4 Winning Ways to Create an AI Content Marketing Strategy
The artificial intelligence (AI) revolution continues to make an impact on the global market with disruptive efficiency. Whether it’s the marketing industry, FinTech or healthcare, and cybersecurity, AI technologies continue to make their mark as standard practice. When it comes to content marketing, digital transformation is starting to take shape.
[Related Article: Watch: Building Highly Autonomous Digital Marketing Automation Systems]
According to Adobe, some of the biggest personalization challenges marketing experts face today include gathering relevant data quickly for it to be relevant to their content marketing (40%) as well as having enough data available to make an informed personalization decision (39%). This data comes at the heels of 74% of customers who have expressed their frustrations with websites that advertise their personalization strategies yet very rarely manage to hit the right beats and cater to their needs with both content and advertisement.
Introducing AI into the mix can play a crucial role in ensuring that your business has a fighting chance in regards to carving out a niche in your industry, however. With that in mind, let’s take a look at some of the winning ways to integrate AI for the betterment of your content marketing strategy going forward.
- Curated Content Production
The crux of personalization lies in knowing which content pieces to produce, in what format and for which audience at any given moment in your content production cycle. With so many variables in play, it can be difficult to manually choose which content pieces to focus on and which ones to eliminate due to their potential low performance. While things such as the social context and live customer interaction with your content should be taken into consideration, AI can help you determine the best course of action during the production itself.
Estelle Liotard, Head of Content Department at Studicus spoke on the matter recently: “Many creators of AI models like chatbots, for example, proudly claim that their products can be used for different tasks in different contexts, but learning the social context to be applied fairly is something they’re yet to learn”. While AI-powered platforms such as SEM Rush and Google AdWords can indeed provide you with relevant data to siphon from, your production staff, writers and managers should still make the final call with new data into consideration.
- Chatbot Audience Engagement
One of the most predominant applications of AI in content marketing by businesses of all calibers involves the use of chatbots. In essence, chatbots are machine-learning algorithms designed for audience engagement, rudimentary customer servicing, and 24/7 brand representation. Their introduction into your business model can significantly bolster your brand reputation, customer retention and SEO ranking due to their accessibility.
Likewise, chatbots can be equipped with published content links and product pages in their response repository, actively involving your entire website in the conversational AI algorithm. Lastly, chatbots can also feature localized content in a variety of languages, ensuring that people from around the world can enjoy your content and services, as well as have a good reason to recommend your platform to their social circles as a result.
- Personalized Content Feeds
The traditional use of cookies on the web can be found in saving personal information of individual users for their browsing convenience. However, this data can be used in tandem with AI to allow for personalized, filtered content to be displayed.
For example, if an individual user searches for and engages with posts and products in regards to “kitchen appliances”, they are likely not interested in living room furniture or garden accessories. Given the machine-learning nature of AI, it would effectively eliminate unwanted results from the user’s search results and present them with exclusively relevant content. The data collected from cookies and website engagement can be used to further refine your content marketing strategy and find out which content types and topics are favored by your audience over others.
- Data-Driven Decision-Making
Making hard decisions in regards to future projects, financial investments, and B2B networking is an everyday occurrence. Above all else, AI can help with decision-making in every facet of running a business at peak efficiency. Specialized data scientists are hard to come by for small-scale enterprises and startups in their infancy, not to mention that they too have their professional goals and careers to tend to.
However, integrating AI algorithms designed with data analysis and development suggestions is a great way to effectively bridge the gap between raw data and actionable information. Specialized software centered on data management, processing and analysis can and should be a part of your business model going forward due to its ability to lower the margin for error in your company and allow for more informed decisions to be made in regards to future developments.
[Related Article: 4 Ways Data Scientists Are Marketing Themselves Incorrectly]
In Conclusion
While integrating AI into your already-formed content marketing strategy might seem unnecessary at first, its addition to the formula can have transformative effects. Make sure to explore creative ways to introduce AI-powered software, tools, and algorithms into your business model as an extension of the content marketing strategy and not just as a passing trend. Quicker decision-making, more precise content planning and around-the-clock audience engagement are only the tip of the proverbial iceberg when it comes to AI.
Read more data science articles on OpenDataScience.com, including tutorials and guides from beginner to advanced levels! Subscribe to our weekly newsletter here and receive the latest news every Thursday.
