Social media marketing is now a must in the advertising strategies of almost every small, medium, and big company in the world.
Whenever a new social platform emerges, it provides brands with new opportunities to increase their brand awareness. The pace, size, and variety of advertising techniques on social networks are so huge that companies are recruiting numerous employees to handle them.
Even the smartest social media marketers can’t handle all the required information when monitoring social media performance and making the right decision.
That’s why more and more businesses are utilizing artificial intelligence technology to monitor social media trends, target relevant audiences, and recognize customers’ demands.
In this post, you will learn how machine learning can provide marketing strategists with a smart method for advertising on social media.
Basic Principles of a Great Social Media Strategy
First, it’s good to know what a social media marketing strategy is.
This is a typical social media strategy that marketers use to grow their business on social networks:
- Setting S.M.A.R.T goals
- Defining the target audience
- Choosing the best channels
- Generating content
- Engaging with audiences
- Promoting your content
- Analyzing your performance
As you can see, many stages of this process need big data analysis.
For example, targeting a relevant audience is an important component of a social media strategy. This stage will affect all the other stages in your strategy, especially content marketing. You can’t generate relevant content without knowing your audience and their characteristics.
Imagine your audience are Gen Z; you can’t generate old-fashioned social media posts for them and expect a great conversion.
That’s exactly why you need a smart audience recognition and targeting approach. Machine learning has recently revolutionized the audience targeting process, and you need to include it in your plans.
Many other stages in a social media marketing strategy need advanced methods for recognizing patterns and finding the best response.
Machine learning is definitely the solution.
What is Machine Learning?
Machine Learning is the method of making machines learn systems behaviors and act accordingly, just like humans do.
This process usually happens by feeding computer data and information about the system and an algorithm for learning.
In fact, with machine learning, computers can model the performance of real systems and react based on the model.
With advanced processing technologies and machine learning methods, computers can process a large amount of data within seconds and recognize the patterns.
Artificial Neural Networks are now vastly used for machine learning and have been revolutionized in recent years. Deep learning using ANNs provides researchers with the unprecedented ability to make machines smart.
This is a powerful technology for modeling complex systems and has applications in almost every field like the economy, engineering, meteorology, etc.
So this technology worth considering. As a result, $28.5 billion was allocated to machine learning projects worldwide only during the first quarter of 2019.
Around 75% of companies worldwide believe machine learning will revolutionize future industries and job markets.
Of course, marketing and advertising are not exceptions and can be benefited from this technology.
Benefits of Machine Learning to Social Media Marketing
Now, let’s review some beneficial aspects of using machine learning in social media marketing.
#1 – Sentiment Analysis
Sentiment analysis is the process of analyzing audiences’ comments to recognize negative, positive, and neutral intents.
The results help brands figure out how their customers feel about their products/services. Customer services should apply sentiment analysis and react accordingly.
Of course, sentiment analysis will be a time-sucking task when the number of audiences increases. Machine learning can tackle this problem properly.
Sentiment analysis tools can be trained with emotions in sample texts to be able to recognize the intents of new inputs.
#2 – Mention Monitoring
As a digital marketer, you should appear wherever your niche keywords are mentioned. This is not possible unless you use machine learning.
For example, if you’re active in the food industry, you can train the neural network to recognize whenever words related to food are mentioned.
Then, you can interact with those social posts and redirect users to your profile.
#3 – Reputation Management
You can’t always expect to have positive mentions on social media. Every brand might face customers’ complaints on social media or even fake news that damage their brand’s reputation.
Without systematic reputation management, you will face significant problems on social media.
If you’re searching for a way to tackle this problem, you can’t find anything better than machine learning. Reputation management tools use artificial neural networks to help brands find these troubles and react accordingly.
#4 – Image Processing
Tracking mentions of your business, products, and services are useful in social media marketing. Many times, users don’t mention the name of the brand or product when posting an image.
To include these mentions, you should apply image processing and interact with those social posts. This is a smart and targeted promotion to those who are certainly related to the specific brand, product, or service.
Image processing is another application of machine learning and can be used to recognize images. You can train computers to recognize a logo or even certain kinds of goods across social media channels.
With this method, you have the chance to kill two birds with a single stone.
First, performing a targeted outreach campaign to your audience and smart promotion. Second, increasing the chance of being mentioned in more posts because users will be encouraged.
#5 – Selective Content Offering
You must have used Instagram explore page and browsed through its offered posts. Have you ever thought about how the platform chooses these posts?
You might think that this is a random selection process. If so, you’re wrong!
Instagram is using AI to choose content for your Instagram Explore page, based on your previous interactions on the platform. The platform uses an algorithm to recognize what content is of more interest to you to prioritize and show them to you.
This is what many other platforms Facebook and Twitter are using for offering new connections, ads, content, trends, etc.
On Twitter, for example, trends will be shown based on your location. Ads and “Who to follow” are also offered using machine learning.
#6 – Smart Audience Targeting
With social platforms, it is straightforward to reach out to as many audiences as possible and to convert them to potential customers.
But the truth is the number of audiences can’t increase your marketing ROI, and you need a more advanced method to choose your target audience.
Defining the target audience and reaching out to them is a critical stage in social media marketing plans. If you can target the users that are highly likely to buy your products/services, you will definitely reach success in marketing. This approach is much more impactful compared to mass outreach for getting more and more followers.
Mass advertising without any specific focus can lead to a low ROI. Many social platforms, especially Facebook, use deep learning to decide which users should watch which ads.
Not only these giants, but many other companies are shifting towards this approach to optimize their ads. By collecting enough data, sorting it in terms of important factors like gender, age, region, language, accent, interests, position, etc., brands can prioritize their audiences on social media.
Smart audience targeting predicts the interests of social media users using artificial neural networks. This technology can then be used to offer relevant content, ads, and even the best posting times.
#7 – Choosing The Right Social Platform
As mentioned earlier, choosing the right platform for your brand is an important part of your marketing strategy.
You should know the demographics of every platform to know where you can find your target audience better.
For example, Pinterest is of more interest to women as opposed to men. On the other hand, TikTok appeals more to Gen Z compared to other generations.
Social media analytics tools provide users with insightful data in this regard. Of course, machine learning plays a significant role in analyzing such information and getting major patterns.
Try to prioritize the best platforms for your niche before embarking on social media marketing.
The application of machine learning in social media marketing is growing day by day, and each company that is ignoring it will lose the market.
If you own an eCommerce business, you need to hurry to take advantage of this tech to optimize your performance.
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About the author
Tom Siani is an online marketing expert with more than 5 years of experience in this digital industry. He is also collaborating with some well-known brands in order to generate traffic, create sales funnels, and increase online sales. He has written a considerable number of articles about social media marketing, brand marketing, blogging, search visibility, etc.