Cinemex's Social Virtual Guide has significantly increased engagement and it is now generating social commerce activity. Unstructured data processing and analysis has led to 400,000 Cinemex Facebook fans viewing creative posts promoting the Social Virtual Guide in the two months the campaign has been live.

The social media campaign is being measured using direct engagement: interactions with the Social Virtual Guide, complete conversations, and social commerce transactions.

29,000 or 7.3% of these Facebook fans engaged with the Social Virtual Guide. 53% of these consumers had complete dialogues with Cinemex. This activity generated 1,400 social commerce transactions with an average of 3 tickets per transaction.

Cinemex Facebook fans continue to engage with the Social Virtual Guide in higher numbers. The behavior can be attributed to the brand engaging with consumers using creative and simple text dialogues or Facebook chats. User experience with the social media campaign has been positive because of its personalized approach to content.

In order to personalize content we need to understand consumers at the personal dialogue level. These dialogues consist of data that does not have a structure, something found in databases for instance.

By processing and filtering unstructured data we provide structure and meaning to characters that are part of user's stream of thought. This data that has been repurposed can be translated and mined in order to serve consumers with personalized creative assets in the form of branded content and promotions.

The customization of social creative assets could not be possible without the data gathering, input and eventual optimization of a digital creative, content, and channel strategy.

Data in our strategy begins and ends in a 1) social creative asset that lives on Cinemex's Facebook page. This creative asset sits on the third navigation tab at www.Facebook.com/Cinemex; 2) from this point the data migrates through our Data Manager to this initiative's database; 3) once in a database, unstructured data goes through natural language processes such as taggers and semantic parsers; 4) to create user value and utility in the form of content personalization, data goes through classifiers and machine learning algorithms that generate the right engagement in the form of dialogues, media, and promotions; 5) the personalized content is deposited in the brand's Facebook page.