytics which is a cloud-based digital marketing service, Tableau, and Power BI which are both data visualization tools for business intelligence, and of course our coding software like SQL, Python, and R that are used to perform complicated analysis with a few lines of code. Search engine optimization (SEO) is one of the biggest channels of digital marketing and has increased in the space of data science and artificial intelligence. “Data science focuses on eliminating guesswork from SEO. Rather than presuming what works and how a specific action affects your goals, use data science to know what’s bringing you the desired results and how you’re able to quantify your success. Brands like Airbnb are already doing it and so can you.” (Sharma, 2020).
Why use data science in marketing?
1. It aids faster campaign planning -the data gathered from sites and or your current campaigns on social media channels will tell you why, when, and how your clients engage with your product or service.
2. Channel and Budget Optimization - the key is to analyse what amount of money you need for which channel, so consider budget optimization once you determine which channels you want to focus on.
3. Real-Time Data Aligned to Customers - data science will inform everything about market trends, the effectiveness of timing, as well as customer response and their purchasing patterns. It is predominantly important if you want to see the new openings, forecast trends, and stay ahead of your competitors.
4. Increasing Customer Experience and Customer Retention – the information you gather will help advise what ads to run to your customers. By finding out their interest you will provide them with a real personalized experience, meaning they have to feel special while considering buying your product.
How Do You Leverage Data Science in Digital Marketing?
Customers like to feel satisfied after a purchase or the receival of a service. Lucky for us data science gathers the necessary information about customers giving us a personal guideline on how to be experts in what our customers want and providing marketing campaigns to match.
Many people are afraid of data science being used in digital marketing; but why? It`s due to not understanding that data is not just about coding. Yes! Some coding is necessary but there is much more to it than what meets the eyes. For example, python and R are used to analyse campaign performance, measure customer engagement, and predict customer churn. These systems can be automated; meaning that a code does not need to be written every time you want to run an analysis. For reports, it is safe to assume that most companies gather information about clients from the same place every month. With this software, this collection can be automated. SEO indexation can be automated through python, and this can be set up so that the code tracks the changes to the data being gathered. In addition, it can track repetitive data, customized error checking and even the data mining process.
To aid in understanding how the general population viewed data science in the marketing industry I did a mini-survey. Here are the findings.
1. What Industry do you work in?
2. Do you think Data has influenced Marketing?
100% agreed that data has influenced marketing and the major reason behind the yes is that companies like Facebook use lots of data to target people for advertising, and then expose this to marketing teams by allowing them to describe the audience they want to target. If Facebook didn't organize or summarize their data using data science then marketing with Facebook ads wouldn't be possible. Correspondingly, in order to run a successful marketing campaign, you need to know what your audience is looking for, to b me able to properly quantify the information and process it into adding to the growth of a company.
3. Is data science used in your company?
84.6% agreed that data science is necessary to collect and understand their audience better, who watches the channel, who and what time most people use their social media accounts, what gets them excited etc.
4. When you hear the words Data Science what do you think of?
5. Do you want to know more about data science and how it can be used to influence digital marketing?
76.9% want to know more. I hope this article is useful in helping you use data science in your digital marketing strategies.
Conclusion
To conclude, imagine your firm needs a social media influencer for a new digital marketing campaign. There are so many to choose from, yes, I know. Data science can help you narrow that down by analysing these influencers and their audience while comparing them also with your brand. The hard task of interviewing 30 influencers just got cut all the way down to 3 influencers who match your business brand and the new campaign goals. Purely because the analysis shows that only these 3 actually have followers who currently interact with your brand or are potential new clients you can gain from the new campaign.
Data science is awesome. I told you! So, get business using data science to build your next marketing campaign or to run an ad more effectively and efficiently to optimize your business goals.
Works Cited
Dholakia, S. (n.d.). digital-marketing/. Retrieved from https://www.marketo.com/: https://www.marketo.com/digital-marketing/
Hansen, Rina and Kien, Sia Siew. (2015). "Hummel's Digital Transformation Toward Omnichannel Retailing: Key Lessons Learned," MIS Quarterly Executive: Vol. 14 : Iss. 2 , Article 3. Retrieved from https://aisel.aisnet.org/misqe/vol14/iss2/3
Leeflang, V. D. (2014). Challenges and solutions for marketing in a digital era. Algorithms for online influencer marketing., pp. 1-12.
Saura, J. R. (2021, April - June ). en-revista-journal-innovation-knowledge-376-articulo-using-data-sciences-in-digital-S2444569X20300329. Retrieved from https://www.elsevier.es/: https://www.elsevier.es/en-revista-journal-innovation-knowledge-376-articulo-using-data-sciences-in-digital-S2444569X20300329
Sharma, S. (2020). Everything About SEO: 2020.
Venables, M. (2019, Oct 23). how-data-science-is-shaping-digital-marketing-5a149443f90a. Retrieved from https://towardsdatascience.com/: https://towardsdatascience.com/how-data-science-is-shaping-digital-marketing-5a149443f90a
Zita, C. (2020, Jan 26). is-data-science-still-a-rising-career-in-2021-722281f7074c. Retrieved from https://towardsdatascience.com: https://towardsdatascience.com/is-data-science-still-a-rising-career-in-2021-722281f7074c
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