Predictive and prescriptive tools for strategic analysis and consumer behaviour simulation

Branding is not about beautiful logos and nice statements anymore, nor is just a question of making enormous investments in advertising. The new game of marketing is about managing complexity and understanding emergent phenomena on the consumer side. Only when we reproduce the conditions in which our brand lives can we understand the invisible forces that give meaning to it and determine its failure or success. This understanding comes from modeling an extremely complex reality composed by hard facts and subjective perceptions that interact simultaneously.

In our Top-down and Bottom-up models we re-create the system of effects with critical factors that operate in relation to our brand. At the same time we create populations of virtual agents that replicate the behaviour of real consumers. This approach provides an understanding of what happens in their decision making journey as it occurs in real life.

Our model runs on Zio®, a unified proprietary platform for modeling with 
System Dynamics (SD)Agent Based Modeling (ABM) and Kansei Engineering (KE). Once the model is validated and calibrated, we run a series of simulations to test different alternatives and what-if scenarios so our clients are able to try different ideas and possible strategies before going to market. Then finally we use Artificial Intelligence techniques to come up with the optimal solution.
Similarly to what happens in the field of navigation or aerospace transportation, strategic brand management requires advanced guidance tools to support decision making.

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There has never been a greater amount of information about customers and the market, however, key aspects in the purchase and decision making processes still remain obscure.

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In today's market where differences in price and functionality between the alternatives are almost nonexistent, brands that evoke strong feelings and associations are more likely to succeed.

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