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When to Use Predictive Analytics in B2B Marketing

If there’s a consistency in social media, it is always a constant evolution. That of course that in order to stay relevant and effective, marketers need to stay on their feet. For example, Facebook’s recent decision to shift its feed algorithm that will focus on actual audience engagement, or Google’s recent updates in its search algorithm, or the popularity of new social platforms like SnapChat, Instagram, and Vine. Nowadays, it is inviting to talk about the latest piece of the social media marketing elements – predictive analytics.When to Use Predictive Analytics in B2B Marketing

Predictive analytics, simply means, use previous data and statistics to structuralize and predict the future. Among other things, predictive analytics can allow brands to pin point social media users with purchasing intent.

So how predictive analytics can help you meet your marketing campaigns? Here’s a few examples:

Milestones: John and Kates’s upcoming engagement proposal is just one of many example of how predictive analytics can benefit marketers approach to their audiences in a timely, relevant way. Eventful days such as, graduations, pregnancies, and new purchases can all be ripe opportunities for marketers. A social search for the term “eventful day”, for example, might help utility providers, alarm system installers, and truck rental companies pinpoint users who will need their products/services.

Product Launches: Social data can educate businesses with tons of information in using launch plans. For instance, Deutsche Telekom-Hosted Business Services (DT-HBS) recently launched a product to provide Voice Over IP (VoIP) phone services to small businesses. DT-HBS was able to use predictive social media analytics to locate users in need of VoIP services (by searching for “#VoIP” and “new office” on social), connect those users, and determine the influencers in the space.

Sentiment Analysis: Businesses depends on social media to provide them with accurate, unfiltered thoughts and conversations around their brand, product, or service – as well as that of their brand competitors. Sentiment analysis uses sophisticated technology and natural language terms to sort social mentions as “positive”, “negative”, or “neutral”. This can benefit businesses in discovering the consumer opinion trends about a particular product or service, leading to potentially invaluable insight.

So how can B2B marketers switch social data into tangible results and converted dollars? By integrating predictive analytics with marketing automation, marketers can locate, target, and hopefully convert leads into signing-in customers.

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