While the term Big Data was more common in scientific articles in the 90s, today it is part of the marketing jargon and holds an important place in the market. And for good reason, Big data marketing has revolutionized the strategies of companies and allows them to target their customers innovatively, in accordance with the evolution of today's digital world.

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Big data marketing: an innovative approach to reaching customers
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Réalisation
of business decision-makers see Big Data projects as a way to make the best strategic decisions.
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60%
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of decision-makers have already used Big Data by integrating it into their business process or as part of a pilot project.
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40%
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of policymakers believe that Big Data is a topic of interest.
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88%
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What is Big Data Marketing?
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Big data analysis is used in the field of marketing to understand the behavior of customers towards a product or service based on data from the entire digital ecosystem such as social networks, websites, mobile applications, media campaigns, registration forms, etc.

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Big Data Marketing: why turn to Esokia?
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Digital marketing requires a certain mastery of the subject, and the expertise of Esokia's teams in the field can be put to good use. They will take into account not only the technical point of view to meet customer needs, but also the strategic aspects, the marketing objectives as well as the expected commercial results while being based on the various analyses of behavior in the field. Esokia supports its clients in the implementation of adapted digital marketing devices using various digital marketing techniques such as Marketing Automation, among others. Our agency takes care of the automation of marketing campaigns, which allows our clients to focus on the overall vision and long-term strategy.

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What are the benefits of Big Data Marketing?
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Targeting customers better
Building customer loyalty
Profiting from predictive marketing
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Esokia is proof that the intervention of experienced external developers makes it possible to:
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Targeting customers better
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With Big Data, you can better understand your customers, in order to better target them. It is therefore possible to focus on a specific circle depending on the responsiveness to offers, for example. Big Data enables the gathering of information about purchasing behavior, searches or activities on social networks, among others. This makes it possible not to create annoyance in prospects by sending them irrelevant emails.

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Building customer loyalty
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Big Data also makes it possible to retrieve enough data on customers and consumers to set up more adapted and personalized loyalty campaigns. The data collected is useful to anticipate the needs and expectations of a customer based on his purchases and their frequency.

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Profiting from predictive marketing
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Behavior analysis gives a view of current trends, but also of future changes in trends. Anticipating the future needs of acquired and potential customers makes it possible to make an offer adapted to their needs. Extract indicators from the data collected to optimize your time by proposing more adapted offers.

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Have more and more data to collect, analyze and understand, using big data as part of your marketing strategy. However, the different Big Data Marketing solutions make it possible to do this effectively and confer certain advantages to the company:

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Big Data Marketing: the different types of data processed

In the context of Big Data marketing, the data obtained is from various sources and then stored in different places. Specialists are interested in three types of important data:

Customer data

This information is useful for marketers to understand their target audience. For example, this data comprises names, e-mail addresses, purchase histories and internet searches. Some may also be collected based on the target's behaviors from social media activities, surveys, and online communities.

Financial data

This data helps to measure performance and act accordingly more effectively. This category encompasses the organization's sales and marketing statistics, costs, and margins. Competitors' financial data, such as pricing, can also be understood.

Operational data

They may include shipping and logistics, customer relationship management systems, or feedback from hardware sensors and other sources. Analyzing this data can lead to improved performance and reduced costs.

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