That’s understandable if we look at the massive amount of content created every day: 400+ hours of video uploaded to Youtube and 456,000 tweets every minute, more than 300 million photos uploaded to Facebook daily.
So as marketing departments dash to create more and better content, faster, how can they make sure it yields the desired results?
To answer that, they should start at understanding the who, how, when, and why of their customer – content interactions.
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The race for consumer attention
The consumer buying decision is largely driven by brand trust*. In the absence of prior brand interactions, consumers take to peer reviews, recommendations, or the company website.
Surveys show that 85% of consumers trust online reviews as much as personal recommendations, and 97% searched for a local business online in 2017. The same year, the average blog post was 1142 words – 40% longer than in 2014.
With new content produced every second, attention span has shrunk to seconds. To be successful, marketers must put in front of their customers content that is relevant, engaging, and consistent with consumer behavior.
This kind of content intelligence can be built by combining content consumption patterns and behavioral insights and it can transform the customer experience.
The availability today of large amounts of insight enables brands to enhance both customer experience and service. 35% of Amazon’s revenue is driven by its recommendation algorithms and Netflix has long used big data to build predictive algorithms that allow the company to provide the best viewer experience.
What is content intelligence?
– Roy H. Williams
Content intelligence refers to Artificial Intelligence techniques – including machine learning, big data, or natural language processing – applied to content marketing with the aim of steering businesses towards better informed decisions.
Content intelligence helps brands analyze and understand the ways in which customers interact with content across channels, so that marketers can decide what and how to publish in order to create the best experience for each customer.
Marketers will rely on this technology to gather the data and to make sense of it. According to Inc. magazine, if marketers want to “draw conclusions from a huge pool of data”, they will need to “work in tandem with machines to analyze data and to make decisions based upon it.”
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Brands’ interest in AI goes beyond personalized recommendation systems and chatbot shopping assistants. In 2016, Nike created ‘Nike On Demand‘ to engage with athletes and help them reach their goals. The service combined activity data with with real human interaction to provide individual training plans and products. A staggering 70% of users reported they expected this type of service from Nike.
The rise of content intelligence reflects an essentially user-centric approach to marketing, as opposed to more traditional, product-focused strategies. In this new framework, purchase decisions depend more on the customer’s journey, brand rapport, and sentiment, rather than product characteristics.
Image Source : Instagram.com
Content intelligence can be applied by retailers that want to:
- analyze content performance across different channels (social media, paid advertising, website, blog) over time, and in context;
- understand which topics and formats resonate with which customers and how different consumers interact with brand content;
- map user journeys and personalize content to enhance the customer experience;
- optimize their efforts and maximize marketing ROI.
Content intelligence benefits for retailers
In a time when massive amounts of content are created daily, the computing power to process such data is increasingly available, and consumer expectations are harder and harder to meet, content intelligence does look like the sensible solution.
And the trend is on the rise. A recent survey showed that 49% of mobile marketers say machine learning will become a part of their customer journey in 2018, while 36% intend to use artificial intelligence.
Retailers who leverage content intelligence to measure the effectiveness and impact of their marcom strategies might discover unique benefits like:
- better analytical capabilities that help personalize customer journeys at scale
- competitive advantage by truly anticipating latent customer needs
- differentiation by meeting ever rising consumer expectations
Luxury Products Retailer Improves Conversion with Highly Relevant Shopping Experiences
Knexus platform is an AI decision making engine that matches customer data with marketing & social content like thought leadership & blogs, delivering highly relevant content experiences on any digital channel.