The biggest challenge in content marketing is the insufficient content available to sustain the technology investments. As a result, it’s difficult for companies to see an ROI. Some marketers invest in personalization technology to share a targeted story with an individual customer. But they lack volume content to ensure that personalization is a worthwhile effort. Despite that, the Internet is still loaded with content. There are 2.5 quintillion bytes of data made every day. Hence, it’s difficult to penetrate the targeted marketed because of the digital noise. But you can change that by implementing a new strategy, i.e. the application of machine learning tools.
Machine learning involves programming computer algorithms to learn from the information they input. The output of these machines can vary every time as they change resulting actions based on patterns and trends. The more information the machine gets, the more accurate the results are. Since we’re loaded with content, there’s too much to read. As a result, it decreases engagement. To fight that issue, it’s vital to track analytics of your blogs and social media. Doing so will help you better understand trends so you can determine the direction of your blog efforts and social media campaign. With the use of machine learning tools, content marketing strategy becomes more effective and beneficial to the audience. Here are some ways machine learning tools can help you push your content marketing strategy so your audience can read your content and increase engagement.
Maximize benefits of email marketing
Email marketing is still the most effective ways to interact with the audience and reach out to a target market. But to make it more useful, you need to personalize it for your recipient. Personalization requires sending of information that’s relevant to your prospects. A machine learning tool utilizes predictive email marketing that can increase CTRs and ensure repeat business.
Machine learning tools can analyze eCommerce transactions and the behavior of customers. From the data taken, these tools can send product recommendations through email at those times that prove to generate more clicks. They could show the items that customers clicked when they last visited your site. Machine learning tools could also offer promotions or products that your customers might be interested in. This smart tool can identify products to ensure that the recommended items sent to the recipients are relevant. It can send your email subscribers products that they’re going to love at the time when they’re likely to buy them.
Create blog content that increases engagement
A machine learning tool can tell you when should you share your articles and what part of it that truly matters to your readers.
It shows the audience level that offers the most engagement. Then, it tells you how you can maximize that engagement through predictive analysis. Some machine learning tools can show parts of the content that achieve the standard of optimal engagement. They also tell which areas you can optimize for maximize engagement. These tools are also useful in helping you schedule what articles to share to your social media accounts. What’s great about them is that they can schedule it based on the social engagement behavior of the audience. Furthermore, machine learning tools can ensure that every article you publish is high-scoring. With that in mind, you can maintain providing your audience with a high level of content based on social media engagement and blog data.
Choose the right content creators
In your company, you may have content writers who generate posts for your blogs. Unfortunately, it’s not easy to find those writers that fall within your budget. It’s challenging and time-consuming. If you need to hire content creators, you can use machine learning tools that help you maximize a job listing. This kind of tool predicts the success of a job listing. It can also tell whether or not candidates will respond to the request. Because of its benefits, you find candidates that match the personality of your team and your company’s work ethic. The tools save time in writing a job listing that’ll never attract the right candidate. With it, you can acquire the best new content writer or content marketer for your company.
Provide an excellent customer experience
Machine learning tools don’t just make suggestions according to what they learned from questions and requests. But they also process language commands so they can respond like how humans respond to text or verbally. They can understand, reason and learn, as well as interact. How they improve customer experience? If your users interact with them, the tools can solve a problem quickly without having to fill out a standard form. These tools can help your customers with their immediate question. They can direct the users to marketing materials related to their inquiry. Machine learning tools can open a lot of possibilities to personalize your message to your customers. As a marketer, you can understand your audience through the collected data so you can create personalized and dedicated pages for your users. Because they’re personalized, they are more likely to click on your CTA button to fulfill your conversion goal.
Concerns about machine learning tools that analyze content
Some marketers are wary about these tools in identifying or predating the performance for their content. But technology allows them to have full control over their content, and it empowers them to have a well-informed decision. They also have to understand that humans are still the ones to choose what to publish. A content marketing strategy based on machine learning can store all user-generated and branded posts centrally. It ensures that they’re tagged and classified in such a way that it enables marketers to choose the right content for the right audience at the proper time. Marketers can obtain those tagged materials and place them in an automation tool or an ad. All posts are stored in a central library for future purposes. As a result, marketers can quickly move to a multi channel approach. It makes it easier to manage and avoid a disconnected user journey.
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