How Can AI Help Content Marketers?
The name is Generative Pre-trained Transformer 3, but it’s more commonly called GPT-3. Since its release in May 2020, the AI, language generation model created by OpenAI has received substantial attention. This is a third-generation Natural Language Generation model that produces human-like language at scale, and is available as an application program interface (API). In […]
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The name is Generative Pre-trained Transformer 3, but it’s more commonly called GPT-3. Since its release in May 2020, the AI, language generation model created by OpenAI has received substantial attention. This is a third-generation Natural Language Generation model that produces human-like language at scale, and is available as an application program interface (API).
In September, the Guardian carried an article written entirely by GPT-3 using the prompt “convince us robots come in peace”. The robot made several arguments about how it lacked a feeling brain but excelled at making rational decisions and had “no desire to wipe out humans.” At the end of the 500-word essay, readers may not have been convinced about an AI takeover, but content marketers were interested in leveraging the tool to ease growing content requirements.
The year 2020 further reinforced what we knew about the power of persuasion in content marketing. According to the GlobalWebIndex, during the lockdown, total internet hits increased between 50 and 70 per cent. Consequently, ad fatigue became a real issue for brands as users were more frequently exposed to adverts. By definition, information overload occurs when the amount of input to a system exceeds its processing capacity. Consumers are likely to ignore ads which marketers call banner blindness, or develop a negative perception towards brands with intrusive advertising.
The good news is that content marketing continues to answer important questions raised by potential consumers across the customer journey. According to 2020 data from Google, 51 per cent of shoppers say they use Google to research a purchase they plan to make online. Moreover, “Where to buy” and “Near me” mobile queries have grown by over 200 per cent since 2019. Content marketing teams need to thread the needle to produce content that engages their target audience, facilitates customer journeys, and drives meaningful traffic from search engines.
Also Read: Generate ROI with CRM & Marketing Automation
Discover mass personalisation
AI solutions promise to help content marketers tackle tedious tasks such as keyword research, content optimisation, curating content that resonates and in some cases, even generating simple content pieces such as stock reports and news. Take the example of rasa.io, a curation tool that can sift through online content to find what is relevant to your audience and add short descriptions. Marketers commonly use rasa to build smarter email newsletters. It automatically pulls content from news websites, blogs, social media and RSS feeds to create a personalised pool of content for every subscriber.
In the same way, RSS feeds can be powered by AI to aggregate articles based on each individual user’s interests. Take the case of Feedly where users can add their favourite content sources, set topics and keyword priorities. The platform’s AI then serves up the most relevant articles based on these preferences. Another tool called Curata focuses not just on discovering new content but also new topics that your audience might be interested in. It uses machine learning to automate the curation process and serves up customised content. Its dashboard also allows brand managers to insert a summary and brand voice to curated posts.
Quuu is a curation tool that integrates with social media scheduling tools like HubSpot, buffer, Hootsuite and SocialBee. The software automates the content discovery process, curating and recommending content in more than 500 interest categories. When it comes to content, creatives have often followed the less is more philosophy. But when it comes to AI and content, more is more. More data to base decisions on, more sources to scrape and index. Most of these models use algorithms that calculate a relevancy score which predicts the chances of a piece of content being viewed as valuable or spam. It does so using historical data and cross-references it with behaviour across other sources. Over time, the algorithm only gets better at predicting which content will stick thereby reducing the chances of a miss.
Also Read: Is AI Changing Content Marketing?
Say goodbye to writer’s block
Can machine-made content have the same character and creativity of stories written by humans? Perhaps not, but it can definitely compete when it comes to creating content at scale.
A tool called WordAI is best described as a content spinning solution. It works by rewriting the original article by changing each and every word. First, it uses Natural Language Processing to understand each word, finds replacements and aligns syntax so it reads afresh but preserves the original meaning of the sentence. It is also capable of bulk spinning, meaning you can feed one article and get multiple versions that mean the same thing but not set off duplication alerts.
Then there is Article Forge, a software that swallows existing content as a whole and then rewrites it to attract a better ranking. Marketers feed in their keyword, the software then scrapes the web for research and produces a unique piece that passes plagiarism tests and is SEO-friendly. It also integrates with CMS to post regularly which means that websites could run on auto-pilot. The final blow? It can create content in seven languages including Dutch, French, German, Italian, Portuguese, Spanish and English. Take that humans!
