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5 applications of Artificial Intelligence to marketing strategy

5 applications of Artificial Intelligence to marketing strategy

Artificial Intelligence has multiple applications in marketing strategies. It is logical if we think of its ability to automate processes and gather information. But, from a practical point of view, how can it be applied to marketing today? We tell you about it.

Artificial Intelligence is a perfect ally to deploy and accelerate the marketing strategy in all its aspects: we are talking about the creative, procedural and analytical level. Let's take a look at the five major contributions of AI to business intelligence.

1. Data collection and consumer behavior

Thanks to technologies integrated in the AI ecosystem such as Big Data and Machine Learning, it is possible to obtain a multitude of data about users. This allows companies to personalize their offers and customer service, to anticipate their needs with personalized messages and to increase ROI.

Let's look at it from a CRM and predictive analytics perspective.

1.1. CRM - Customer Relationships 

A CRM (Customer Relationship Management) is a solution for centralized management of customer relationships. Generally, it does so from three perspectives: sales, marketing and customer service.

CRMs allow the pooling and sharing of all customer knowledge between different areas of the company. They can also direct and automate segmented marketing campaigns for each type of customer. For this purpose, techniques such as customer segmentation and micro-segmentation and lead scoring are used.

CRM functionalities continue to grow with Artificial Intelligence and we will soon see even greater development, especially in the field of predictive analytics. We will see this in the next block.

1.2. Predictive analytics

The predictive analytics techniques focus on anticipating customer needs. The analysis process always begins with data collection, classification and adaptation for subsequent analysis to detect patterns and trends. An algorithm will then be developed to process the data and provide predictions.

An example of a very common predictive analysis is the predictive text provided by Google's suite of tools. Have you noticed that it is getting more and more accurate with the words you want to type? This is the result of years of training the algorithmwith millions of users in different languages.

Imagine this applied to understanding any other user behavioral domain.

2. Chatbots

Chatbots are increasingly present on websites, apps and social networks. One of the most widely used systems is ChatGPT.

Although in the coming years we will see a qualitative improvement in the communication of Artificial Intelligences with humans through chatbots, it is essential to understand that on many occasions the assistance of real employees will be absolutely necessary. Speed in the process is also necessary.

If you want to go deeper into the subject, in this article we talked in detail about this type of technology.

3. Content generation with AI

This is perhaps one of the most controversial technologies of recent times. Using Natural Language Processing (NLP), these types of intelligences are capable of generating content in a very similar way to that of a human.

Open AI's GPT-3 language model is the most popular at the moment. It is powered by millions of files on the Web that aggregate (or aspire to) all human knowledge and create connections from user input into the system. 

4. Object recognition with AI

The application of intelligences for object recognition or facial recognition is not new. Any Google Lens user finds it very useful to be able to identify objects that appear in an image (locations, products, web pages, etc.). 

It started by identifying faces, but now the AI is already able to attribute to those faces their respective identities. It is also capable of inferring a multitude of data from features and gestures. Facebook has long known who our friends are so it can tag them in photos.

From a marketing strategy point of view, leveraging this technology can be linked, again, to the personalization of messages or offers through the synchronization of on and offline experiences.

5. Programmatic advertising with AI

Programmatic advertising consists of the automated purchase and sale of advertising space on the Web. Millions of websites offer their pages for sale to insert advertising and it is through programmatic advertising platforms (or Real Time Advertising) where these spaces can be purchased.

These inventory purchases are made throughReal Time Bidding (Real Time Bidding) managed by algorithms that are in charge of adjusting bids and adjusting purchases to the target audience to segment it in the most optimal way.

This means unparalleled time savings and delivery optimization. A much more efficient way to use your marketing budget and increase your ROI.

To help you optimize your budget and maximize your results, Konecta offers you FunnelSuite®, the all-in-one Martech tool.

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