Big Data for Marketing: Do you know what Big Data is? Disruptive innovations directly influence social behavior and market perspective.
Internet, social networks, cell phones, online shopping, streaming… it is no longer news that we live in a time of constant production and consumption of information.
But how and why is the analysis of this data so valuable? Big Data comes to help answer! Not only when thinking about consumption but also in business management or predictive analytics. The fact is that this technique is increasingly developed and accessible, influencing several operations and sectors, among them: Marketing.
What Are The Best Practices A Data Scientist Should Adopt?
When working with Big Data, it is necessary to be aware of best practices to create an efficient database for the business:
- Align Big Data with the company’s goals. Before training the team and investing in projects and infrastructure, it is necessary to understand the purpose of your business, as the application of Big Data is multiple. The data can be used to understand consumer behavior in e-commerce, the feelings of the brand’s followers on social networks, and the speed of problem-solving by the service team, to name a few examples.
- Create a center of excellence to share knowledge: this approach allows for control over the supervision and management of project communications. If Big Data is still implemented, the costs can be shared across the company as all sectors will eventually benefit.
- Align structured with unstructured data: Best practice will bring insights to the business by integrating low-intensity big data with structured data that is already in use. Big data should be an extension of business intelligence, data warehousing, and information architecture capabilities.
- Keep in touch with all sectors of the company: Analysts and data scientists need to work collaboratively with all teams to understand what gaps need to be filled. They are the ones who will help other employees to find and analyze the data they need for the development of the business.
- Master Cloud Computing: Using big data connected to the cloud is a storage, integration, processing, analysis, and modeling solution. Public and private cloud security strategies must be adopted to ensure control of the entire flow of data.
How Do You Combine Big Data And Marketing To Benefit The Business?
Corporate competitiveness and the most demanding consumers are two aspects always to remember. And when we think of Digital Marketing, where changes are getting faster and faster, it is impossible not to pay attention to such issues. To keep up with all this, professionals need to keep up to date – and this is just one of the five reasons to take a Big Data course.
Big Data is, therefore, a great ally of Marketing and can be a differentiator in several processes, whether internal or external, Inbound or Outbound. For example, the technique helps predict consumer behavior and create impact strategies when thinking about market analysis.
It also influences the personalization of the shopping experience, especially if we also pay attention to Small Data. With the information provided in the data analysis, it becomes easier to understand the customer’s needs, the right approach, and when it should be done.
In addition, we can list other benefits, such as:
- Automation and process optimization;
- Employer branding support;
- Increased engagement with the brand;
- Better pricing;
- Development of new services or products;
- Goal achievement;
- Information integration;
- Competition analysis;
- We are creating more targeted and diversified content.
Imagine being able to test an advertising campaign virtually or avoid text production failures. Such possibilities already exist and reinforce the acceptance of the idea that Big Data is and should continue to be on the rise in corporations.
What It Takes To Work With Big Data
There is no specific training to work with Big Data. But the professional who wants to specialize in the area must have the following technical and behavioral skills:
- Basic programming knowledge, especially data analysis languages (R, Python, and SQL).;
- Master the concepts of Machine Learning, Internet of Things (IoT), and Artificial Intelligence (AI);
- Know the leading Big Data infrastructure tools (Hadoop, MapReduce, and Spark);
- Critical thinking;
- Logical reasoning;
- Risk analysis;
- Ability to solve problems;
- Assertive communication.
The marketer who wants to work with Big Data must constantly adapt to new technologies and market demands. The same goes for data scientists and technology professionals who wish to specialize in the field and are looking for new opportunities.
Also Read: Ten Marketing Tips For Successful Startups