How-Deep-Learning-Affects-Social-Media-Monitoring

How Deep Learning Affects Social Media Monitoring

Back in the day, postcards, e-mails, website and the phone were the most common tools for engaging with

Back in the day, postcards, e-mails, website and the phone were the most common tools for engaging with brands. The customers would pick up their phones and dial customer care reps. Their concerns were answered through the phone, and if not, one had to book an appointment with the customer care.

Since the advent of social media platforms, things have changed. The social media has become rooted in the business environment, creating a need to involve third parties in social media monitoring. The number of social media applications has increased. Customers are using different channels and brands are forced to keep an eye on all these channels. Statistics also show that user-generated content on social media is increasing at a high rate. Consequently, there is a need for brands to adopt a new technology for social media management. This is where deep learning and artificial intelligence comes into perspective.

Deep learning has become very important in different sectors. From self-driven vehicles to use of voice assistants, deep learning is basically everywhere. Deep learning is also referred to as deep structured learning. It is a subset of Artificial Intelligence that is concerned with imitating how human brain would react to a situation. Machines employ deep learning algorithms that are capable of learning unsupervised from unstructured data (Investopedia).

In this article, we explore how deep learning affects social media monitoring. Through the use of deep leaning, social media monitoring tools help businesses uncover deep consumer insights. Keep reading to find out how and why!

Deep Learning Aids Text and Image Recognition

It is a fact that among the social media users, we have haters and genuine customers. The haters will spit all types of insults and post negative comments about brands. The social media subscription and use has grown to exceed the capability of human monitoring, hence necessitating the use of deep learning. The reason why businesses need social media monitoring is to be able to monitor mentions and identify opportunities. Basically, brands want to be able to identify positive and negative comments. Through this, businesses can be able to identify where they need to change how they operate and where to keep up the trend. Therefore, through deep learning algorithms, they can effectively achieve this objective.

Deep learning allows social media monitoring agents to easily classify these negative and positive comments. Clustering helps in determining how to respond to different concerns raised on social media. In some cases, we still have the human beings doing social media monitoring, though not as effective as those using deep leaning enabled monitoring tools. For the brands, monitoring social media through human efforts solely, it is not an easy task.

However, social media monitoring through deep learning algorithms allows businesses to be able to gain more consumer insights. Further, the analysis is done and presented in real time. This means that businesses can be able to keep up with what is happening on social media.

Deep Learning Will Help Ensure Conformance to Customer Needs

One of the objectives of social media monitoring is ensuring businesses conform to needs of customers. Note that clients will express themselves on different social media platforms. It is important to identify what they say about your brand and at the same time match their unique needs.

Effective social media monitoring is achieved through the use of deep learning algorithms. This helps identify and categorize customer needs. Therefore, businesses can respond to these needs while making sure they are matched. This is through developing better-targeted marketing strategies and developing relevant content. These are the first steps that are important when trying to attract new prospects to a business. Ultimately, the business will see a higher return on investments courtesy of better targeting approaches.

The faster a business responds to what its potential clients want the better. Therefore, a business that wants to ensure they win opportunities should embrace deep learning in social media monitoring so as to effectively learn what to offer their clients.

Using Deep Learning in Social Media Monitoring Helps Ensure Effective Customer Service

Social media is not only good as a marketing platform. We have also outlined that social media helps in customer service. Real-time interaction is one of the strategies for ensuring effective customer care. There are dozens of clients reaching out to brands through social media. These clients are after a fast reply from these brands. Therefore, they want to ensure that they can easily identify communication from clients. This will ultimately help the business make a timely reply.

There are hundreds of comments being sent by concerned clients each hour. How can a business identify which ones want an immediate reply? It’s through deep learning algorithms deployed for social media monitoring. Therefore, a business that has deployed deep learning social media monitoring platform will register a high level of customer satisfaction. In turn, they will achieve happier clients leading to more profits.

One of the application areas of deep learning in improving customer satisfaction is the development of chatbots. These are able to interpret customer request and respond appropriately. Brands have introduced chatbots on their social media accounts that respond to customer queries even after business hours. Through this strategy, a business is able to offer 24/7 responses to customer requests.

Example

A good example where deep learning is used in social media monitoring to drive customer support is by KLM. The Dutch Airline deployed wanted to ensure that clients feel a personal touch on every reply that they send to the airline. The KLM Facebook Chatbot sends automated updates to clients enquiring about the available flights and flight schedules. See the screenshot below to see some of the responses that the company sent to its clients over the chatbot.

KLM-Facebook-Chatbot Deep Learning

Deep Learning for Social Media Data Analysis

Apart from interacting with clients, the brands use social media as a learning platform. There is a lot of information on the social media that businesses need to analyze for effective decision making. Therefore, it is critical to make sure that businesses can analyze this data for logical conclusions. But how do businesses ensure they have the information they need? It’s of course, through the use of deep learning algorithms to analyze raw data. Therefore, through deep learning a business will be able to analyze the data corrected through the social media analysis tool.

Analyzing this data without making use of deep learning can result in missing on some crucial data. In addition, it will take a longer time to analyze the massive data collected from the social media. Of course, this will have a significant effect on the performance of the business. However, a business that has applied deep learning in analyzing the data corrected through social media monitoring, will have an added advantage.

Therefore, deep learning will help businesses to overcome the information overload. We have noted that social media monitoring tools will generate a lot of information. However, not all of this information makes sense to the company. Basically, the businesses are facing information overload in the form of text, video, image, and sounds. To overcome the overload, social media monitoring tools need to have appropriate deep learning tool. Through this tool, the business will categorize the information and so can extract the important data needed for decision making.

Deep Learning Enables Businesses to Keep an Eye on Emerging Topics

The social media is the best platform where you can read the latest news and be up to date with what is happening. Businesses want to be up to date with current trends so as to take advantage of the potential to market their products. If you are familiar with social media trending hashtags, then you already know about the great potential they offer businesses.

For a business that wants to be informed of the trending news, deep learning in social media monitoring is the best approach. Much insight can be gleaned from examining what bloggers are sharing on social media (Researchgate).

From a business perspective, marketers would also be interested to find out what is being said about the trending topics. This involves digging beyond the keywords to establish what the contributors are saying. The use of deep learning is therefore essential to achieve this. Once they establish what the topic is about, they can then come up with appropriate content. This content helps the business to take advantage of the current trending topics to drive engagement.

Deep Learning Helps Businesses Achieve Higher ROI

Businesses using deep learning for social media monitoring will achieve higher Returns on Investment. But why is this case? The use of machine learning in social media monitoring eliminates the need for human intervention. The machines have a higher capability when it comes to achieving consumer insights since they can work for longer time. Therefore, the deep learning algorithms can run for more time with minimal downtime experienced.

In the business world, it is all about making timely decisions and taking opportunities before they are taken by competitors. Remember that businesses are competing for the same consumer. Marketers want to be able to identify a consumer who is ready to spend and ensure they win the opportunity. It is a fact that consumers have embraced the social media as a learning and communication channel. Therefore, they start their shopping journey from the social media and complete it there. This is by doing research online as they discuss products and do a comparison of related brands.

As a marketer, joining the conversation increases the chances of ensuring you will win the deal. On the other side, you also want to be able to share and comment on posts from satisfied customers who share their experience through social media. These efforts have a positive impact on your overall profitability. To maximize the ROI, businesses should ensure that they invest in deep learning systems.

Conclusion

Deep learning will generally make it possible for the businesses to make appropriate decisions. To begin with, machines don’t need to sleep. Therefore, through the use of machines to run deep learning algorithms, businesses can monitor social media space throughout. This helps to create a bigger knowledge tank for businesses. Through deep learning, businesses can gain better consumer insights helping in decision making. This is because deep learning enables thorough scrutiny of the data available through social media space.

Deep learning also enables businesses to watch what is happening in the industry holistically. You already are aware of how trending hashtags and how effective these are for social media marketing. Businesses that use a deep learning social media monitoring tool will be able to identify trending topics much quicker. This allows them to take advantage of these topics before competitors find them. In the long run, businesses that take advantage of deep learning will achieve higher Return on Investment.

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What's more, you can also get access to the same data for your competitors. Also, you can monitor keywords and phrases related to your industry, and this way you can get very useful consumer insights in real-time. These insights could cost hundreds of dollars to acquire from a research agency.

About John Kopanakis

John is a co-founder of Mentionlytics supervising Business Development and Business Processes. He is a Professor of Business Intelligence with interests in Data Analytics and Innovation.