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Medios de comunicación social

¿Cómo abordar un proyecto de Social Media Analytics?

In previous occasions we have dedicated blog posts to the Social Media analytics topic, however we still had not written about which are the most common questions our projects must answer or which are the objectives we should aim for when we plan to extract insights from a Social Media network.

 

What you should deliver

Last year, SAP gave a series of webinars focused on Social Media (that you can find here if you have a valid SAP user) where they shared some interesting ideas about what a social media project should deliver to a customer. As consultants, we put a great portion of our efforts in endorsing our projects with as much value as possible, which was one of the topics discussed in these webinars. From them I extracted 4 principles that we should try to align our projects with in order to accomplish our goal of delivering value from Social Media analytics.

  • Speed: Social Media analytics must enable the customer to solve challenges faster through a comprehensive understanding of the technologies and experts related to their business. On the other hand, in a world where we have 6000+ tweets per second in average (source: https://twitter.com/TPS_watcher) there is a lot of information to analyze and not enough time to digest all of it, so we have to make sure that whatever our customer is analyzing from their social networks we are able to do faster!
  • Impact: The data that you extract and produce needs to give the necessary information to the customer to enable them to drive higher quality outcomes and build a reputation among their targets in the social networks. If you know what your target is hungry for, the easier it gets to satisfy their needs. Your analytics must be capable of making the customer understand how much they stand out and to monitor their presence in the social networks.
  • Insight: This principle is also related with the above in the sense that when your customers are constantly listening to what experts in their industry are talking about, they could benefit from that collective wisdom to innovate and differentiate themselves from other competitors. It is not just a matter of gathering data, it is also necessary to gather knowledge and trends. It also comes without saying that this also applies to monitoring what your customers' prospects are saying, an accurate and timely understanding of their needs or opinions, increases your customer’s probabilities of delivering what they want.
  • Efficiency: With all the information that you deliver from the Social Media analytics, you can make it possible for your customer to reduce time and investments spent in the monitoring of their Social Media activity. You should deliver with a server in minutes (why not in real-time?) what several brains take to process in many hours of work.

What you should be asking

One of the main risks of these projects is that it is very easy to lose yourself in the gigantic amount of information that you can extract, so from the very beginning you have to determine the main questions that your customer wants answered and solely focus on them. In my opinion, the most common key points that you should always look for are:

  • Who are the business influencers and what are they talking about?
  • What is the competition doing and how are they using their Social Networks? How big is their impact compared to your customer's?
  • Which are the Social Media networks that are best suited for your customer's needs?  Are they being used enough?

 

What are the benefits for your customer

Now, imagine yourself in a position where you have to sell the key benefits to a potential customer. He does not want to hear the whole “Social Media is the future” speech, he just wants you to get to the point… If your project can deliver these points below, you will be indubitably in good shape:

  • Discover key business influencers and reach them
  • Design effective strategies assessing the competition’s activities
  • Understand if the message sent to the target has good visibility

If you have any questions or anything to add to help improve this post, please feel free to leave your comments. You may also find other interesting articles related to this topic in our blog here.

BI y Social Media - Una combinación poderosa (Parte 3: Sentiment Analysis)

In previous posts we have covered the role thatGoogle Analytics and Facebookplay in BI projects focused on Social Media Analysis. Therefore, it was only a matter of time before we covered Twitter - the most popular micro-blogging network you can find on the web. Besides that, it will not be rare to find analysts and reviews that consider Twitter the social network that can potentially deliver the highest amount of meaningful information to analyze.At this point, I guess everyone has a general idea of what Twitter is and what it delivers, so the objective of this article will be to make an overview of a Sentiment Analysis showcase that we built extracting data from Twitter with SAP BusinessObjects Tools. Then, in future articles we will cover each phase of the development in more detail. Generally speaking, we consider Sentiment Analysis as the process of identifying, extracting and measuring data from a subjective information source, such as customer surveys, opinion polls, or tweets as in our case.

Extracción de datos

Como en cualquier proyecto de BI, el primer paso es definir los datos que necesita y cómo obtenerlo. Utilizando las herramientas de SAP BusinessObjects, la mejor manera de hacerlo es desarrollar un adaptador para Data Integrator utilizando el SDK que esta herramienta incluye en sus carpetas de instalación (consulte este artículo De SAP SDN que resultó ser muy útil).

Sin embargo, para hacer la demostración lo más rápido posible, utilizamos otro enfoque:

  • We developed a Java program that made use of Twitter’s getSearch API to extract tweets and place them in text files Note that for demo purposes this is more than enough, but for a broader project the flat files are not a satisfactory solution.

  • Con Data Integrator, configuramos un flujo ETL para extraer los datos de los archivos y almacenarlos en tablas de base de datos para acumular tweets suficientes para que la demo sea significativa.

También considere que en esta fase es muy importante ponerse cómodo con la API de Twitter y los diferentes parámetros que utiliza para poder aprovecharlo tanto como sea posible.

Análisis de datos y análisis de sentimientos

Una vez que pudimos colocar los tweets en archivos de texto y personalizar los parámetros de extracción como queremos, entonces podríamos analizar los tweets para empezar a ofrecer información de ellos. Para ello, seguimos estos pasos:

  • Obtenga los tweets crudos que almacenamos en la base de datos antes y realice un proceso de análisis con Data Integrator para deshacerse del formato JSON que usa la API de Twitter, lo que nos permite manipular los tweets como cadenas de texto.

  • Use the feature of Text Analysis that Data Integrator includes to perform the “Sentiment Analysis” process and classify the tweets in one of the different sentiment categories that we used. For the demo purposes that we had there is a SAP Blueprint called Text Data Processing Data Quality that contains Data Integrator jobs with a Voice of Customer implementation that already contains a set of extraction rules implemented for the English language. Therefore, you can make use of this blueprint and its rules to develop the Sentiment Analysis phase.

  • Construya un universo en la parte superior de las tablas con los datos analizados para que esté disponible para generar informes con cualquiera de las herramientas de SAP BusinessObjects que toman un universo como fuente de datos, por ejemplo, Xcelsius, WebIntelligence, Explorer, etc. Hizo un uso de un universo que vino incluido en el mismo modelo de datos de datos de procesamiento de datos de calidad que utilizamos para el punto anterior.

Visualización de datos

Por último viene la parte llamativa: presentar todo el trabajo duro que ha hecho. Para mostrar a los usuarios lo flexible que puede ser esta solución, decidimos presentar los datos con Explorador y algunas Vistas de Exploración construidas sobre sus Espacios de Información. Sin embargo, como se dijo antes, si se construye un universo en la parte superior de las tablas que resultaron del proceso de análisis de texto, entonces tendrá un gran número de posibilidades y herramientas para jugar, con el fin de producir la presentación que desee de acuerdo a su Requisitos y objetivos.

En futuros artículos, cubriremos cada una de estas secciones con mayor detalle. Sin embargo, con este diseño general esperamos que tengas una buena idea de lo que debes hacer para que tu demo de Análisis de Sentimientos ocurra.

Si tiene alguna pregunta o algo que añadir para ayudar a mejorar este post, no dude en dejar sus comentarios.

BI y Social Media - Una combinación poderosa (Parte 2: Facebook)

To continue with my Social Media series  (read the previous blog here BI and Social Media – A Powerful Combination Part 1: Google Analytics), today I would like to talk about the biggest social network of them all: Facebook. In this blog post, I will explain different alternatives I have recently researched to extract and use information from Facebook to perform social media analytics with SAP BusinessObjects’ report and dashboard tools. In terms of the amount of useful information we can extract to perform analytics, I personally think that Twitter can be as good or even better than Facebook, however, it has around 400 million less users. Facebook still stands as the social network with the most users around the world - 901million at this moment - making it a mandatory reference in terms of social media analytics.

Facebook

Antes de comenzar a hablar sobre detalles técnicos, lo primero que debe entender es que Facebook está fuertemente enfocado en la experiencia del usuario, las aplicaciones de entretenimiento, el intercambio de contenido, entre otros. Por lo tanto, la actividad del usuario es más dispersa y variable en comparación con la moda ordenada en tiempo real que Twitter nos brinda, lo cual es muy útil al construir tendencias y análisis cronológicos. Por lo tanto, asegúrese de lo que está buscando, manténgase enfocado en sus indicadores clave y asegúrese de buscar algo que sea significativo y medible.

API de Facebook relevantes para fines analíticos

The APIs (Application Programming Interface) that Facebook provides are largely directed at the development of applications for social networking and user entertainment. However, there are several APIs that can provide relevant information to establish Key Indicators that can later be used to run reports. As Facebook’s developer page1 states: “ We feel the best API solutions will be holistic cross API solutions.” Among the API’s that you will find most useful (labeled by Facebook as Marketing APIs), I can highlight the Graph API,  the Pages API, the Ads API and the Insights API. In any case, I encourage you to take a look at Facebook pages and guides for developers, it will be worth your time:

API de Facebook

Aplicaciones de terceros para extraer datos de Facebook

Solo encontré algunas aplicaciones de terceros para extraer datos de la API de Facebook que eran lo suficientemente completas como para garantizar un acceso confiable a los datos. A continuación se presentan algunas alternativas diseñadas para este requisito:

GA Data Grabber: This application has a module for the Facebook APIs, which costs 500USD a year. As in the case of Google Analytics, it has key benefits such as ease-of-use and flexibility to make queries. It may also be integrated with some tools from SAP BusinessObjects such as WebIntelligence, Data Integrator or Xcelsius dashboards through LiveOffice.2

Custom Application Development: It is the most popular option, as I already mentioned in my previous post about Google Analytics. The Facebook APIs admit access from common programming languages, allowing to record the results of the queries in text files that can be loaded into a database or incorporated directly into various tools of SAP BusinessObjects.

Implementation of a Web Spider: If the information requirements are more focused on the user’s interactions with your client’s Facebook webpage or any of its related Facebook applications, this method may provide complementary information to that which is available in the APIs. The information obtained by the web spider can be stored in files or database for further integration with SAP BusinessObjects tools. Typically, web spiders are developed in a common programming language, although there are some cases where you can buy an application developed by third parties, as the case of Mozenda.3

Final Thought

Como mencioné en mi publicación anterior, en el área de las redes sociales aparecen nuevas aplicaciones y tendencias a un ritmo agitado, se espera que ocurran muchos cambios, por lo que es solo cuestión de tiempo hasta que tengamos más y mejores opciones disponible. Le animo a que tenga curiosidad por el análisis de las redes sociales y sus redes más populares, porque en este momento esta es una mina de oro de información en crecimiento.

Si tiene alguna pregunta o algo que agregar para ayudar a mejorar esta publicación, no dude en dejar sus comentarios. También puede encontrar interesante la publicación anterior que escribí sobre SAP BusinessObjects y Google Analytics: http://juancaruiz.com/clariba/bi-and-social-media-a-powerful-combination-part-1-google-analytics/

Referencias

1 Programa de desarrollador de marketing: http://developers.facebook.com/preferredmarketingdevelopers/why_build/

2 GA Data Grabber: http://www.gadatagrabbertool.com/

3 Mozenda: http://www.mozenda.com/

BI and Social Media - A Powerful Combination (Part 1: Google Analytics)

Si echa un vistazo a las últimas tendencias de Business Intelligence (BI), verá una gran cantidad de menciones que giran en torno al tema "Redes sociales". Hay muchas ideas interesantes por ahí y parece seguro que esto se hará aún más prominente en el futuro cercano, ya que continúa creciendo y se está convirtiendo en una parte intrínseca de nuestra sociedad. Esto también significa que la información relacionada con las redes sociales se vuelve más valiosa con cada día que pasa, convirtiéndose en la nueva "mina de oro" para los consultores de Business Intelligence cuando se maneja correctamente. ¡No es de extrañar que hay muchos de nosotros que queremos comenzar a cavar!

En esta publicación de blog, compartiré la investigación que hice recientemente con el objetivo de determinar las posibles alternativas para extraer y usar información de Google Analytics para desarrollar informes y paneles de SAP BusinessObjects. Una nota importante es que no consideré las capacidades de análisis de datos y datos no estructurados de SAP BusinessObjects Data Integrator a propósito, para ver qué otras opciones había disponibles.

Extrayendo datos de Google Analytics

Lo primero que debe saber es que en diciembre 2011, Google lanzó el API de informes principales de Google Analytics (en reemplazo de su antiguo API de exportación de datos) lo que nos permite extraer datos de su aplicación. Aunque no es raro ver que la antigua API todavía se está utilizando, si está comenzando un nuevo desarrollo y tiene la oportunidad de elegir, vaya con la nueva versión, por supuesto. Considerando estas interfaces, encontré cuatro estrategias diferentes que se destacaban del resto.

Programmed Google Docs spreadsheet: It is a Google Docs spreadsheet available free of charge, which contains embedded Google Apps Script code to connect to the Google Analytics Data Export API. Once authenticated, it allows the user to define the dimensions, metrics and filters filling in the fields of the document with the desired values. Subsequently, this spreadsheet can be exported as a .CSV file and use it as a data source to be reported with several tools of SAP BusinessObjects such as Web Intelligence or Data Integrator, for example. Credits go to Mikael Thuneberg who developed this. 1

GA Data Grabber: It offers a 7-day trial version, the cost to purchase the Google  Analytics module is 299USD per year (at the present date). It consists of an Excel file containing Macros and Visual Basic code to run queries with any of the dimensions, metrics or filters available in the Google Analytics Core Reporting API. This is one of the best options I found so far, since it has a user interface that is very easy to use, good flexibility to select metrics, dimensions and filters, besides having a fairly comprehensive structure that facilitates the understanding of the type of information that can be obtained from the API. By having the data available in an Excel file there are more SAP BusinessObjects tools that can be involved in addition to Web Intelligence and Data Integrator, such as LiveOffice that allows direct integration with Xcelsius dashboards. 2

Reporting Utility of Google Analytics: This functionality is already included in the Google Analytics application. It is a relatively manual process, which requires the user to have some prior knowledge of the dimensions and metrics that can be obtained. However, custom reports can be created with specific information that can be exported to .CSV files so they can be incorporated into the reporting capabilities of SAP BusinessObjects.

Custom Application Development: If third party tools are not the desired option, then the best strategy to use is to develop a custom application in any common programming language, such as PHP, Ruby, Python, Java and JavaScript. The Google Analytics Core Reporting API lets you connect with these type of applications. In spite of representing the option that requires more effort to be implemented, it is also the one that permits to have a perfectly tailored, automatable and free solution. The data can be potentially stored in text files or custom databases from where any SAP BusinessObjects tools can draw information.

La documentación oficial siempre hace el truco

No quería entrar en demasiados detalles técnicos porque son muy susceptibles a cambios a lo largo del tiempo, y siempre es una buena práctica consultar la documentación oficial publicada por Google. En este sentido, te dejaré con algunos enlaces que serán muy útiles para profundizar los conocimientos técnicos necesarios para desarrollar una solución integrada con Google Analytics.

  • Descripción general de la API de informes principales de Google Analytics:

https://developers.google.com/analytics/devguides/reporting/core/v3/

  • Referencia de dimensiones y métricas (para comprender qué información se puede recuperar):

https://developers.google.com/analytics/devguides/reporting/core/dimsmets

  • Registro de cambios de API de Google Analytics Core Reporting & Data Export:

https://developers.google.com/analytics/community/export_changelog

  • Bibliotecas de cliente de API de informes centrales de Google Analytics:

https://developers.google.com/analytics/devguides/reporting/core/v3/gdataLibraries

  • Consola de API de Google:

https://code.google.com/apis/console

Final Thought

Al igual que con todas las cosas que se convierten en "la última tendencia" y se desarrollan a un ritmo agitado, se espera que ocurran muchos cambios, lo que significa que más pronto que tarde habrá más y mejores opciones disponibles. Entonces, mi pensamiento final es mantener un ojo inquisitivo para todo lo que se está moviendo en las redes sociales y sus redes más populares, porque este es el futuro que ya está sucediendo.

Si tiene alguna pregunta o algo que añadir para ayudar a mejorar este post, no dude en dejar sus comentarios.

Referencias

1 Para más información: http://www.automateanalytics.com/2010/04/google-analytics-data-to-google-docs.html

2 Para más información: http://www.gadatagrabbertool.com/

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