CONTENT AND DATA: WHY THE FORMER DEPENDS ON THE LATTER
We all know and understand content marketing. Everything that we see online is content marketing – videos, blogs, infographics and research reports. They are mostly developed by brands or content publishers to have a level of engagement with their target audience. I’d like to elicit that I personally spend a lot of my content time on recipe videos by food companies in the hope of becoming a better chef!
Overall expectation of investing in content marketing by a brand is that it will indirectly lead to driving conversions. Marketers generate this type of content with the intent that a significant part of the content’s target audience will take that action. A few prerequisites are needed for this to happen. Firstly, the content must drive some value for the person seeing it. It should elicit an emotive response, and/or help them understand a topic better, or in my case, make me a better chef. Second, it’s equally important that it should be relevant for the potential user base and it should be crafted keeping them in mind and ensure it reaches them via some form of effective distribution. And lastly, it is important to analyse, and course correct the activity to ensure it is driving results. This is where data comes in, since it plays an important role in identifying who is it being made for, where will they see it, to what extent it is fulfilling the objective, and so on.
The data we talk about here can largely be split into two categories:
PRE RELEASE: research – Using data prior to content development as an input to elicit or predict certain responses.
Research requires a marketer to dig into the audience, their online habits, and preferences. Social media listening is an effective medium to understand this. What users talk about online gives us detailed insights into what issues they care about. Ideas for creating value-driven content can be identified via listening tools and brands can accordingly speak to what the audience is asking for. The best performing ideas are usually the ones identified from here.
We can also use the same tools to understand platform preferences and other online behaviours. By doing this, we can ensure better visibility for the content as well. A very simple example would be identifying data on Instagram insights showing when a brand’s followers are most active online, and using that insight to actually get better engagement and visibility for all content that the brand posts.
POST RELEASE: the feedback – To understand the content’s performance and use it as a learning for the next campaign
Here, we check the extent to which the content is performing – how it is fulfilling the expected business objectives that we had first set out to achieve. One of the easiest ways is to implement Google Analytics on the brand website. This tool provides us with web traffic origin details and every action taken on the website by users, giving us a detailed understanding of what the consumer is looking for when they are on our brand website. We can trace what content is driving more business actions, like sign-ups or transactions. A popular practice here is the A/B testing model. In this we test content A and content B, observe which performed better, and double down on that content or on that approach. This ensures the content gets better with each iteration.
Considering the content overload that an average user has in the current digital age, if content marketing is done without considering the data insights, it is likely to be lost in the jungle of online content.
Tags : digital marketing Content Data SOCHEERS Siddharth Devnani