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Analysis

Data is supposed to provide insights that drive decisions. The problem with most quantitative research (including surveys, social media analytics, and business intelligence) is that it is retrospective. It is a snapshot of the past, meant to provide guidance for future actions. Experts, tasked with interpreting the data are left with crude prediction tools, such as extrapolating a trend line through regression analysis, data models that can be inflexible and expensive to produce, or cognitive computing systems that are costly, complex, and require expertise that most companies lack. For social media analysis, these methods are either overkill or imprecise.

Blab (www.blabpredicts.com) is looking to change the way companies make decisions by providing a more sophisticated look at the future. Their flagship product, BlabPredicts, analyzes digital and social media data in much the same way as companies such as Crimson Hexagon, Oracle, or Adobe do, using machine learning to classify conversations. BlabPredicts then takes the analysis a step further by producing a prediction of what will happen based on pre-observed patterns in social media data. Instead of linear projections that assume a steady state progression, BlabPredicts performs a statistical analysis of the data and compares it to historical patterns. It then maps those patterns to similar outcomes that have been previously observed. As the analysis continues over time, the forecast is compared to actual results and the predicted pattern is reevaluated. Newly observed patterns are also stored for future reference. By integrating newly observed patterns, BlabPredicts forecasting capabilities are self-improving.

Guidance

It’s difficult to take action without a forecast but most forecasts are based on crude or costly methods. BlabPredicts provides the type of guidance that decision makers need when interpreting social media data and considering interventions. This is especially useful to marketing professionals who need to continuously adjust on-going efforts and manufacturers trying to predict upcoming demand for products.

Conclusion

Social media analytics, like most data analysis, is look back in time. There’s nothing wrong with that. A look into the future, however, is much more valuable when making important decisions. Ultimately, this provides a more flexible, future-proof forecasting tool for anyone using social media data to make decisions.

 

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