How To Supercharge Your Social Media Marketing Strategies
The increasingly popular buzzword Machine Learning, known by the acronym of ML is revamping the marketing world. Gartner predicted that by 2020, 30% of all B2B companies will employ Machine Learning to augment their lead generation processes. Companies are making use of Machine Learning to tackle marketing challenges such as instant customer support, and big data in order to compete with rivals. Before we get into the marketing world, let’s have a quick glance at what Machine Learning really is, and what future applications it might have.
Machine Learning (ML) is a branch of Artificial Intelligence (AI). It is simply a highly sophisticated algorithm that can be optimized for machines to exhibit intelligence to perform certain activities as humans demonstrate as a characteristic of their intelligence. Based on the availability of the data, Machine Learning empowers the systems to come up with better solutions automatically by learning from mistakes and experiences. The more the useful data is, the better is the solution it proposes.
Data plays an important role in the marketing world. The marketing teams not only put efforts into making sense of all the data they have at their fingertips but also having valuable insights to make better decisions. The data analysis ground is where Machine Learning comes into action because it has the ability to comprehend data manifolds much faster and much more effectively than humans.
Machine Learning algorithms involve a process where the systems run through the data multiple times to identify patterns and make predictions almost instantly. Given that it has impacted every field constructively, digital marketing is no exception. Reportedly, there are 95 million Instagram posts/day, 31.25 million Facebook posts/minute, and 6,000 tweets/second. Therefore, as data is huge in volume, and growing exponentially with time we can call it big data. In order to gain more insights into your marketing strategy, social media analysis relies on this data. The more you know about social media audiences, the better you can market your products.
Let’s dig deep to know how Machine Learning is valuable in making big data actionable in the field of social media.
● Analysis of Data Sets
Using Machine Learning in Social Media Marketing starts with an analysis of datasets. ML gives leverage by analyzing data by crawling through user activity patterns without having to manually sift it, which takes double the time as compared to AI-powered solutions. Based on these patterns, predictions about user behavior are used for optimization purposes. Moreover, Machine Learning assists in a better understanding of your audience based on their actions and behavioral patterns. With the ability to interpret tiny nuances, it helps in quickly identifying important conversations, highlighting posts that are particularly valuable by learning patterns in texts or images. Consequently, it returns the most relevant results to your questions with great accuracy.
● Understand the Consumer Voice
By analyzing the textual content Machine Learning algorithms automates the learning procedures to categorize new posts based on the intended sense and tone by using sentiment analysis as long as these posts are correctly annotated with the expected prediction.
● Creation and Optimization of the Content
We cannot deny the importance of content while crafting Social Media Marketing strategies. However, Machine Learning can augment the impact of the content by ranking it higher in search engine results. Good content not only depends on the writer but also requires tools for smart content creation. There are many tools available that utilize the Machine Learning algorithms to make sure the content is up to the mark by comparing it against Google’s top results. Many AI-powered copywriting tools are also being used to write the content. These tools use Machine Learning algorithms to:
1. Create content that it believes will drive the highest return on investment.
2. Curate and publish the most relevant engaging content for the audience.
● Increase Personalization
Deliver the customer with the most personalized experience as it matters for consumers, otherwise, they switch to a competitor. Accenture claims that 91% of consumers prefer brands that own themselves in a unique way and as a result put forward relevant offers and recommendations.
Machine Learning plays the role here by providing the most personalized customer experience possible. The algorithms continuously track the user pattern on a granular level, precisely learning about what products they like, and as a result create a personalized homepage, recommendation lists, and offers for each customer and email them when there’s a high chance for them to buy.
● Improve Marketing Automation
Besides engaging customers, another way to provide the customers with a better personalization experience is to automate brand marketing efforts and consequently improve customer engagement significantly. According to Invesp, sales productivity increments by 14% and decrements marketing overhead by 12% reduction by simply employing marketing automation. Machine Learning algorithms help in tailoring the content and offers based on the consumer’s browsing history and let you automatically send an email to customers when they sign up for your newsletter or abandon their cart.
AI-powered marketing automation tools allow sales teams to prioritize those leads that are much more likely to convert by analyzing much larger and disparate data sets. The combination of marketing automation involving AI-powered tools is incredibly powerful and provides highly personalized consumer experiences.
● Glean insights from images
Due to the exponential increase in the visual content with platforms such as Instagram, Snapchat, or Pinterest only a few hints or no hints are available in the content of the text. Machine Learning comes to the rescue again, via image recognition algorithms, enabling systems to recognize logos, faces, and objects, in both images and videos. Now you have a track record of when people are sharing your products on social media.
● Utilize Chatbots
In the world of e-commerce business, an essential yet powerful customer service tool is Chatbot. Around 80% of consumers reported positive feedback related to chatbots. With AI-powered chatbots, the customer queries can be automatically answered with a scarily high rate of accuracy without the need for human involvement. The chatbot continuously learns the website content and continuously improves the answers based on past conversations with customers.
All thanks to Natural Language Processing (NLP), chatbots can now have human-level conversations with customers. Moreover, the data gathered by AI-powered chatbots can be analyzed and used by another machine learning algorithm to generate insights and predict the consumer behavior that marketers can use to optimize their efforts going forward.
● Detection of emerging topics and trends
Pattern recognition in language, images, or metadata is now made easy with machine learning algorithms and sorts posts into predefined categories. However, these patterns also predict new trends or topics that do not fit into a pre-existing set of values. These new trends and topics pave the way for engaging content that can lead to a sales boom.
Final Words
It’s true that Machine Learning supercharges Social Media Marketing strategies and the advances in AI-based marketing occur quickly, you might have gotten overwhelmed for the future after reading the article, but start adopting the above-mentioned points after understanding them and work your way through them without rushing. Like in websites, mobile machine learning will be enhanced with AI-powered digital assistants and mobile applications will soon integrate machine learning features giving another field to implement SMM strategies. Start today.