Why segmented content is so (damn) crucial – but hard to create

Writing content that appeals to all your target groups is hard! Brands need to send messages to different target groups in different places with different needs on different platforms, and that can be next to impossible and at least put a lot of demand your resources. 

One core message with many audiences

Producing content often require significant resources to ensure segmented, high-quality content that’s loyal to your Tone of Voice. For many, that takes a lot of effort, and the process can be confusing and rather time consuming. 

Imagine you have both B2B customers and B2C customers. Imagine your target groups consist of more than just one gender, one age group, one language variable, one type of interest, and one preferred channel. Imagine they are spread across industries, departments, job titles, or countries.

It’s not exactly a farfetched marketing situation…

A lot of content producers need to find a way to easily change one core main message to fit different segments – and if they manage that, they’ll need to handle several versions of content without getting them mixed up.

AI assisted content

One way to achieve that is through AI, which can save content producers a lot of time by making tasks such as translations and versioning faster. 

Some companies use regular AI engines but beware that the results from these tools might depend very much on the person who provides the input. Such AI tools also often need a lot of manual work, like copying and pasting by hand, which takes time. And note, that they might not have a place to store and share data, making it hard to keep track of content. Plus, they might not have rules to keep data safe, which can lead to leaks. Ick. 

If you want to do a bit more reading on what goes wrong in AI projects (and how to fix them), check out our blog post Too many AI projects flop – what goes wrong and how to fix it?.

AI orchestration making segmented content efficient

If you want to mitigate some of the challenges of AI assisted content, you can consider basing it on an infrastructure that’s designed to orchestrate and accelerate data at scale. That basically means that you can orchestrate data across systems and that all content producers share the same scalable workflow. Your published content will be far less dependent on the specific producer as they all work in the same AI model, and it doesn’t really require very much AI knowledge. 

AI can be trained to understand your specific content needs and keep improving with feedback. This ensures the content is always getting better. With that said, it’s always a good idea to keep in human approval to make sure the content is appropriate and fits your brand. 

So, to sum up – data orchestration at scale is a way to achieve a coherent, structured approach to segmented content can help you create, manage, scale, and distribute customised content across all channels with limited effort.