Optimization of sales and consumer experience through Artificial Intelligence in the fashion sector

Son muchas las bonanzas que pueden aportar las nuevas tecnologias desarrolladas bajo el paraguas de la Inteligencia Artificial (IA). Lo cierto es que sobre la IA se tiene un concepto más ligado a la robotica oa tecnología de uso para procesos cognitos como la vista, la lectura o el habla.

In addition to these possible applications with great potential, we have other equally powerful services, including those with a greater impact on the account of results, such as the automation of bureaucratic processes in the billing process, the optimization of resources, the intelligent monitoring of machinery and the estimation of the need for production as well as the demand for mayors, aggregaters and/or clientes finales.

El sector de la moda tiene ciertas particularidades que hace que algunos de estos procesos sean ciertamente complejos y críticos en el ciclo de venta. One of the most relevant processes for the sector is demand forecasting, and the whole path includes from the estimation of production needs to the estimation of the final supply of physical stores and online.

The main characteristics of this sector have to do with something that we all know, the trends of each year, seasonal changes and discount campaigns that are increasingly frequent and intense. This translates into that we will find a high rotation of seasonal products, products with continuity, and the need to realize two types of estimates and follow-ups.

On the one hand, we need to estimate with a horizon of between 6 and 8 months the production and supply needs to manage requests to suppliers, on the other hand, we need to predict the demand for our products to be able to supply in an efficient manner each time tienda, eviento roturas de stock y sobre estocaje de productos.

For the rotation of references it will be necessary to establish families of similar products, and mirror products that share the maximum number of possible characteristics, to start with the historical behavior of these products and assume that the procedure for the new reference will behave in a similar way until que se tengan nuevos datos de dicha referencia e ir poco poco incorporando esta información en el modelo para finally usar unión estos datos en su estimación.

Ahora bien, el proceso de estimation de las necessidades de abastecimiento parte de la habilidad de capturer las tendencias del mercado, de aquellos products, formas y colores que van a estar de moda para la siguiente temporada. This exercise is usually carried out by teams of experts who define the line of trends of the brand to follow for the next seasons, although there are also processes based on artificial intelligence that can help identify these trends, either through the networks sociales o de analysis de imágenes.

Once defined, this line begins the process of estimating supply needs (o assortment), con lo que se pretende hacer una estimación del estocaje total a proveer durante la siguiente temporada. With this, we need to be able to estimate this volume with an advance of between 6 and 8 months in advance.

Normally, a correction is made 3 or 4 months before the start of the season to correct changes identified in the forecast. This estimation del assortmentaunque se realiza a 6 meses vista del inicio de temporada, no se entrega en su totalidad a inicio de temporada, sino que se se va entregando sequentialmente a lo largo de ella.

There are processes based on artificial intelligence that can help identify these trends, either through social networks or image analysis

Una vez concluida la identificación del assortment llega el momento de trasladar este abastecimiento a la provisioni de stocaje optimo a las tiendas, o channel online, para dar servicio al cliente final. Here we need to make our second forecast, the final demand forecast with the objective of being able to identify shop orders at a glance.

In primer lugar, es necesario identify todos aquellos factors o variables que puedan influence en la venta final. Estos factores se dividen en 2 familias de variables: variables internas y variables externas. The internal variables are todas aquellas leveras que la empresa tiene para actuar sobre el mercado, esto son por ejemplo campañas de marketingduración e intensidad de las rebajas o el nivel de stock deseado de cada producto.

The external variables are todas aquellas variables que afectan a las ventas que quedan fuera del control de la empresa, por ejemplo, climatológicos factors, calendar of festivities or the influence of macroeconomic variables. In this case, the capture of this information is a rare addition, because it is not information that is directly available, but there are specific providers and automation with the capture, so that there are different technologies that allow us to automate it.

Una vez desarrollado este proceso de captura de variables internas y externas, y tras un proceso limpieza, se procede al desarrollo del modelo, en el que se plantean diferentes alternativas in función del type de negocio y horizons definitos. For long horizons, much of the necessary information will not be available, so it will not be possible to include specific models for the estimation of variables external to the prediction horizon.

Para patrones de consumo más estacionales será optimo proceder con models de temporales series, para patrones más reactive estos models serán poco ágiles y necesitaremos hacer uso de models basados ​​de tróbales de decisión o redes neurales dedicado al analísi de dependencias temporales.

Sin lugar a duda the use of artificial intelligence is an important tool for the fashion sector. Permitiendo mejorar la visión de demanda, conocer y anticiparse el behaviora de los clientes, optimizar las cadenas símpio y stock, así como crear una experiencia unique.

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