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Posts tagged ‘fashion’

02/04/2012

tdrlogoblack94

El calzado como termómetro de la crisis

Hace unos meses podíamos leer una nota de prensa de IBM en la que la empresa norteamericana presentaba un estudio, basado en el análisis de millones de mensajes a través de redes sociales y blogs, en el que se identificaba un descenso en la altura de los tacones como tendencia asociada a la crisis económica. Fruto de esa noticia, en The Data Republic nos hemos preguntado si se podía contrastar para España esa hipótesis de cambios de preferencias en el calzado debidos a la crisis económica. Para ello, hemos procedido a extraer y analizar más de 30.000 looks subidos a Chicisimo por usuarias españolas en 2011 y en lo que llevamos de 2012.

La primera hipótesis a contrastar era clara: si la crisis ha propiciado que los usuarios de las webs de street style opten por zapatos más baratos. Entendiendo que comprar zapatos más baratos puede significar el vestir tipos de calzado más asequibles o bien comprar marcas más baratas.

Respecto a lo primero, si analizamos la web de Zara, con diferencia la marca de moda más vendida en España y también con mayor presencia en Chicisimo, vemos cómo botas y botines son el calzado con un precio medio más elevado, por encima de los zapatos de tacón, y de entre los dos primeros, las botas son más caras que los botines. Pues bien, si vemos qué tipo de calzado es el más habitual entre los looks subidos en los periodos de enero a marzo de 2011 y de 2012, observaremos cómo tacones y botines han crecido ligeramente mientras que botas y botas sobre la rodilla han descendido, al igual que zapatos planos y sandalias de gladiador. Si bien en ambos años el dominio de los zapatos de tacón es claro, mientras en 2011 las botas se situaban por encima de botines como segundo tipo de calzado más utilizado, en 2012 las tornas han cambiado.

Primer dato relativo a tipos de calzado que puede contribuir a confirmar la hipótesis del impacto de la crisis: las botas, el calzado generalmente más caro, han perdido cuota entre los looks que visten los usuarios de Chicisimo. Segundo dato: se ha producido un desplazamiento de la bota hacia el botín, un tipo de calzado que tiene de media precios más bajos, como se puede ver en Zara.

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April 2, 2012  

05/10/2011

tdrlogoblack94

Analyzing Twitter followers: Let us tell you a little bit about your customers

Companies have decided that they should be in Twitter, but in most cases they look for a quantitative approach of their performance: “We have 3,000 on Twitter“.

But is that enough? What do these numbers tell us? Well, we think that not really much. Some companies, the eagest ones, want to look further and try to gather some personal details about their followers: Where are they? What music do they like? What are their sources of information? What other brands do they consume? Through this analysis, companies are able to profile their followers as they might be potential customers. Therefore they will be able to know some of their preferences, habits and behavior patterns.

That is great, that is something we have already done at TDR. But now, we want to go a little bit further: what about those Twitter accounts followed by my Twitter followers?

With this new project we want to offer companies and organizations that are in Twitter an easy and simple way to find out what other accounts are followed by their followers. Take a fashion brand such as H&M. In Spain, the Twitter account @hmespana has more than 18,000 followers. If we know what other accounts are most followed by these 18,000 followers, we would be able to detect some common patterns, preferences and dislikes by our potential customers. If we know what celebrities they are following the most, maybe we can make the right decision when looking for someone to promote our products. Moreover, if we track this data in a long-term, we will able to understand changes in preferences and, for example, change the TV stations or other media channels we are using to broadcast our adverts.

So, we are currently working to offer brands and companies an analytic and qualitative tool to better understand their customers. We are using data 2.0 to help businesses to to achieve their strategic and commercial objectives.

Take a look at our Twitter analytics project.

October 5, 2011  

19/09/2011

tdrlogoblack94

How real people wear Mango’s clothes. A Data 2.0 research about fashion brands

A couple a months ago we published a post about coolhunting 2.0 and how fashion trends might be somehow researched through the analysis of looks uploaded by users at streetstyle communities. We are now releasing our project and we can now reveal that we have carried out a study about Mango.

For the development of this project we obtained 3,160 pics uploaded at chicisimo.es, lookbook.nu and chictopia.com during June 2011, on one condition, we picked those which were tagged with at least one garment by Mango. From all these pics we got more than 12,600 different garments from more than 1,300 different brands, which were combined with Mango items by users from 75 countries.

We found out some interesting things. Bags are the preferred Mango’s garments in general terms, and specifically in the cases of Spain and Germany, whilst in the UK they prefer dresses and French love Mango’s shorts. Spaniards’ top outfit by Mango is composed of a dress, a bag and a pair of shoes. In most of the cases, users that wear a Mango’s garment like to combine it with Zara and H&M‘s items, despite in some countries such as the US, the second hand and vintage clothing is even more popular. It is also remarkable the fact that the Philippines is the second country by number of Mango’s looks uploaded, whilst there are only a few Mango stores in the Philippines. Other Asian countries such as Indonesia also has a presence in the streetstyle communities higher than countries such as France, Germany, UK or Italy.

Our goal is to show fashion brands and professionals how data 2.0 such as this might be useful for them in order to get to know what real people is wearing, how they are wearing it and, eventually, how they can use this information to set the trends for the coming seasons.

What do you think?

Read the project.

September 19, 2011