November 08, 2018
Content done well can create value; content done bad can destroy you. In a series of four blogposts, we hope to convince you to start putting content first, distribute it correctly, and share our aspirations for a future of relevant content only.
The strategic requirement of relevant content, now and tomorrow
In case you missed it, don’t cheat yourself out of the first two blogposts in this series which address the two core issues of content – production and distribution:
With these core elements in place, we now want to challenge you on a new dimension of relevance: time. Like Facebook feed pages, you want your content to inspire, inform, and engage from the very moment the viewing experience unfolds. Something new on the page, every time.
We need to stop thinking about content as something static and start thinking about organic or fluid content strategies that can unfold right in front of our users’ eyes. Effectively offering them live, relevant content in the micro-moment. This content can take the form of an ad, video, product, news, articles, etc. – it all depends on the product offering, the type of business and of course, the user.
So, how do we do this?
Unwrapping boxes and finding individuals
In the past, we have tried to answer that question by applying some rules or by understanding patterns in the behaviour of our visitors. Patterns help us make sense of the millions of interests, wants, and needs experienced by our visitors and to strategize for them.
We grouped our users with persona groups, target markets. We learned to understand them through user journeys and behaviours. But does it really work?
If the alternative is one size fits all – then yes! But there’s a new alternative that’s much more efficient and adapted to the needs of today.
From static to fluid content
We, as humans, can’t be put in a box. And even if we could, would our user journey be the same every time? Of course not.
Now this doesn’t mean the content or the process is wrong – it just doesn’t work as effectively as it could. We need to get better at dealing with live data.
This is particularly true for multi-businesses such as Amazon. Someone buying a TV might buy a dress or a book at another time. It’s very rare to buy a TV on a whim without researching the market. On the other hand, a user might realize on Tuesday that they have no dress for Friday, thus experiencing a micro-moment of urgent need. Users go through completely different user journeys and Amazon needs to be able to facilitate all of them.
That’s why we need to look closer at what our sites are being used for. Use data to find out what is working and what isn’t. We need to write for interests that are specific to our business, not creating content for content’s sake, but tailoring content based on what works.
Netflix is one of the biggest producers of content – why not learn from them? It seems that they know what they’re doing, right. They’re a massive success and produce astoundingly good content. Why? Analytics based on algorithms that learn what you like and make sure you’re supplied with more of it. They then look closely at what has been watched, what has been re-watched, what point in time people turn off the video, which scenes are replayed, and even what makes better music tracks for certain scenes. This allows Netflix to make movies that the mass market love. They know beforehand if it will be a success or not.
This is the way we need to start thinking about how we produce and make content.
Hello Machine Learning
We need to free our content projections of personas and turn to interests. Does it really matter to us if our user is categorized in box A or Z? Or do we want to know what that specific person is interested in, how that affects his/her journey on our site, and not least, his/her purchases?
No longer can we have a knee jerk reaction to content and just publish what is relevant now and leave it. We need to think about content in the long term. Develop longer content strategies that evolve just as our audience does.
No army of marketing people or content writers can handle that task. We can only process, predict, and strategize what content goes where by using historical data combined with machine learning. Giving rules or goals to Machine Learning allows the Machine to find patterns in the behaviour as well as page usage. Offering up relevant content, learning what is clicked and what is passed over. Making a better, more engaging experience than ever before and it’s all dynamic.
This is how we need to start thinking about content in the future. This is how we need to start thinking about digital experiences - fluidity as opposed to static noise.
The relevant player takes it all
By looking at content in this way, we can start learning more about what is trending on our site and what is not. We can establish warnings or alerts that notify us to take actions when content is either not consumed or eaten up.
These analytical warnings will allow marketing teams to make fast decisions that can really impact their business by providing the consumers with a much better experience with their brands. Win, win.
If you have further interest in these platforms, don’t hesitate to reach out.