We hear a lot about how learning the machine will be part of the future of each buyer content. But in reality, machine learning is here and ready to work for you now . The best way to extrapolate the future is to look at what learning the machine is doing today.
Marketers are under pressure to reach the speed of content faster. Demand for content is exploding, driven by the number of channels, the specificity with which the traders want to create targeted content for the public, and how specific they want to be in the mail to specific audiences through these channels . The challenge is how to use, reuse and remix the content of new ways to reach these audiences – encourage them to engage and respond – without recreating lot of content. There is no way to do this manually and to scale. Machine learning can help in three ways :. by automating repetitive tasks, using the content targeted, and create good content
Automate repetitive tasks – you can focus on more important issues
How time do you spend on administrative tasks, such as marking of assets, compared to content creation? Tagging assets with relevant keywords is essential to do the research, but it is also a tedious time as most traders prefer to avoid. The technology of the machine-learning can intelligently include the most valuable keywords or cheaper copies. It may involve similar or related assets, making it easier to combine relevant copy, images and videos to target audiences. If your audience has consumed some content, it can intelligently recommend what to get next to the highest conversions. It can help to predict what content will lead to behaviors – sharing or engage with the content, increased sales, improved loyalty of customers – you try to reach customers. Adobe Smart Tag technology is now available to automate the insertion of metadata, so you can get better search results while reducing the amount of time you spend on this task.
Use and reuse your content and ways in Channel-specific audience.
Each marketing channel has a unique set of requirements regarding the size and resolution of marketing assets. When a new platform emerges – or if you decide to add a new channel – it could require the time and expense of the overhaul of existing assets. For example, if you have a piece of content delivered to a web channel or blog, learning machine can intelligently reframe the content of a mobile channel or reduce the copy intelligently. Visual content and videos can be shortened to optimize the experiences of different channels based on grounds on which people consume.
Machine Learning will be providing recommendations – or actually provide a first draft of the new content – which can then help to accelerate the pace by which you get these different copy songs or creation or even videos on the different channels and selected audiences.
Create good content without creating a lot content.
You do not want to have to create huge amounts of content, hoping that some of it will be effective. It is more important to be able to create good content that is effective in your channels, learn from it, and then create more content based on these ideas and develop from there.
Machine learning can provide the information necessary to determine quickly what works and recommendations to direct you to amplify things (or something similar) that could also work with the public. The learning machine learning part means that, over time, the machine becomes smarter. We are still in the early stages with this, but the machines could potentially learn so fast that you can remix, reuse and adapt the content almost instantly; Try it; and whether it will be an improvement over your previous campaign or you need a different approach.
The future is within your reach!
The best way to think of learning the machine as an intelligent assistant that can quickly draw conclusions or recommendations based on large amounts of diverse data. Marketers can then learn and understand how content is consumed, how behaviors “its impact on consumers and how to create more relevant, interesting and engaging experiences for consumers. The potential impact of machine learning all aspects of the customer experience is vast -. Search marketing technology solutions that allow you and your team to experiment with learning in depth to see how it can increase your productivity now