Published on July 11, 2017 by Rasmus Skjoldan
E-commerce has moved light years beyond the concept of simply pushing your product catalogue to a receptive audience. Now, you have to connect your products to the desires, longings, expectations and context of your prospective buyers. Any online marketer worth his salt knows the power of storytelling and why you need to connect content and commerce to sell well.
From the marketer’s point of view, the biggest pain point of the content commerce experience is not about creating all the pieces of engaging content. It’s about making sure that content doesn’t get lost, and is seen by the right person at the right point of her buying journey.
But why are so many companies having problems connecting content and commerce effectively? In reality, it’s massively time-consuming for human beings to connect all the dots between product over stories and to an actual conversion: that point in time where a buyer reaches a conclusion about what to buy.
Completing the jigsaw of content-driven commerce continues to be elusive. You can try your best to become more and more effective in your content production process but in reality, virtually all organizations simply run out of time and human resources when trying to piece together stories that support selling products —in a fast changing market where both products and customer expectations change fast.
Artificial intelligence can provide the central, missing piece to complete the whole content commerce experience. Let’s look at an example about how companies can ignite their content commerce dreams by using existing video content.
On March 8th 2017, Google announced their Google Cloud Video Intelligence API, which allows artificial intelligence to take care of the tedious plowing through video archives to find specific content, whether it’s cool cats, snowboarders or skyscrapers. Google is not alone, as IBM Watson launched a similar application last year and more will come.
Now imagine asking those pieces of artificial intelligence to go through all of your own storytelling videos or an archive of footage to find those magic pieces of video content that can personalize the customer experience that you’ve laid out within your content management system.
The result is this: rich automatically produced recommendations about which videos thematically connect the best to which products. Suddenly, the path to pushing that footage into your digital experiences becomes much more manageable. The chances that you’ll be able to present a relevant experience to end users just got a lot bigger. You can apply the same technology to your texts and images, bringing all that content together.
The point is this. Content-driven commerce and AI in combination seems like a big step. But there’s no need to be intimidated, especially not as new tools are popping up everywhere now. You can start small, by connecting available technologies to your existing content. Technologies like this enable enterprises to get value from their archives of unstructured content and to connect it to shopping experiences.
We’re moving fast toward a future where content curation to support a buying experience will no longer rely solely on human beings understanding the needs, longings and context of the buyer. Instead we can increasingly rely on machines to do the mundane time-consuming work of tagging content resources or connecting buyer preferences to the right products.
Up to now, most targeting has been based on very basic traits such as sex, age and location. But just because you have the same demographic as your neighbour doesn’t mean that you will have the same preferences, values or personality traits. Those underlying characteristics affect your habits and your decisions. So what do you do if you want to deliver personalized content that goes deeper than basic attributes?
The explosion of data gathering techniques has led to a growth in psychographics in recent years. What you like, what you look at, for how long and at what time of day, all adds to your personality profile. Being able to tease out what kind of person you really are - from this data collection, is becoming the new norm, creating a new standard for exceptionally well-targeted marketing.
When you manage to apply machine learning to your existing content - and then match that to what you know about your buyers’ personalities and preferences through psychographic profiling, you end up with ways to connect content and commerce - without the intense struggle of manually piecing it all together.
If you’re confronted with an extrovert prospect on your website, you can empathize with that personality trait by picking content that matches. You can also use it in down-to-earth practical ways like offering someone objects in their favourite colour.
Today, we’re in a situation where so many online experiences feel utterly irrelevant to us, either because we’re just getting the product catalogue and have to do the matching between what we need and what we can have ourselves - or because the tone of voice or actual content shown is just out of synch with our personal traits.
Where content-driven commerce is driven by AI and psychographics, the missing pieces come together, and the result is a customer experience that is steeped in delightful encounters with your brand.
Image courtesy of Alex Knight, Unsplash
Rasmus Skjoldan is Lead Product Manager at Magnolia. He brings a wealth of experience in the area of content hubs and omnichannel content management to the table. A former brand manager of TYPO3, Rasmus was user experience lead of the TYPO3 Neos open source project before running Cope, a Copenhagen-based content strategy consultancy.
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