Want to know how to predict and forecast your followers’ behavior?
Wonder what modeling techniques can help you predict the lifetime value of your customers?
Tracking the pulse of social media allows your company to gain feedback and draw insights to market better. Analyzing data and interpreting it through modeling can help make your brand’s social media more meaningful for each user.
What is modeling?
Social media models are generated by understanding and analyzing patterns of the available data. Modeling techniques allow you to experiment with available data and add more value through your social media in the days to come. With a few generated models, you can understand your user behavior and capture user preference to offer a better experience.
You create models based on your desired outcomes or understanding. Three of the most common models include predictive, descriptive, and prescriptive.
How you use a predictive model
Generated based on the associations between measurable variables, these models help predict what will happen and why it will happen. Such models work well for brands that have a lot of human interaction and a large amount of social media data.
In social media, predictive models bring out customer patterns derived from the historical and transactional data to identify risks and opportunities. Predictive models can rank customers by their preferences and guide your decision-making for lead scoring.
Watson understands unstructured data and context. Watson Analytics for Social Media lets you sieve millions of interactions on social media platforms, including Facebook, YouTube, Amazon, Google Plus, WordPress, and Reddit.
The tool collects corpus of information, interprets the information, and sets possibilities from a volume of information to allow you to discover every pattern pertaining to every customer.
How to use this predictive tool
Once you sign in, you get to see the main screen of Watson Analytics with three tiles – data, discover, and display.
In the data tile, you can add and access data, and shape it for analysis. Data can come from a variety of sources. Import social media data and Watson will respond based on all the data available. Begin your exploration by asking a question and understanding the results.
In the discover tile, you can analyze and visualize data. This is where you can work on your predictive models.
The display tile lets you format your discoveries.
To use the predictive analytics feature, create your data set first. To create predictive models, use a previously created data set.
Select “Predict” and pick a maximum of five target variables from your data set to learn what will happen and why it will happen.
For example, maybe you lead marketing for a fitness center and want to analyze all customers who may renew their membership. You analyze the data and eventually run a scheme for those who have a high chance to drop out. Watson’s predictive feature can help you foresee if a change in your social media interactions would reduce the risk of those unlikely to renew.
Explore your results by reviewing the newly identified prime factors that drive your target. Such results can help you understand the probability based on current data and give you a clear picture of what you may do to change an outcome.
You also can drag the variable into the spiral to view both positive and negative associations and co-relations in your data.
A classic feature of this tool helps you understand the sentiment percentage per topic, context based on sentiment analysis.
Using Watson Analytics makes it easier to gain knowledge to all hidden customer insights in seconds. The tool liberally combines social behavior with smart data discovery, enabling you to have a model, drive confident decisions, and gain a better understanding of your business.
With predictive analysis, you get model data that can help you predict rightly and take actions accordingly.
Other features of predictive modeling include:…
