By Meenakshi Krishnan published May 28, 2018

3 Models (and Tools) to Understand, Predict, and React to Your Social Media

3-models-tools-understand-predict-react-social-mediaWant 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.

#Socialmedia modeling lets you experiment based on data and adds value to your planning, says @iammeekrish. Click To Tweet

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You create models based on your desired outcomes or understanding. Three of the most common models include predictive, descriptive, and prescriptive.

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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.

Predictive tool: IBM Watson Analytics for Social Media

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.

.@IBMWatson ‏#Analytics sorts millions of interactions on #socialmedia platforms, says @iammeekrish. Click To Tweet

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.

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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.

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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.

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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.

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You also can drag the variable into the spiral to view both positive and negative associations and co-relations in your data.

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A classic feature of this tool helps you understand the sentiment percentage per topic, context based on sentiment analysis.

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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.

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Other features of predictive modeling include: influencer analysis, demographic and geographic recognition, behavioral patterns, guided topic creation and configuration, advanced text analysis, and so on.

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Price: Free trial for 30 days, $30 per month for a single user with 2GB storage, $80 per month for more than one user with 100 GB storage

How to use a descriptive model

Often used in sales and marketing reports, descriptive models are the most primitive pieces of business intelligence. Based solely on data from past activities, they can detail what happened and what is happening to help you plan.

For example, you can use data to create a model to understand customer responses to a marketing activity. In social media, customer comments, posts, mentions, page views, and reviews are descriptive data. By analyzing such information, you can categorize customers by their preferences and identify opportunities from that stage.

Descriptive #socialmedia models analyze customer comments, posts, mentions, page views, etc. @iammeekrish Click To Tweet

Descriptive tool: Buffer Analyze

Let’s discuss the Buffer Analyze tool to gather descriptive models for Twitter data. The number of followers, replies, “likes,” retweets, and mentions are highly useful indicators of the level of engagement with your consumers.

The reports you gather by creating such models are more descriptive to enable your Twitter social media to perform better on a day-to-day basis.

Launched specifically to gain insights from your social media data, Buffer Analyze, a product of Buffer, enables marketers to track and measure every engagement and understand which activity inspired customers in the past.

.@Buffer #Analyze insights enables marketers to understand which activity inspired customers. @iammeekrish Click To Tweet

How to use this descriptive tool

Once you are inside your Buffer page, you can view the Analytics tab.

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Click the Analytics tab then click Analysis to view the graphical representation of your posts’ performance.

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The Posts tab presents a drop-down menu with options such as most retweets, most popular, most favorites, most replies, most clicks, and most reach.

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Pick the Most Clicks option to see a report displaying the most-clicked post. You also can choose the time period.

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Likewise, you can see the most-retweeted posts.

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The tool’s structure allows more transparency to the data analytics and enables more granular insights into what can work for you and what will not.

The best part is the ability to select dates on the calendar or a single day for your analytics. Such facility helps you to fine-tune your strategy for a specific period, day, or time.

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Price: Starting as low as $10 per month per user

TIP: Built-in social media analytics also generate descriptive models. The insights derived from such cross-sectional detailing of the available information helps you to improve your brand health.

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How to use a prescriptive model

Generated by analyzing a combination of numerical, categorical, and big data along with artificial intelligence, machine learning, human interaction, and business rules and sciences, prescriptive models suggest possible decisions.

Prescriptive modeling is the best practice to optimize your operational efficiency, mitigate risk, and manage resources. Its algorithms relate internal and external variables to help you understand what you should do, what actions are appropriate, and why you should do them.

Prescriptive modeling optimizes operational efficiency, mitigates risks, & manages resources. @iammeekrish Click To Tweet

Mike Gualtieri, vice president and principal analyst at Forrester, calls prescriptive models any combination of analytics, math, experiments, simulation, and/or artificial intelligence used to improve the effectiveness of decisions made by humans or by decision logic embedded in applications. Such models help you mitigate a future risk by illustrating the boundaries of each decision option.

Prescriptive tool: Followerwonk

Using data specific to your brand, prescriptive tools can help you optimize your social media actions.

Instead of getting a statistical generalization of the optimal time for posting content, the prescriptive model is more specific to each follower. You need to have a tool that can access personalized data about your individual audience members and give valuable information regarding each of their social media habits.

Followerwonk is a tool for this kind of prescriptive model for Twitter activity.

How to use this prescriptive tool

Now, let’s identify how to get the optimal engagement time on Twitter.

From the main page of Followerwonk, you can see five tabs – Search Bios, Compare Users, Analyze, Track Followers, and Sort Followers.

Click Analyze. Type your handle and quickly get the results. You can even get precise tracking of new and lost followers.

You can check the most active hours for your users.

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You also can check the most active hours for your brand.

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You can see the geographical spread of your users.

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The Track Follower tile allows you to understand your followers’ behavior with interactive charts.

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You also can segment users based on psychographic segments – gender, location, Twitter activity, etc. Next to each of the charts are links that enable you to find specific users in each segment.

This way you get to know who your followers are, where they are, when they tweet, and much more. Dig into that framework to understand the optimal time to tweet and interact with your customers.

Use @followerwonk to understand the optimal time to tweet and interact with your customers, says @iammeekrish. Click To Tweet

Price: Starts at $29 per month

Conclusion

Leveraging data is not an option, it is a requirement.

Real-time predictive customer experience analytics are growing. The metrics you gather through analytics enable you to form predictive, descriptive, and prescriptive models. By understanding and predicting the behavior of customers using existing models, marketers can understand their future actions to maximize the value of each customer.

True, as you specialize in analyzing the data and in creating models, you can improve the ability to predict better, to market better, do business better, and to create experiences that matter to your customers. It makes sense to invest in tools that will help you leverage models using social media data.

Please note: All tools included in our blog posts are suggested by authors, not the CMI editorial team. No one post can provide all relevant tools in the space. Feel free to include additional tools in the comments (from your company or ones that you have used).

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Cover image by Joseph Kalinowski/Content Marketing Institute

Author: Meenakshi Krishnan

Meenakshi Krishnan is a content consultant at OpenXcell, a pioneering mobile app development company in India and USA. A techie at heart, Meenakshi is passionate about the start-up ecosystem, entrepreneurship, latest tech innovations, and all that makes this digital world. When she is not writing, she loves to read, cook and paint. You can find her work on company blogs like: Jeff Bullas, GetResponse, CrazyEgg, SEMrush, Smart Insights, Sitepronews, LiveChat and more. Also, her articles are frequently featured on Business2Community. Get in touch with Meenakshi at meenakshi.krishnan@openxcellinc.com, Twitter or LinkedIn.

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