How will Automation improve the lives of Data Analysts and Scientists in Marketing?
The growth and success of businesses depend on many key factors. One of those factors is marketing. Businesses that have good marketing strategies tend to flourish as compared to those that don’t have good marketing plans. Marketing is so important that businesses spend a large amount of capital on developing marketing strategies and then implementing them.
As time has progressed, the marketing strategies have also changed and developed to be more effective. As the world went digital, marketing also followed suit and went digital. First businesses started marketing through digital means and now they are using computers and the strides made in the fields of data science and artificial intelligence to develop marketing strategies.
Marketing using automation tools has seen a huge boost in the past decade. Automation has helped data analysts and scientists make effective marketing plans. Furthermore, better and innovative marketing strategies are being developed every day as automation tools are improving.
This blog will discuss why and how automation helps data analysts and scientists in marketing. So, if you are interested in knowing how it works, stay tuned as this is going to be an informative ride.
What is Data Automation?
Data automation is the process of using computer or artificial intelligence (AI) algorithms to automatically generate, store and analyze data. By automatically, we mean to say that there is no need for human intervention, the computer makes all the decisions and performs all the actions by itself.
In data automation, there are usually three elements. These elements are called ETL in short and their description is as follows.
- Extract: in this step, data is extracted from one or multiple sources.
- Transform: the extracted data is then passed through filters in order to get what we require from the data.
- Load: means that the data is stored in databases or data warehouses.
Why Automation Is Important and How It Can Help in Marketing?
There are many reasons why automation is important. It is a fact that computers are better than humans in all things related to data. Thus, if an enterprise integrates computers in their data analysis, the process and the output become much better.
Speed. In the business world, time is crucial. The speed at which the business operates can determine its success or failure. Automation allows data to be handled in the fastest way possible. It is especially true for processing huge amounts of data. Thus, automation gives enterprises real-time analysis of data without manual intervention. This analysis can then be used to improve their business plans, develop new marketing strategies make better decisions etc.
Efficiency and Productivity. As the processing of data is done through automation, data analysts can focus on receiving the processed data and then use it for improving the business. Automation 
gets rid of the complexities that can arise when handling data manually. The bulk of the work is done by computers, and this allows analysts to spend their energy and time focusing on key business problems. Thus, the business can get better results as the work done by their data and marketing teams improves in both quality and quantity.
Customer Satisfaction. One of the common ways automations is integrated with marketing is by using AI/ML algorithms to study                     customer behavior patterns and then predict which kind of product customers would preferably buy. You can dive deep into a customer’s thinking pattern by creating personalized workflows and databases for each customer. Once you have the data of a 
large number of customers, you are in a better position to create an effective and profitable marketing strategy.
If you are able to sell what your customer wants, your customers are satisfied. This had been going on for a few years with varying degrees of success. However, when this technique was used in combination with data analytics, the results of the subsequent        marketing campaigns got better. This also proves that using automation alone is not enough. You need good data analysis as well.
Reduced Expenditure. Through automation, businesses can save capital as the costs of data gathering and analysis manually are eliminated. The capital that is saved can then be used for other purposes.
With all the reasons listed above, it is fair to say that marketing can and does become easier when automation is in the picture. You get better data with better speed and efficiency. The analysts and the marketing team can do more quality work. Automation can help unlock the hidden potential of an enterprise.
Some Examples of Automation in Marketing.
By using social media, the online behavioral data of a customer can be noted. Next, marketing posts can be scheduled for a specific time when it is predicted that the post would make the best impact. A similar thing can be done for marketing through email. A peak time can be calculated when the activity of the customers of an enterprise is at its highest. Then you can send out marketing emails at that specific time.
A business can also use machine learning models on Customer Lifetime Value (CLTV), Return On Marketing Investment (ROMI), and the churn rate to predict which customers can become valuable moving forward. You can also use the data from these models to make smarter and more effective campaigns.
Businesses can also use models based on the age, intent, price point and needs of the customers. They can also combine the above-mentioned factors with existing geospatial data and a customer’s proximity to a rival product. As a result, a much more sophisticated and personalized experience can be generated for each customer.
Automation and data analytics are a combination that is proving to be highly beneficial for businesses around the world. Considering the fact that about 2.5 quintillion bytes of data is being generated through the internet every day, the usage of data automation will keep on growing. With the numbers just mentioned, highly accurate predictive models can be developed. This can only pave the way for better marketing strategies as it is estimated that artificial intelligence could contribute $15.7 trillion to the global economy by 2030.Â
