Facebook Pages, Consider Natural Language Analysis

Guest writer Bastien Hillen says that traditional Facebook management platforms' reliance on keyword or semantic functionality falls short in recognizing modern "natural" language and variations on words and letters.

While many brands have created successful Facebook communities, it’s a constant challenge to keep fans, increase the engagement rate and protect brand integrity.

Traditional Facebook community management platforms rely on keyword or semantic functionality to alert moderators of spam or negative content. Where this approach falls short is in the recognition of the modern “natural” language or word and letter variations.

Understanding what your community is saying and participating in the conversation are the two main ingredients of social marketing. But it goes beyond comprehending the well written, correctly spelled post, to awareness of the more than 1,300 chat abbreviations, different alterations and variants of expressions (such as small or capital letters, letter repetition or missing letters, orthographical variations, or non-alpha symbols).

Consider the reality that a fan’s emotional state directly contributes to the spelling and grammatical accuracy of his post. The angrier he is, the faster he types and the more likely he is to make such mistakes. In turn, moderators are probably not alerted of the message as a post to be addressed, when in reality, they must respond immediately to avoid losing momentum, loyalty and credibility.

If a customer called your service hotline and was so angry and flustered that her complaint needed some deciphering, you certainly wouldn’t hang up on her. Yet that is exactly what you are doing to your Facebook fans if you are not using natural language analysis to understand them.

When considering natural language analysis as an element of your community management strategy, it’s important to remember the importance of bridging the gap between intelligence and action.

Sentiment analysis: Beyond the obvious “likes” or positive or negative comments, marketers can harness the power of sentiment recognition to measure the success of a social campaign, identify recurring product issues or even identify competitive offers that are compelling to fans.

Real-time Notification: What’s the use of being able to understand all fan posts and comments if you aren’t able to respond immediately? Filtering out the noise through immediate alerts of fan questions, negative content and sentiment trends is absolutely essential.

In a marketplace that’s increasingly driven by online, peer-based influence and opinion, the importance of natural language will only continue to grow. For businesses using Facebook, incorporating natural language recognition and sentiment analysis can help kick your community management strategy up a notch.

Guest writer Bastien Hill is chief executive officer of Paris-based Scan & Target, which specializes in text analysis.