Have you ever closely looked at a wild field? It’s full of different kinds of plants all reaching for the sky. From a distance, it looks harmonious. But if you were to look closer and study it for some time, you’d see that it’s not harmonious at all. It’s a constant war for sun, water, and soil nutrients.
Content marketing is much the same way. You and your competitors are all fighting in the same field for your audience’s attention. It is, alas, a zero-sum game. Humans only have so much they can pay attention to. This means that, like a plant, you need to take advantage of any available tactics to gain more attention from your audience than your competitors. Hopefully, with that increased attention is also a revenue generator.
Digital marketers already have a plethora of attention-grabbing tactics, but every so often a new thing comes along that blows the old tactics out of the water. Often it’s a search engine change, like when Panda and Penguin obliterated old SEO-oriented content tactics and birthed modern content marketing. This time the change comes from marketers who are learning to grasp the power of content intelligence.
Content intelligence is the synergy of artificial intelligence strategies with content marketing. It aims to solve some long-standing inefficiencies with current content marketing. And if you can master it now, your company is going to get a really unfair advantage over your competitors.
Content Marketing Inefficiencies
Content marketing rests on the assumptions that if we give our customers content that they enjoy consuming they’ll want to come back to us for more. Repeated content consumption raises trust between the reader and the content provider, ultimately making it easier to push the reader to conversion.
It’s well-established that repeated contact with a brand is necessary to create enough trust to cause conversion. But the major inefficiency is that content marketers are not mind readers. We have to guess what content our audience wants to read. Companies and data scientists have gathered massive amounts of information about our responses to different kinds and forms of content, but it is still hit and miss.
Many strategies lean on our instinctual psychological impulses to drive us to read things (e.g. clickbait titles). This may get us to read, but it doesn’t necessarily bring us the audience we want or, even more important, give our audience the impression about our business or its products that we want them to have.
In short, a lot of content marketing is much like using a slot machine. Put your content out there and hope for a jackpot. Granted, there are ways to raise the conversion efficiency, especially for financial institutions such as banks who are used to using lead scoring and CRM tracking to see which customers see which pieces of content. But there is still too many unknown factors.
Thanks to all that data and the new ways to analyze it with content intelligence, we’re approaching the point where CMOs know what their audience wants to read. Moreover, we may be getting to the point where it is feasible that you can give each member of your audience a unique content path based on their prior interactions with your brand.
Content intelligence strives to answer the question “what content does my audience need to keep them engaged with my brand?” CI programs study the vast array of data signals generated by people in your niche, not just on your site but also on competitor’s sites and the sites of industry publications.
At its current level, it can determine the overall topic or keywords that are starting to gain buzz. The earlier you can write on these bubbling topics, the faster you can get your views out ahead of the competitors while also meeting the reader at the precise point when their interest meets your content.
Just think of how powerful this idea is. Here’s an example involving banks. Banks have a variety of customers depending on their location and the type of banking services they provide. It’s very hard to develop a general content strategy for a bank because of this. Additionally, a single customer’s interest in a bank’s products depends a lot on the state of their finances. One day they might be a homeowner looking to start investing, and the next they need nothing more than a checking account after a foreclosure.
Content intelligence, in its current state, can study the data points generated by the local community to start developing a general topic-based content strategy. But it will reach the point soon where a customer’s content consumption patterns will lead to recommendations for additional pieces to read. Think like Amazon’s recommendation engine.
A customer investigating savings accounts might be well-primed to learn about retirement accounts or investment accounts since they are interested in saving money for the future. Someone looking for mortgages might want to read happy stories about other homeowners who have mortgages. These are just examples, but instead of guessing you’ll be able to know when the reader is ready by their habits and the habits of others like them.
ROI for Content Marketing, Finally
Once content intelligence can get to this point, CMO managers will be able to access a holy grail of content marketing. They’ll be able to determine which pieces bring in revenue and which ones don’t. Yes, this means that they’ll have the ability to calculate the ROI of a content marketing campaign.
That’s not just for revenue either. We believe that content intelligence will be able to judge the reaction someone has to a piece in the future as well. CMOs will be able to judge how brand perception changed in the people who engaged with a particular piece of content. This is still some way off. More research is needed to nail down the right signals. But you can be sure that this problem is under research right now as various Content Strategy Platforms (CSPs) are being developed using AI.
In the meantime, predicting which content topics people want to read next and then learning from those reactions is a big step forward. It makes content less of a guessing game and more of an educational process. As the AIs study human behavior patterns and learn from the results, the better their recommendations will be. Who knows what we’ll be able to accomplish in a few years time?
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