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19 agosto 2019

Machine Learning en Google Ads

Uno de los retos de la publicidad en Google Ads es reconocer a los usuarios que pueden estar interesados en nuestro producto o servicio y descartar los que no van a realizan una conversión.

Escrito por: Margarita Arias

Teniendo en cuenta que más del 80% de las búsquedas diarias son únicas, llegar a tener ese conocimiento parece una utopía, pero con el aprendizaje automático o machine learning es posible.

Las conversiones son la base de cualquier campaña publicitaria. Tener claro qué es lo que se quiere conseguir (una visita de un minuto, una visualización de un vídeo, usuarios que vuelven cada dos semanas…) no sólo es necesario para elaborar el mapa de cualquier proyecto , es vital para poder mejorar mes a mes. Pero, tener esta medición nos da una ventaja añadida: hacer uso del machine learning en Google Ads.

Con una cuenta trabajada, una inversión rentable y un funcionamiento de meses podemos pasar a la fase en la que los algoritmos de Google logren formar parte de nuestro equipo de publicidad. Este compañero de trabajo tendrá un intuición exquisita, tan potente que lo vamos a llamar “la bola de cristal”.

Cada interacción con los usuarios que llegan desde Google Ads deja una huella en forma de dato, el uso del big data, junto a técnicas de machine learning hace que nuestra bola de cristal sea aún más mágica.

Con esa bola podemos predecir ¿Cuál es la mejor página de destino para una búsqueda del tipo “camisas para chicos” en una tienda con más de 200 camisas? ¿Cuál es la mejor página de destino para un usuario que está haciendo una búsqueda genérica como “seguros del hogar”? ¿Cuál es la mejor versión del anuncio para un usuario que ya conoce el servicio, pero quiere cambiar de marca? Y una de mis funcionalidades favoritas: ¿cuáles son los términos que usará mi próximo cliente para encontrarme?

Nuestra bola mágica (machine learning de Google Ads) necesita datos para poder extraer el máximo potencial a nuestras campañas y nos ayudará a eliminar comportamientos imprevisibles del usuario, analizar patrones de elección y a conocer cómo va a evolucionar una tendencia de búsqueda.

Trescom aplica a sus proyectos SEM, técnicas de machine learning para poder llegar al punto de programar acciones (pujas, estrategias, diseños…) no a conjuntos de usuarios, sino a nivel individual, de esta manera podemos evolucionar igual que lo hace el usuario en sus navegación en internet.

Si quieres saber más sobre machine learning con este vídeo tendrás un visión más clara:

SOBRE EL AUTOR

Margarita Arias

Consultora y analista SEM

Casi 10 años jugando con Google Ads. Si necesitas un guía en la montaña u organizar un viaje cuenta con ella.

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