An introduction to AI content distribution
AI content distribution — what is that? Between Chat GPT-generated essays that induce a sense of the uncanny valley with their generic optimism and DALL-E’s abysmal representation of human hands, AI’s infancy in content generation is infamous. However, while these early attempts at content creation are still relatively primitive, AI capabilities in content distribution are significantly more sophisticated.
Technologies that we recognise as artificially intelligent (natural language processors, machine learning, and predictive analytics) are increasingly being used to analyse consumer behaviour and preferences with satisfying accuracy and efficiency. AI sucks at approximating an appropriate number of fingers per human hand, but it excels at recognising and categorising historical patterns — which is brilliant news for B2B marketers.
Whether you’re reaching out to a prospect through a digital ad, an email, or a search engine-optimised blog, conversion is predicated on two features: the relevance of the asset (which has always been in your control) and the timing of its delivery (which has not always been in your control — until now).
The application of AI in B2B content marketing and advertising has proven to be extraordinarily effective, as it empowers brands to reach their target audience with pinpoint accuracy and optimal timing. AI-powered content delivery can be effectively implemented across multiple platforms, making it one of the most versatile distribution tools in the B2B marketer’s utility belt.
The overarching role of AI in content distribution
AI can play a pivotal role in efficient content distribution, ensuring that the most relevant content reaches the right audience at the right time. That’s because AI is really good at analysing vast seas of data at a rate that even your most eager-to-please intern could never hope to emulate.
Ever a voracious fiend for patterns, AI can track useful things like user preferences, behaviours, and demographics almost instantaneously, empowering B2B marketers to refine targeting efforts and personalise content delivery with time to spare for making up a new acronym by COL (that’s Close of Laptop for the uninitiated).
Additionally, AI automates the distribution process, freeing marketers to focus on more titillating pursuits like creative strategy, content ideation, and shopping online for ambient office lighting (only joking about that last bit). Automating distribution also provides real-time insights into content performance for “data-driven decision-making”, the alliterative Holy Grail of SaaS-y copy. Finally, automation is just more efficient with AI. At the push of a metaphorical button, engaging content can be intelligently scheduled and optimised for multiple channels, and manual publishing is banished to redundancy forevermore.
AI-driven, targeted content delivery: delight, or dilemma?
Do you ever feel like your phone is listening to you? One minute you’re regaling your friends with your personal goal to compete in your first triathlon and, before you know it, Google ads are recommending electrolyte powder in bulk and your newsfeed is littered with inspirational Iron Man success stories. The good news is that nobody is spying on you — at least, not in a creepy, non-consensual way. But you might have AI to thank for offering you such targeted and therefore relevant content.
AI can be effectively leveraged to filter and present relevant content to engaged readers from an increasingly large pool of data. This entails the deployment of algorithms to identify and prioritise the most relevant information for a specific audience or user. Not only does this unlock the possibility of highly targeted content delivery, but it also makes it possible to hyper-personalise marketing efforts that are tailored right down to a single person’s user preferences and behaviours.
The formidable power of targeted content delivery truly shines in applications like news aggregation sites, content recommendation systems, and social media platforms. By profiling patterns of user engagement, AI can turn almost anything into a “For You” page — a curated feed of relevant information that provides a welcome respite from the overwhelming chaos of the Age of Information.
While the benefits of targeted content delivery for both marketers and Internet users are clear (marketer makes more direct contact with user, user gets a “cleaner” user experience), the curatorial powers of AI do provoke an ethical question. There are concerns about the potential for AI systems to perpetuate biases about race, gender, and socioeconomic status, as well as general misinformation about anything from public health to politics.
Furthermore, the existence of an information feed that has been trimmed and hedged according to an individual history of data patterns poses the risk of creating innumerable ideological echo chambers. We’ll have to wait and see what effects the development of AI regulations and guidelines have on AI-powered content generation and distribution but, for now, these ethical questions highlight the need for considered mindfulness of the ethics of AI.
The power of personalisation in AI content distribution
We’ve done a deep dive into the ethics and efficacy of AI content distribution tactics, but it’s time now to consider the pinnacle of AI-powered personalisation: the algorithm. As mystified as it is maligned on platforms like Instagram, the AI algorithm can analyse swaths of user data like demographics, browsing patterns, and purchase histories to create detailed user profiles. These profiles can help clarify user preferences and make it easier to achieve personalised content delivery.
On the buyer’s side of Instagram, that looks like receiving targeted ads and posts that can make you feel as though your phone is plugged directly into your brain. However, the benefits of hyper-personalisation are as applicable in the world of B2B professionals as they are in the world of aspirational marathon runners being plagued by ads for Rehydrat electrolyte powder.
For example, let’s entertain the concept of using AI as a subject matter expert — but for people. Simply by scanning public LinkedIn profiles, AI can amass critical insights like a prospect’s career history, personal interests, and expertise in an instant. While we would not personally outsource the human connection part of this interaction on a non-human by conscripting AI to produce LinkedIn messaging copy, having a profile on hand to inform your outreach messaging brings you one step closer to a positive response.
The role of AI in effective content distribution is an undeniable advantage for B2B marketers and a robust example of where AI functions best in the world of content generation. But hyperefficient and fine-tuned content distribution strategies count for nought without quality content — content that isn’t just mildly helpful and informative, but packs a perspective-defining punch with a zero-tolerance policy for repetitive bullshit. If that’s what you’re after, drop the ChatGPT prompt and read the rest of our human-generated content.
