AI-powered tools can revolutionize the content research process. They provide strategic insights that go beyond simple analytics. Marketers can identify content gaps, optimize content clusters, and conduct competitive content analysis to refine their approach.
Studies reveal that AI adoption has helped businesses increase revenue and improve customer experience by automating tasks and freeing employees to do more meaningful, critical work.
Artificial intelligence (AI) has long been a hot topic. Just last week it was reported that ChatGPT has become the fastest growing user base in history, reaching 100 million monthly users in just two months!
Fictional plots in TV, film, and books have infinitely pitted AI against humans. And with the advent of AI tools for output that has traditionally been created by humans, such as art, marketing content, and even (quite controversially) academic writing, the anxiety surrounding AI is quite understandable.
However, research on AI technology paints a less grim picture, especially concerning the application of AI to improve business workflows. A recent IBM survey reveals that global AI adoption is growing steadily. Per IBM, 77% of companies are currently exploring AI to some extent, with 35% using AI in their businesses and 42% studying how they can incorporate AI into their workflows.
Many businesses have found AI useful in addressing labor gaps by automating repetitive tasks, allowing finite human resources to focus on more intensive pursuits that require high-level critical thinking.
AI sales tools have proven to be effective in increasing conversion rates and improving customer experiences, especially for online-based businesses.
As such, startups venturing into digital content or eCommerce should leverage AI tools to supplement their existing content strategies and automate a wide range of tasks.
A brief history of AI in marketing and related fields.
There’s no doubt about the value of AI in many areas of business, especially in marketing. With such high demand for agile, high quality content more and more teams are leveraging the power of AI to fill content gaps, create prompts, and even carry out technical functions such as keyword research and analytics.
Google’s continual refinement of its search algorithm has forced many businesses to whip their website into shape by creating grammatically correct, informative, and engaging content.
Back in 1998, Amazon spearheaded the use of AI based on research by Columbia University computational linguist Jussi Karlgren. Amazon used it to develop collaborative filtering, a function that displayed product recommendations based on collected data.
Today, the same technology gives us film and TV show suggestions on Netflix and music recommendations on Spotify. AI cross-references consumer data and browsing history with user profile information and demographics to tailor recommendations based on one’s likes and dislikes.
In 2013, AI content creation was first used to generate sports articles that could be published almost in real-time. Yahoo! used Automated Insights’ Wordsmith platform to write personal reports, match recaps, and match previews based on fantasy football data.
The platform used natural language generation (NLG) to personalize content for each user. Particular care was given to ensure that the AI captured Yahoo’s brand voice and tone.
“The tone of the narratives for Yahoo were intentionally snarky and sarcastic, so there was a process to making sure the jokes, language, and stats about each week’s match up (or the draft reports at the beginning of the season) that are highlighted were what Yahoo was looking for,” Automated Insights spokesperson Laura Pressman shared.
Programmatic ad buying boomed in 2014. With AI, digital ads could be bought and sold based on defined campaign goals and a set budget, as AI made decisions and recommendations based on collected data.
In 2015, Google’s AI algorithm RankBrain revolutionized the way people consume and create content by considering user intent when returning search results. Take the query “shepherd’s pie” as an example. The search engine would return results for recipes and tutorial videos based on the understanding that the person is likely looking for information on how to prepare it. As such, historical and literary references about shepherd’s pie would be farther down the roster of search engine results pages (SERPs).
In 2016, AI progressed to listening and verbally responding, and virtual assistant devices became valuable additions to modern homes.
Since then, more mainstream uses for AI content generation have emerged, with apps like Slack, WhatsApp, and Messenger leveraging AI to answer basic customer support questions via chatbots. This feature provides better customer service, lead generation, and user experience.