In the last decade, in demand data science skills have flooded the job market. Online consumption of information has grown exponentially. Over 6 billion devices are connected to the internet and almost 2.5 million terabytes of data are generated on a daily basis.
This is great news for marketers. Gathering user data and extracting useful insights can help marketers target audiences and decrease overall marketing costs. However, this cannot be done without leveraging in demand data science skills.
Marketers with specialised skills in data science are considered a valuable resource in today’s industry. Data science helps marketers gain insights on consumer behaviours and user experiences to optimise campaigns and tailor marketing strategies to maximise ROI from marketing spend.
Let’s look at how data science has taken over the marketing industry and if getting trained for in demand data science skills will make you a better marketer.
Understanding how in demand data science skills and analytics contribute to effective marketing strategies
Technology changes every time we turn around. Marketers must anticipate and adapt to technological changes to stay on top of consumer behaviours. As a result, marketers adopt marketing automation tools to keep up.
Learning from data professionals encourages marketers to adopt in demand data science skills, extract insights and make informed business decisions. When marketers possess in demand data science skills in an internal marketing team, they are able to quickly track audience behaviour and provide a personalised digital experience. Marketer’s who get trained in science stand out from the crowd. As businesses rely more on marketing automation software, marketers need to adapt to the changing trend to promote data-driven outcomes.
How to apply in demand data science skills to your daily marketing activities
Data science helps to simplify, clean, and sort big data sets into meaningful and actionable insights. These insights are a gold mine for marketers so the sooner you understand them, the better your marketing strategy will be. The data is used to inform campaigns based on customer intent, behaviour, experience, and more. Get in demand data science skills training to level up in your career. Let’s look at the ways in which data science can be used for daily marketing activities:
Marketing campaigns directed at large audiences without location and demographic targeting is a waste of money. It can cost firms millions of dollars and generate very little revenue. This broad campaign targeting approach is generic and impersonalised. It makes it difficult for businesses to reach the right audience. As a marketer with in demand data science skills, you will be able to analyse data and target audiences accurately by location and demographics resulting in higher ROI.
Optimising marketing budgets
Every marketer works with strict budgets with the expectation to drive high ROI on their marketing activities. This is a challenge for every marketer. However, learning in demand data science skills can help. In demand data science skills such as data analysis allows marketers to analyse overall spend and acquisition data. This creates a model that prioritises budget distribution across different channels, locations, campaigns and platforms.
Determining the right channels for your market
Data science skills allow marketers to accurately determine the channels that are generating the most ROI to the business. A time series model can help a marketing data scientist to identify and compare the various channels that are delivering higher returns and help in strategizing the focus on different channels.
Building customer personas
Marketers build personas to create products and services that match consumer needs and wants. It is essential to use buyer personas to drive marketing campaigns specific to each persona. Data science helps marketers to determine the right personas needed to target specific audiences for each campaign.
Sentiment analysis is an in demand data science skill that marketers should use
Trending, in demand data science skills like sentiment analysis, is used to gain insights into the beliefs, opinions and attitudes of customers. Marketers should use this skill to monitor the level of customer engagement across live campaigns.
Some of the best examples of data science used in marketing
Organisations are investing in big data analytics to stay competitive in the market and reach customers first before their competitors. Businesses need to make quick and agile decisions to stay competitive.
Here are a couple of real-world examples of companies using in demand data science skills, like big data, in their marketing activities.
Coca-Cola uses data science to boost customer acquisition and retention. Big data allows companies to monitor trends and patterns in consumer behaviour for customer retention. Understanding these trends will help companies strategise their campaigns to meet the needs of the customers.
Here’s what the director of data strategy at Coca-Cola had to say –
“Data is also helping us create more relevant content for different audiences. We want to focus on creating advertising content that speaks differently to different audiences. Some people love music. Other people watch every sport no matter what time of year. Our brands are already visible in those spaces, and we’re working hard to use data to bring branded content that aligns with people’s passions.”
In demand for data science skills like big data analytics are helping big businesses solve problems in advertising to create powerful marketing campaigns. Marketers leverage big data to change product offerings to match customer expectations.
For instance, Netflix uses big data analytics for targeted advertising. Netflix monitors subscriber behaviour and provides them with movie suggestions based on their past search and watch data.
Amazon Fresh and Wholefoods are examples of companies driving marketing strategies with the help of big data. Amazon leverages data analytics to improve existing products and move into larger markets. They continuously study the interaction of customers and suppliers with the products of the company in order to make changes in their service delivery to match customer needs.
Popular marketing positions that require in demand data science skills
Careers in marketing require you to have marketing-centred skills and experience, while most companies today look for additional skills like data science.
Some of the in demand data science skills that marketers need to have are:
- Ability to generate prescriptive insights
- Exploratory data analysis
- A/B Testing
- Aiding management with data pipeline
- Communicating the importance of data and its use to stakeholders
Some of the common marketing jobs that demand data science skills are:
- Generate prescriptive insights – UX Manager, Media Buyer, eCommerce Manager
- Exploratory data analysis – Brand Manager, Digital Marketing Director
- A/B Testing – UX Designer, SEO, Email Marketing Manager
- Aiding management with data pipeline – Social Media Manager, SEO, Email Marketing
- Communicating the importance of data and its use to stakeholders – Digital Marketing Manager
Steps to switch your career from marketing to data science
If you are looking to transition to data science entirely or move sideways within your company, here’s how you can:
- Explore different job titles in the market.
- Look through the job description of the job title that matches your skillset.
- Shortlist your target companies.
- Network with the right people. Attend industry and networking events relevant to data science.
- Join online communities with like-minded people.
- Get trained in data science skills through an industry certification.
- Lastly, be confident and start applying!
The role of a marketing data scientist has become crucial in recent times due to the overflow of data. Companies are constantly facing a challenge to work with big data sets and transform them into valuable insights capable of generating ROI. With additional skills in data science, marketers today can make use of technologies and tools at their disposal to uncover insights that will help companies drive marketing strategies more efficiently within set budgets.