By: Rajesh Rajani, Program Director

Content marketing is all about creating content like whitepapers, blogs, videos, social media posts, etc. This content can be distributed to selected audiences to attract & retain the targeted audience to your brand, product, or services. Undoubtedly this requires a lot of intelligent effort in terms of understanding your customer journeys, their preferences & aspirations. It’s a time-consuming process to create highly personalized content to target a huge audience and it calls for automation of the content generation process.

Artificial intelligence (AI) can play a great role by automating some of the content creation activities. AI is well known to simulate human intelligence by using systems and includes many technologies like natural language understanding and generation, machine learning, neural networks, and expert systems. This blog touches upon different use cases for which AI can be applied to scale content marketing.

The key question that arises in the mind of a curious reader is how AI can be leveraged for content marketing. Anyone who has worked as a content editor/content marketer knows that it requires good articulative skills, adequate knowledge of the subject, and a habit of improvisation, in order to create a good piece of content. Given all the skills required, the question remains – is it possible for a system to create content that requires continuous improvisation?

Artificial intelligence covers a lot of different technologies and by using natural language processing and the generation capabilities of AI, an advanced system can be created that reads and/or writes human language. In essence, it is a system that learns how to improve every time it reads or writes. Gmail, for instance, uses AI to predict the next word while writing emails and offers an automatic suggestion to speed up your typing.

So, where is AI used in the content marketing lifecycle? According to a survey conducted by Drift & Marketing Artificial Intelligence Institute in 2021, 235 people answered 13 survey questions and completed the full assessment to rate 49 AI use cases. The survey respondents included a diverse set of roles and 57% of them were at the Director level or above. Among the top AI use cases found by the survey, the key ones related to content marketing are:

1. Analyzing existing online content for gaps and opportunities
2. Creating data-driven content
3. Optimizing website content for search engines
4. Recommending highly targeted content to users in real-time
5. Forecasting campaign results based on predictive analysis

All the above-listed AI use cases can be mapped to the Content Marketing lifecycle stages as shown below:

Let us investigate the detail of each of the use cases as shown in the Content Marketing Lifecycle

1. Creation of Data-driven content:

Data-driven content strategy relies on insights from data to create content for marketing. Data derived based on your audience, the channels you want to publish, your competition, your offering’s USP, etc. is used to develop and execute a content strategy. The goal is to ensure that the content reaches its intended audience and motivates them to take the desired action.

An AI-powered Content Strategy Platform can be used to perform topic research based on competition, create content briefs, and measure performance. This saves a lot of time spent on brainstorming sessions and effort on creating content that is based on assumptions.

2. Analyze existing online content for gaps and opportunities:

Performing the gap analysis is a labor-intensive job as it requires going through thousands of web pages of similar content, making it difficult to scale through manual effort. AI can play a great role by creating a model that highlights the topics missing from the content of the top-ranking URLs. This also provides a view on how well topics are covered by the competition. Analyzing the topic model can help in understanding the gap in the existing content available and can be used to create content that can provide a competitive advantage.

3. Alignment with corporate guidelines, style, and tone of the content:

In big marketing organizations, a process is followed wherein the content created by authors gets reviewed by editors before being published. Content writers spend a lot of time editing and standardizing marketing content to align it with corporate guidelines, usage of words, brand tone and style, etc. AI systems can read the content, highlight the parts that are not as per the guidelines and provide help text to users to improvise. This helps in reducing hundreds of hours that are consumed reviewing content before it gets published. So, while AI may not write the content for you, it can free up editors’ time to create more and better content that is standard across the organization.

4. Recommend highly targeted content to users in real-time:

Research by Microsoft indicates that an average consumer’s attention span is no more than eight seconds. In the digital space, it is imperative to keep customers interested, which is however trickier than ever. Therefore, whenever a customer visits a store or a website, it is critical to have a friendly customer executive or personal guide for better engagement. Chatbots developed using AI can play a crucial role in improving customer engagement. The data from AI algorithms can be used to provide customized recommendations through smart targeting so that consumer preferences can be reflected.

LTIMindtree has immense capabilities in Conversational AI and has helped many clients in the design and implementation of chatbots. LTIMindtree’s customer engagement conversational AI solutions address queries across all touchpoints – pre-purchase, in-purchase, and post-purchase – for consumers to engage and have a seamless experience. Click here for a detailed case study on customer engagement using Conversational AI.

5. Content optimization (Optimize website content for search engines):

Content optimization is key to ranking higher on Google search pages and there are some well-known ways to achieve this. AI tools can help automate simpler processes like including primary and secondary keywords at the correct densities and improving text readability based on the learnings from other content. Other aspects like ensuring an appropriate word count, having the optimal meta title and description tags, etc. can be easily performed by AI tools.

The AI team in LTIMindtree has created bots to help marketing organizations on similar use cases. The bot can assist content authors by recommending page titles, CTAs, keywords/tags, etc. for a given webpage, based on the web page content. Marketers can perform A/B testing to see which keywords perform better and can choose from the options to increase the SEO ranking of the page.

6. Forecast campaign results based on predictive analysis

Predictive analysis is used to predict the outcome of a business activity, for instance, the probability of success of a marketing campaign for a given channel.

There is tons of online data available that can be used to identify the target audience and their behavior. AI-powered predictive tools use deep insights about your target audiences, audience interests, demographics, and psychographics. AI tools can also analyze online behavior online across social media and can exactly predict what your audience wants to see, buy, and consume. All these insights can be leveraged by AI tools to forecast campaign results even before it’s rolled out to the target audience. Based on the forecast & recommendation, campaigns can be tailored to increase their effectiveness to maximize RoI.

Wrapping Up:

AI is revolutionizing the marketing industry at a faster pace than we can imagine, and for businesses, there will be many opportunities to leverage AI technology. Businesses need a trusted partner who can help them understand the specific applications of AI to improve their customer engagement and achieve the desired RoI using AI technology. LTIMindtree is an experienced partner when it comes to identifying key use cases and has worked with industry-leading platforms like MS Bot framework, Dialogflow, Alexa, and others like Amelia and LivePerson. LTIMindtree’s AI implementations integrate well with various enterprise systems like Microsoft Dynamics, SAP, Workday, Service Now, Salesforce, Oracle, and Pega. For more details on LTIMindtree’s Conversational AI capabilities and accelerators, click here.

References:

1. https://www.zdnet.com/article/5-ai-tools-that-can-think-and-write-like-humans/
2. https://www.marketingaiinstitute.com/blog/ai-for-content-marketing
3. https://www.algolia.com/blog/ai/how-to-identify-user-search-intent-using-ai-and-machine-learning/
4. https://www.mindtree.com/services/customer-success/immersive-and-cognitive-experiences/
5. https://www.newbreedrevenue.com/blog/ai-powered-content-marketing
6. https://blog.marketmuse.com/marketing-ai-use-cases-why-content-optimization-ranks-so-high/