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Data Driven


Sicredi Serrana


_ Relationship intelligence
_ Behavioral technology

_ Data Science


Assertive financial product recommendation engine for each member profile. Member profile tracking with 90% assertiveness

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Development of a predictive algorithm implemented through the elaboration of a set of Personas, with more than 90% of assertiveness.

Relationship between all union customers identified through Personas.

The project included the direct integration of Data Pocket, UCS and Sicredi Serrana's IT team.

" ... we get to know the associate better and strengthen the relationship with them. We were able to develop quite simple questions that give us a direction to know much more about the associate".

Felipe M, Business Manager


The Galaxies Relationship - Predictor Algorithm for business assertiveness, won the Bronze Service Design category - User Research   at the 11th Brasil Design Award (2021). This is an award with national recognition (the largest award in the sector in the country), held annually, with 1,624 projects registered this year. The projects are evaluated by a highly qualified panel of judges, made up of important professionals in the field of design.


a Data Science

Personalized service is a very present value for Sicredi Serrana, which seeks to offer the best opportunities to meet people's real needs. However, in order for the product offer to match the moment of the associates, it is necessary to gather data that provide intelligence about each customer profile. Therefore, we created a data science solution to support the union's business growth and ensure the delivery of value through an assertive business relationship. 


Nômade, together with its partners, developed a technological solution, that dynamizes the relationship between the business team and the associates. From ethnographic research on behavior and using Strategic Design methodologies, it was possible to understand in depth who the different associates of the base are, their history, their life context, and how this influences the relationship with the credit union.


_   Persona segmentation

new client

Sicredi Serrana identified its outdated customer segmentation strategy as one of its main down points. We would need to devise a new approach to define an client segmentation. We proposed that this new segmentation be based on behavior, purchase journey, professional moment, family structure, dreams and all the possible variables to make this social decoding of the union’s customers.


Once the new segmentation was understood, the challenge imposed was how to rethink the current relationship model, looking at the specific behavior data of each customer as input. Through extensive research, different Personas were created, representing the different types of customers of the union. This new information served as the basis for the development of a predictor algorithm, which recommends the best product offers for the business team to relate assertively with its customers. This algorithm was integrated into the union´s CRM, providing a virtuous cycle of recommendations for new marketing actions and relationship practices that act directly on the real needs of customers.

Our Process

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The project development process was divided into six macro steps:
To understand important descriptive aspects of the membership database, we apply discriminant analysis methods. From the results, we confirmed that income was not enough to determine the relationship and defined the qualitative research sample.
Step when we went to the field for the first time. We raised a series of exploratory variables and asked some customers and business managers which they believed to be profilers. From these returns, we developed the quali questionnaire.
2 months
of face-to-face administration of the survey in some cities that make up Sicredi Serrana.
We talked in depth with

120 union associates.
The responses were processed, tabulated and analyzed, generating a portfolio of 14 personas, characterized by different attributes and criteria, with relationship recommendations and product offerings.
Quantitative research was carried out to collect the data that make up the formation of Personas and were not available in the official database of the union.
In total, 1,000 associates
were interviewed.

The classification method was administered and the algorithm was developed in R, using 33 variables. However, we understand the need to optimize the business process and data collection, so we applied a sensitivity analysis to find out which are the main variables of Persona composition, so we reduced it to 10 main variables.
We worked dynamics in the digital environment and added tools to provide collaboration between a small group of Sicredi Serrana employees to accompany the construction of the solution over the months of the project. We developed a CRM prototype already including the algorithm for classifying associates in Personas.
The project was finalized with a face-to-face Design Sprint. We validated the algorithm and its interface in the official system. With associates dynamics, they recognized themselves in the persona assigned by the algorithm. We paved the way for Cooperativa Sicredi Serrana to relate in a more humane way, considering dreams, life moments and real needs.

_   Design Sprints online for building Personas 

Testimonials from those who witnessed this impact 
" ... it is a project that contributes to our vision of increasing market share, while providing the employee with a tool to be much more assertive in conversations with associates, in service approach, and prospecting for more business. It is very nice to get feedback from those who are using the tool at the end, showing adherence and that it makes a lot of sense".

  Cassiane Misturini, business advisor at Sicredi Serrana RS 
" .... as employee's learning experience, I believe it brings an opportunity to experiment with new skills. The project will be inspiring for so many other cooperatives in the system." 

Andreia Horbach , People Management Advisor at Sicredi Serrana RS
" ... it was possible to build an algorithm that gives us a better idea of each person's personality and moment of life, leading to better decisions in practice, I understand the member better. This project will have a great impact on the future of the union".

Gustavo, IT 
" ... it's a way for us to get to know our associates even better, in fact to get to know the whole of them and not simply characterize them according to the financial products we deal with them. For the Union it is certainly an advance, since that we detach ourselves from a service model that we have been working on until now, we will be approaching what each associate is within their personal and family characteristics. Let's get to a deeper understanding of it, to really comprehend their real interest. The project raises the knowledge that I apply on a daily basis".

Liane R, Business Manager
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_   Quantitative Research and Personas

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