Differentiate Your Facebook Topic Data Product by Archiving Insights

5th April 2016 1 Comment

In our previous blog, we showed you how to differentiate by baselining. In this blog, we want to further explore how you can stand out by creating an insights archive. This blog is the last blog in a mini blog series on product differentiation.

In the face of growing competition in saturated markets, the field of predictive analytics is gaining importance as firms try to find their competitive edge. Predictive analytics is particularly valuable for marketing, allowing marketers to make predictions of the most likely behaviors of customers such as determining how they might respond to a promotional offer or identifying the best product, service or message to attract target customers. Access to historical data is a requirement for any type of predictive analytics to discover trends or patterns over time. Beyond leveraging real-time social insights from Facebook topic data, you can add value by providing predictive modeling through creating an archive of Facebook topic data insights.

Due to PYLON’s privacy controls, interaction data you recorded is only retained for 32 days in your index, however you can store the results of your analysis queries permanently in a repository of your choice. By exporting your analysis results, you will begin building an archive of insights, which you can use to measure the evolution of topics or simply understand the impact of a topic at any given time in the past. This approach puts you in a unique place where you have a set of historical insights that no one else has access to.

We created a video to highlight some of the techniques you can apply to differentiate your product with. Check it out and start innovating.

  • http://www.jatheon.com/ Jatheon Technologies Inc.

    Sounds interesting. We must try new things and be innovative, so we can find solutions suitable for us.

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