2020
Client: Sicredi Serrana
By Estúdio Nômade
Client: Sicredi Serrana
By Estúdio Nômade
A digital solution for the recommendation of assertive financial products based on the development of a predictive algorithm implemented through the elaboration of a set of Personas. More than 90% assertiveness in tracking the profile of the credit union associates.
• design research • service design • digital solution • behaviour technology
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My role: I was engaged in the design research process, running 1:1 interviews, ethnography observation in the agencies and synthesizing data information to draft the Personas. Following, I delivery the graphic design representation of these Personas.
Who is the client: Sicredi Serrana is a credit union based on cooperativism. It operates in more than 28 cities in the south of the country (Serra Gaúcha and Vale do Caí) and has more than 134,706 associates.
What people said:
“... now we know better and narrow the relationship with the associate. We managed to develop some very simple questions that give us a way to learn more about them”.
Felipe, Business manager of Sicredi
design flow ↡
Problem Statement:
Personalized service is a very present value for Sicredi Serrana - a Brazilian credit union 💸. However, in order for them to offer products that make sense to associates, it is necessary to gather data that deliver intelligence about each customer profile. We created a data science solution based on a human-centred approach to support business growth and ensure value delivery through an assertive business relationship.
Process:
One of the main pains of the credit union is its lagged customer segmentation strategy. We devised a new approach to define a new segmentation based on Personas. 1) We started with an exploratory data analysis applying discriminant analysis methods to understand important descriptive aspects of the membership database.
2) Through ethnographic research and qualitative research (1:1 interviews), it was possible to understand in-depth who the different associates were, their history, their life context, and how this influences the relationship with the credit union.
3) A quantitative survey was carried out to collect the data that made up the formation of personas and were not available in the official database of the cooperative.
4) The translation of these data into insights made possible the creation of a new algorithm.
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2 months ￫ 150+ interviews with associates in 10 cities 📍
The in-depth conversations, resulted in the creation of ￫ 14 personas
Quantitative research with 1,000 associates
🏹 A survey that generated data to validate the personas and guide the algorithm
3 Design Sprints with the cooperative’s team to ideate the implementation
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Result:
We developed an original technological solution, which automates the relationship between the business team and associates. We interact and validate (test) with hundreds of clients and various business managers to formalize the best data to explore the current moment in the associate's life, which allows us to offer financial products in a consistent and non-invasive way. This data is processed through our algorithm configured to deliver accurate information to conduct a unique customer service relationship.
cards representing the personas and used to cocreate with the client
& field research (2019) ↡
& field research (2019) ↡
mockup of the personas evolution graphic, showing how
each persona can turn into another profile as time goes.
each persona can turn into another profile as time goes.
we described the personas using demographic elements,
customer behaviour, family history and qualitative life aspects ↡
customer behaviour, family history and qualitative life aspects ↡
mockup representing the tree graphic used for yes and no
questions to differentiate the personas and orient the algorithm ↡
questions to differentiate the personas and orient the algorithm ↡
mockup of the survey validation & picture of the validation process
of the digital solution with the client's team using the prototype ↡
of the digital solution with the client's team using the prototype ↡
remote design sprints (2020) ↡
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