Comtrade System Integration | Data Science Marketing Pack

30% of companies’ marketing budget is spent on inefficient campaigns and failed sales strategies. Organizations lose even more money due to missed sales opportunities and lack of understanding of the buyers’ needs. We can help you know when, where, how and what to offer to your target group in order to maximize revenue, increase sales and lower failed marketing investments.

What is Comtrade Data Science Marketing Pack?

Comtrade Data Science Marketing Pack is a group of selected machine learning models developed by our team in order to improve sales and marketing activities of various organizations. The recommended approach includes implementation of a model in a basic set, with a selection of specialized additional models. It is also possible to individually implement chosen models, outside of the recommended sets. For more information, download the brochure.

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Comtrade Data Science Marketing Pack

Basic set

Propensity to Buy model predicts the possibility of a consumer buying a certain article. This approach makes finding buyers, planning campaigns and returning investments easier.

Next Best Action je is a complex model based on a customer-centric paradigm, predicting which of the actions offered is the most suitable for a buyer at a certain moment.

This model calculates the probability of a buyer being suitable for a cross/up sell campaign, increasing the importance of individual customers.

Churn prevention model predicts the risk of a buyer leaving the company. This risk score acts as a basis for further customer-related actions, in order to keep him around.

The model identifies customer groups by common characteristics, helping to adjust marketing activities and offers to a specific group of byers.

This model predicts future sales based on the historic data, helping organizations to plan, create marketing campaigns and set goals for the sales department better.

Specialized models

This model is most commonly used in Telco and Banking sector. Its goal is to recognize certain social groups and analyze the behavior of individuals belonging to them.

The model directly helps setting optimal prices, taking into consideration the potential customers’ reaction to the price strategy and company goals.

Using an automated text analysis, this model identifies and sorts the various opinions expressed by the buyers. It also recognizes neutral, negative or positive tone of voice.

This is a software solution using predefined algorithms and artificial intelligence to create a natural conversation with the user in various communication channels.