Complexity science, behavioural economics, artificial intelligence and agent-based modelling shape our solution.

Complexity science, behavioural economics, artificial intelligence and agent-based modelling shape our solution.

Agent-based modelling:
the whole is greater than the sum of its parts

Agent-based modelling:
the whole is greater than the sum of its parts

Agent-based modelling is a computational technique that allows simulating actions and interactions of virtual consumers in a market.

Zio® measures how these virtual consumers, based on their actual behavioural rules, react to different strategies proposed by competing brands. This gives rise to emergent phenomena on a complex system (“the market”), which cannot be managed with traditional models used in the marketing industry.

The science behind Zio

Zio technology overcomes
traditional marketing approaches

Our technology considers the market as a whole, going beyond traditional approaches such as econometric models, to address infinite questions as if we were in a virtual market lab.

Statistical Models

One source of insights.
Independent measurement of sales.
Analyses one brand at a time.

Market Simulations

Insights from all current analytics.
Interdependent KPI forecasts.
Analyses a brand and its competitors.

Zio overcomes
traditional marketing approaches

 

Our technology considers the market as a whole, going beyond traditional approaches such as econometric models, to address infinite questions as if we were in a virtual market lab.

Statistical Models

One source of insights.
Independent measurement of sales.
Analyses one brand at a time.

Market Simulations

Insights from all current analytics.
Interdependent KPI forecasts.
Analyses a brand and its competitors.

Discover our recent scientific publications

Take a look at the most recent marketing and computational
model publications from our team members

Building agent-based decision support systems for
managing word-of-mouth programs: a freemium application

M. Chica, W. Rand.
Journal of Marketing Research
(American Marketing Association) 54:5 (2017) 752-767, 2018

Multimodal optimization: an effective framework for model calibration
M. Chica, J. Barranquero, T. Kadjanowicz, O. Cordón, S. Damas
Information Sciences 375, 79-97, 2017

When Shared Joy Is Lessened: Comparing Psychological
Costs Between Online and Offline Positive Word of Mouth

A. Suárez, M. Chica
Advances in Consumer Research Volume 44, eds.
Association for Consumer Research, Pages: 760-760. Berlin, 2016

Incorporating Awareness and Genetic-based
Viral Marketing Strategies to a Consumer Behavior Model

JF. Robles, M. Chica, O. Cordón
In the IEEE WCCI 2016, Vancouver (Canada)