Data Science is the process of using data to understand different things to solve a real-life problem. The process of deriving useful insights from raw data is known as Data Analytics.

The responsibilities of a professional data scientist are –

• Business Understanding: In order to acquire the correct data we should be able to understand the business.
• Data Collection: Based on the domain understanding, Data should be collected from the field.
• Data Preparation: Data collected from the field may or may not be in the required format. To perform any analytical step on the data it needs to be in a certain format. It could also be said that data needs to be cleaned before processing any further. This process is also known as Data Cleaning or Data Wrangling.
• Exploratory Analysis: Now that we have a sparkling clean set of data, we are ready to finally get started with the analysis.
• Data Modelling: At this stage, the machine will be trained based on the available data.
• Model Evaluation: Once the training is done, we need to evaluate its success.
• Model Deployment: Once the evaluation process is complete, we can deploy the model that was developed for prediction.

Now let’s see how this data science will help with digital marketing

1.    Data Science in Search Engine Optimization

Search Engine Optimization is a set of activities undertaken by people to make their website or webpage more attractive for the search engine algorithm. When a webpage is properly optimized, it appears in the top position for queries on the Search Engine. The purpose of SEO is to increase the organic traffic to your website or webpage through organic Search Engine Results.

Data science is quickly transforming how we maximise website traffic. Data scientists enhance search engine functionality by gathering, interpreting, and responding to data.

Data science in SEO aims to do away with speculation. Data scientists determine what’s providing you with the results you want and how you may quantify your success rather than assuming what works and how a single action influences your goals.

2.    Data science in the Optimization of Marketing Budget

Digital marketers are always on a tight budget. A data scientist can build a spending model that will help digital marketer better utilise their budget by analysing their spending and acquisition data. The model can assist digital marketers in allocating their budget among locations, channels, mediums, and campaigns in order to optimise key metrics.

3.    Data Science in Email Marketing

When it comes to marketing, emailing is still one of the most basic and important tasks that every marketer must complete on a daily basis. However, in this highly competitive market, how we handle emails in terms of targets, content, quality, and even the time we should send the emails is critical for better outcomes and results. In this case, data science will be critical for email campaigns and management in terms of effectiveness, quality, and other factors.

There are different types of Data Analytics

• Demographic Data: This gives the information and details, such as location, interest, age, gender, etc., from which we get our target audience. You can use these insights to develop email marketing campaigns.
• Customer Preference: This data can be measured by the convenience of the customer’s preferred brand, for example. A company allows customers to rank a few of the goods it sells based on their utility level. These preferences are unaffected by price or income.
• Behavioral Data: This gives valuable data and insights regarding how the target customer behaves and interacts with your email.
• Transactional Data: This contains the data regarding the items, first and last purchases, number of purchases, time, average order value, product purchase history, and amount spent by a customer. This data can help you enhance your email marketing strategies.

4.    Data Science in Sentiment Analysis

Data Science can assist digital marketers with sentiment analysis. This will provide them with a better understanding of their customers’ beliefs, opinions, and attitudes. They can also track how customers react to marketing campaigns and whether or not they interact with their company.

5.    Customer and Marketing Strategy Alignment

To get the most out of their online marketing campaigns, digital marketers must match them with the right customers. Data scientists can create a customer lifetime value model that can segment customers based on their behaviour to accomplish this.