All the power of data analytics and predictive analytics for market segmentation and multichannel campaigns

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Easy to manage

Cortteza helps create the market analytics for understanding your customer behavior without having to depend on an IT department.

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Data integration

We can integrate Cortteza with your company’s POS or ERP to get updated data for real-time analysis of customer behavior.

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Cortteza generates segments for email campaigns, push notifications, CRM integration, call centers, and points of sale.

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Predictive analytics

We use predictive algorithms for segmentation and influencing of consumer behavior.

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An innovative solution that helps you analyze your customers and design multichannel marketing strategies to achieve assertive interaction with them, Cortteza works with marketing intelligence to drive traffic and repeat purchases through methods and techniques that use consumer and shopping habits to determine the likelihood of a future event.


With Cortteza you can get to know and identify your customers from different dimensions and learn their behaviors and consumer habits. From there you can identify customer groups with similar behaviors, which will let you provide them a better shopping and service experience. You’ll be able to extend the customer life cycle and change their shopping behavior with intelligent recommendations and offers. All this is done with timely, relevant communication that enhances your positioning with your customers.

Why use Cortteza?

Cortteza lets you automate your data management to identify and interact with customer groups with similar behaviors by implementing real-time multichannel marketing strategies.


Cortteza is conceived and designed for use by marketers or any other department staff, freeing them from dependence on IT staff or in-house data analysts. This is achieved through its two main pillars, Data Analytics and Marketing Insight, all in a single tool.

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Cortteza consists of five modules for post-sale management and marketing strategies, speeding up daily tasks when creating customer segments with user-defined characteristics and launching real-time marketing campaigns.

It provides you with a friendly, intuitive RFM (recency, frequency, and monetary value) analysis of each customer along with demographics, favorite products, purchase periods, a product or service consumption matrix, and other aspects.

Customer behavior

Using analytics, we identify your customers’ shopping behavior and the monetary value of their purchases, allowing us to create segmentations and strategies for influencing purchase frequency and amounts spent.

Similarity algorithm

Specific recommendations are given for increasing the average amount spent. The idea is to know what a customer is not buying but that other customers with similar shopping habits are buying (machine learning).

Predictive model

Specific recommendations are given for reinforcing current behavior and/or knowing which offers would be highly relevant to a customer (machine learning).

Correlation model

Specific recommendations are given about what might interest customers next according to their recent decisions.

Real-time filters

All variables and previous results are used to create, in real time, new segments with specific characteristics.

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RFM is segmentation method that allows us to create customer groups based on their value and the following variables: 1. how recently the customer has purchased from us, 2. how frequently they purchased, and 3. how much they spent. These three dimensions are taken into account to give us a segmentation.


We then implement strategies to modify behaviors and migrate customers from one segment to another, enhancing the customer’s life-time value (LTV).


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