How to use big data in your marketing activities

The goal of the data-driven method is to increase productivity by attracting new customers and retaining old ones.
How? The data approach is based on the use of user information, starting with geographic location, demography, and ending with actions (and inactions) on the network. Marketers spend more than $6 billion yearly to get targeted message to the user through DMP (Data Management Platform) and DSP (Demand Side Platform).


Here are a few examples of how to use this data to make extra profit.

Customer segmentation

It is an easy but powerful way to use data in e-mail marketing. You should record actions, purchases, customer characteristics, and you will understand what content will be interesting to every user. Make E-mail Personalized Buyer Communication Channels.

70% of marketers report increased engagement after segmented e-mails. This allows you to increase ROMI up to 760%.


Increase customer loyalty

Around 30% of executives prioritize customer retention. This is not a big surprise, because bringing new customers is usually 5-25 times more expensive than maintaining existing ones.

With increasing customer loyalty, data is what you need. And the more, the better. Analyze sales, and you will understand what are the products best to offer. For example, you have three similar products in stock, and a customer bought two of them. It is highly likely that he will be sensitive to the advertising of the third product.


90% of marketers almost never use data visualization in their work. But in vain! It is more understandable for the viewer than a page of text. It allows you to deliver the main thoughts to the customer quickly.
Translate your data into a colorful visual range. This is useful for analysis. It is more convenient to study the dynamics of sales when you have a schedule in front of your eyes.


New Product Development

Predictive analysis refers to the study of past data to calculate the likelihood of the future. If you have a big amount of information, predictive analysis can help with the introduction of a new product or service.

A decrease in customer churn rate

You can also use predictive analysis to reduce the outflow coefficient. Make a list of clients who are more likely to leave. One of the factors of the outflow may be a period of inactivity in your account.
Now design and run a return campaign. This may be an offer of special bonuses that will show the client that you value them.

No matter how the industry relies upon, data is the only logical way for the development of marketing. This is exactly the way to advertise in a personalized way of brand communication with consumers. Honestly, is this not everything we are looking for?

With love, 


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