To offer a customized value proposition in e-commerce environments.


The challenge of this project, co-funded by the Ministry of Energy, Tourism and Digital Agenda (No. TSI-100105-2017-2), has been to be able to customise a consistent message and a specific value proposition for each user based on their needs and specific preferences, regardless of the device or channel used.

Based on all the profile data and behavior collected in all channels, we try to obtain patterns that allow us to predict and generate messages and personalized value proposals for each user.

Omni-channel Marketing

Omni-channel Marketing

The omni-channel marketing tries to offer a continuous and fully integrated user experience regardless of the channel or device the user uses to connect/access.

In fact, omnichannel marketing aims to stop talking about user-clients to start talking about people -clients, a person who connec with our company at many different times through different channels and through different devices.

Our solution

Bussines and technology challenge.
Data and source integration
Data and source integration
360 Customer Vision. Having a holistic vision of our customer means to get a vision of the whole life cycle, from the first advertisig impact to when he or she returns to us as a convinced customer. So we need to connect and cross the information that comes from sources in every step of the customer´s journey, such as purchase, website analytics, customer relationship management ( CRM ) and later fidelity programs campaigns.
Processing data using ML techniques.
Processing data using ML techniques
Taking into account navigation data of hundreds of miles demands to use a platform consistent with massive data management, such as GCP. Thanks to it, we will be able to store key data to our study in a structured and easily recoverable way. Moreover, we will be able to apply pre-processing techniques that make these data prepared to use it later with automatic learning algorithms.
Insights commercial exploitation.
Insights commercial exploitation
Analytic data true value appears when thanks to it we get knowledge we can apply effectively. It also materializes when it allows us take better decisions or doing something in a superior way. In Coniecto-360 case we are developing a recommedation system that makes possible to offer a customized value proposition for every user. In this manner we optimise conversion and return rates.

State of the art enhancements

Obtain characteristic behaviour patterns existing in the data, for use in the field of e-Commerce.


Recommendation system based on problematic Big Data and that applies Automatic Learning techniques, with the purpose of offering a personalized service to users based on their browsing history. The final solution is splited into different stages:

  • Data collection and storage
  • Preprocessing of the data
  • Learning and obtaining the model
  • Implementation of the learned model


Machine learning
Big Data
Google Cloud Platform
Google Analytics
Google Big Query

The project has been co-financed by the Ministry of Energy, Tourism and Digital Agenda.

Project Number: TSI-100105-2017-2
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