{"id":12164,"date":"2022-11-21T11:38:13","date_gmt":"2022-11-21T11:38:13","guid":{"rendered":"https:\/\/projectsofar.info\/aisuperior\/?post_type=blog&#038;p=12164"},"modified":"2023-12-04T13:02:23","modified_gmt":"2023-12-04T13:02:23","slug":"how-machine-learning-is-revolutionising-the-real-estate-sector","status":"publish","type":"blog","link":"https:\/\/aisuperior.com\/es\/blog\/how-machine-learning-is-revolutionising-the-real-estate-sector\/","title":{"rendered":"C\u00f3mo el aprendizaje autom\u00e1tico est\u00e1 revolucionando el sector inmobiliario"},"content":{"rendered":"<p>En la d\u00e9cada pasada, la transformaci\u00f3n digital y sus tecnolog\u00edas asociadas se han convertido en debates habituales en las salas de juntas. Si prepar\u00e1ramos una nube de palabras de esas discusiones,\u00a0<em>datos<\/em>\u00a0probablemente superar\u00eda a otros, lo que significa que podr\u00eda decirse que es la palabra m\u00e1s utilizada en las sesiones de lluvia de ideas sobre estrategia empresarial. Dado el amplio conjunto de puntos de datos disponibles, el aprendizaje autom\u00e1tico en el sector inmobiliario constituye un caso de uso interesante y descubriremos algunos de ellos.<\/p>\n<p>Usado casualmente como sin\u00f3nimo de Inteligencia Artificial (IA),\u00a0<a href=\"https:\/\/aisuperior.com\/es\/technology\/core-data-science-and-machine-learning\/\" target=\"_blank\" rel=\"noreferrer noopener\">Aprendizaje autom\u00e1tico\u00a0<\/a>(ML) es una rama de la IA que aprovecha datos y algoritmos para crear aplicaciones de software capaces de emular la inteligencia humana para resolver problemas complejos.<\/p>\n<p>Al observar el sector inmobiliario, la clase de activos m\u00e1s grande del mundo y el segundo sector menos digitalizado del mundo (seg\u00fan el \u00cdndice de Digitalizaci\u00f3n de Morgan Stanley), a trav\u00e9s de un prisma de aprendizaje autom\u00e1tico, se revela un espectro de oportunidades que esperan ser aprovechadas.<\/p>\n<h3><span class=\"wp-block-heading\">Aplicaciones de aprendizaje autom\u00e1tico en el sector inmobiliario<\/span><\/h3>\n<h3 class=\"wp-block-heading has-medium-font-size\">Modelos de precios avanzados<\/h3>\n<p>La fijaci\u00f3n de precios inmobiliarios es un problema fascinantemente complejo de resolver. Si bien deber\u00eda estar determinado por una multitud de factores internos y externos a la industria, tradicionalmente solo se define por unos pocos:<\/p>\n<ul>\n<li>An\u00e1lisis de datos hist\u00f3ricos<\/li>\n<li>Tama\u00f1o de la unidad<\/li>\n<li>Demanda existente<\/li>\n<li>Intuici\u00f3n y experiencia<\/li>\n<\/ul>\n<p>Si desbloqueamos el potencial de la IA y el aprendizaje autom\u00e1tico en la inversi\u00f3n inmobiliaria, podemos incluir factores adicionales que pueden parecer triviales al principio pero que ayudar\u00e1n a determinar los precios con precisi\u00f3n.<\/p>\n<ul>\n<li>Ingreso familiar medio<\/li>\n<li>Vacante<\/li>\n<li>Ocupaci\u00f3n media<\/li>\n<li>Puntos de inter\u00e9s<\/li>\n<li>Capacidad de servicio del comercio electr\u00f3nico<\/li>\n<li>Tasa de criminalidad<\/li>\n<li>Panorama comercial de la zona.<\/li>\n<li>Transporte p\u00fablico<\/li>\n<li>Apreciaci\u00f3n prevista<\/li>\n<li>Oportunidades de empleo<\/li>\n<li>Promedio de horas de luz solar mensuales<\/li>\n<li>Calificaci\u00f3n de las escuelas vecinas.<\/li>\n<li>Plazas de aparcamiento<\/li>\n<li>Niveles de ruido esperados (construcci\u00f3n, tr\u00e1fico, etc.)<\/li>\n<li>Opciones gastron\u00f3micas, de entretenimiento y recreaci\u00f3n.<\/li>\n<\/ul>\n<p>Podemos seguir agregando a la lista y el c\u00e1lculo se vuelve m\u00e1s complejo con cada punto de datos. Esto requiere un enfoque coherente, cient\u00edfico y de autoaprendizaje para fijar los precios que la experiencia y la intuici\u00f3n no pueden ofrecer. Los conjuntos de datos grandes y complejos requieren un algoritmo de c\u00e1lculo iterativo y de mejora autom\u00e1tica, exactamente lo que ofrece la automatizaci\u00f3n de la industria inmobiliaria a trav\u00e9s de IA y ML.<\/p>\n<h3 class=\"wp-block-heading has-medium-font-size\">Marketing<\/h3>\n<p>En la era actual, las aplicaciones, los chatbots e interfaces similares permiten a las empresas recopilar cantidades considerables de datos de los clientes. Los modelos de aprendizaje autom\u00e1tico pueden procesar estas grandes cantidades de datos no estructurados para brindar informaci\u00f3n basada en datos, que luego los agentes inmobiliarios pueden utilizar para centrar sus esfuerzos en los clientes elegibles. Centrarse en convertir una lista de clientes genuinamente interesados en lugar de realizar llamadas en fr\u00edo y enviar correos electr\u00f3nicos a una lista recopilada al azar puede aumentar las tasas generales de participaci\u00f3n y conversi\u00f3n.<\/p>\n<p>Adem\u00e1s, tener suficiente informaci\u00f3n sobre el tama\u00f1o, el \u00e1rea, la ubicaci\u00f3n, el presupuesto y las preferencias generales de vivienda de un cliente permite a los agentes inmobiliarios entablar conversaciones m\u00e1s personalizadas con los clientes y brindarles una mejor experiencia desde el principio.<\/p>\n<h3 class=\"wp-block-heading has-medium-font-size\">Centros de experiencia impulsados por ML<\/h3>\n<p>El atractivo visual es un factor clave a la hora de tomar una decisi\u00f3n de inversi\u00f3n inmobiliaria. Es tan importante como dif\u00edcil de cuantificar. La visita al sitio es el enfoque m\u00e1s sencillo para resolver este problema, pero a menudo no es pr\u00e1ctico. Los modelos de reconocimiento de im\u00e1genes basados en Machine Learning pueden permitir a sus clientes experimentar los alrededores de una propiedad a miles de kil\u00f3metros de distancia. Los modelos de aprendizaje profundo pueden revelar informaci\u00f3n clave al acceder a millones de im\u00e1genes en poco tiempo, mientras que las redes neuronales convolucionales pueden extraer, analizar y presentar aspectos visuales clave de una propiedad como:<\/p>\n<ul>\n<li>Niveles de actividad del vecindario<\/li>\n<li>Tama\u00f1o y calidad de las calles.<\/li>\n<li>Disponibilidad de plazas de aparcamiento<\/li>\n<li>alumbrado p\u00fablico<\/li>\n<li>Verdor<\/li>\n<li>Densidad de poblaci\u00f3n<\/li>\n<li>Proximidad a parques<\/li>\n<\/ul>\n<p>Adem\u00e1s de capturar las im\u00e1genes, estos modelos pueden mejorarse al determinar el papel que jug\u00f3 cada factor en la decisi\u00f3n final del cliente. Es un circuito de retroalimentaci\u00f3n importante que alimentar\u00e1 las decisiones futuras de todas las partes interesadas.<\/p>\n<h3 class=\"wp-block-heading has-medium-font-size\">Sistemas de recomendaci\u00f3n<\/h3>\n<p>Este es un aspecto clave del aprendizaje autom\u00e1tico que est\u00e1 generando recompensas exponenciales en todas las industrias. Los motores de recomendaci\u00f3n est\u00e1n a nuestro alrededor, los reconozcamos o no. Los anuncios de YouTube, los resultados de b\u00fasqueda patrocinados, las sugerencias de productos de Amazon, el algoritmo de coincidencia de Tinder y la secci\u00f3n recomendada por Netflix son ejemplos de avances de ML.<\/p>\n<p>Las empresas inmobiliarias pueden aprovechar estos casos de uso para perfilar a sus clientes y propiedades cotizadas. Luego pueden relacionar a un cliente con un conjunto de propiedades seg\u00fan las preferencias seleccionadas, como ubicaci\u00f3n, tama\u00f1o, presupuesto, puntos de inter\u00e9s y mucho m\u00e1s. Tambi\u00e9n pueden realizar un perfil financiero completo de sus clientes para predecir las propiedades que un cliente podr\u00eda desear.<\/p>\n<p>Dada la complejidad inherente del sector inmobiliario, aqu\u00ed s\u00f3lo estamos ara\u00f1ando la superficie. A medida que se embarque en el viaje de transformaci\u00f3n digital de su negocio inmobiliario, descubrir\u00e1 un tesoro de informaci\u00f3n que le permitir\u00e1 tomar decisiones estrat\u00e9gicas informadas.<\/p>\n<h3><span class=\"wp-block-heading\"><strong>C\u00f3mo puede ayudar AI Superior<\/strong><\/span><\/h3>\n<p>En AI Superior, somos expertos en construir de extremo a extremo\u00a0<a href=\"https:\/\/aisuperior.com\/es\/technology\/core-data-science-and-machine-learning\/\" target=\"_blank\" rel=\"noreferrer noopener\">Soluciones de aprendizaje autom\u00e1tico<\/a>\u00a0para elevar el rendimiento de las empresas inmobiliarias al siguiente nivel. Ya sea que est\u00e9 buscando aprovechar el aprendizaje autom\u00e1tico para\u00a0<a href=\"https:\/\/aisuperior.com\/es\/projects\/real-estate-property-estimation\/\" target=\"_blank\" rel=\"noreferrer noopener\">predicci\u00f3n del precio de la propiedad<\/a>\u00a0o para predecir tendencias clave del mercado, podemos ayudarlo a aprovechar sus datos para aumentar el retorno de su inversi\u00f3n.<\/p>\n<p><a href=\"https:\/\/aisuperior.com\/es\/contact\/\" target=\"_blank\" rel=\"noreferrer noopener\">Ponerse en contacto<\/a>\u00a0con nosotros para descubrir c\u00f3mo podemos crear una soluci\u00f3n personalizada que aborde las necesidades de su negocio<\/p>","protected":false},"excerpt":{"rendered":"<p>In the decade gone by, digital transformation and its associated technologies have become regular boardroom discussions. If we prepared a word-cloud of those discussions,\u00a0data\u00a0would likely outsize others, meaning it is arguably the most frequently used word in enterprise strategy brainstorming sessions. Given the vast pool of available data points, Machine Learning in real estate makes [&hellip;]<\/p>\n","protected":false},"featured_media":12167,"template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}}},"categories":[8],"class_list":["post-12164","blog","type-blog","status-publish","has-post-thumbnail","hentry","category-ai","blog_category-ai"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>How Machine Learning Is Revolutionising The Real Estate Sector - aisuperior<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/aisuperior.com\/es\/blog\/how-machine-learning-is-revolutionising-the-real-estate-sector\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How Machine Learning Is Revolutionising The Real Estate Sector - aisuperior\" \/>\n<meta property=\"og:description\" content=\"In the decade gone by, digital transformation and its associated technologies have become regular boardroom discussions. 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