Marketing is an essential aspect of any company. You cannot deny the significance of this element when you plan your company’s strategies. The methods of strategizing have changed over time. Presently, companies are dependent on digital media to gather and analyse data. You might have come across the term ‘Big Data’ while going through the various marketing strategies.
In the following sections, we will dig deep into the term ‘predictive analytics’ and understand how big data has transformed the methods of formulating marketing strategies.
Big Data and Predictive Analytics: How are they Related?
Presently, you are surrounded by technology. Data is everywhere. The company which races ahead of the others knows how to use the data and formulate effective marketing strategies. Of late, big data has been in the news for its significance in various industries. The term refers to a huge volume of data that is hard to manage. Let me help you understand the volume of big data:
Every day over 2.5 liquidation bytes of data are created
It was expected that by 2020, 1.7 MB of data would be created every second for each person
You can understand how big the data is, and the companies are trying to use the same to formulate effective marketing strategies. You might wonder how predictive analytics is related to big data. Well, you cannot use the data without understanding predictive analytics. This procedure will help you analyse such extensive data using advanced analytics and predict future events.
Predictive analytics has been beneficial for companies, and they have successfully formulated effective marketing strategies using the same. Even the assignment writing websites that you sign up with to get an essay writer use such technology to beat the competition.
The following section will help you understand the value of predictive analytics and how the same can be used in formulating marketing strategies.
How to Use Predictive Analytics for Better Results?
Most companies can feel the impact and importance of predictive analytics. But to your surprise, only 23% of the businesses use such advanced tools and the predictive analytics system. But most of the companies acknowledge the benefits attached to the same. So, where is the problem in implementing? Well, the problem lies in their understanding and the ability to use the method correctly. Here are a few ways predictive analytics can be used in your business.
Detailed lead scoring
The marketing and sales team is always looking for leads to keep the business going. A persistent problem among these teams is the understanding and arrangement of the leads correctly. Predictive analytics can help you overcome such hurdles. The procedure will help you arrange the leads correctly and take the next step cautiously. You will understand whom to approach next once you know about the person’s buying habits. Thus, predictive analytics helps in finding the most relevant answer to the question, “How to maximise the sales?”
Segmenting the population for various campaigns
You will understand the need for segmenting the population while planning the various campaigns. You cannot send the same posters or emailers everywhere. Therefore, it is essential to understand the demographics and plan the campaigns accordingly. You will fail to target the right audience and plan your campaigns if you do not understand the demographics. Predictive analytics can help you analyse these things without any hassles.
Targeting the right audience
You will rarely see a professional getting mails regarding online exam guidance from the various assignment writing websites. It is necessary to understand who your customers are and plan the promotional campaigns accordingly. It isn’t easy to find out the mail Ids or the numbers of your targeted audience. Using predictive analytics can make things easier for you. The method will help you relate your campaign to the right set of audience and will also help you choose the right distribution channel.
Lifetime value prediction
Understanding a customer’s value to your company is very important. You cannot deny the significance of each customer, but if the customer will be loyal to your brand, is a significant concern. Predictive analytics can be used to predict the customer lifetime value (CLV). You will be able to understand the customer’s mindset and plan your next steps accordingly. As you will know, the CLV is the actual ROI for your company.
Churn rate prediction
Customers are not always loyal to a particular brand. With advanced technology, companies are coming up with products that can take away your customers. Predictive analytics can help you predict the churn rate. You will be ready with your marketing plans once you understand the number of customers that might leave your brand. It is an essential aspect of businesses. Predictive analytics is, therefore, considered to be one of the best methods to formulate effective marketing strategies.
Predicting up selling and cross-selling
A company has a lot of products. You might get a customer to buy one product without having any idea that the person will look for an upgrade soon. For example, if you look at Apple users, they are always ready to upgrade their devices, and the company also releases upgrades quickly. This is a great example of predictive analytics. The company has seen the customer behavior and is constantly working on upgrades to retain their customers and make them buy the same. You can do the same and predict up selling and cross-selling using predictive analytics.
Marketing is not easy. You need to look into various aspects to promote your products correctly. Predictive analytics has taken centre stage with time. You will see most of the companies using the method to formulate effective marketing strategies. It is essential to understand where to use the method and use them correctly. The aforementioned points will help you understand and use the method correctly.
Patrick Bate is an experienced writer associated with the Global Assignment Help website MyAssignmenthelp.co.uk He is also a food-lover and loves to browse through various cuisines now and then.