Using AI to Create Content for WordPress

One issue with using AI to create content for WordPress sites is that AI generated content doesn’t necessarily match your own or your brand’s writing style. In this Case Study I’ll show you an article generated by ChatGPT and point out some style issues. Then I’ll show you how I taught ChatGPT to match my own writing style better and finally, I’ll show you the resultant article.

Let’s start with a ChatGPT generated article. Here’s the prompt.

Write a 250 word article about using AI to generate WordPress articles for SEO purposes.

Here’s the output.

<Starts> Using AI to Generate WordPress Articles for SEO Optimization

The digital age has ushered in a new era of content creation. As businesses and bloggers strive to maintain an edge in the saturated world of online content, there’s a growing trend towards utilizing artificial intelligence (AI) to generate WordPress articles tailored for search engine optimization (SEO).

Traditional content creation can be time-consuming, and even with a team of skilled writers, the demand for fresh, relevant content can be overwhelming. Enter AI-driven tools. These platforms utilize advanced machine learning algorithms to draft articles that are not only coherent and engaging but also optimized for search engines. This means the content is tailored to rank higher on search engines, driving organic traffic to websites.

The advantages are numerous:

  1. Consistency: AI ensures a steady stream of content, crucial for websites that need regular updates.
  2. Optimization: AI tools can be programmed to follow the latest SEO best practices, ensuring articles are primed for high search engine rankings.
  3. Scalability: Instead of hiring more writers for increasing content demands, businesses can scale up with AI.

However, while AI offers numerous benefits, it’s essential to strike a balance. Over-reliance on AI-generated content can make a brand’s voice feel impersonal. Furthermore, readers value genuine human connection and insights, which AI can’t replicate completely.

In conclusion, integrating AI with WordPress for SEO-optimized articles offers an exciting frontier for content creators. It’s a tool that, when used judiciously, can propel online presence, but the human touch remains irreplaceable in crafting truly compelling stories. <Ends>

My comments

I don’t like this style much. There are phrases I wouldn’t use. For example, “the demand for fresh, relevant content can be overwhelming”.

These two sentences say pretty much the same thing.

“These platforms utilize advanced machine learning algorithms to draft articles that are not only coherent and engaging but also optimized for search engines. This means the content is tailored to rank higher on search engines, driving organic traffic to websites.”

To say the advantages are numerous needs to be followed up by more than 3 advantages in a list too!

But overall the writing is what I call low-bandwidth. It doesn’t actually say much and so delivers very little value to reader. I like my own writing to be concise and to convey useful information and to get ChatGPT to match my preference more closely I’ll need a better prompt or to upload a good sample of my own writing first.

Impact of Grok AI on Business

Elon Musk’s X.ai is launching its own LLM called Grok that will have the currently unique feature of having access to the live Twitter / X data stream. This means it will be able to answer questions about near real time events, thoughts, controversies, ideas and, tediously, celebrity news too no doubt. So what will be the impact of Grok AI on business?

It’s far too early to know at the moment but as a first attempt I asked ChatGPT the following question.

“Suppose a new LLM had access to up to the second information via the Twitter platform, what would be the implications for business and how might one utilise the tool?”

<STARTS>

If a new Language Model (LLM) had access to up-to-the-second information via Twitter / X, it could have significant implications for businesses in various ways, particularly in the areas of market intelligence, customer service, and real-time decision-making. Here’s how businesses might utilize such a tool:

Market Intelligence and Trends Analysis:

Real-time Monitoring: Companies could monitor real-time public opinion and reaction to events, products, or services, allowing them to adjust marketing strategies promptly.

Trend Spotting: The LLM could identify emerging trends by analyzing the velocity and sentiment of tweets on particular topics, providing businesses with early insights into consumer interests and market shifts.

Customer Service and Engagement:

Instant Response: By integrating the LLM with their customer service platforms, businesses could provide instant responses to customer queries on Twitter, improving customer experience.

Sentiment Analysis: The LLM could assess customer sentiment in real-time, allowing businesses to address complaints or issues before they escalate.

Personalization: By analyzing tweets, businesses could tailor their communication to individual customers, enhancing engagement and loyalty.

Crisis Management:

Issue Detection: The LLM could quickly identify negative trends or potential crises related to the company, enabling faster response and mitigation efforts.

Communication Assistance: It could help draft real-time responses and communication strategies to manage public perception during a crisis.

Competitive Analysis:

  • Competitor Monitoring: Businesses could use the LLM to keep track of competitors’ activities, announcements, and customer feedback, providing insights into their strengths and weaknesses.
  • Benchmarking: It could help in analyzing how competitors’ events or product launches are being received by the market.

Content Creation and Curation:

  • Content Ideas: The tool could generate content ideas that are currently trending or likely to resonate with the audience.
  • Automated Posting: Businesses could use it to create and post Twitter content in real-time, reacting to ongoing discussions or events.

Financial Markets:

  • Market Sentiment: In financial services, the LLM could gauge market sentiment on financial products, stocks, or cryptocurrencies, potentially influencing trading decisions.
  • Event-Driven Trading: Traders might use insights from Twitter to inform event-driven trading strategies.

Product Development:

  • Feedback Analysis: Real-time analysis of feedback on products could inform product development and improvement.
  • Idea Generation: The tool could identify gaps in the market or consumer pain points that could lead to new product ideas.

Risk Management:

  • Reputation Monitoring: Constant monitoring of the brand’s perception on Twitter could help in assessing and managing reputational risks.
  • Compliance and Governance: The LLM could detect discussions related to regulatory compliance, potentially identifying risks or required actions.

Strategic Planning:

  • Data-Driven Decisions: Insights gleaned from Twitter data could be incorporated into strategic business decisions, making them more responsive to current events and trends.

Advertising and Promotions:

Targeted Campaigns: Analysis of Twitter could help in creating targeted ad campaigns that align with current discussions and user interests.

Influencer Identification: It could identify key influencers and opinion leaders in real time, providing opportunities for partnerships or endorsements.

Challenges and Considerations:

  • Data Privacy: Businesses must navigate privacy concerns and adhere to regulations regarding the use of public data from social platforms.
  • Information Overload: The sheer volume of data might require sophisticated filtering to avoid analysis paralysis.
  • Misinformation: The tool would need to be capable of distinguishing between credible information and rumors or fake news.
  • Contextual Understanding: Tweets are often nuanced and filled with slang, humor, and sarcasm, requiring advanced understanding to interpret correctly.

Overall, a real-time LLM with Twitter access would be a powerful tool for businesses, provided it is used responsibly and in compliance with data protection laws and ethical guidelines. The key would be integrating the insights into the decision-making process in a meaningful way that enhances, rather than overwhelms, business intelligence functions.

<ENDS>

Impact of Grok AI on Business

The impact of Grok AI on business is likely to be profound both directly and indirectly. Accessing real time data will be increasingly important as the competitive environment becomes all the more intense and nimble businesses that respond to events fastest could gain competitive advantage. Consider a situation where an influencer tweets about your product or service. You could automatically respond with a tweet offering a special one-day only offer to capitalise on the publicity. Clearly a social media manager could do the same but most businesses don’t have the resources to employ a dedicated social media manager.

Indirectly, X.ai giving Grok AI access to the twitter feed will put considerably pressure on other LLM suppliers like OpenAI, Google, Microsoft and others to make up to date information available to their LLMs too. However, at the moment, those suppliers don’t have access to anything like the up to date information fire hose that Twitter / X has and it seems unlikely that Elon Musk and X.ai will want to release it in a hurry either. Why would they?