How Predictive Analytics Software Helps You Understand Your Audience

Artificial intelligence making possible new computer technologies and businesses

Understanding an audience and providing personalized content to them is an essential part of modern media delivery. Because of advancements in Artificial Intelligence (AI), media companies have every ability to deliver quality and personalized content to each and every member of their audience.

A.I Software or Predictive Analytics

People hear about artificial intelligence and wonder, what is that? According to the Forbe’s Primer on AI, current AI is so closely tied to machine learning that the two terms are used interchangeably. This means that artificial intelligence analyzes large amounts of data and changes the software algorithm to get a certain result. Thus predictive analytics is a core part of the development and continued use of artificial intelligence because the machine analyzes the data at hand and predicts changes needed to get results. This is key to self-driving cars, and it is key to behavioral analytics in media consumption and advertising.

Understanding Your Audience Through Behavioral Analytics

Human behavior is largely predictable when given enough information about a person’s habits and lifestyle. While we can always change our behavior, just think about the last 5 times you went to a coffee shop. Were they all different, or did you visit the same coffee shop 5 times? Based on just this tiny data set, someone could predict the likelihood that you would be at a certain coffee shop at a certain time tomorrow.

For media companies and advertising agencies, the use of OTT media to deliver content directly to their customers drives the motive behind predictive analytics software.

How OTT Provides More Analytical Information

OTT media is loosely defined as media delivered independently of a controlled distribution channel, like cable or satellite. Since individual customers are able to access OTT channels like Netflix or iTunes from anywhere and anytime, these channels provide a large amount of user-specific information to the channel owner.

What do people like to watch, listen to, or otherwise engage on a media platform? OTT analytics can accurately collect information relevant to each user, especially when combined with viewing profiles. This analytics is more useful to companies than any previous media consumption analysis. For example, a preschool age mom is likely to play children’s movies on a media platform during the day, but then switches her viewing to older content after 7 or 8 PM. Preferred time to consume media preferred device for certain media, and even smaller data sets all play a part in creating a behavioral analysis system.

As a data analysis platform is given more information, the predictive analysis gets more accurate and creates more specific recommendations for each customer. This provides companies a great base to retain and increase customer use of their platform.

Use AI to Retain Customers

It is easier and more affordable to keep a current customer engaged than it is to get a new customer. Predictive analytics software gives companies the ability to engage their customers, retaining them for long-term growth.

Customers who get content they want to watch are more likely to keep watching on that platform. This individualized access to content is a driving force that leads people to “cut the cord” and go completely OTT in their viewing habits. Anyone over 30 remembers the feeling of clicking the remote, and continuing to click it, hoping that something “good” will be on.

“100s of channels and nothing’s on.” If you know this feeling, you understand the power of analytically driven content to retain customers. Since each individual has different viewing preferences, a standardized product lineup will always drive some customers away while engaging other customers.

On the other hand, personalized content will help customers keep using the platform and consuming media. Because of personalized content on Netflix and Hulu, predictive analytics software and AI are quickly becoming essential parts of any content delivery platform. Even the traditional platforms are working to be more and more individualized to compete, so that cable subscribers get personalized content online.

Endorsement Culture: Why Your Audience’s Opinion Matters

We live in a world where we depend on other people’s opinions prior to buying a product or service. It has been this way for quite some time. Years ago, if a celebrity endorsed one product over another, that would become the most popular product.

Now that everything has become Internet-focused, endorsements have changed. They are still important and consumers rely on them to make decisions. Product affinity is commonly linked to sentiment, which is why social media reviews are vital.

Opinions from real people are utilized in Facebook, Yelp, directly on the websites, and more. It shows potential consumers that real people have tried a product or service and the full review is provided. Integrations also make sure that the reviews are backed by a specific source to ensure that the opinions are authentic.

The Importance of Sentiment
It’s hard to argue that search engine optimization is one of the most critical components to the success of your web presence. If you want your business to be more visible, you need to make sure that your website is coming up in search engines when people search for products or services that you have to offer.

There is a lot that goes into search engine optimization tactics, Including keyword planning and backlinks. Sentiment analysis is also becoming a major part of the algorithm. Search engines look to see what kind of opinions are circulating about a business. More reviews and more positive reviews will help a business to rank higher than a business that doesn’t have many reviews or doesn’t have many positive reviews. Essentially, it is the search engine’s way of providing their own endorsements regarding the various websites that could be shown for a particular keyword.

The insights that you can receive from sentiment analysis can help you with your marketing strategy and ensure that you have greater success with campaigns.

Creating Your Content Strategy
Your brand needs to be visible everywhere so that people can learn more about you. Your brand strategy is based on the content that you deliver, the experiences that you provide, as well as the reviews that come in from past customers.

A.I. can help with your content strategy to ensure that you’re able to deliver relevant content and provide the most meaningful experiences possible. Meaningful experiences lead to positive reviews, which are a necessity to grow as a business.

Content preference can be created on your site to ensure that people see what they want to see. Establishing this allows you to tap into next generation insights so that you can ensure media consumption is what your consumers want instead of what you think they want.

Connect with Consumers
You need all the help that you can get to connect with consumers. What they think of you and what they read about what others think of you will be used in their decisions. You can gain considerable insights by using artificial intelligence to your advantage.

A lot of data can be pulled from reviews to learn more about the meaning of word combinations. It allows the computers to figure out whether reviews are positive or negative. From there, it will give you more information about what consumers want, what they’re going to buy, how they’ll buy, and more. This data can be used to help you market more effectively so you have greater understanding of who your target market is.

For more information about endorsements and how it impacts sentiment, contact Misha T Williams today. You can see how A.I. will work to show you more about your target demographic and use insight to get the competitive edge in the marketplace.

How Social Media and A.I. Influences Streaming Media (Video & Music) Content Preferences


Using A.I. technology can assist in social media analytics and audience personalization

There isn’t any denying that social media has become the major digital metropolis of our times. Twitter and Facebook alone make up a good portion of the world opining about virtually everything. In some cases, it also means setting precedents, something we’ve seen with the great organization in political groups.

Technology plays as much of a factor now in scoping out social media information. Machine learning can scan social channels to create preferences for specific types of media.

Take a look at how social media influences streaming media today and in setting content preferences for audiences.

How Does Social Media Opinion Influence Music Streaming?
Tech analysts continue to look at how much social media affects what you play on music streaming sites from Spotify to SoundCloud.

It’s not a new analysis when you consider the ability to create personal communities on social media was already around more than five years ago. Those options are even greater five years later, including the rise in media influencers and abilities to share information in real-time through live streaming apps.

All of this factors into one giant melting pot of opinion about music today. Trying to assess all that opinion, though, is impossible for even a large group of humans.

Only artificial intelligence and machine learning can tap into what’s said about music on social media and influence what you’ll hear on streaming music services.

Content Personalization on Music Streaming Services
If you’ve read up on machine learning recently, you’ve probably seen how much personalizing goes into entertainment and media. Thanks to A.I. programs being able to understand consumers better than they know themselves, more personalized recommendations can take place through media streaming.

In music streaming, you’re seeing this being used effectively at Pandora. The algorithms they use in machine learning work on a far deeper level beyond providing music recommendations from past behavior.

Their platform works by also extracting information about the emotions of songs and how they affect listeners. Known as the Music Genome Project, the Pandora team is made up of musicologists who understand the mechanics of music and how it resonates.

Using metadata from machine learning, Pandora can now provide more relevant music recommendations than any other service available. As eerie as this might sound, providing the music their users really want to hear is a powerful way to retain their user base.

Personalizing Streaming Video
Artificial intelligence works with streaming video as well. When machine learning programs scan social media, video companies can find out cumulative opinion on which TV shows or movies are being discussed. This can persuade leading streaming services like Netflix to decide which movies or TV shows they’ll promote over others.

Machine learning works equally on a more technical level particularly in preventing potential buffering lags. MIT Computer Science and Artificial Intelligence Lab (CSAIL) worked to create an AI program that prevents this from happening. They designed a neural network allowing a way to decide when a connection requires one particular algorithm over another.

It’s a way forward to prevent future buffering problems in video streaming services, which is good news as public demand increases.

The Future of More Targeted Marketing
Since streaming services are already mainstream and likely the main source of how we’ll view entertainment in the coming decade, machine learning is going to help with marketing. A.I. continues to evolve and help with this by working on social media channels. It results in clustering and knowing more detail about human behavior, bringing a way to mimic how specific demographics talk on social channels.

Creating a more personalized linguistic approach to streaming service marketing results in providing a truly customized experience no one’s seen before.

Visit our website to learn how we can use machine learning to scan social media and help influence what you provide in the way of streaming media.

A.I. and the Power of Personalization in the Entertainment & Media Sector


In almost every industry today, you’re seeing an increase in personalized experiences for consumers. With more people wanting control over how they buy or consume content, entertainment companies are in the midst of abiding by these customer demands.

The consumer need to personalize content is a psychological impulse to find more control in a world filled with information overload. Since media content choices are often overwhelming, it’s all the more important for consumers to find something fitting their world views.

At the center of all this is artificial intelligence. Take a look at how machine learning continues to evolve personalized experiences in entertainment and media.

How Is A.I. Creating What You Want to See?
Most people know about how artificial intelligence operates in the financial services, healthcare, and manufacturing industries. In the entertainment world, it’s perhaps a little more discreet, though it’s actively being used.

Media analysts point out that A.I. is being used most actively in media companies at startup mode or in major conglomerates. In both cases, it’s important to use machine learning to find the proper demographics, and to keep dominance going in a more competitive media landscape.

Big company names like Spotify, Facebook, and Netflix are all focusing on using machine learning and using behavioral analytics to create content discovery.

Real Cases of Content Discovery
One of the most powerful methods toward personalization in entertainment is helping consumers find exactly what they initially didn’t think they wanted. These happy content discovery surprises are what’s going to change the way the entertainment industry works.

For smaller media companies who want audiences to find their work online, machine learning can help find an audience for everything. Statistics show tens of millions of people who create content end up having most of what they created never seen.

Underway now is creating machine learning programs that teach the model what people consider great content. Eventually, this could lead to millions of media sites being better sorted and presented as content discovery on various sites.

It could mean content written years ago finally being discovered and finding a proper audience.

Interaction Through Entertainment Systems
While content discovery is going to become a major development in machine learning, so too will interactions with numerous media devices.

The ability to make entertainment easily accessible at any time (and on any device) is already in development. Making it available on-demand through voice controls is also the next evolutionary leap. Amazon’s Echo is currently at the helm, including a major team-up with DISH last year to create a voice-activated DVR system.

Machine learning continues to work through Alexa to customize more than just a TV show or movie you prefer. It’s also going to help media companies know what kind of commercials or trailers you’d want to see.

Personalizing on this level might sound initially intrusive. Regardless, most consumers are likely to appreciate having a platform that makes consuming media more convenient with our schedules and viewing habits.

Interactive Participation in Entertainment
If more personalized interactions can take place on giving media consumers choice, what about having interactive participation in certain types of media?

We’ve already seen some of this in the social media realms thanks to live streaming apps. However, the possible integration of machine learning with virtual reality could create entirely new entertainment experiences.

Imagine being able to interact in a virtual reality space that’s customized based on your own personal preferences? Artificial intelligence is at a level now where it more or less knows you better than you know yourself.

Interacting in a customized entertainment landscape would become the ultimate escape, something many people may prefer in the times we live in.

Visit our website to learn more about how we can bring more personalized entertainment & media experiences to your customers.


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